Miracle-dz/UniFAR-FTUs huggingface dataset:
Social Categorization and Stereotyping: A Functional Perspective

Social categorization and stereotyping are discussed as normal perceptual processes upon which perceivers rely for an adequate understanding of everyday social events. Social categorization and stereotyping are treated as strongly linked. It will be argued that in many situations social categorizations are used because perceivers expect the categories involved to differ in important respects. Thus, spontaneous social category selection is guided by the content of the perceiver's stereotypes. It is further argued that stereotype activation and application are largely governed by functional principles based on, for instance, the perceiver's task or goals, the usefulness of the stereotype in a situation, and individual differences in stereotypic beliefs. Subsequently, the functional determinants of stereotype content are discussed. In the final section of this paper, we pay attention to some of the mechanisms that operate in information selection, perception, and memory in the service of the preservation of stereotypes. What is it then, I pressed her further, that goes on between normal people, from which she feels herself excluded? It has to do, she has inferred, with an implicit knowledge of social conventions and codes, of cultural presuppositions of every sort. This implicit knowledge, which every normal person accumulates and generates throughout life on the basis of experience and encounters with others, Temple seems to be largely devoid of (Sacks, 1995, p. 270).
A Serum MicroRNA Panel as Potential Biomarkers for Hepatocellular Carcinoma Related with Hepatitis B Virus

Background The identification of new high-sensitivity and high-specificity markers for HCC are essential. We aimed to identify serum microRNAs (miRNAs) as biomarkers to be used in diagnosing hepatitis B virus (HBV) –related hepatocellular carcinoma (HCC). Methods We investigated serum miRNA expression in (261 HCC patients, 233 cirrhosis patients, and 173 healthy controls), recruited between August 2010 and June 2013. An initial screening of miRNA expression by Illumina sequencing was performed using serum samples pooled from HCC patients and controls. Quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) was used to evaluate the expression of selected miRNAs. A logistic regression model was constructed using a training cohort (n = 357) and then validated using an independent cohort (n = 241). The area under the receiver operating characteristic curve (AUC) was used to evaluate the accuracy of the use of the biomarkers for disease diagnosis. Results We identified 8 miRNAs (hsa-miR-206, hsa-miR-141-3p, hsa-miR-433-3p, hsa-miR-1228-5p, hsa-miR-199a-5p, hsa-miR-122-5p, hsa-miR-192-5p, and hsa-miR-26a-5p) and constructed an miRNA set that provided high diagnostic accuracy for HCC (AUC = 0.887 and 0.879 for training and validation sets, respectively). The miRNAs could also be used to differentiate HCC patients from healthy (AUC = 0.893) and cirrhosis (AUC = 0.892) patients. Conclusions We identified a serum of miRNA panel that has considerable clinical value in HCC diagnosis.
Efficient Support for Similarity Searches in DHT-Based Peer-to-Peer Systems

Distributed hash tables (DHTs) provide a scalable and robust building block for content discovery in distributed applications such as Peer-to-Peer (P2P) systems. However, the basic DHT put/get API only supports simple exact queries. In this paper, we present a DHT-based system that efficiently supports similarity queries on multidimensional datasets. Our system embeds a logical kd-tree into the DHT's identifier space to form a distributed indexing structure, the distributed kd-tree (DKDT). We avoid creating bottlenecks, which are typical in tree- based systems, by relying on fully distributed protocols for tree management and data registrations and queries. We propose tree compressing and node shrinking techniques to efficiently support applications with high dimensionality datasets. Simulation results using both synthetic and real data show the effectiveness of our system.
Comprehension with[in] virtual environment visualisations

For many years, basic visualisation based around simple boxes and lines, has been done in an attempt to be able to ease some of the cognitive overload caused by program comprehension. The problems with such visualisations is that they can very easily become incomprehensible by trying to force large amounts of information into a small space, relying solely on two dimensions for the representations. Three-dimensional visualisations are one approach that is being considered to combat these problems, although there are also many different issues that must be considered for these sorts of visualisations. Especially when those visualisations are of intangible software systems. A solution is to use virtual environments as a base for these three-dimensional visualisations, which allows a sense of context to be maintained and also promotes collaboration between the people trying to comprehend the code.
The Formative Purpose: Assessment Must First Promote Learning

The work described in this paper started with a review of the literature on formative assessment (Black & Wiliam, 1998a). That review presents evidence from more than 250 articles by researchers from several countries that helped us to establish three main points. First, there is strong and rigorous evidence that improving formative assessment can raise standards of students’ performance. There have been few initiatives in education with such a strong body of evidence to support a claim to raise standards. The second point concerns the quality of current classroom assessment practices in schools. Here again, the published evidence from classroom research gave a clear and positive answer: the assessment methods that teachers use are not effective in promoting good learning; marking and grading practices tend to emphasize competition
Cerebellar Involvement in Murine Sphingomyelinosis: A New Model of Niemann-Pick Disease

Mice with sphingomyelinosis (spin) with a C57BL/KsJ inbred background showed hepatosplenomegaly as early as four weeks (wk) of age and cerebellar signs around seven wk. Almost all animals died by 14 wk. Sudanophilic lipid accumulated in the liver, spleen, and lymph nodes as well as in the brain. The striking neuropathologicaf change was a marked atrophy of the cerebellum, where Purkinje cells were predominantly involved. Loss of Purkinje cells started at the age of six wk before the cerebellar signs had become evident clinically. The cell loss appeared to be more marked in the vermis than in the hemispheres. Cytoplasmic inclusions in most cells consisted of myelin figures composed of concentric membranous lamellae. These inclusions were found mainly in the Purkinje cells at an early stage; thereafter, they were widely distributed in the granule cells, Golgi cells, some glial cells, macrophages and endothelial cells. The neuronal inclusions were frequently located in the vicinity of the Golgi apparatus; there were no unusual mitochondrial configurations. The clinicopathological characteristics of the mutant mice are similar to those of the human Niemann-Pick disease type C.
Accounting for Bias Due to Selective Attrition: The Example of Smoking and Cognitive Decline

Background: Selective attrition may introduce bias into analyses of the determinants of cognitive decline. This is a concern especially for risk factors, such as smoking, that strongly influence mortality and dropout. Using inverse-probability-of-attrition weights, we examined the influence of selective attrition on the estimated association of current smoking (vs. never smoking) with cognitive decline. Methods: Chicago Health and Aging Project participants (n = 3713), aged 65–109 years, who were current smokers or never- smokers, underwent cognitive assessments up to 5 times at 3-year interval. We used pooled logistic regression to fit predictive models of attrition due to death or study dropout across the follow-up waves. With these models, we computed inverse-probability-of-attrition weights for each observation. We fit unweighted and weighted, multivariable-adjusted generalized-estimating-equation models, contrasting rates of change in cognitive scores in current versus never-smokers. Estimates are expressed as rates of change in z score per decade. Results: During the 12 years of follow-up, smokers had higher mortality than never-smokers (hazard ratio = 1.93 [95% confidence interval = 1.67 to 2.23]). Higher previous cognitive score was associated with increased likelihood of survival and continued participation. In unweighted analyses, current smokers' cognitive scores declined 0.11 standard units per decade more rapidly than never-smokers' (95% CI = −0.20 to −0.02). Weighting to account for attrition yielded estimates that were 56% to 86% larger, with smokers' estimated 10-year rate of decline up to 0.20 units faster than never-smokers' (95% CI = −0.36 to −0.04). Conclusions: Estimates of smoking's effects on cognitive decline may be underestimated due to differential attrition. Analyses that weight for the inverse probability of attrition help compensate for this attrition.
The Sample Complexity of Simple Binary Hypothesis Testing

The sample complexity of simple binary hypothesis testing is the smallest number of i.i. d. samples required to distinguish between two distributions $p$ and $q$ in either: (i) the prior-free setting, with type-I error at most $\alpha$ and type-II error at most $\beta$; or (ii) the Bayesian setting, with Bayes error at most $\delta$ and prior distribution $(\alpha, 1-\alpha)$. This problem has only been studied when $\alpha = \beta$ (prior-free) or $\alpha = 1/2$ (Bayesian), and the sample complexity is known to be characterized by the Hellinger divergence between $p$ and $q$, up to multiplicative constants. In this paper, we derive a formula that characterizes the sample complexity (up to multiplicative constants that are independent of $p$, $q$, and all error parameters) for: (i) all $0 \le \alpha, \beta \le 1/8$ in the prior-free setting; and (ii) all $\delta \le \alpha/4$ in the Bayesian setting. In particular, the formula admits equivalent expressions in terms of certain divergences from the Jensen--Shannon and Hellinger families. The main technical result concerns an $f$-divergence inequality between members of the Jensen--Shannon and Hellinger families, which is proved by a combination of information-theoretic tools and case-by-case analyses. We explore applications of our results to robust and distributed (locally-private and communication-constrained) hypothesis testing.
Mining history with Le Monde

The last decade has seen the rise of large knowledge bases, such as YAGO, DBpedia, Freebase, or NELL. In this paper, we show how this structured knowledge can help understand and mine trends in unstructured data. By combining YAGO with the archive of the French newspaper Le Monde, we can conduct analyses that would not be possible with word frequency statistics alone. We find indications about the increasing role that women play in politics, about the impact that the city of birth can have on a person's career, or about the average age of famous people in different professions.
UTILISATION OF COMPUTER BASED GUIDED SURGERY IN THE MANAGEMENT OF PARTIAL EDENTULISM

Case Selection All of the standard inclusion and exclusion criteria pertinent to dental implants are applicable. Sufficient residual jaw bone must be present to house the implants adequately within bone. The procedure described is via a flapless approach, therefore bone quality must be sufficient to avoid perforation of the outer cortex during preparation of the installation site and subsequent engagement of soft tissue. An oral opening of 40mm in the incisor region is required for ease of instrumentation. The anterior region offers amenable access, however posteriorly, particularly in the mandible, difficulty can be encountered especially when the opposing arch is dentate.
Integrating Complex Data Access Methods into the Mosaic/WWW Environment

This paper describes object-oriented extensions to the Harvest information discovery and access system that allow users to de ne type hierarchies and associated access methods for Web objects. These extensions enable Mosaic and the Web to represent, manipulate and display arbitrarily complex data in application-speci c ways. Types and access methods are extensible; new ones can be de ned and exported from Web servers and imported into Mosaic on demand, without changes to Mosaic and HTML for each new data type. This paper describes our design and prototype system implementation, including an application we built using the system. Merkel is currently a Leutenant in the U.S. Air Force, stationed at Maxwell Air Force Base.
Immature NK Cells Suppress Dendritic Cell Functions during the Development of Leukemia in a Mouse Model

To analyze the mechanisms by which cancer cells escape from hosts’ immune surveillance, we investigated the changes in immune status during the progression of leukemia induced by injecting mice with WEHI-3B cells. In the bone marrow (BM) of leukemic mice, only DX5+CD3− cells were continuously increased, despite the progression of leukemia. In addition, DX5+CD3− cells were rapidly increased in peripheral blood (PB) 20 days after inoculation. We also found that myeloid dendritic cells (DCs) expressing low levels of I-Ad and having low allo-T cell stimulatory activity were markedly increased in PB and spleen. The increase in DX5+ cells in BM was thought to be induced by soluble factors from leukemic cells. DX5+ cells from leukemic mice were CD3−, B220−, Gr-1−, CD14−, CD94−, Ly-49C/F−, asialo GM1+, CD25+, CD122+, Thy-1bright, and c-kitdim and showed low killing activity against YAC-1 cells, suggesting that those DX5+ cells were immature NK cells. NK cells from leukemic PB down-regulated the expression of I-Ad on DCs, an effect mediated by TGF-β. Moreover, these NK cells significantly suppressed the allo-T cell stimulatory activity of DCs, an effect requiring cell-to-cell contact between NK cells and DCs and thought to involve CD25. Importantly, NK cells from leukemic PB inhibited generation of autotumor-specific CTL induced by DCs in primary MLR or by DC immunization. In conclusion, we identified circulating immature NK cells with immunosuppressive activities. These cells may be important for understanding the involvement of the host immune system during the development of leukemia.
Unsupervised Adaptive Deep Learning Method For BCI Motor Imagery Decoding

In the context of Brain-Computer Interfaces, we propose an adaptive method that reaches offline performance level while being usable online without requiring supervision. Interestingly, our method does not require retraining the model, as it consists in using a frozen efficient deep learning backbone while continuously realigning data, both at input and latent spaces, based on streaming observations. We demonstrate its efficiency for Motor Imagery brain decoding from electroencephalography data, considering challenging cross-subject scenarios. For reproducibility, we share the code of our experiments.
A Note on the Estimation of Factor Scores

IN an otherwise clarifying article appearing recently in this journal, Cattell (1962) wrongly equates two apparently quite different formulae for estimating common factor scores. Because the error is apt to prove puzzling to those who read the article and because the second of the two formulae has not been given elsewhere in the psychometric literature, we propose here to correct the error and give a simple derivation of the second formula. The error occurs in Cattell’s equation (7), written as:
Intracranial Hemorrhage Associated With Revascularization Therapies

Background and Purpose— This review discusses the state of our current knowledge on hemorrhagic transformation (HT) and summarizes key factors to be considered when comparing risk associated with various approaches to revascularization. Summary of Review— HT is a common and natural consequence of infarction, likely related to matrix metalloproteinases and free radical pathways disrupting permeability barriers between blood and brain during ischemia and reperfusion. Symptomatic HT rates within 24 to 36 hours of stroke are increased in the setting of revascularization therapy regardless of modality. HT incidence rates must be considered in the context of the timing of imaging, the period of the study, the definition of clinically significant HT, and other key predictors of HT. The most consistently identified predictors of clinically significant HT in acute revascularization trials have been thrombolytic therapy, dose of lytic agents, edema or mass effect on head CT, stroke severity, and age. Other risk factors may be hyperglycemia, concurrent heparin use, timing of therapy, and timing of successful recanalization. Future predictors may also include imaging parameters, serological markers, variables related to intra-arterial technique, and arterial lesion location. Conclusions— Understanding how baseline and treatment variables impact HT rates after acute stroke is critical for those designing and interpreting acute stroke trials. Future trials should consider the use of PH-2 as a standardized safety end point, putting hemorrhagic changes in the context of overall clinical outcome, and developing strategies to reduce the rates of clinically significant intracranial hemorrhage.
The cone conjecture for vector-valued Siegel automorphic forms

We prove that the effective cone of automorphic vector bundles on the Siegel modular variety of rank $n$ in characteristic $p$ at a place of good reduction is encoded by the stack of $G$-zips of Pink--Wedhorn--Ziegler. Specifically, we show that the degree zero cohomology groups of automorphic vector bundles always vanish outside of the zip cone. This result is a special case of a general conjecture formulated by the Goldring and the author for all Hodge-type Shimura varieties of good reduction. In the case $n=3$, we give explicit conditions for the vanishing of the $0$-th cohomology group. Finally, in the course of the proof we define the notion of automorphic forms of trivial-type and study their properties.
Ev-Edge: Efficient Execution of Event-based Vision Algorithms on Commodity Edge Platforms

Event cameras have emerged as a promising sensing modality for autonomous navigation systems, owing to their high temporal resolution, high dynamic range and negligible motion blur. To process the asynchronous temporal event streams from such sensors, recent research has shown that a mix of Artificial Neural Networks (ANNs), Spiking Neural Networks (SNNs) as well as hybrid SNN-ANN algorithms are necessary to achieve high accuracies across a range of perception tasks. However, we observe that executing such workloads on commodity edge platforms which feature heterogeneous processing elements such as CPUs, GPUs and neural accelerators results in inferior performance. This is due to the mismatch between the irregular nature of event streams and diverse characteristics of algorithms on the one hand and the underlying hardware platform on the other. We propose Ev-Edge, a framework that contains three key optimizations to boost the performance of event-based vision systems on edge platforms: (1) An Event2Sparse Frame converter directly transforms raw event streams into sparse frames, enabling the use of sparse libraries with minimal encoding overheads (2) A Dynamic Sparse Frame Aggregator merges sparse frames at runtime by trading off the temporal granularity of events and computational demand thereby improving hardware utilization (3) A Network Mapper maps concurrently executing tasks to different processing elements while also selecting layer precision by considering both compute and communication overheads. On several state-of-art networks for a range of autonomous navigation tasks, Ev-Edge achieves 1.28x-2.05x improvements in latency and 1.23x-2.15x in energy over an all-GPU implementation on the NVIDIA Jetson Xavier AGX platform for single-task execution scenarios. Ev-Edge also achieves 1.43x-1.81x latency improvements over round-robin scheduling methods in multi-task execution scenarios.
Learning for the Twenty-First Century: Maximising Learning Transfer from Learning and Development Activity

This article builds on the learning gathered from the evaluation of a Scotland-wide child protection training programme. Based on Kirkpatrick's four-level framework, the study aimed to evaluate the impact of the learning programme on the practice of participants in the workplace. The study prompted the authors to examine the literature on maximising learning transfer across a range of occupations. This literature is discussed in the light of the findings from the evaluation and the experience of the authors in designing and implementing continuous professional development programmes in social services. The practice of inspection, monitoring and audit seems to have impacted negatively on staff's willingness to participate in data collection, and coupled with what appeared to be confusion about data protection legislation, the perceived burden of audit and inspection has significant implications for research and evaluation activity. Suggestions are made for the future design, delivery and evaluation of learning and development activity, and the role of managers is explored in relation to their responsibility for preparation, support and follow-up of workplace learning.
Crime and popular culture in the classroom: Approaches and resources for interrogating the obvious

"As a criminologist I feel more and more that my function is very similar to that of a book-reviewer or art critic. " (Christie 1994:186) That "toys" are merely playthings that occasionally educate, but more frequently provide parents respite from rambunctious children, is but one reading of their social function. At a deeper level, toys represent a microcosm of the adult world. Whether implicitly or accidentally, they prepare the child for adulthood before s/he has the ability to think about it critically. Is it any wonder that toy guns, plastic soldiers, and action figures serve so prominently in lives of male children, while girls bake goods in make-believe ovens and change dolls that actually wet themselves? Of course, this very social function of toys also accounts for their mass appeal, for what child turns down an opportunity to play grown-up? Therefore, as part of mass culture, the popularity of toys may be uncovered by examining the symbolic function they serve in the prevailing social elimate (Barthes 1983). Like toys, the many products and images that comprise popular ctdture are infinitely fertile in suggestions and contain both a manifest existence and a latent, but nonetheless potent symbolic state. And among the varied products that makeup popular culture, such as books, movies, and music, those containing themes of crime and violence are certainly central. A historical review of the popular arts in Western civilization reveals a culture persistently fascinated with crime. Whether painted on a cave wall, carved in Ass)~an stone, performed in Greek tragedies, or projected onto the silver screen, images of crime have always been a defining feature of society (Twitchell 1989). Yet while Emile Durkheim noted the paradoxical importance of crime for communal solidarity, his treatise on its normalcy overlooked an important cultural phenomenon: crime is not only socially necessary, it is also artistically popular. In response to the increasing importanee afforded popular culture in criminological publications (Anderson and Howard 1998; Bailey and Hale