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Enemies' Eyes_ , p. 125. . Los detalles sobre el intento de asesinato proceden de Muhammad Ibrahim Naqd, «The First Attempt to Assassinate bin Laden Was Attempted by a Libyan Who Was Trained in Lebanon», _Al-Hayat_ , 18 de noviembre de 2001; e Ibrahim Hassan Ardi, «Al-Watan Places the Period the Head of al-Qaeda Spent in Sudan», _Al-Watan_ , 25 de octubre de 2001; «Ossama bin-Ladin: Muslims Who Live in Europe Are Kafirs», _Rose al-Yousef_ , __ 9 de diciembre de 1996; al-Hammadi, «The Inside Story of al-Qa'ida», parte 3, 21 de marzo de 2005; y de las entrevistas con Isam al-Turabi, Sadiq al-Mahdi, Hassabulla Omer y Jaled Yusuf. Varias fuentes sostienen que en realidad hubo dos tentativas de asesinar a Bin Laden, y algunas afirman que con solo unas semanas de diferencia, pero esas informaciones proceden del propio Bin Laden, que considera el tiroteo a la mezquita la noche anterior como un intento de matarle. . Entrevista con Yamal Jalifa. Algunos de los detalles sobre el hijo de Bin Laden, Abdullah, proceden de al-Hammadi, «The Inside Story of al-Qa'ida», parte 3, 21 de marzo de 2005. . «Ossama bin-Ladin: Muslims Who Live in Europe Are Kafirs», _Rose al-Yousef_ , __ 9 de diciembre de 1996. . _Ibidem_. . Wright, «The Man Behind bin Laden». . Entrevista con Yamal Jashoggi. . Entrevista con Michael Scheuer. . Entrevista con una fuente sudanesa anónima. . Entrevista con Yamal Jalifa. . _Ibidem_. . Entrevista con Said Badib. . «Walidee Ramama al-Aqsa Bilkhasara» [Mi padre renovó la mezquita de al-Aqsa, con pérdidas], _Al-Umma al-Islamiyya_ , __ 18 de octubre de 1991. . Daniel McGrory, «The Day When Osama bin Laden Applied for Asylum – in Britain», _Times_ , __ 29 de septiembre de 2005. . Entrevista con un portavoz de la familia Bin Laden. . Entrevista con Yamal Jalifa. . Entrevista con Hassabulla Omer. . Benjamin Weiser, «Ex-Aide Tells of Plot to Kill bin Laden», _New York Times_ , 21 de febrero de 2001. . Declaración de Yamal al-Fadl, _U.S. v. Usama bin Laden, et al._ Entrevista con Muhammad Loay Baizid. . Declaración de L'Houssaine Kherchtou, _U.S. v. Usama bin Laden, et al._ . Declaración de Yamal al-Fadl, _U.S. v. Usama bin Laden, et al._ . _Ibidem_. Las cantidades reales fueron: 795.200,49 dólares del Programa de Protección de Testigos y 151.047,2 dólares del FBI. Eso no incluye el dinero que le podría haber dado a Fadl la CIA, que fue la primera en interrogarle. . Entrevista con Jack Cloonan. . _Ibidem_. . Alegato, _U.S. v. Ali Mohamed._ . Hasin al-Banyan, «The Oldest Arab Afghan Talks to 'Al-Sharq al-Awsat' About His Career That Finally Landed Him in Prison in Saudi Arabia», _Al-Sharq al-Awsat_ , 25 de noviembre de 2001, traducido al inglés por FBIS. . Entrevista con Yamal Jalifa. . Anónimo, _Through Our Enemies' Eyes_ , p. 146. . Entrevista con Muhammad Loay Baizid. . Entrevista con Yamal Jashoggi. . Entrevista con Ahmed Badib. 11. EL PRÍNCIPE DE LAS TINIEBLAS . Entrevista con Richard A. Clarke. . Entrevista con Steven Simon. . Entrevista con el almirante Paul E. Busick. . Naftali, _Blind Spot_ , p. 242. . Reeve, _New Jackals_ , p. 104. . Entrevista con Mark Rossini. . Taysir Aluni, entrevista con Osama bin Laden, al-Yazira, octubre de 2001. . Entrevista con Richard A. Clarke. . Alain Geresh, _From Index on Censorship_ , www.geocities.com/saudhouse_p/endofan.htm, abril de 1996. . Kevin Dennehy, «Cape Man Relives Close Call with Terrorist Bombing While in Saudi Arabia», _Cape Cod Times_ , __ 25 de octubre de 2001. . Se puede encontrar una vívida descripción de los arrestos y las torturas que sufrieron los árabes afganos tras el atentado de 1995 en Jerichow, _The Saudi File_ , pp. 136-140. . Kohlmann, _Al-Qaida's Jihad in Europe_ , p. 158. . Teitelbaum, _Holier Than Thou_ , p. 76. . Anónimo, _Through Our Enemies' Eyes_ , p. 141. . Salah Najm y Yamal Ismail, «Osama bin Laden: The Destruction of the Base», al-Yazira, 10 de junio de 1999. . Conferencia del príncipe Turki al-Faisal en la Universidad Seton Hall, 14 de octubre de 2003. 12. LOS NIÑOS ESPÍAS . _Al-Ahram_ , 5 de julio de 1995. . Entrevista con David Shinn. . Entrevista con Sadiq al-Mahdi. . _Al-Ahram_ , 5 de julio de 1995. . Entrevista con Said Badib. . Entrevista con Hisham Kassem. . Entrevista con Muhammad el-Shafey. . Entrevista con Said Badib. . Petterson, _Inside Sudan_ , p. 179. . Entrevista con Hisham Kassem. . Las organizaciones de derechos humanos calculan que el número de islamistas que aún están encarcelados en Egipto asciende a 15.000; los islamistas hablan de 60.000. . Entrevistas con Yassir al-Sirri, Montassir al-Zayyat y Hani al-Sibai. . Muhammad el-Shafey, «Al-Zawahiri's Secret Papers», parte 6, _Al-Sharq al-Awsat_ , 18 de diciembre de 2002. . Entrevista con Yassir al-Sirri. . Muhammad el-Shafey, «Al-Zawahiri's Secret Papers», parte 6, _Al-Sharq al-Awsat_ , 18 de diciembre de 2002. . Confesiones de Ahmed Ibrahim al-Sayed al-Nayyar, en el caso de los «repatriados de Albania», septiembre de 1998. . _Ibidem_. . La narración del atentado contra la embajada egipcia procede de al-Hammadi, «The Inside Story of al-Qa'ida», parte 9, 28 de marzo de 2005. . «Al-Qaida, Usama bin Laden's Vehicle for Action», documento anónimo de la CIA, 12 de julio de 2001. El documento describe a Abu Jabab como un «conductor de limusina», lo que normalmente en Oriente Próximo es un eufemismo de «taxista». . Entrevista con Ismail Jan. . Maha Azzam, «Al-Qaeda: The Misunderstood Wahhabi Connection and the Ideology of Violence», _Royal Institute of International_ _Affairs Briefing Paper No. 1_ , febrero de 2003.
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of ratios of average wages of higher education and secondary school graduates ( ) May 7 Acknowledgements In various ways, numerous researchers from around the globe have provided input to this project, which the authors gratefully acknowledge. The authors would like to thank in particular our international advisors D. Bruce Johnstone, Jan Sadlak and Jamil Salmi for providing their expertise at various stages of the project; it was invaluable for designing the study and conducting the analyses on which this final report is based. Furthermore, the authors would like to acknowledge the support in data research and interpretation provided by the national experts: Martin Unger and Jakob Hartl (Austria), Alison Johnston (UK-England), Jussi Kivistö and Elias Pekkola (Finland), Tamás Kozma, József Temesi and Zsuzsanna Veroszta (Hungary), Cezary Kościelniak (Poland), Luisa Cerdeira (Portugal) and Hwanbo Park (South Korea). Finally, the authors would like to acknowledge the contribution of Lori McElroy, Pamela Marcucci and Ronja Wöstheinrich, who helped conduct background research and improve the national and comparative reports. May 8 Executive Summary Higher education systems have been and are still faced with the task of accommodating growing numbers of students without compromising the quality of education, and without creating undesirable inequalities in access and completion. It is in this context that governments have been adjusting the balance of public and private resources with the goal of achieving more inclusive, more effective, and more sustainable higher education systems. Internationally comparative data sets show that over the last two decades, there has been a general shift towards larger shares of private funding of higher education (see Chapter 2). This shift was achieved largely through raising additional or higher revenues from tuition fees (sometimes termed student contributions ). The concept of cost-sharing is used here to investigate this shift in the balance of public and private funding. Changes in the way costs are shared can take several forms, including the introduction of tuition fees where they did not previously exist or a sharp increase where they already did. They can also involve a reduction or even a freezing of student grants or student loan subsidies (reductions in student aid also constitute an increase in the private funding necessary to cover educational and living costs), but also public policies that encourage enrolment shifts from a heavily subsidised public sector to a much less subsidised, fee-dependent private sector. Looking at cost-sharing from the student perspective, the study focusses on student netcosts, i.e. total costs borne by a student after consideration of tuition fees and compensatory study aid. Even in countries without tuition fees, there is still a substantial amount of cost-sharing because no higher education system covers students' educational and living costs completely. It is surmised that an increase in private costs to students will impact on the behaviour of students. The study also looks at the institutional side of cost-sharing and investigates the changing balance of public and private revenues for higher education institutions (HEIs). From the perspective of HEIs, cost-sharing involves changes to the share of public and private funding as income sources (and thus the respective role of tuition fees, contract income, philanthropic donations, etc. as opposed to state funding). Since a change to this balance affects the relative importance of these sources, it is assumed that it will also change the behaviour of HEIs. Reflecting on the expected impacts on student and HEI behaviours of changes to the cost- sharing balance, the study is framed by four hypotheses as part of a single comprehensive policy analysis model. The hypotheses pick up on key aspects of sustainability, effectiveness and equity of tuition fee policies in higher education. Hypothesis A: As private funding increases, total revenue of HEIs increases. Hypothesis B: As the incentives to earn private funding increase, HEIs become more responsive to student demand. Hypothesis C: Increasing private funding has a negative effect on student demand. Hypothesis D: Increasing private funding affects student choice of how and what to study. To investigate how public and private funding changed and what impact various changes have had on the behaviour of HEIs and students, the authors carried out nine systematic country case studies seven countries from the European Union and two from outside Europe (Austria, Canada, England, Finland, Germany, Hungary, Poland, Portugal and May 9 South Korea). This selection of countries provides a variety of settings in which to investigate the effects. Different countries were chosen according to the following criteria: geographic coverage, economic strength, population size, enrolment numbers, share of students in private higher education, degree of public funding of institutions, changes to private funding, tuition fee policy, and student financial aid provision. It was surmised that the countries with the biggest and most rapid shifts in tuition fee policy would be most interesting for the study, since such shifts could be expected to have greater impact on student and HEI behaviour than a generally stable tuition fee policy. For this reason the cases were split into discontinuity countries (Austria, England, Germany and Portugal) and continuity countries (Canada, Finland, Hungary, Poland and South Korea) for the analysis. The table below presents a summary overview of the country patterns (a detailed overview of the developments can be found in Table 2.2 of the main report). Overview of tuition fee policy change in the period of investigation Share of fee-paying students Increased England 1998 England 2006 Germany 2006/07 Austria 2001 Stayed the same Finland Portugal 2003 (England 2012)* South Korea Canada Decreased Poland Austria 2009 Germany Hungary Average amount paid per student Decreased Stayed the same Increased Note: When no year is given it means that any change was gradual. (England 2012)*: The 2012 tuition fee reform in England is outside the period of investigation of this study, but will be included where data are available and relevant for the purpose of this study. For each case study country, a detailed national report assembles all the elements of the respective cost-sharing system to fully portray the balance between public and private sources of revenues (see National Reports in the main appendix). Main Findings From the analysis, we can make the following observations with respect to how changes in fees affect students and institutions: Higher education data systems remain incomplete The state of the data needed to reasonably assess the state of access to higher education is in many countries fairly poor. In some countries notably Hungary and Poland even obtaining simple information about institutional income sources is nearly impossible. Furthermore, even tracking the level of tuition fees which are actually paid remains difficult in some jurisdictions. This situation presents a constraint for policy-based research on a national level, but makes studies aiming to provide a robust evidence base on a cross-national level even more challenging. The conclusions drawn from this study must be viewed in the light of this fact. May 10 The introduction of tuition fees usually makes the system better-off overall, by increasing the total amount of resources available The study concludes that as private funding for institutions increased, public revenues did not tend to decrease, bringing about an overall increase in institutional income (Hypothesis A, see Chapter 3). The hypothesis was tested using per-student income from public and private sources as a basic indicator. It was found that for most countries and periods of time, the hypothesis can be verified. The few periods of decreasing public perstudent income corresponded to phases of either economic crisis (Canada in the 1990s) or massive enrolment growth (Poland in the 1990s to early 2000s, Austria in the late 2000s). In these specific cases, overall student funding (public and private funding combined) also decreased, i.e. private funding was not used to compensate for this. Most interesting from a policy evaluation perspective are cases in which governments had the goal of bringing about shifts in the cost-sharing balance. Such attempts were made in four of the case study countries: Austria, England, Germany and Portugal. It was shown that from a purely financial point of view, the tuition fee reforms in Germany and Portugal were comparatively modest in scope. Their aim was to provide the system with more funds, without fundamentally altering the predominance of the public sector in higher education funding. The analysis showed that this objective was achieved in Portugal and to some degree in Germany. In Austria, the initial goal of introducing tuition fees appears to have been to bring about a net shift in the cost-sharing balance rather than to increase the funds available to the system. If this is the correct interpretation of the underlying policy goals, then the Austrian reform can be considered a (short-lived) success: the introduction of tuition fees changed the cost-sharing balance, but did not lead to an increase in overall funds for institutions. In England, in contrast to the other three discontinuity countries studied here, the tuition fee reforms successively transformed the system into a model in which private contributions serve as a mainstay of institutional funding of higher education. Particularly the most recent reform from 2012 (which cannot yet be evaluated sufficiently because it is so recent) shows a clear shift to private funding of higher education with liquidity and affordability problems being alleviated through a comprehensive public loan scheme. The resources gained through new fee-derived income are not always invested in ways that would be expected to perceptibly improve the student experience We note that across a number of case studies, the tendency over time was for studentsper-staff ratios to rise, even when institutional income per-student was rising. This is a question of HEI behaviour investigated using Hypothesis B (see Chapter 4). The most extreme example of this was in Canada, where student-teacher ratios rose detrimentally by 20% even as per-student income rose by 40%. Thus, while it may be true that fees make institutions better off, they do not necessarily make for a better student experience, even when per-student income is rising. There are three main reasons why this is so. Firstly, in some cases, new funds are dedicated to expansion rather than
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table for Chapman. The Angels also are making a push to sign the hard-throwing Cuban defector. The story says the Marlins raised their offer from five-years, $13 million to $16 million. The report, quoting an unnamed Florida source, said the club hasn’t completely given up hope of signing Chapman. But the team is well aware there are higher bids out there. With their limited economic resources, the Marlins aren’t prepared to reach the $20 million mark. With no state income tax in Florida, the Marlins were hoping a slightly less offer for Chapman may have swayed the 21-year-old to sign. Chapman has been working out in South Florida with his close friend Kendry Morales of the Angels. Chapman’s ties to Morales could ultimately become a deciding factor. There is a chance Chapman will make his decision soon, perhaps over the weekend. Meta The following are trademarks or service marks of Major League Baseball entities and may be used only with permission of Major League Baseball Properties, Inc. or the relevant Major League Baseball entity: Major League, Major League Baseball, MLB, the silhouetted batter logo, World Series, National League, American League, Division Series, League Championship Series, All-Star Game, and the names, nicknames, logos, uniform designs, color combinations, and slogans designating the Major League Baseball clubs and entities, and their respective mascots, events and exhibitions.The Federal Communications Commission (FCC) is planning to gut the 2015 net neutrality laws, which declared that internet service providers (ISPs) could not offer paid prioritization to web companies and lower speeds for other services. Comcast is happy to see the regulations go, it was one of the ISPs that introduced fast lanes, most notably… Read more » Connect with ReadWrite Donald Trump has now been sworn in as the 45th president of the United States of America. Along with his administration, the new president will usher in a number of drastic changes — specifically in the area of telecommunications and the world of IoT. There is a strong possibility that the new White House administration… Read more »Q: Detect if app got focus due to UILocalNotification I'm making an app that keeps track of some reminders that repeats with an user defined interval. I've made it so when the alert displays, the action title says "Renew". When you click this, the app opens, and here I want to create the next reminder, but the problem is that I don't know if the app opens because the notification button was tapped or if the notification fired while the app was running. Anyone got any ideas? A: I don't know if my question was unclear but it seems that I got 4 different answers that all misinterpreted my question :P However, I discovered that the didReceiveLocalNotivication happens between willEnterForeground and didBecomeActive, so I did this to determine if the app was already open or not: -(void)application:(UIApplication *)application didReceiveLocalNotification:(UILocalNotification *)notification { NSLog(@"Opened from notification? %@", wasInactive ? @"yes!" : @"no!"); } - (void)applicationWillEnterForeground:(UIApplication *)application { wasInactive = YES; } - (void)applicationDidBecomeActive:(UIApplication *)application { wasInactive = NO; } A: The 'correct' way to do this is to examine your NSApplication's applicationState property in the application:didReceiveRemoteNotification: method of your delegate. From the documentation for handling local notifications: iOS Note: In iOS, you can determine whether an application is launched as a result of the user tapping the action button or whether the notification was delivered to the already-running application by examining the application state. In the delegate’s implementation of the application:didReceiveRemoteNotification: or application:didReceiveLocalNotification: method, get the value of the applicationState property and evaluate it. If the value is UIApplicationStateInactive, the user tapped the action button; if the value is UIApplicationStateActive, the application was frontmost when it received the notification. This is similar to your solution using flags set in applicationWillEnterForeground and applicationDidBecomeActive but with system support. Disclaimer The facts and information provided to users in the pages of the Virtua website are for informational purposes only. Users should not rely on information on this Virtua website for any purpose other than for gaining general knowledge of the company. Material may be changed or updated without notice. Virtua is a data provider on behalf of Q4 Inc. Online Daters Say a Good Credit Score is More Attractive Than a Fancy Car RIVERWOODS, Ill.--(BUSINESS WIRE)-- Online daters might have better luck finding Mr. or Ms. Right if they swap out the profile picture of their expensive car with an image of their credit score, according to a recent survey by Discover and Match Media Group. The two companies collaborated on the independent survey of online daters to better understand the relationship between finance and romance. The survey found that a potential date’s credit score could—or perhaps should—be the difference between swiping left or right. For example, 58 percent of online daters say having a good credit score is more attractive than driving a nice car. Likewise, 50 percent think a good credit score is more attractive than an impressive job title, and 40 percent favor a good score over a physically fit body. “If you have a good credit score, flaunt it,” says Dr. Helen Fisher, Ph.D., chief scientific advisor for Match.com. “When it comes to dating, a good credit score ups your mate value, helping you win a responsible, long-term partner, more so than some other qualities that online daters might highlight on their profile. Money talks, but your credit score can speak more about who you are as a person, and singles agree that those with good credit tend to be conscientious and reliable.” A credit score is a measure of financial responsibility, which 69 percent of survey respondents say is a very or extremely important quality when looking for a person to date. Financial responsibility rated higher than several other important qualities, as 67 percent say a sense of humor is very or extremely important, 51 percent say attractiveness, 50 percent say ambition, 42 percent say courage and 39 percent say modesty. Both women and men value financial responsibility, as 77 percent of women and 61 percent of men say financial responsibility is a very or extremely important quality in a potential partner. What does good credit suggest about a potential date? When asked to identify characteristics of someone with a good credit score, 73 percent of survey respondents said responsible, 40 percent said trustworthy and 38 percent said smart. “A credit score is an important measure of financial responsibility as it rewards diligence and consistency over time when it comes to managing your finances, not necessarily how much money you make or what you have in the bank,” says Kate Manfred, Discover’s vice president of brand and consumer insights. “Regardless of your credit score, one of the keys to improving your credit health is simply being aware of your score. That knowledge can set you on the path toward improving or maintaining your score. Plus, it can spark an interesting—and important—conversation on a date.” Anyone interested in checking their FICO® Credit Score1, including those who are not Discover customers, can do so for free by going to Discover.com/CreditScorecard. In addition to a FICO® Score, Discover’s Credit Scorecard provides information and insight into the five categories that contribute to one’s FICO® Score. Online Daters Are Hesitant to Talk Finances While online daters think a potential partner’s finances are important, the survey found that the soonest most would feel comfortable disclosing financial details—such as their amount of debt, credit score, income and spending habits—would be within the first six months of a relationship. Just 7 percent or fewer would disclose such info before meeting someone in person. The majority of survey respondents say they are only slightly comfortable or not comfortable at all with the idea of sharing financial information on a dating app or website. This includes 69 percent who feel slightly comfortable or not comfortable at all sharing information about their amount of debt, 69 percent their credit score, 64 percent their income and 53 percent their spending habits. The one thing respondents do feel comfortable sharing on a dating website or app is their employment status, as 64 percent feel very or extremely comfortable sharing that information. Finances Are More Straining than Kids and Politics Despite their hesitancy, online daters would do well to have the money talk with their partner sooner rather than later. The survey found that finances are a more common relationship strain than goals for the future, career decisions, politics, kids and religion. In fact, the majority of those surveyed, 53 percent, say finances were a source of strain in a past or current relationship, and 18 percent say finances led to a break-up. Survey Insights Featured in T
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, input logic we_core_i, output logic we_mem_o, input logic [3:0] be_core_i, output logic [3:0] be_mem_o, input logic [31:0] stall_en_i, input logic [31:0] stall_mode_i, input logic [31:0] max_stall_i, input logic [31:0] gnt_stall_i, input logic [31:0] valid_stall_i ); import cv32e40p_pkg::*; import perturbation_pkg::*; `ifndef VERILATOR logic req_per_q, grant_per_q, rvalid_per_q; typedef struct { logic [ADDR_WIDTH-1:0] addr; logic we; logic [ 3:0] be; logic [DATA_WIDTH-1:0] wdata; logic [DATA_WIDTH-1:0] rdata; } stall_mem_t; class rand_gnt_cycles; rand int n; endclass : rand_gnt_cycles class rand_data_cycles; rand int n; endclass : rand_data_cycles mailbox #(stall_mem_t) core_reqs = new (); mailbox #(stall_mem_t) core_resps = new (); mailbox #(logic) core_resps_granted = new (); mailbox #(stall_mem_t) memory_transfers = new (); always_latch begin if (req_core_i) req_per_q <= 1'b1; else req_per_q <= 1'b0; end always_latch begin if (rvalid_mem_i) rvalid_per_q <= 1'b1; else rvalid_per_q <= 1'b0; end always_latch begin if (grant_mem_i) grant_per_q <= 1'b1; else grant_per_q <= 1'b0; end //Grant Process initial begin stall_mem_t mem_acc; automatic rand_gnt_cycles wait_cycles = new (); int temp; int stalls, max_val; #10;//wait at the very beginning while(1) begin @(posedge clk_i); grant_core_o = 1'b0; #1; if (!req_per_q) begin wait(req_per_q == 1'b1); end if ((stall_en_i[0]) && (stall_mode_i == STANDARD)) begin //FIXED NUMBER OF STALLS MODE stalls = gnt_stall_i; end else if ((stall_en_i[0]) && (stall_mode_i == RANDOM)) begin max_val = max_stall_i; temp = wait_cycles.randomize() with{ n >= 0; n<= max_val; }; stalls = wait_cycles.n; end else begin stalls = 0; end while(stalls != 0) begin @(negedge clk_i); stalls--; end @(negedge clk_i); if(req_per_q == 1'b1) begin grant_core_o = 1'b1; mem_acc.addr = addr_core_i; mem_acc.be = be_core_i; mem_acc.we = we_core_i; mem_acc.wdata = wdata_core_i; core_reqs.put(mem_acc); core_resps_granted.put(1'b1); end end end initial begin stall_mem_t mem_acc; automatic rand_data_cycles wait_cycles = new (); logic granted; int temp, stalls, max_val; while(1) begin @(posedge clk_i); rvalid_core_o = 1'b0; rdata_core_o = 'x; #1; core_resps_granted.get(granted); core_resps.get(mem_acc); if ((stall_en_i[0]) && (stall_mode_i == STANDARD)) begin //FIXED NUMBER OF STALLS MODE stalls = valid_stall_i; end else if ((stall_en_i[0]) && (stall_mode_i == RANDOM)) begin max_val = max_stall_i; temp = wait_cycles.randomize() with { n>= 0; n<= max_val; }; stalls = wait_cycles.n; end else begin stalls = 0; end while(stalls != 0) begin @(negedge clk_i); stalls--; end rdata_core_o = mem_acc.rdata; rvalid_core_o = 1'b1; end end initial begin stall_mem_t mem_acc; we_mem_o = 1'b0; req_mem_o = 1'b0; addr_mem_o = '0; be_mem_o = 4'b0; wdata_mem_o = 'x; while(1) begin @(posedge clk_i); #1; req_mem_o = 1'b0; addr_mem_o = '0; wdata_mem_o = 'x; core_reqs.get(mem_acc); req_mem_o = 1'b1; addr_mem_o = mem_acc.addr; we_mem_o = mem_acc.we; be_mem_o = mem_acc.be; wdata_mem_o = mem_acc.wdata; wait(grant_per_q); memory_transfers.put(mem_acc); end end initial begin stall_mem_t mem_acc; while(1) begin memory_transfers.get(mem_acc); wait(rvalid_per_q == 1'b1); @(negedge clk_i); mem_acc.rdata = rdata_mem_i; core_resps.put(mem_acc); end end `endif endmodule A headrest positioning system for automatically adjusting the position of a headrest of a vehicle seat. The headrest can be a power headrest that is part of a power seat system, where the position of the headrest can be preset by a seat occupant with the other positions of the seat in a memory function....http://www.google.com/patents/US20060250016?utm_source=gb-gplus-sharePatent US20060250016 - Automatically adjusting head restraint system A headrest positioning system for automatically adjusting the position of a headrest of a vehicle seat. The headrest can be a power headrest that is part of a power seat system, where the position of the headrest can be preset by a seat occupant with the other positions of the seat in a memory function. The system includes a seat occupant sensing system that senses the position of the seat occupant's head, eyes or other facial features to determine a desired position of the headrest. The system compares the actual position of the headrest to the desired position, and automatically adjusts the position of the headrest to the desired position. In one embodiment, an imaging system determines the position of the seat occupant's head. In another embodiment, the system determines the position of seat occupant's eyes based on the position of the driver side mirror. Images(7) Claims(22) 1. A headrest positioning system for automatically positioning a headrest of a vehicle seat, said system comprising: a headrest sensor for detecting the position of the headrest, said headrest sensor generating a headrest position signal indicative of the position of the headrest; a seat occupant detecting sub-
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THGenerateFloatTypes.h THGenerateComplexTypes.h THGenerateIntTypes.h THGenerateQUInt8Type.h THGenerateQInt8Type.h THGenerateQInt32Type.h THGenerateQTypes.h THLapack.h THStorage.h THStorageFunctions.h THTensor.h THTensorApply.h THTensorDimApply.h THVector.h THHalf.h THTensor.hpp THStorageFunctions.hpp THGenerator.hpp DESTINATION "${ATEN_INSTALL_INCLUDE_SUBDIR}/TH") install(FILES vector/AVX.h ../ATen/native/cpu/avx_mathfun.h DESTINATION "${ATEN_INSTALL_INCLUDE_SUBDIR}/TH/vector") install(FILES generic/THBlas.cpp generic/THBlas.h generic/THLapack.cpp generic/THLapack.h generic/THStorage.cpp generic/THStorage.h generic/THStorageCopy.cpp generic/THStorageCopy.h generic/THTensor.cpp generic/THTensor.h generic/THTensor.hpp generic/THTensorLapack.cpp generic/THTensorLapack.h generic/THTensorMath.cpp generic/THTensorMath.h generic/THTensorRandom.cpp generic/THTensorRandom.h generic/THVectorDispatch.cpp generic/THVector.h # See Note [TH abstraction violation] generic/THTensorFastGetSet.hpp DESTINATION "${ATEN_INSTALL_INCLUDE_SUBDIR}/TH/generic") 2001 Bolivian census The Tenth Census of Bolivia was conducted on 5 September 2001. The population was 8,274,325. References Category:2001 in Bolivia Category:Censuses in Bolivia BoliviaMa’an News Agency As Palestinian leaders prepare to seek UN recognition of statehood in September, there is increasing talk in the US, Israel and elsewhere of disbanding the UN agency for Palestinian refugees, the UN Relief and Works Agency, and handing responsibility for Palestinian refugees to the UN High Commission for Refugees (UNHCR). Some argue UNHCR would resettle the refugees, robbing them of their right to return to their homes. But are these ideas based on a sound understanding of international law and refugee practice? Are they based on a real grasp of the mandates of UNRWA and UNHCR? To set the record straight, Ma‘an turned to UNRWA spokesman Chris Gunness. It is argued that if UNRWA was disbanded and responsibility for Palestinian refugees handed over to UNHCR they would be resettled out of Israel and give up the right of return. Is this the case and if not, what would UNHCR’s role be? Gunness: This is not the case. Palestine refugees are entitled to a just and lasting solution to their plight. This solution would optimally be achieved by the parties and political actors in the context of a negotiated conclusion of the Israeli-Palestinian conflict, and must be in accordance with UN resolutions and international law. It should also be voluntary which means consulting the refugees. There is no merit to claims that the Palestine refugee issue can be addressed by transferring responsibility for Palestine refugees from UNRWA to another agency. Please note two important caveats. First, UNRWA and UNHCR work to distinct mandates, operational and legal definitions, areas of operation, operational realities and constitutive instruments. My responses are consistent with these distinctions and should not be read to assume or imply direct correspondence between the two agencies or their refugee definitions. Rather, I should be understood to draw on the shared premises and common concepts that underpin the precepts applied by UNRWA and UNHCR in their efforts to assist and protect refugees in their respective areas of responsibility. Second, UNRWA is not in a position to speak for UNHCR and does not purport to speak for UNHCR. However, responses to your questions require reference to documents that are posted on UNHCR’s website and are available to the public. My responses are based on UNRWA’s understanding of the plain meaning of these documents as well as the Agency‘s own appreciation of its mission and its knowledge of the system of international law and practice that govern the protection of refugees globally. Established principles and practice – as well as realities on the ground - clearly refute the argument that the right of return of Palestine refugees would disappear or be abandoned if UNHCR were responsible for these refugees. Over decades of international practice, refugee situations have been resolved in three principal ways: local integration, resettlement in third countries and voluntary repatriation. Of these, the voluntary return of refugees to their country of origin has come to be recognised by refugees, states and international agencies as the optimal solution to the plight of refugees. It is equally recognised that for refugees everywhere, a precondition for solutions to refugee situations is the resolution by political actors of the underlying causes of dispute and conflict. This point is made in the 2008 UNHCR document, Protracted Refugee Situations: A discussion paper prepared for the High Commissioner’s dialogue on Protection Challenges. Paragraph 7 of the document observes that "Protracted refugee situations are usually created and sustained by the failure to resolve … differences in a peaceful manner and in a way that respects human rights." Paragraph 9 of this document goes on to note that: "[…] the functions of refugee protection and humanitarian action, vital as they are, can make only a very modest contribution to the prevention and resolution of conflicts that oblige people to live in exile for long periods of time. If those objectives are to be attained, political will and political action are required on the part of states, regional organisations and relevant components of the UN system, including the Security Council and General Assembly." The preface to the UNHCR Handbook on Voluntary Repatriation states that "voluntary repatriation is usually viewed as the most desirable long-term solution by the refugees themselves as well as by the international community. UNHCR‘s humanitarian action in pursuit of lasting solutions to the refugee problems is therefore oriented, first and foremost, in favour of enabling a refugee to exercise the right to return home in safety and with dignity." Chapter 1, paragraph 6 of the UNHCR Handbook states that "the right of refugees to return to their country of origin is fully recognised in international law. The Universal Declaration of Human Rights (1948) established in article 13 (2) that "Everyone has the right to leave any country, including his own, and return to his country." While the Universal Declaration of Human Rights, as a Resolution of the General Assembly, is not a treaty requiring signature or consent, it sets the code of conduct and serves as a point of reference for all universal and regional human rights instruments subsequently adopted." The UNCHR Handbook in its subsequent chapters sets out the obligations of states and of UNHCR in protecting the right of return in the context of voluntary repatriation as well as monitoring, protecting and advocating for the rights of refugees who have returned home. Conclusion 4 of the report to UNHCR’s Executive Committee of 2005, on Local Integration states "Voluntary repatriation, local integration and resettlement are the traditional durable solutions and […] all remain viable and important responses to refugee situations;" "voluntary repatriation, in safety and dignity, where and when feasible, remains the most preferred solution in the majority of refugee situations;" a combination of solutions, taking into account the specific circumstances of each refugee situation, can help achieving long lasting solutions." It is often said that UNRWA perpetuates the Palestinian refugee problem by granting refugee status through the generations and that handing the refugees over to UNHCR would not allow this. Is this the case? This is not the case. As I have already noted, Palestine refugees are entitled to a just and lasting solution to their plight. In the absence of -- and pending the realisation of -- such a solution, it stands to reason that their status as refugees will remain. Questions raised about the passing of refugee status through generations stem from a lack of understanding of the international protection regime. These questions serve only to distract from the need to address the real reasons for the protracted Palestinian refugee situation, namely the absence of negotiated solution to the underlying political issues. UNHCR‘s Handbook on Procedures and Criteria for determining Refugee Status provides in paragraph 184: "If the head of a family meets the criteria of the definition, [for refugee status] his dependants are normally granted refugee status according to the principle of family unity." In effect, refugee families everywhere retain their status as refugees until they fall within the terms of a cessation clause or are able to avail themselves of one of three durable solutions already mentioned -- voluntary repatriation, local integration or resettlement in a third country. Also, Chapter 5 of the UNHCR publication, Procedural Standards for Refugee Status Determination under UNHCR’s Mandate is very clear that in accordance with the refugee’s right to family unity, refugee status is transferred through the generations. According to Chapter 5.1.2 "the categories of persons who should be considered to be eligible for derivative status
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2))$ is a deformation retract of $\Omega^{(1,0)}(n+1,n+1)$, there exists the homotopy equivalent fiber map$$\mathfrak{i}_{SO}:SO_{n+2}(\gamma_{G_{n+1}}^{n+1}\oplus\varepsilon_{G_{n+1}}^{1},TP\oplus\varepsilon_{P}^{2})\longrightarrow\boldsymbol{\Omega}_{n+1}^{(1,0)}=\Omega^{(1,0)}(\gamma_{G_{n+1}}^{n+1},TP\oplus\varepsilon _{P}^{1})$$ over $G_{n+1}\times P$ associated to $i_{n+1}^{SO}$. The image is denoted by $\mathbf{SO}_{n+2}$. Furthermore, $\mathfrak{i}_{SO}$ induces the bundle map $$\mathfrak{B}:\widehat{\gamma}_{\boldsymbol{\Omega}_{n+1}^{(1,0)}}^{\ell }|_{\mathbf{SO}_{n+2}}\longrightarrow\widehat{\gamma}_{\boldsymbol{\Omega }_{n+1}^{(1,0)}}^{\ell}$$ covering the inclusion $\mathbf{SO}_{n+2}\rightarrow\boldsymbol{\Omega}_{n+1}^{(1,0)}$. \(i) The fiber map $\mathfrak{i}_{SO}$ is a homotopy equivalence. \(ii) The Thom map$$T(\mathfrak{B)}:T\left( \widehat{\gamma}_{\boldsymbol{\Omega}_{n+1}^{(1,0)}}^{\ell}|_{\mathbf{SO}_{n+2}}\right) \longrightarrow T\left( \widehat {\gamma}_{\boldsymbol{\Omega}_{n+1}^{(1,0)}}^{\ell}\right)$$ is a homotopy equivalence. Let $SO(TP\oplus\varepsilon_{P}^{1})$ denote the total space of the principal bundle over $P$ associated to $TP\oplus\varepsilon_{P}^{1}$, whose fiber is $SO(n+1)$. Let $(SO(\ell)\times E_{n+1})\backslash SO(n+\ell+1)$ be the Stiefel manifold. Consider the natural actions of $SO(n+1)$ on $SO(TP\oplus \varepsilon_{P}^{1})$ from the right-hand side and on $SO(n+2)$ through $SO(n+1)\times E_{1}$ from the left-hand side, and the natural actions of $SO(n+1)$ on $SO(n+2)$ through $SO(n+1)\times E_{1}$ from the right-hand side and on $(SO(\ell)\times E_{n+1})\backslash SO(n+\ell+1)$ from the left-hand side respectively. Then we can express as$$\begin{aligned} \mathbf{SO}_{n+2} & =SO(TP\oplus\varepsilon_{P}^{1})\underset{SO(n+1)}{\times}SO(n+2)\\ & \text{ \ \ \ \ \ \ \ \ }\underset{SO(n+1)}{\times}((SO(\ell)\times E_{n+1})\backslash SO(n+\ell+1)).\end{aligned}$$ Identify the quotient space $SO(TP\oplus\varepsilon_{P}^{1})/SO(n+1)$ with $P$. Then we have the projection $pr_{P}^{SO}:\mathbf{SO}_{n+2}\rightarrow P$ by forgetting the component $SO(n+2)\underset{SO(n+1)}{\times}((SO(\ell)\times E_{n+1})\backslash SO(n+\ell+1))$, denoted by $\mathfrak{f}$, which is the canonical fiber of $pr_{P}^{SO}$. Let $pr_{S^{n+1}}^{\mathfrak{{f}}}:\mathfrak{f}\rightarrow SO(n+2)/SO(n+1)=S^{n+1}$ be the projection forgetting the component $(SO(\ell)\times E_{n+1})\backslash SO(n+\ell+1)$. Since the last space is $(\ell-1)$-connected,$$(pr_{S^{n+1}}^{\mathfrak{f}})_{\ast}:\pi_{i}(\mathfrak{f})\rightarrow\pi _{i}(S^{n+1})$$ is an isomorphism for $i<\ell$. Hence, we have the following lemma. The homomorphism $(pr_{P}^{SO})_{\ast}:\pi_{i}(\mathbf{SO}_{n+2})\rightarrow\pi_{i}(P)$ is an isomorphism for $i<n+1$ and is an epimorphism for $i=n+1$. Let us define a bundle map$$\mathbf{b}_{\mathcal{T}}:(\pi_{G_{n+1}}^{k})^{\ast}(\gamma_{G_{n+1}}^{n+1})|_{\mathbf{SO}_{n+2}}\longrightarrow TP\oplus\varepsilon_{P}^{1}$$ as follows. We denote an element of $\mathbf{SO}_{n+2}$ and $(\pi_{G_{n+1}}^{k})^{\ast}(\gamma_{G_{n+1}}^{n+1})|_{\mathbf{SO}_{n+2}}$ by $[a,y,h]$ and by $[a,y,h,\mathbf{v]}$ respectively, where $a\in G_{n+1}$, $y\in P$, $\mathbf{v\in}a$ and $h:a\rightarrow T_{y}P\oplus\mathbb{R}$ is an isomorphism preserving orientations and norms. Then we set $\mathbf{b}_{\mathcal{T}}([a,y,h,\mathbf{v])}=h(\mathbf{v)}$. Let us consider the trivialization $(t_{P}\oplus id_{P}\times\mathbb{R})\circ(id_{TP}\oplus\mathbf{k}_{P}^{\backsim}):TP\oplus\varepsilon_{P}^{1}\oplus\nu _{P}^{\ell}\rightarrow\varepsilon_{P}^{n+\ell+1}$. By [@FoldSurg Proposition 3.3], there exists a bundle map$$\mathbf{b}_{\nu}:\widehat{\gamma}_{\boldsymbol{\Omega}_{n+1}^{(1,0)}}^{\ell }|_{\mathbf{SO}_{n+2}}\rightarrow\nu_{P}^{\ell}$$ such that $(t_{P}\oplus id_{P}\times\mathbb{R})\circ(id_{TP}\oplus \mathbf{k}_{P}^{\backsim})\circ(\mathbf{b}_{\mathcal{T}}\oplus\mathbf{b}_{\nu })\circ t_{\boldsymbol{\Omega}_{n+1}^{(1,0)}}|_{\mathbf{SO}_{n+2}}$ is homotopic to $pr_{P}^{SO}\times id_{\mathbb{R}^{n+\ell+1}}$. Then we have the following lemma. The homomorphism induced from the Thom map of $\mathbf{b}_{\nu}$$$T(\mathbf{b}_{\nu})_{\ast}:\pi_{i+\ell}\left( T(\widehat{\gamma }_{\boldsymbol{\Omega}_{n+1}^{(1,0)}}^{\ell}|_{\mathbf{SO}_{n+2}})\right) \longrightarrow\pi_{i+\ell}\left( T(\nu_{P}^{\ell})\right)$$ is an isomorphism for $i<n+1$ and is an epimorphism for $i=n+1$. By Lemma 6.2, (6.2), [@SpaAT Section 5, 9 Theorem] and the Thom Isomorphism Theorem,$$T(\mathbf{b}_{\nu})_{\ast}:H_{i+\ell}\left( T(\widehat{\gamma}_{\boldsymbol{\Omega}_{n+1}^{(1,0)}}^{\ell}|_{\mathbf{SO}_{n+2}})\right) \longrightarrow H_{i+\ell}\left( T(\nu_{P}^{\ell})\right)$$ is an isomorphism for $i<n+1$ and is an epimorphism for $i=n+1$. Since $T((\pi_{G_{n+1}}^{k})^{\ast}(\widehat{\gamma}_{G_{n+1}}^{\ell})|_{\mathbf{SO}_{n+2}})$ and $T(\nu_{P}^{\ell})$ are simply connected, it follows from the Hurewicz Isomorphism Theorem that$$T(\mathbf{b}_{\nu})_{\ast}:\pi_{i+\ell}\left( T(\widehat{\gamma }_{\boldsymbol{\Omega}_{n+1}^{(1,0)}}^{\ell}|_{\mathbf{SO}_{n+2}})\right) \longrightarrow\pi_{i+\ell}\left( T(\nu_{P}^{\ell})\right)$$ is an isomorphism for $i<n+1$ and is an epimorphism for $i=n+1$. According to [@SpaDual], let $\{S^{n+\ell},T(\nu_{P}^{\ell})\}$ denote the set of S-homotopy classes of S-maps $S^{i}\wedge S^{n+\ell}\rightarrow S^{i}\wedge T(\nu_{P}^{\ell})$ $({i}\geq0)$. An element of $\{S^{n+\ell},T(\nu_{P}^{\ell})\}$ represented by a map $\alpha:S^{n+\ell}\rightarrow S^{i}\wedge T(\nu_{P}^{\ell})$ is written as $\{\alpha\}$. Since $\ell\gg n$, $\{S^{n+\ell},T(\nu_{P}^{\ell})\}$ is isomorphic to $\pi_{n+\ell}\left( T(\nu_{P}^{\ell
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amme niiden lausekkeiden poistamista, joilla välittäjille myönnetään sopimusperusteinen suoja, on yksinkertaisesti se, että kilpailulainsäädäntö ei ole asianmukainen väline sopimusosapuolten välisen mahdollisen epätasapainon käsittelemiseen. Nämä kysymykset, kuten keskusteltiin, kun laadimme asetusta (EY) N:o 1/2003, kuuluvat kauppaoikeuden alaan. Automarkkinoiden kaltaisilla kilpailukykyisillä markkinoilla kilpailulainsäädännöllä ei pitäisi puuttua eri sopimusosapuolten väliseen voimatasapainoon. Niin tekeminen olisi tungettelevaa. Meidän on toimittava oikeasuhteisesti, kun puutumme markkinoiden toimintaan. Kuulemisprosessissa saimme selville myös muita, ehkä vähemmän myönteisiä asioita: toisin kuin autojen hinnat korjaustyön keskimääräinen hinta on itse asiassa noussut viime vuosien aikana. Korjaus ja huolto ovat kuluttajille hyvin tärkeitä: ei vain turvallisuuden ja luotettavuuden takia, vaan myös siksi, että korjauslaskut ovat 40 prosenttia auton omistamisen kokonaiskustannuksista. Valitettavasti riippumattomien korjaamojen valmiuksia kilpailla valtuutettujen korjaamojen kanssa haittaavat edelleen monet rajoitukset, mukaan luettuna varaosien ja teknisten tietojen rajallinen saatavuus. Uudistuksellamme pyritään siksi antamaan riippumattomille korjaamoille parempi pääsy varaosiin ja teknisiin tietoihin ja estämään se, että ne suljetaan markkinoilta muilla, uudemmilla käytännöillä. Se johtaa laadukkaampiin korjauspalveluihin ja alempiin hintoihin. Lopuksi, uskon lujasti, että uudet puitteet ovat kuluttajille entistä suotuisammat. Ensisijainen tavoitteemme on lisätä kilpailua jälkimarkkinoilla - korjaus ja huolto - joilla sitä on vähiten? Vaikka ajoneuvojen valmistajien kaupallinen asema saattaa olla vahva välittäjiin verrattuna, ne taistelevat raivokkaasti toistensa kanssa, ja siksi nyt ei tarvita poikkeusta, tällaisia sopimuksia koskevan kilpailun säilyttämiseksi, alakohtaisia sopimuksia koskevasta ryhmäpoikkeusasetuksesta, jonka komissio antoi äskettäin ja joka myös tulee voimaan tämän kuukauden lopussa. Todellakin, komissio ja erityisesti minun yksikköni, kilpailun pääosasto, valvovat alaa hyvin huolellisesti, eikä pitäisi olla epäilystäkään komission päättäväisyydestä valvoa kilpailusääntöjä ja ryhtyä tarvittaviin toimiin, jos huomataan joitakin vakavia rikkomuksia tai puutteita. Othmar Karas Arvoisa puhemies, arvoisa komission jäsen, hyvät kollegat, olemme nyt kuulleet paljon. Tällä suullisella kysymyksellä ja päätöslauselmalla halusimme antaa autojen välittäjille ja pienille ja keskisuurille yrityksille äänen, koska komissio ei ole kiinnittänyt viime vuosina tarpeeksi huomiota tähän ääneen. Kuulemisen aikana ennen kaikkea autojen välittäjät ilmaisivat huolta ja epävarmuutta epätasa-arvoisesta kohtelusta valmistajiin verrattuna. Oikeudellinen epävarmuus otettiin esiin kuten myös kilpailun väheneminen pienten autonvälittäjien kohtaamien ongelmien takia. Emme kuitenkaan ole saaneet vastausta. Pyydän teitä - minuuttia vaille 12 - käyttämään 21 päivää ennen toukokuun 26. päivää sisällyttääksenne päätöslauselman, jonka parlamentti antaa huomenna, asetukseenne, jotta voitte tulla autonvälittäjiä puolitiehen vastaan muuttamatta suuntaa, jonka komissio haluaa valita. Olkaa hyvä ja suhtautukaa parlamenttiin ja autonvälittäjien huoliin vakavasti ja sisällyttäkää heidän huolensa ja pienten ja keskisuurten yritysten huolet asetukseen. Olle Ludvigsson S&D-ryhmän puolesta. - (SV) Arvoisa puhemies, haluaisin korostaa neljää kysymystä tässä keskustelussa. Ensinnäkin, on olemassa valitettava pyrkimys asettaa autoteollisuuden pienet ja suuret yritykset toisiaan vastaan. Niillä on tietyssä määrin erilaiset edut, mutta meidän on ensisijaisesti keskityttävä luomaan sääntelyjärjestelmä, jonka avulla ne voivat tehdä tehokkaasti yhteistyötä. Toiseksi, on hyvin myönteinen merkki, että uusien autojen markkinoiden kilpailu on parantunut viime vuoden aikana. Tämä on hyvä esimerkki siitä, että mitkään markkinat eivät ole mahdottomia ja että pitkällä aikavälillä on mahdollista saada paljon aikaan kilpailua vahvistavilla toimenpiteillä. Toivottavasti jälkimarkkinoilla kehitys on tulevaisuudessa yhtä myönteistä. Kolmanneksi, on tärkeää, että komissio seuraa hyvin aktiivisesti kehitystä uusien autojen markkinoiden kilpailun osalta. Sitä pitäisi valvoa jatkuvasti. Kaikkien asianosaisten osapuolten pitäisi saada mahdollisimman pian lopulliset tiedot säännöistä, joita sovelletaan vuoden 2013 kesäkuusta alkaen. Neljänneksi, meidän pitäisi tehostaa keskustelujamme siitä, miten aiomme vaihtaa vihreisiin, ympäristön kannalta suotuisampiin autoihin. Se on ehdottomasti olennaisen tärkeä prosessi. Toisaalta, kilpailusääntöjen on oltava joustavia niiden tukien osalta, joita tarvitaan, jotta sähköajoneuvot ja muut ympäristön kannalta suotuisat vaihtoehdot voivat vakiintua markkinoilla, ja toisaalta säännöillä on varmistettava, että ympäristön kannalta suotuisat autot eivät joudu epäedulliseen asemaan vähittäisalalla tai jälkimarkkinoilla. Cristian Silviu Buşoi ALDE-ryhmän puolesta. - (EN) Arvoisa puhemies, auton hankintaa ja omistamista pidetään yhtenä kotitalouksien suurimpana menoeränä. Kilpailupolitiikan perimmäinen tavoite on varmistaa kuluttajien valinnanvapaus ja tuotteiden saatavuus alemmilla ja koht
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premium butters, our tasters had trouble telling the difference, even when tasted plain. Regular unsalted butter contains 81 to 82 percent fat; premium brands have 83 to 86 percent fat. Because higher-fat butter remains solid over a wider temperature range, we like it when making croissant dough and other recipes where rapid softening of the butter would cause problems. GAUGING BUTTER TEMPERATURE CHILLED **Temperature** : About 35 degrees **Method** : Cut into small pieces and freeze until very firm, 10 to 15 minutes. **How To Test** : It should not yield when pressed with a finger and should be cold to the touch. **Why it Matters** : Cold butter is cut into flour for flaky pie dough. SOFTENED **Temperature** : 60 to 68 degrees **Method** : Let refrigerated butter sit at room temperature for 30 to 60 minutes. **How to Test** : At 60 degrees, it should yield to slight pressure and crack when pressed. At 68 degrees, it should bend easily without breaking and give slightly when pressed. **Why it Matters** : Sugar can be creamed with softened but still cool butter (60 degrees) or completely softened butter (68 degrees) to make different types of cakes (see concepts 46 and 47). MELTED AND COOLED **Temperature** : 85 to 94 degrees **Method** : Melt in small saucepan or microwave-safe bowl and let cool for about 5 minutes. **How to Test** : It should be fluid and slightly warm to the touch. **Why it Matters** : Water in liquefied butter mixes with flour to create chewy cookies. # CONCEPT 44 ## Vodka Makes Pie Dough Easy Whoever coined the phrase "easy as pie" clearly had never made a pie. Yes, the recipe for a pie crust sounds simple to prepare. Mix flour with salt and sugar, cut in fat, add just enough cold water so that the dough sticks together, then roll out and bake. You want a dough that bakes up tender and flaky and is relatively easy to work with. But the reality is that pie dough often bakes up tough and leathery and it's often a pain to work with—cracking and tearing are common problems. HOW THE SCIENCE WORKS The trouble with pie dough is that it never seems to behave the same way twice. This means that you need to troubleshoot every time you make a pie. And troubleshooting requires experience, so that you can recognize what's going on with that particular dough and then make the proper adjustments. Most modern cooks make pies only a few times a year and can't be expected to troubleshoot at all. Perfect pie dough has just the right balance of tenderness and structure. The former comes from fat, the latter from long protein chains called gluten that form when flour mixes with water. Too little gluten and the dough won't stick together—but too much and the crust turns tough. We've developed an approach that keeps gluten in check but also allows for an unusually supple dough that's easy to handle and reduces the chances of overworking. Our revolutionary pie dough recipe removes the guesswork by relying on a secret ingredient: It all comes down to alcohol. You see, gluten forms readily in water. Water hydrates the proteins in flour. This means that the water molecules attach themselves to the proteins through the formation of hydrogen bonds. Hydrogen bonds are weak, electrostatic bonds that hold water molecules onto the surface of the protein molecules, giving the coiled protein molecules flexibility to unravel and bond with each other in order to form strands of gluten. (For more on this, see concept 38.) But gluten won't form in alcohol. The ethyl alcohol in vodka and other liquors does not attach itself in the same way as water. Because of this, it does not hydrate the proteins, and therefore does not aid in gluten formation. By replacing some of the water in our recipe with vodka (which contains 40 percent ethanol and just 60 percent water), we're able to add more liquid to the dough so it stays soft and malleable, but without increasing the danger of the crust turning tough. But what if you don't have vodka in your pantry—can another 80-proof liquor be used in its place? We baked pie crusts made with rum, whiskey, and gin and compared them side by side with our vodka crust. Surprisingly, the vast majority of our tasters could not distinguish among the different flavors of booze. In fact, they could not taste the alcohol at all. All of the crusts had a clean taste and flaky texture. So if vodka is not your tipple of choice, go ahead and substitute any 80-proof liquor. ADDING ALCOHOL TO PIE DOUGH WATER ALONE In pie dough made with water alone, the water interacts with the flour to form a good deal of gluten, which can cause the dough to be tough. VODKA AND WATER Gluten does not form in alcohol. Therefore pie dough made with a mixture of vodka and water has less gluten and is much more tender. TEST KITCHEN EXPERIMENT While science might provide support for using vodka in pie dough, we weren't going to be convinced of its value until we could see it with our own eyes. To determine whether or not the use of vodka makes a difference in the texture of a flaky pie crust, we baked batches of our Foolproof Double-Crust Pie Dough—one with a 1:1 ratio of vodka to water (¼ cup of each), and another with just water (½ cup of water total). To make cross-section comparisons easier, we ditched the pie plates and instead rolled out the dough into large sheets and cut them into 5-inch by 2-inch rectangles, which we baked on a parchment-lined baking sheet. Once the strips of baked pie crust were cool, we balanced them on two small metal cups, like a tightrope, and placed a 250-gram cup of pennies on top of each crust to assess its "toughness." THE RESULTS The pie crust made with vodka immediately snapped in two, dropping the cup of pennies, which then spilled out onto the counter. The pie crust made with only water remained intact, however, and kept its pennies balanced for about a minute. Tasters said that the vodka pie crust was much more tender and flaky. The all-water crust was noticeably tougher. THE TAKEAWAY Because gluten will not form in the presence of alcohol, the pie crust made with equal parts vodka and water had a much less developed gluten network than the pie crust made with water alone. And less gluten makes for a tender and flaky crust. In addition, using a mixture of vodka and water allows us to add more liquid to the dough to get it to be as malleable and easy to work with as possible without causing excessive toughness. The lesson? Vodka isn't just for drinking. As a secret ingredient in pie crust, it can both make the pie crust more tender, and the life of the cook trying to roll out the dough easier. THE POWER OF VODKA: EASY-TO-ROLL, TENDER PIE CRUST We made two batches of our pie crust, one with the correct ratio of vodka to water, the other with water alone, and then tested the results with a cup of pennies. The flaky vodka dough didn't stand a chance. VODKA AND WATER This tender pie crust cracked immediately. WATER ALONE This tougher crust held the pennies for a full minute. ### GLUTEN MINIMIZATION AT WORK PIE DOUGH Replacing part of the ice water with vodka is the key to creating a well-hydrated dough that is easy to work with. And because the vodka doesn't activate gluten, our dough bakes up flaky. In contrast, most well-hydrated doughs made with just ice water bake up tough and leathery because the extra water activates too much gluten. In addition to the recipes in this concept, pie dough is a key ingredient in Pumpkin Pie and Lemon Meringue Pie. #### FOOLPROOF DOUBLE-CRUST PIE DOUGH MAKES ENOUGH FOR ONE 9-INCH PIE * * * Vodka is essential to the tender texture of this crust and imparts no flavor—do not substitute water. This dough is moister than most standard pie doughs and will require lots of flour to roll out (up to ¼ cup). A food processor is essential for making this dough—it cannot be made by hand. 2½ | cups (12½ ounces) all-purpose flour ---|--- 2 | tablespoons sugar 1 | teaspoon salt 12 | tablespoons unsalted butter, cut into ¼-inch pieces and chilled 8 | tablespoons vegetable shortening, cut into 4 pieces and chilled ¼ | cup vodka, chilled ¼ | cup ice water | 1. Process 1½ cups flour, sugar, and salt together in food processor until combined, about 5 seconds. Scatter butter and shortening over top and continue to process until incorporated and mixture begins to form uneven clumps with no remaining floury bits, about 15 seconds. 2. Scrape down bowl and redistribute dough evenly around processor blade. Sprinkle remaining 1 cup flour over dough and pulse until mixture has broken up into pieces and is evenly distributed around
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have some bad news about your car." "Which one?" "I think it's best you see for yourself." "I'll let them know we're on our way." "What do you know about this guy?" "He's another c.I." "Peter leans on him when neal's not around." "Really?" "We should talk to him." "No, let's let it play out." "Let's see where he leads us." "So, Thursday has a view, huh?" "To say Thursday has a view... is like saying the hubble telespe... has a magnifying glass." "It ithe most spectacular cityscape... our fair city has to offer." "Really?" "I have to go now." "Ay." "Are you gonna watch "moon landing..." "factr fiction?"..." "No." "Oh." "Then it leaves with me." "It was nice to see you, Mrs. suit." "Nice to see you, too, moz." "Thanks for the vino." "It was neal's." "Looks like our c.I. 'S left the building." "You want us to follow him or stay here?" "We should follow him." "We do both." "My guys stay and monitor the house." "We'll follow the miniature Caffrey." "I guess it's "put your c.I. To work" day." "This way." "Pretend you know me." "Give me a reason." "I've given your sweetheart safe passage, and in about two minutes, we're gonna clear his name." "They got to be talking about Burke and Franklin." "Excuse me, guys, I got to take this." "This is neal." "Hey." "Are you with deckard?" "Yeah, yeah." "Are you there, sir?" "I am." "Who that?" "Tell him it's bancroft." "It's bancroft." "Diana should be with stan volker." "Yeah." "Uh-huh." "That's correct." "Give me the phone." "Look, I think deckard wants to speak with you." "Caffrey, you still there?" "Did you lose him?" "It's deckard, sir." "Deckard?" "Put Caffrey back on." "Yes, sir." "I'm back." "Okay." "Have you ever run a prisoner's dilemma?" "I've been in one." "Well, now's your chance to run it on a U.S. marshal." "You clear on what to do?" "Crystal clear." "Thank you, sir." "What's going on?" "Just follow my lead." "$tan 1 was stolen earlier today... and apparently taken on quite a joy ride." "They thought they could bring it here for parts." "What are they doing in there?" "I think you know what they're doing in there." "That's it." "Who did this?" "We have them in custody, Mr. volker." "Don't worry." "Well, they're gonna pay." "Just need your signature..." "If you could read over this statement for me." "I think you'll find everything's in order." "Volker's cutting a deal with the FBI." "He's selling you out." "Yep, there it is..." "a signed confession." "See, once you showed up at volker's office, he knew it was only a matter of ti before you turned on him." "He made a deal." "Come on, deckard." "Don't make it harder than it is." "There is one more thing." "What is this all about?" "Deckard says you paid off an FBI Agent... to intimidate and kill witnesses in federal trials." "You're looking at 25 to life..." "Unless you start talking." "Deckard came up with the whole thing." "What do you want to know about him?" "Give it up." "Stay back!" "Hands up, deckard!" "It's over." "Put the gun down on the ground!" "You realize the grief you caused me with bancroft... when you fled?" "Being on this side of a manhunt... isn't all peaches and dandelions, is it?" "Beats being led away in cuffs." "Good working with you, deckard." "How'd it go?" "They've cleared Franklin of all charges." "Bancroft's reinstating him into the white collar division." "That's great work, everyone." "Let's get some rest." "Neal..." "Good work." "Thank you." "I'll be headed home, too." "Won't be going to the Powell today, 'cause, you know, it's outside my radius." "Please?" "Thanks for playing last night, moz." "Oh, the follow-the-leader stuff?" "That was child's play." "The reason I'm calling now... is because I've obtained some information since then." "What'd you find?" "I know who Kate called from the plane." "It was the FBI Agent who set up the deal between you and Kate." "Garrett Fowler." "Now I need to find him." "Caffrey!" "I'll get right back to you." "Sir." "Come here." "You planning on seeing this?" "Well, yeah, I was, but, you know, it's out of my range and..." "Uh-huh." "I've wanted to see this thing since it opened." "Let's go." "You know, from the moment I met you," "I could tell you're a man of refined tastes." "Oh, I know, hon." "I'll be home. 15 minutes, tops." "Oh, I can't wait, either." "Just a few hours sleep, and I'll be yours all day..." "And night."My First (and perhaps only) Blogging Award! My friend Susie has nominated me for the Very Inspiring Blogger Award. She is so sweet. Her blog is SusieShy45, and it always a joy to read: so please check it out. This is my second blogging host site, and I love WordPress: I have made so many friends and found so many blogs to read some days I can’t keep up. I started a blog because I want to write. Good reason, right? What I have found a vivid community of bloggers that I never expected. They are supportive, funny and very necessary to me. I thank everyone who reads my blog, and hope that I will continue to interest, entertain or inspire you (whatever it takes to keep you reading 😉 ) There are some rules I need to follow to accept this award, the first was taken care of by thanking Susie (which I would have done anyway). The second is that I need to list the rules and display the award (as if I wouldn’t!), the third is share seven facts about myself (forthcoming) and the fourth is that I nominate 15 fellow bloggers for the award (also forthcoming). Seven Facts about me: 1) In my 20s I was terribly depressed that I would never write anything to measure up to War & Peace 2) I have an odd combination of OCD and ADD, which makes me both compulsive and a scatterbrain ( I am not diagnosed, just have certain tendencies that way that have been generally noticed by most people I come in contact with) 3) I love anything that has four legs and a tail, and, fortunately, they love me back 4) I am currently unemployed and working to get a certification in Medical Admin Assistant to find a grown-up career 5) I really enjoy helping people 6) I was a farmer 7) I no longer care if I write War & Peace, I happy to write on my two blogs and see what comes I chose my bloggers for different reasons. Some are inspiring for the quality and quantity they write. It can be difficult to post several times a week and still be interesting and relevant. These bloggers do that. Some I picked for what they write. Opening a vein and spilling your life’s blood for the world to see is hard, and it is inspiring how unflinchingly these bloggers do that.Q: Loading images in array Java Which is the best way to store images in an array? I'm using ImageIO and I now wish to store them in an array. A: PixelGrabber is what you want. Image img = null; try { img = ImageIO.read(new File("img.png")); } catch (IOException e) { e.printStackTrace(); } int w = img.getWidth(null); int h = img.getHeight(null); int[] pixels = new int[w * h]; PixelGrabber pg = new PixelGrabber(img, 0, 0, w, h, pixels, 0, w); try { pg.grabPixels(); } catch (InterruptedException e) { System.err.println("interrupted waiting for pixels!"); return; } if ((pg.getStatus() & ImageObserver.ABORT) != 0) { System.err.println("image fetch aborted or errored"); return; } for (int i = 0; i < pixels.length; i++) System.out.println(pixels[i]); A: If you read the whole images in memory, you can
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-09-00012} ----------------------------------------------- ### 5.2.1. Deep Learning Used for Antibody Lead Optimization {#sec5dot2dot1-antibodies-09-00012} A successful application of deep learning within the domain of interaction prediction comes from a sequence-based approach proposed to optimize an existing antibody candidate by Mason et al. \[[@B35-antibodies-09-00012]\]. Rather than using a public domain dataset, the authors generate a relatively small number of variants (5 × 10^4^) of an existing therapeutic antibody by introducing mutations to the H3 regions of the CDR and screening the variants for binding against a target antigen. The H3 sequences, labeled as binding or non-binding, were used as input to long-term-short-term recurrent neural networks and convolutional neural networks which were trained to predict the binding label of the sequences. Trained networks were then used to filter a computationally generated set of 7.2 × 10^7^ candidate sequences to 3.1 × 10^6^ predicted binders. Experimental testing showed that 30 out of 30 randomly selected predicted binding sequences bound specifically to the target antigen, with one of the thirty exhibiting a three-fold increase in affinity. The significance of this method is highlighted by the comparative analysis with a structure-based approach. The authors demonstrate that the number of new binding sequence suggestions generated by the structural modeling software is orders of magnitude smaller than the actual expected binding sequence space and that the free energy estimation of the modelled structures could not be used as a reliable classifier of binding activity. While structure-based methods have the potential to represent richer features for a given input, sequence-based methods benefit from more data availability due to developed experimental methods such as next-generation sequencing. ### 5.2.2. Ens-Grad {#sec5dot2dot2-antibodies-09-00012} Another sequence optimization algorithm, Ens-Grad, uses an ensemble of neural networks and gradient ascent to optimize an H3 seed sequence \[[@B36-antibodies-09-00012]\]. Briefly, Liu et al. report training an ensemble of six neural networks (five convolutional) using experimental phage display data generated from panning experiments. Panning experiments approximate enrichment in binding affinity by subjecting a set of H3 sequences bound to phages to a binding competition where non-binders are washed away and binders are kept for subsequent rounds \[[@B37-antibodies-09-00012]\]. Several different models with varying architectures were trained using either a means squared error loss for regression of enrichment, or a binary cross entropy for classification of H3 CDRs that were successively enriched in rounds of panning. After fitting the ensemble of neural networks, the authors use gradient ascent to optimize input seed sequences. Contrary to gradient descent, which is generally used to modify neural network weights so as to minimize a loss function such as classification error, gradient ascent is used in this case to modify the input sequence so as to maximize the output. The authors suggest that the use of an ensemble of several neural networks allows for optimization to take controlled paths by optimizing with respect to different network outputs. Using this optimization protocol, the authors were able to generate sequences with greater enrichment than both seed sequences and sequences within the training dataset. This significant result suggests that the neural network models were able to extrapolate beyond input training data, possibly by learning high level representations of what determines enriched binding. Additionally, the authors demonstrate superior performance using a gradient ascent method compared to more common generative models such as variational auto-encoders and genetic algorithms. However, it is unclear whether or not the difference between these methods is attributable to the style of optimization, or to the difference in the architecture of the network (e.g., number of layers or layer sizes). Similar to the method developed by Mason et al. \[[@B35-antibodies-09-00012]\], this method completely circumvents the need for structural data which is significantly more difficult to acquire. However, it is highly unlikely that these methods generalize well across target antigens. In each method the network is fit to data points derived from a single target antigen and therefore applying this method to a different target would require extensive wet-lab testing to generate the training data and refit the model. ### 5.2.3. DeepInterface {#sec5dot2dot3-antibodies-09-00012} DeepInterface is a structure-based method which aims to classify protein complexes in their docked conformational state as either true or false binders \[[@B38-antibodies-09-00012]\]. The input to the network is a voxel grid constructed from a fixed-size box placed around the interface. To handle rotation ambiguity, the authors align the vector between the structures center of mass to one of the three coordinate axes. The network itself is composed of four convolutional layers followed by batch normalization and rectified linear units. To transform the voxel space into a one-dimensional vector and subsequently into a prediction of binding, global average pooling is applied to the voxel space followed by two fully connected layers. Of note here is the generation of negative data used to train the network. Negative examples in this case refer to any structures which are not true binders. Using negative examples is a vital step in classification, as the network must be exposed to some form of negative input for successful training. To generate these negative examples, the authors use a fast-Fourier transform (FFT)-based docking algorithm, ZDOCK, to select incorrect docking solutions from the set of sampled conformations \[[@B13-antibodies-09-00012]\]. Representation of the protein interface as a voxel grid is an intuitive yet problematic strategy. Firstly, the input size of the network restricts the voxel space to a single size. The authors overcome this by limiting the size of the interfaces passed into the network to those small enough to fit into the bounded grid space. Secondly, a rotational ambiguity problem arises due to the absence of a common axis across all interfaces. Similar voxel methods used for 3D objects can usually take advantage of an implied gravity vector to eliminate ambiguity across an axis. Handling ambiguity between the remaining axes can be done using a randomly rotated version of the input or by implementing rotational pooling into the network architecture. However, these methods are impractical for more than two dimensions as the number of possible rotations needed grows exponentially. Despite these limitations, DeepInterface achieves 75% classification accuracy on benchmark datasets, demonstrating viability in this classification task Due to the differences previously mentioned between antibody-antigen interfaces and general PPIs, it is not clear that the model here presented would be capable of avoiding false positive classification. This problem may give rise to out-of-distribution errors, which arise when the underlying training dataset is not representative of its real-world use case. However, except for the bounding voxel space size, the model architecture and input structure presented within DeepInterface is somewhat agnostic to the type of interface evaluated. It should be noted, however, that the model's reliance on spatial arrangement of the interface area should not hinder its applicability towards antibody--antigen interfaces, which possess non-discernable differences in shape complementarity \[[@B6-antibodies-09-00012]\]. ### 5.2.4. MaSIF-Search {#sec5dot2dot4-antibodies-09-00012} The MaSIF approach comes out of the growing field of geometric deep learning. Starting from a mesh representation of a protein surface, a patch is created by selecting a point on the mesh and all neighboring surface points within a defined geodesic distance \[[@B39-antibodies-09-00012]\]. Each of the surface points is annotated with geometric and chemical features which describe degrees of curvature, concavity, electrostatic potential, hydrophobicity and hydrogen bond potential. The patch is down-sampled into a grid of 80 bins (5 radial × 16 angular). Each bin contains the statistical mean of the feature attributes of the points which are assigned to the corresponding bin. The 80 bins, indexed by polar and angular coordinates, are passed as input into a set of geodesic convolutional filters to generate a one-dimensional descriptor of the protein surface. Rotational max-pooling is used to overcome angular ambiguity. The one-dimensional descriptor is then refined by a fully connected layer. The remaining architecture is regarded as application-specific, which expresses the ability to use the 1D descriptors as input into an application specific model. To train an application specific model for interaction prediction, a modified version of the triplet loss function is used, which minimizes the Euclidean distance between the 1D descriptors of an anchor (a binding protein patch) and a positive (a complimentary patch to the anchor), and maximizes the distance between the anchor and a negative (a randomly chosen, non-complementary surface patch to the anchor). The authors deem two surface patches from two separate proteins to be positive pairs if the patch centers are within a small distance from one another at the protein--protein interface. To measure the model's performance, the authors classify interacting vs. non-interacting pairs and report an area under the curve of the receiver operating characteristic (ROC AUC) of 0.99 when using geometric and chemical features. The authors further evaluate the model's performance on different subsets of the data by creating subsets of low, high and very high interface complementarity. It is interesting to note that, as expected, the classification performance of the model drops to 0.81 ROC AUC using both geometric and chemical feature sets on the low shape complementary subset and further to 0.73 and 0.75 when using only the geometric and chemical features on this subset, respectively. MaSIF search is trained on a mix of antibody--antigen and protein--protein interfaces with no distinction between the two. As mentioned previously, antibody--antigen interactions exhibit a similar shape complementarity to that of other protein--protein interfaces \[[@B6-antibodies-09-00012]\].
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731, 347, 5926, 1066, 7223, 762, 34294, 20898, 323, 14532, 3724, 15, 187, 187, 7845, 4579, 604, 368, 1089, 667, 5816, 4859, 27, 187, 187, 1473, 939, 33, 31166, 621, 48460, 15, 681, 187, 187, 20968, 8339, 187, 187, 7845, 1928, 1959, 281, 897, 285, 3894, 436, 1491, 342, 634, 11651, 285, 12440, 275, 253, 1673, 15, 6101, 897, 273, 253, 4753, 323, 634, 3946, 943, 2486, 3806, 281, 436, 2670, 347, 253, 4328, 273, 6510, 15, 7764, 513, 417, 12119, 667, 273, 436, 1491, 390, 7177, 281, 634, 3367, 390, 1345, 4422, 1293, 2720, 3542, 9612, 15, 7820, 13, 368, 476, 1501, 247, 3048, 432, 634, 4422, 281, 436, 4422, 281, 2289, 253, 7177, 15, 187, 187, 47258, 4211, 327, 43048, 12286, 43048, 403, 417, 3894, 494, 285, 403, 6885, 407, 9451, 15, 7764, 1928, 1959, 281, 1480, 634, 11651, 281, 619, 4657, 281, 7471, 616, 1211, 10125, 15, 322, 3485, 247, 1643, 4957, 275, 619, 4657, 7729, 281, 8409, 253, 2105, 273, 11850, 436, 2670, 285, 4483, 479, 281, 3959, 1959, 5300, 281, 14532, 3724, 15, 11239, 368, 2, 48640, 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4292, 497, 4236, 347, 253, 2622, 1387, 15, 2732, 2460, 11931, 13, 253, 6821, 23876, 4871, 313, 56, 582, 9544, 313, 53, 582, 2978, 313, 45, 582, 253, 9080, 273, 253, 20280, 17716, 313, 5414, 10, 285, 6821, 23876, 17716, 313, 3871, 10, 497, 4080, 285, 253, 6821, 23876, 4644, 313, 55, 10, 369, 5118, 15, 380, 36120, 285, 330, 10189, 497, 4080, 327, 308, 19, 56, 42, 15, 380, 34026, 8115, 497, 5118, 970, 253, 270, 10487, 275, 20091, 2513, 285, 253, 34026, 2193, 497, 4080, 15, 20901, 342, 253, 26308, 1387, 13, 253, 6821, 23876, 657, 13, 6442, 285, 7388, 6137, 3012, 275, 253, 16002, 1387, 313, 49, 654, 470, 15, 1762, 481, 1876, 6821, 23876, 21418, 2193, 497, 3012, 1027, 875, 26308, 285, 2622, 2390, 313, 49, 654, 470, 15, 1762, 481, 380, 6821, 23876, 418, 285, 657, 497, 3012, 1027, 313, 49, 654, 470, 15, 1762, 10, 875, 16002, 285, 2622, 2390, 15, 380, 36120, 285, 330, 10189, 2193, 497, 1722, 15, 2526, 3279, 577, 15, 3763, 285, 2145, 15, 1093, 3279, 495, 15, 805, 13, 1903, 15, 1235, 3279, 337, 15, 1540, 285, 818, 15, 2031, 3279, 577, 15, 1237, 13, 577, 15, 1348, 3279, 337, 15, 1348, 285, 495, 15, 2941, 3279, 374, 15, 3156, 275, 253, 26308, 13, 16002, 285, 2622, 2390, 13, 2975, 15, 6295, 36120, 285, 330, 10189, 6137, 846, 473, 20072, 13, 533, 597, 369, 1335, 2169, 685, 253, 2622, 2193, 15, 380, 36120, 369, 3012, 1027, 875, 667, 767, 2390, 313, 49, 654, 470, 15, 1762, 481, 380, 330, 10189, 369, 3012, 1027, 313, 49, 654, 470, 15, 1762, 10, 875, 253, 26308, 285, 16002, 2390, 13, 26308, 285, 2622, 2390, 15, 380, 6821, 23876, 34026, 2193, 497, 313, 18, 15, 23688, 3279, 470, 15, 35340, 10, 6806, 884, 1490, 20, 10, 5823, 9, 19, 1933, 84, 13, 313, 18, 15, 8193, 3279, 470, 15, 15161, 10, 6806, 884, 1490, 20, 10, 5823, 9, 19, 1933, 84, 285, 313, 17, 15, 28315, 3279, 470, 15, 28943, 10, 6806, 884, 1490, 20, 10, 5823, 9, 19, 1933, 84, 275, 253, 26308, 13, 16002, 285, 2622, 2390, 13, 2975, 15, 380, 3064, 273, 34026, 2193, 497, 1534, 313, 49, 654, 470, 15, 1762, 10, 875, 253, 26308, 285, 16002, 2390, 13, 285, 253, 26308, 285, 2622, 2390, 15, 473, 20072, 310, 271, 3576, 1332, 273, 1971, 323, 20280, 14300, 15, 496, 1635, 281, 16821, 11052, 253, 6821, 23876, 657, 13, 352, 476, 671, 6379, 253, 6821, 23876, 36120, 13, 330, 10189, 285, 34026, 2193, 275, 1363, 342, 20280, 14300, 15, 380, 2544, 273, 6821, 23876, 36120, 13, 330, 10189, 285, 34026, 846, 473, 20072, 778, 320, 9371, 275, 5277, 1327, 26681, 24864, 1491, 275, 18005, 253, 9282, 1055, 273, 473, 20072, 327, 20280, 14300, 15, 46, 3205, 372, 42078, 15333, 4014, 71, 3876, 42888, 1753, 10028, 266, 14822, 3897, 209, 2246, 44654, 372, 826, 37568, 2960, 372, 1244, 83, 5069, 31903, 418, 1954, 29283, 473, 1288, 9325, 247, 826, 3327, 301, 14994, 372, 826, 2719, 26907, 66, 15761, 35871, 1304, 15333, 30670, 4474, 441, 86, 12416, 372, 4358, 30924, 2675, 265, 13, 2899, 20302, 1448, 30787, 80, 1448, 4613, 4611, 372, 826, 24901, 38680, 1473, 299, 2899, 20302, 372, 19345, 29378, 3667, 4330, 7860, 40322, 15, 187, 187, 53, 255, 8960, 1639, 2001, 1321, 31247, 16078, 13, 5245, 249, 324, 6464, 372, 826, 2986, 47341, 838, 301, 49016, 1448, 20730, 26869, 10334, 284, 1452, 21000, 13, 340, 12294, 37831, 8502, 26228, 47900, 4420, 13, 1957, 7961, 372, 3010, 2072, 22943, 1045, 19244, 14345, 40322, 11051, 7909, 13, 37266, 257, 711, 585, 406, 254, 258, 523, 274, 345, 20320, 19664, 1778, 900, 372, 7460, 9390, 340, 36188, 37581, 284, 46154, 22636, 7766, 372, 826, 49712, 992, 571, 546, 15563, 372, 418, 1954, 29283, 473, 1288, 9325, 13, 20056, 246, 40594, 8254, 80, 1753, 396, 492, 682, 372, 440, 769, 80, 711, 265, 468, 3377, 5586, 28080, 274, 1045, 1195, 328, 4786, 1448, 4613, 4611, 372, 402, 629, 7112, 15, 187, 187, 9323, 503, 3377, 4474, 16495, 30731, 20406, 14822, 12368, 711, 446, 466, 25070, 372, 42078, 15333, 247, 295, 35209, 48473, 13, 1045, 2949, 38, 3794, 22125, 273, 5660, 12704, 27, 773, 2369, 19273, 1501, 5650, 1448, 2949, 38, 278, 850, 6230, 642, 288, 12451, 37732, 36075, 14822, 1753, 6362, 1246, 2960, 6598, 187, 187, 30641, 309, 29997, 570, 473, 75, 15055, 13, 1608, 647, 66, 11957, 356, 293, 340, 33609, 336, 10876, 332, 66, 187, 187, 42524, 35813, 372, 36912, 46591, 13, 818, 372, 12468, 900, 313, 40194, 30731, 20406, 481, 1253, 914, 66, 2986, 47341, 247, 10115, 20092, 66, 15563, 1244, 83, 5069, 31903, 418, 1954, 29283, 473, 1288, 9325, 13, 4613, 4611, 838, 301, 49016, 372, 826, 10089, 32206, 773, 43, 2084, 375, 388, 609, 19530, 13314, 571, 7521, 26510, 298, 11670, 2960, 19764, 3300, 3230, 247, 11074, 5069, 372, 42078, 15333, 4014, 71, 3876, 42888, 38106, 10028, 266, 14822, 3897, 209, 2246, 44654, 372, 1753, 1045, 1957, 7961, 372, 826, 24901, 38680, 1473, 37568, 489, 247, 826, 3327, 301, 14994, 372, 36912, 46591, 15, 187, 187, 8677, 549, 4011, 1452, 372, 12368, 711, 446, 466, 25070, 372, 42078, 15333, 9425, 34627, 28588, 345, 1045, 2349, 25568, 287, 372, 418, 1954, 29283, 473, 1288, 9325, 345, 3897, 2899, 20302, 1448, 40764, 5309, 6691, 280, 4692, 372, 15186, 1118, 375, 313, 14546, 46, 582, 1963, 15119, 26926, 614, 1448, 37581, 1792, 3377, 479, 89, 280, 4692, 13, 345, 1045, 1753, 1045, 20730, 26869, 10334, 284, 1452, 21000, 11737, 5711, 440, 31310, 624, 36726, 391, 1950, 1033, 7112, 546, 4358, 32528, 47793, 3300, 24288, 340, 1753, 13, 355, 22865, 1209, 13, 298, 35784, 372, 402, 27135, 4501, 1448, 16172, 265, 7222, 3377, 13, 1579, 1954, 1578, 284, 347, 365, 14852, 284, 15, 187, 187, 3848, 913, 10207, 3088, 345, 28887, 8960, 1639, 2001, 1321, 31247, 16078, 13, 5245, 249, 324, 6464, 372, 826, 2986, 47341, 838, 301, 49016, 1448, 20730, 26869, 10334, 284, 1452, 21000, 13, 826, 2986, 47341, 8227, 571, 18219, 31310, 406, 2960, 247, 9500, 40954, 35860, 27, 773, 52, 7391, 274, 1666, 5650, 15563, 34653, 48, 5586, 2336, 4927, 19565, 257, 31801, 11158, 826, 540, 2083, 4501, 1448, 362, 4881, 13, 340, 2412, 23537, 1753, 826, 41171, 2836, 66, 27, 2802, 85, 351, 375, 3347, 45862, 265, 340, 642, 21554, 1484, 362, 4881, 16236, 20056, 826, 41171, 14076, 642, 3293, 260, 658, 6598, 187, 187, 7647, 270, 6836, 13, 6706, 343, 785, 13, 18219, 546, 826, 476, 13420, 1448, 19244, 14345, 40322, 11051, 7909, 313, 7570, 582, 1448, 1753, 35656, 266, 2340, 489, 247, 14753, 80, 15, 187, 187, 7647, 5245, 249, 324, 6464, 372, 2986, 47341, 1448, 10334, 284, 1452, 21000, 6583, 1954, 1753, 4358, 42078, 15333, 546, 15563, 1448, 4613, 4611, 372, 3010, 2072, 396, 15761, 761, 487, 7112, 546, 826, 32982, 35813, 372, 36912, 46591, 13, 714, 1028, 255, 9435, 13, 19660, 284, 1940 ]
have I read a book--surely not in psychoanalysis or psychotherapy--so scholarly and so accessible, so theoretically challenging and so humanistically rich." --International Journal of Psychoanalytic Self Psychology People intuitively know that we travel the byways of life jointly. Dr. Staemmler takes this common sense perspective and through professionally astute examination transforms it into a dependable guideline for living. His de-mystification and humanization of the elusive dynamics of communal existence returns the reader to the old adage that we are all in the same boat and, further, that it is emotionally imperative to let ourselves be there. Erving Polster, PhD Director, The Gestalt Institute of San Diego According to large scale studies on therapeutic outcomes, psychotherapists' ability to understand their clients has been considered the second most important healing factor in all therapies. The author of this scholarly volume seeks to improve our understanding of the immense therapeutic potential that the human capacity for empathy holds, and to improve our use of it in therapeutic practice. Drawing from the work of great thinkers in philosophy, literature, theology, psychology, and social sciences, and recent discoveries in neuroscience, the author provides a critique of traditional concepts of empathy and creates a new, more expansive definition. More specifically, the author exposes the basic characteristics of current individualistic ideologies that are concealed within traditional concepts of empathy and focuses on the concept that empathic relating between human beings does not just take place in the psyche but is an embodied process. The book also considers scientific phenomena from the field of parapsychology such as telepathy and clairvoyance, which can be thought of as special cases of empathy. The potential for certain types of meditation to increase our empathic abilities is also explored. Key Features: Improves our understanding of the potential for empathy to greatly enhance therapeutic practice Draws from philosophy, literature, theology, psychology, social sciences, and neuroscience to create a new definition of empathy Critiques traditional concepts of empathy and highlights their strengths and weaknessesSPEECH Bumper Stickers and MAGNETS are here! Online/On-Demand Workshop: Let's Hear It For /R/! Are you struggling with /r/? Do you want a structured approach to remediate this difficult sound? Email if you are interested in an online workshop for your company/school OR sign-up for the on-demand presentation! Therapy Documents This page has been moved to individual pages for easier organization. You will find all of them as drop down pages under Therapy Materials for SLPs. Please email if you find any missing links: dawn@expressionsspeech.com Copyright Information Please feel free to use and share this information with your colleagues and professionals in the field. Any use of the materials for your practice should include reference to this site as the location of origin. Please do not upload any of this information or documents to your personal or public website without prior written approval. Instead, you can post a link from your website to this website to access the documents. Products sold on Teachers Pay Teachers are not shareable and are protected by copyright. Please feel free to direct your colleagues to my store to purchase their own copies. Selling a few items in my store helps to offset the cost of maintaining this site and allows me to offer free resources to SLPs. Thank you!Evaluation on therapeutic effects of orthotopic liver transplantation by megnetic resonance imaging in patients with portal hypertension. Orthotopic liver transplantation (OLT) has become the therapeutic option of choice for end-stage liver disease. The aim of this study was to investigate the changes of splenic morphology, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), apparent diffusion coefficient (ADC) values and explore their value in evaluating the therapeutic effects of orthotopic liver transplantation (OLT) on portal hypertension at 1.5 Tesla MRI. Twenty patients with portal hypertension undergoing OLT were included in this study. Conventional MRI and diffusion-weighted image (DWI) (b value = 600 s/mm(2)) sequences were applied on each patient before and after OLT, and these patients were referred to as the preoperative and postoperative groups. Twenty healthy individuals were selected as the normal group. After image acquisition, the splenic width (W), thickness (T), length (L), the diameter of the portal vein (PD) and splenic vein (SD) were measured and the splenic volume (V) was calculated. The SNR and CNR were measured on T2WI. The ADC maps were calculated using the b600 in DWIs and the ADC values were measured. Compared with the preoperative group, the splenic V, PD and SD decreased significantly in the postoperative group (P < 0.05). All splenic morphological values were significantly different between preoperative and normal groups (P < 0.05). The splenic L and V were significantly different (P < 0.05) between postoperative and normal groups. The SNR and CNR values were 17.66 ± 4.62 and 13.18 ± 3.12, 11.50 ± 1.64 and 7.44 ± 4.32, 4.24 ± 1.24 and 3.03 ± 2.41 in the preoperative, postoperative and normal groups, respectively. Both SNR and CNR decreased after OLT, but they was still higher than the normal values. The SNR was significantly different between any two groups (P < 0.05). The CNR was significantly different (P < 0.05) between the preoperative and postoperative groups, preoperative and normal groups. The splenic ADC values were (1.339 ± 0.482) × 10(-3) mm(2)/s, (1.120 ± 0.254) × 10(-3) mm(2)/s and (0.997 ± 0.447) × 10(-3) mm(2)/s in the preoperative, postoperative and normal groups, respectively. The difference of ADC values were significant (P < 0.05) between the preoperative and postoperative groups, and the preoperative and normal groups. OLT is an effective method of treatment for portal hypertension. In addition to dramatically decreasing the splenic V, it can also decrease the splenic SNR, CNR and ADC values in patients with portal hypertension. The changes of splenic SNR, CNR and ADC after OLT may be helpful in providing noninvasive supplementary information in assessing the therapeutic effect of OLT on portal hypertension.Miles de llamadas telefónicas que alertan sobre los riesgos de la llegada de Andrés Manuel López Obrador a la Presidencia de la República han sido reportadas tanto por usuarios de las redes sociales, integrantes del equipo del candidato de la izquierda e integrantes de Movimiento Regeneración Nacional. Tatiana Clouthier Carrillo, coordinadora de la campaña presidencial del político tabasqueño, y Horacio Duarte Olivares, representante de Morena ante el Instituto Nacional Electoral, dicen desconocer o contar con algún indicio de quién y qué empresas están detrás de la estrategia en contra de López Obrador, pero tienen claro que se trata de un acto desesperado para frenar el triunfo del candidato de su partido. Consultado por SinEmbargo sobre este despliegue de llamadas a nivel nacional, el INE respondió oficialmente: “no hay postura del INE mientras no haya resolución sobre queja presentada”. Por Ivonne Ojeda, Shaila Rosagel y Dulce Olvera Ciudad de México, 7 de junio (SinEmbargo).– Una campaña a gran escala contra Andrés Manuel López Obrador, candidato presidencial de la coalición “Juntos Haremos Historia”, fue lanzada esta semana a través de llamadas telefónicas donde alertan sobre los riesgos de que el representante de la izquierda llegue a la Presidencia de México. El arranque de este despliegue de llamadas masivas coincide con el encuentro de López Obrador con los integrantes del Consejo Mexicano de Negocios (CNM), organismo élite del empresariado mexicano, con el que el político tabasqueño tuvo un enfrentamiento ríspido en las últimas semanas y que, al parecer, luego de su reunión del martes pasado, limó esas asperezas. De acuerdo con Tatiana Clouthier Carrillo, coordinadora de la campaña presidencial del político tabasqueño, la campaña sucia está enfocada a dos objetivos: “Soltar basura contra AMLO para ver si pueden cambiar la intención del voto, y lograr que la gente diga: ‘todos son iguales y no voy u voto’, pero la gente ya no les cree”. La bola, afirma, está en la cancha del Instituto Nacional Electoral (INE), del que esperan investigue a fondo. La coordinadora de campaña del tabasqueño confirmó que las llamadas en contra del candidato de Morena se han recibido en la Ciudad de México, Yucatán, Tabasco
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