Miracle-dz/UniFAR-FTUs huggingface dataset:
The pro-apoptotic activity of a vertebrate Bar-like homeobox gene plays a key role in patterning the Xenopus neural plate by limiting the number of chordin- and shh-expressing cells

Targeted disruption of effectors molecules of the apoptotic pathway have demonstrated the occurrence and magnitude of early programmed cell death (EPCD), a form of apoptosis that affects proliferating and newly differentiated cells in vertebrates, and most dramatically cells of the central nervous system (CNS). Little is known about the molecular pathways controlling apoptosis at these early developmental stages, as the roles of EPCD during patterning of the developing nervous system. We describe a new function, in Xenopus neurodevelopment, for a highly conserved homeodomain protein Barhl2. Barhl2 promotes apoptosis in the Xenopus neuroectoderm and mesoderm, acting as a transcriptional repressor, through a mechanism that cannot be attributed to an unspecific cellular stress response. We show that the pro-apoptotic activity of Barhl2 is essential during normal neural plate formation as it limits the number of chordin- and Xshh-expressing cells in the prospective notochord and floorplate, which act as organizing centers. Our findings show that Barhl2 is part of a pathway regulating EPCD. They also provide evidence that apoptosis plays an important role in regulating the size of organizing centers.
INSIGHTS FROM THE INTERPLAY OF K! AND "K ON THE NEW PHYSICS FLAVOUR STRUCTURE

branching ratios has been observed, allowing essentially only for two branches of possible points, while in other NP frameworks, such as the general MSSM or warped extra dimensional models, no visible correlation appears. We analyse the origin of the correlation in question and show it to be a direct consequence of the stringent experimental constraint on "K, provided that the NP enters with comparable strength and a universal weak phase in both S = 2 and S = 1 transitions. This happens in many NP scenarios with either only SM operators, or where the NP induces exclusively right-handed currents while the left‐right S = 2 operators are absent. On the other hand, if the NP phases in S = 2 and S = 1 processes are uncorrelated, "K has no power to put constraints on the K! system. The latter appears in particular in those NP models where K 0 ‐ K 0 mixing receives contributions from the chirally enhanced left-right operators. We discuss the stability of the correlation in question against small deviations from the assumption of universal S = 2 and S = 1 weak phases, and in the presence of non-negligible NP contributions to "K.
Statistical Estimation: From Denoising to Sparse Regression and Hidden Cliques

These notes review six lectures given by Prof. Andrea Montanari on the topic of statistical estimation for linear models. The first two lectures cover the principles of signal recovery from linear measurements in terms of minimax risk. Subsequent lectures demonstrate the application of these principles to several practical problems in science and engineering. Specifically, these topics include denoising of error-laden signals, recovery of compressively sensed signals, reconstruction of low-rank matrices, and also the discovery of hidden cliques within large networks.
Image-space control variates for rendering

We explore the theory of integration with control variates in the context of rendering. Our goal is to optimally combine multiple estimators using their covariances. We focus on two applications, re-rendering and gradient-domain rendering, where we exploit coherence between temporally and spatially adjacent pixels. We propose an image-space (iterative) reconstruction scheme that employs control variates to reduce variance. We show that recent works on scene editing and gradient-domain rendering can be directly formulated as control-variate estimators, despite using seemingly different approaches. In particular, we demonstrate the conceptual equivalence of screened Poisson image reconstruction and our iterative reconstruction scheme. Our composite estimators offer practical and simple solutions that improve upon the current state of the art for the two investigated applications.
Dynamic sparse state estimation using ℓ1-ℓ1 minimization: Adaptive-rate measurement bounds, algorithms and applications

We propose a recursive algorithm for estimating time-varying signals from a few linear measurements. The signals are assumed sparse, with unknown support, and are described by a dynamical model. In each iteration, the algorithm solves an ℓ1-ℓ1 minimization problem and estimates the number of measurements that it has to take at the next iteration. These estimates are computed based on recent theoretical results for ℓ1-ℓ1 minimization. We also provide sufficient conditions for perfect signal reconstruction at each time instant as a function of an algorithm parameter. The algorithm exhibits high performance in compressive tracking on a real video sequence, as shown in our experimental results.
Coalitions Between Terrorist Organizations: Revolutionaries, Nationalists And Islamists

Acknowledgments Preface About the Author Introduction 1. Theoretical Framework and Research Paradigm 2. Variables and Research Hypotheses 3. Germany - Radical Left-Wing Organizations 4. Italy - The Red Brigades 5. France - Action Directe 6. Euro-Terrorism (1984-88) 7. Italy - Radical Right-Wing Organizations 8. Spain - The ETA 9. The Palestinian Terrorist Organizations 10. Testing the Hypotheses 11. The Islamist Networks Conclusion Abbreviations Bibliography.
3 Consumer Memory , Fluency , and Familiarity

Th e systematic study of consumer behavior is heavily infl uenced by theories and paradigms from memory research, as the behavior of the consumer is largely infl uenced by prior experiences. Th e distinction is oft en drawn between memory-based, stimulus-based (all relevant information is physically present at the time of judgment or choice), and mixed (a combination of memory-based and stimulus-based) decisions (Lynch & Srull, 1982). However, purely stimulus-based decisions are relatively rare; most consumer decisions are necessarily dependent on memory and thereby range from the purely memory-based to mixed (Alba, Hutchinson, & Lynch, 1991). Given the importance of memory in consumer research, it behooves us periodically to take stock of the contemporary theories of memory and consider their assumptions and implications. To that end, we aim in this chapter to provide a review of the dominant accounts of memory and the way they have shaped our understanding of consumer behavior in the past two decades. We discuss the advances that have been made as well as some areas of potential concern. Specifi cally, we frame the review and discussion vis-à-vis an alternative account of memory, the SCAPE framework, developed by Bruce Whittlesea and his colleagues (e.g., Whittlesea, 1997). In addition, we off er some suggestions and future directions for research on consumer memory.
Computational Neuropsychiatry – Schizophrenia as a Cognitive Brain Network Disorder

Computational modeling of functional brain networks in fMRI data has advanced the understanding of higher cognitive function. It is hypothesized that functional networks mediating higher cognitive processes are disrupted in people with schizophrenia. In this article, we review studies that applied measures of functional and effective connectivity to fMRI data during cognitive tasks, in particular working memory fMRI studies. We provide a conceptual summary of the main findings in fMRI data and their relationship with neurotransmitter systems, which are known to be altered in individuals with schizophrenia. We consider possible developments in computational neuropsychiatry, which are likely to further our understanding of how key functional networks are altered in schizophrenia.
Fixing the Infix: Unsupervised Discovery of Root-and-Pattern Morphology

We present an unsupervised and language-agnostic method for learning root-and-pattern morphology in Semitic languages. This form of morphology, abundant in Semitic languages, has not been handled in prior unsupervised approaches. We harness the syntactico-semantic information in distributed word representations to solve the long standing problem of root-and-pattern discovery in Semitic languages. Moreover, we construct an unsupervised root extractor based on the learned rules. We prove the validity of learned rules across Arabic, Hebrew, and Amharic, alongside showing that our root extractor compares favorably with a widely used, carefully engineered root extractor: ISRI.
International consensus study of antipsychotic dosing.

OBJECTIVE Potency equivalents for anti-psychotic drugs are required to guide clinical dosing and for designing and interpreting research studies. Available dosing guidelines are limited by the methods and data from which they were generated. METHOD With a two-step Delphi method, the authors surveyed a diverse group of international clinical and research experts, seeking consensus regarding antipsychotic dosing. The authors determined median clinical dosing equivalents and recommended starting, target range, and maximum doses for 61 drugs, adjusted for selected clinical circumstances. RESULTS Participants (N=43) from 18 countries provided dosing recommendations regarding treatment of psychotic disorders for 37 oral agents and 14 short-acting and 10 long-acting parenteral agents. With olanzapine 20 mg/day as reference, estimated clinical equivalency ratios of oral agents ranged from 0.025 for sulpiride to 10.0 for trifluperidol. Seventeen patient and treatment characteristics, including age, hepatic and renal function, illness stage and severity, sex, and diagnosis, were associated with dosing modifications. CONCLUSIONS In the absence of adequate prospective, randomized drug-drug comparisons, the present findings provide broad, international, expert consensus-based recommendations for most clinically employed antipsychotic drugs. They can support clinical practice, trial design, and interpretation of comparative antipsychotic trials.
Serotypes and antimicrobial susceptibility of Salmonella spp. isolated from farm animals in China

Salmonella spp. can indirectly infect humans via transfer from animals and animal-derived food products, and thereby cause potentially fatal diseases. Therefore, gaining an understanding of Salmonella infection in farm animals is increasingly important. The aim of this study was to identify the distribution of serotypes in Salmonella samples isolated from chickens (n = 837), pigs (n = 930), and dairy cows (n = 418) in central China (Henan, Hubei, and Hunan provinces) in 2010–2011, and investigate the susceptibility of strains to antimicrobial agents. Salmonella isolates were identified by PCR amplification of the invA gene, serotypes were determined by using a slide agglutination test for O and H antigens, and susceptibility to 24 antimicrobials was tested using the agar dilution method. In total, 248 Salmonella strains were identified: 105, 105, and 38 from chickens, dairy cows, and pigs, respectively. Additionally, 209 strains were identified in diseased pigs from the Huazhong Agricultural University veterinary hospital. Among these 457 strains, the dominant serotypes were Typhimurium in serogroup B, IIIb in serogroup C, and Enteritidis in serogroup D. In antimicrobial susceptibility tests, 41.14% of Salmonella spp. were susceptible to all antimicrobial agents, 48.14% were resistant to at least one, and 34.72% were resistant to more than three classes. Strains were highly resistant to sulfamethoxazole-trimethoprim (39.61%), nalidixic acid (39.17%), doxycycline (28.22%), and tetracycline (27.58%). Resistance to cephalosporins and fluoroquinolones ranged from 5.25 to 7.44% and 19.04 to 24.51%, respectively. Among penicillin-resistant and cephalosporin-resistant strains, 25 isolates produced extended-spectrum β-lactamases (ESBLs). The multidrug-resistant and ESBL-producing Salmonella strains identified in healthy animals here will present a challenge for veterinary medicine and farm animal husbandry, and could also pose a threat to public health. The level of antibiotic resistance observed in this study further highlights the need for careful and selective use of antibiotics.
Memory, Psychology and Second Language Learning

This book explores the contributions that cognitive linguistics and psychology, including neuropsychology, have made to the understanding of the way that second languages are processed and learnt. It examines areas of phonology, word recognition and semantics, examining ‘bottom-up’ decoding processes as compared with ‘top-down’ processes as they affect memory. It also discusses second language learning from the acquisition/learning and nativist/connectionist perspectives. These ideas are then related to the methods that are used to teach second languages, primarily English, in formal classroom situations. This examination involves both ‘mainstream’ communicative approaches, and more traditional methods widely used to teach EFL throughout the world. The book is intended to act both as a textbook for students who are studying second language teaching and as an exploration of issues for the interested teacher who would like to further extend their understanding of the cognitive processes underlying their teaching.Mick Randall is currently Senior Lecturer in TESOL and Head of the Institute of Education at the British University in Dubai. He has taught courses in second language learning and teaching, applied linguistics and psychology in a number of different contexts. He has a special interest in the cognitive processing of language and in the psycholinguistics of word recognition, spelling and reading.
The Correlation Between Students' Reading Strategies and Their Reading Comprehension Ability in Reading Academic Text

Abstract : This research was conducted to find out the correlation between students’ reading strategies and their reading comprehension ability. It was also to find out the most category and types of reading strategies used by students and students’ reading comprehension in reading academic text. The subject of this research was 5 th semester students of English Education Study Program. There were 53 students as participants in this research. The method that used in this research was descriptive study. The data collected by distributed a questionnaire and TOEFL test. The data revealed that 49.06% students labeled as high strategy user category and 50.94% students labeled as moderate strategy category. Besides, the most types of reading strategies used by students were Problem Solving Strategy with the average score was 3.93. Furthermore, 5 th semester students have average to good in reading comprehension. The correlation between students’ reading strategies and their reading comprehension showed that the correlation coefficient was 0.51 and classified in “moderate level”. Keywords: Reading Strategies, Reading Comprehension. Abstrak : Penelitian ini dilakukan untuk mengetahui hubungan antara strategi membaca siswa dan kemampuan pemahaman dalam membaca. Penelitian ini juga dilakukan untuk mengetahui kategori dan tipe-tipe strategi yang digunakan oleh siswa dan kemampuan mereka dalam memahami teks dalam bentuk akademik. Subjek penelitian ini adalah mahasiswa semester 5 Program Studi Pendidikan Bahasa Inggris. Terdapat 53 siswa yang terlibat dalam penelitian ini. Metode yang digunakan dalam penelitian ini adalah metode deskriptif. Data dikumpulkan melalui respon siswa terhadap kuisioner dan test TOEFL. Data menunjukkan bahwa terdapat 49.06% siswa termasuk kategori pengguna strategi tinggi dan 50.94% siswa termasuk kategori pengguna strategi sedang. Selain itu, tipe-tipe strategi yang paling sering digunakan oleh siswa adalah strategi mengatasi masalah dengan nilai rata-rata 3.93. Siswa semester kelima memiliki kemampuan rata-rata baik dalam pemahaman membaca. Hubungan antara strategi membaca siswa dan kemampuan pemahaman dalam membaca menunjukkan bahwa hubungan koefisiennya 0.51 dan diklasifikasikan dalam “level sedang”. Kata Kunci: Strategi Membaca, Pemahaman Membaca.
Having your cake and eating it too: discourses of transcendence and their role in organizational change dynamics

Purpose – Previous work on paradox and contradiction has argued for management approaches that transcend dilemmas through a kind of creative synthesis. The purpose of this paper is to investigate empirically how change leaders' efforts to transcend contradictions emerge, evolve and contribute to organizational change.Design/methodology/approach – The paper analyses three case studies in different sectors drawing on interviews, documents and observations.Findings – It is found that discourses of transcendence emerge as leaders bring new elements to the debate and supply a rationale that creatively bridges opposite poles of a dilemma. The credibility of the discourse is enhanced when it is embedded in extant institutional ideas, when stakeholders' interests and values appear to be accommodated and when leaders are viewed as legitimate. However, inherent contradictions tend to resurface over time, suggesting that while transcendence offers a powerful stimulus for change, its range and lifetime may be transit.
Using Noninvasive Brain Measurement to Explore the Psychological Effects of Computer Malfunctions on Users during Human-Computer Interactions

In today's technologically driven world, there is a need to better understand the ways that common computer malfunctions affect computer users. These malfunctions may have measurable influences on computer user's cognitive, emotional, and behavioral responses. An experiment was conducted where participants conducted a series of web search tasks while wearing functional near-infrared spectroscopy (fNIRS) and galvanic skin response sensors. Two computer malfunctions were introduced during the sessions which had the potential to influence correlates of user trust and suspicion. Surveys were given after each session to measure user's perceived emotional state, cognitive load, and perceived trust. Results suggest that fNIRS can be used to measure the different cognitive and emotional responses associated with computer malfunctions. These cognitive and emotional changes were correlated with users' self-report levels of suspicion and trust, and they in turn suggest future work that further explores the capability of fNIRS for the measurement of user experience during human-computer interactions.
Simulation-optimization integrated approach to planning ready mixed concrete production and delivery: Validation and applications

Powered by the simulation and optimization engines resulting from recent research, a computer system named HKCONSIM is ready to provide concrete plant managers with decision support in making the best operation strategy for delivering concrete to multiple site clients. This paper demonstrates case studies of HKCONSIM applications in practical settings with emphasis on addressing two questions: (1) “Can HKCONSIM capture the complexities of the real world? ” and (2) “How to take advantage of HKCONSIM to attain customer satisfaction and cost effectiveness? ” A case study describing one-day operations of the batch plant is used to illustrate the decision support functions HKCONSIM can provide. The case study consists of four parts: (1) input data preparation, (2) the definitions of relevant measures of the system performance, (3) simulation model validation by comparing the simulation outputs against the actual records, and (4) further optimization analysis under three “what-if” scenarios postulated with practical implications. In conclusion, the batch plant operators can draw on HKCONSIM to augment their experiences, corroborate their intuitions, and create new intelligence in coping challenges in day-by-day operations planning.
Spatial Ability and Academic Success of Sixth Grade Students at International Schools

Tests of verbal and mathematical reasoning ability (the Verbal Ability, Quantitative Ability and Mathematics subtests of the CTP III) and a test of spatial ability (the CTY Spatial Test Battery, Form HH) were used to predict academic success in a sample of 423 sixth graders at international schools. The reasoning measures showed high correlations with success (as measured by the grade point average (GPA)); the scores on the spatial test, too, were substantially correlated with GPA, although this correlation was somewhat lower than those of the reasoning measures. When the sample was divided into native English speakers and students with English as a second language (ESL students), native speakers were found to have an advantage on the reasoning tests, especially on the verbal one, but not on the measure of spatial ability. With small group differences on the GPA, the reasoning tests, especially the verbal test, underestimated the academic potential of the ESL students. It was concluded that the spatial test can contribute to reducing the bias against ESL students that is likely to occur when measures of verbal reasoning ability are administered to members of this population.
Discussion on fundamental issues of NPR measurements

This paper investigates the disagreement that exists between noise power ratio (NPR) measurements and a recently published statement that those measurements always underestimate the real nonlinear in-band distortions. A more fundamental approach to settle this discussion is presented. First, it is shown that nonlinear distortions can be split in different contributions, forming the fundamental parts of the NPR or in-band distortions. Next, measurement techniques are presented to obtain these different contributions.
Automatic Pitch Spelling: From Numbers to Sharps and Flats

In this paper a computational model is described that transcribes polyphonic MIDI pitch files into the Western traditional music notation. Input to the proposed algorithm input is merely a sequence of MIDI pitch numbers in the order they appear in a MIDI file. No a priori knowledge is required such as key signature, tonal centers, time signature, voice separation and so on. Output of the algorithm is a sequence of ‘correctly’ spelled pitches. The algorithm was evaluated on 8 complete piano sonatas by Mozart and had a success rate that is greater than 96% (10476 pitches were spelled correctly out of 10900 notes that required accidentals – overall number of pitches in 8 sonatas is 40058). The proposed algorithm was also compared to and tested against other pitch spelling algorithms. Pitch spelling algorithms are important not only for applications such as musical notation software packages but also for a multitude of tonal analytical tasks such as key-finding and harmonic analysis.
Medical Diagnosis From Laboratory Tests by Combining Generative and Discriminative Learning

A primary goal of computational phenotype research is to conduct medical diagnosis. In hospital, physicians rely on massive clinical data to make diagnosis decisions, among which laboratory tests are one of the most important resources. However, the longitudinal and incomplete nature of laboratory test data casts a significant challenge on its interpretation and usage, which may result in harmful decisions by both human physicians and automatic diagnosis systems. In this work, we take advantage of deep generative models to deal with the complex laboratory tests. Specifically, we propose an end-to-end architecture that involves a deep generative variational recurrent neural networks (VRNN) to learn robust and generalizable features, and a discriminative neural network (NN) model to learn diagnosis decision making, and the two models are trained jointly. Our experiments are conducted on a dataset involving 46,252 patients, and the 50 most frequent tests are used to predict the 50 most common diagnoses. The results show that our model, VRNN+NN, significantly (p<0.001) outperforms other baseline models. Moreover, we demonstrate that the representations learned by the joint training are more informative than those learned by pure generative models. Finally, we find that our model offers a surprisingly good imputation for missing values.