Miracle-dz/UniFAR-FTUs huggingface dataset:
Turning up the contrast: self-enhancement motives prompt egocentric contrast effects in social judgments.

Contrast effects occur when people judge the behavior and attitudes of others relative to their own. We tested a motivational account suggesting that these effects arise because people tailor their judgments of others to affirm their own self-worth. Consistent with that interpretation, participants displayed more egocentric contrast in their judgments of another person's intelligence (i.e., their evaluation of his score on the Scholastic Aptitude Test was more negatively related to their own score) after their self-esteem was threatened than after it was bolstered (Studies 1 and 2). High-self-esteem individuals displayed more judgmental contrast overall than did their low-esteem counterparts (Study 2). Strongly pro-choice participants whose esteem was threatened also displayed more contrast in their judgments of another person's attitude on abortion, relative to esteem-bolstered participants (Study 3). Discussion centers on the implications of these findings for theory on social comparison, self-affirmation, and social judgment.
Equal Time in Prime Time? Scheduling Favoritism and Gender on the Broadcast Networks

This study examines the relationship between broadcast network scheduling practices and representation of women on screen and behind the scenes in the 7999-2000 prime-time season. Drawing on previous re- search of scheduling practices and organizational theory, the researchers posited and found that programs airing on the weblets (WB, UPN) employ greater percentages of women on screen and behind the scenes than the big three networks (ABC, CBS, NBC) or Fox. In addition, women working behind the scenes on the weblets correlated with higher representation of female characters when compared to the big three networks and Fox. Moreover, weblet programs featuring women on screen and behind the scenes enjoyed more favorable scheduling practices than those on the big three networks and Fox. The authors concluded that the weblets provide a more hospitable environment for women than the more established networks.
Behavior Recognition with HMM and Feature Analysis using a Wide-view Camera and a PTZ camera

This paper proposes a method for recognizing human behaviors based on a combination of “overall motion analysis using Hidden Markov Model (HMM)” and “detailed feature analysis in a specific area by using an active (pan-tilt-zoom, PTZ) camera”. The PTZ parameters are controlled depending on the intermediate result of analyzing the target’s motions based on HMM. As a result, our system can distinguish between similar behaviors by observing high-resolution characteristic features (e.g., motion/shape). Experimental results demonstrated the effectiveness of the proposed system.
Schedulability Analysis for Real-Time Systems with EDF Scheduling

Real-time scheduling is the theoretical basis of real-time systems engineering. Earliest deadline first (EDF) is an optimal scheduling algorithm for uniprocessor real-time systems. Existing results on an exact schedulability test for EDF task systems with arbitrary relative deadlines need to calculate the processor demand of the task set at every absolute deadline to check if there is an overflow in a specified time interval. The resulting large number of calculations severely restricts the use of EDF in practice. In this paper, we propose new results on necessary and sufficient schedulability analysis for EDF scheduling; the new results reduce, exponentially, the calculation times, in all situations, for schedulable task sets, and in most situations, for unschedulable task sets. For example, a 16-task system that in the previous analysis had to check 858,331 points (deadlines) can, with the new analysis, be checked at just 12 points. There are no restrictions on the new results: each task can be periodic or sporadic, with relative deadline, which can be less than, equal to, or greater than its period, and task parameters can range over many orders of magnitude.
Determinants of attenuation and temperature sensitivity in the type 1 poliovirus Sabin vaccine

To identify determinants of attenuation in the poliovirus type 1 Sabin vaccine strain, a series of recombinant viruses were constructed by using infectious cDNA clones of the virulent type 1 poliovirus P1/Mahoney and the attenuated type 1 vaccine strain P1/Sabin. Intracerebral inoculation of these viruses into transgenic mice which express the human receptor for poliovirus identified regions of the genome that conferred reduced neurovirulence. Exchange of smaller restriction fragments and site-directed mutagenesis were used to identify the nucleotide changes responsible for attenuation. P1/Sabin mutations at nucleotides 935 of VP4, 2438 of VP3, and 2795 and 2879 of VP1 were all shown to be determinants of attenuation. The recombinant viruses and site-directed mutants were also used to identify the nucleotide changes which are involved in the temperature sensitivity of P1/Sabin. Determinants of this phenotype in HeLa cells were mapped to changes at nucleotides 935 of VP4, 2438 of VP3, and 2741 of VP1. The 3Dpol gene of P1/Sabin, which contains three amino acid differences from its parent P1/Mahoney, also contributes to the temperature sensitivity of P1/Sabin; however, mutants containing individual amino acid changes grew as well as P1/Mahoney at elevated temperatures, suggesting that either some combination or all three changes are required for temperature sensitivity. In addition, the 3'-noncoding region of P1/Sabin augments the temperature-sensitive phenotype conferred by 3Dpol. Although nucleotide 2741, 3Dpol, and the 3'-noncoding region of P1/Sabin contribute to the temperature sensitivity of P1/Sabin, they do not contribute to attenuation in transgenic mice expressing the poliovirus receptor, demonstrating that determinants of attenuation and temperature sensitivity can be genetically separated.
AjaxScope: a platform for remotely monitoring the client-side behavior of web 2.0 applications

The rise of the software-as-a-service paradigm has led to the development of a new breed of sophisticated, interactive applications often called Web 2.0. While web applications have become larger and more complex, web application developers today have little visibility into the end-to-end behavior of their systems. This paper presents AjaxScope, a dynamic instrumentation platform that enables cross-user monitoring and just-in-time control of web application behavior on end-user desktops. AjaxScope is a proxy that performs on-the-fly parsing and instrumentation of JavaScript code as it is sent to users' browsers. AjaxScope provides facilities for distributed and adaptive instrumentation in order to reduce the client-side overhead, while giving fine-grained visibility into the code-level behavior of web applications. We present a variety of policies demonstrating the power of AjaxScope, ranging from simple error reporting and performance profiling to more complex memory leak detection and optimization analyses. We also apply our prototype to analyze the behavior of over 90 Web 2.0 applications and sites that use large amounts of JavaScript.
Using assessment to support higher level learning: the multiple choice item development assignment

This paper describes the multiple choice item development assignment (MCIDA) that was developed to support both content and higher level learning. The MCIDA involves students in higher level learning by requiring them to develop multiple choice items, write justifications for both correct and incorrect answer options and determine the highest cognitive level that the item is testing. The article discusses the benefits and limitations of the scheme and presents data on the largely positive student reactions to the scheme. The development of the MCIDA also serves as an example for how traditional summatively oriented assessment procedures can be developed into tools that directly support student learning.
ANOMALY DETECTION USING ARTIFICIAL NEURAL NETWORK

In this research, anomaly detection using neural network is introduced. This research aims to experiment with user behaviour as parameters in anomaly intrusion detection using a backpropagation neural network. Here we wanted to see if a neural network is able to classify normal traffic correctly, and detect known and unknown attacks without using a huge amount of training data. For the training and testing of the neural network, we used the DARPA Intrusion Detection Evaluation data sets. In our final experiment, we have got a classification rate of 88% on known and unknown attacks. Compared with other researches our result is very promising.
Insulin regulates milk production and mammary gland and hind-leg amino acid fluxes and blood flow in lactating goats.

We investigated the roles of insulin and amino acid (AA) in regulating milk production and the uptake of AA and blood flow (BF) by the mammary gland and hind-leg of goats (n = 4). During two periods, either saline or AA (65 g/d) was infused i.v. for 7.5 d, and, beginning on d 5, goats were subjected to a hyperinsulinemic-euglycemic clamp. The insulin clamp elevated plasma insulin levels threefold and insulin-like growth factor-1 by 27%, and euglycemia was maintained by the infusion of glucose. Arterial, mammary, and tarsal vein blood samples were obtained on d 4 and 8 of each period, and blood flow was monitored continuously by probes. Insulin and insulin plus AA infusions increased the yields of milk by 13 to 18% and protein by 10 to 21%, but AA infusion alone had no effect. The insulin clamp reduced milk fat content by 21 to 31% and yield by 8 to 19%, and reduced the yields of milk fatty acids >C16. The insulin clamp increased mammary blood flow by 42%, but insulin and AA infusions both increased hind-leg BF by 29 to 52% and by 25%, respectively. Net uptakes of most plasma AA by the udder were reduced by insulin, whereas AA infusion had no effect. For the leg, the uptake of His and Thr were decreased by insulin, whereas the infusion of AA stimulated the uptake of total essential AA. Insulin increased the uptake of glucose by the udder but not by the leg. This study suggests that the udder and leg tissues respond differently to infusions of insulin and AA; the udder was more responsive to insulin, while the leg was more responsive to AA concentralion (supply), at least in terms of AA uptake and net anabolism (protein gain or secretion).
A Complete Guide to Therapy

In the preface to the first edition of the Critique of Pure Reason, Kant remarks on the pletora of contradictory philosophical systems and comments caustically: “the battlefield of these endless controversies is called metaphysics” (A viii). The claims and counterclaims have finally produced a “prevailing mood of weariness and indifferentism” which, “while not the solution, at least contains the germs of a solution,” for, says Kant, “indifferentism is an indication that ‘the age…refuses to be any longer put off with illusory knowledge’” (A xi). Accordingly Kant proposes to undertake a critique of theoretical reason whose purpose is to “(determine) the rules and limits of its [reason's] employment” (A xvi).
Beyond Psychometric Evaluation of the Student—Task Determinants of Accommodation

Students with learning disabilities obtain a wide range of recommended accommodations in secondary school, which they anticipate will continue into postsecondary education. Although the student’s specific learning disability (SLD) contributes to the accommodation planning process, it is not the sole determinant of appropriate accommodation. Academic requirements have integrity of their own, bona fide elements that cannot be altered without changing the nature of what is being taught or assessed. It is important to remain cognizant of bona fide requirements, which may not be altered when recommending academic accommodations. This is especially true when the student is heading into postsecondary or professional education. This article uses the World Health Organization’s model of disability and the human rights context to highlight the role of bona fide requirements in accommodation planning.
Accelerated Force Computation for Physics-Based Information Visualization

Visualization of similarity is an emerging technique for analyzing relation-based data sets. A common way of computing the respective layouts in an information space is to employ a physics-based mass-spring system. Force computation, however, is costly and of order N2. In this paper, we propose a new acceleration method to adopt a well-known optimized force-computation algorithm which drastically reduces the computation time to the order of N log N. The basic idea is to derive a two-pass, "prediction and correction" procedure including a customized potential function. We have applied this method to two different applications: web access and sales analysis. Both demonstrate the efficiency and versatility of the presented method.
Role for cytotoxic chemotherapy in patients with recurrent glioblastoma progressing on bevacizumab: a retrospective case series

One hundred patients, aged 36–84 years (median 62 years) with recurrent glioblastoma (GBM), were treated previously with surgery, concurrent radiotherapy and temozolomide and postradiotherapy temozolomide followed by single-agent bevacizumab (BEV) at either first (60 patients) or second recurrence (40 patients). Patients were then treated following progression on BEV only with BEV and carboplatin (75 patients), cyclophosphamide (15 patients) or BCNU (ten patients; BEV+). Three hundred and sixteen treatment cycles (median: 2; range: 1–9) were administered of BEV+. There were 74 grade 3 adverse events in 29 patients (29%) and 20 grade 4 adverse events in ten patients (10%). Following 2 months of BEV+, 60 patients (60%) demonstrated progressive disease and discontinued therapy. Forty patients (40%) had neuroradiographic stable disease. Survival ranged from 1 to 12 months (median: 4 months). Median and 6-month progression free survival was 2.5 months and 5%, respectively. BEV plus a cytotoxic chemotherapy demonstrated limited efficacy in BEV-refractory GBM and emphasizes an unmet need in neuro-oncology in adults with BEV-refractory GBM.
Artificial Neural Network Models based Cardiac Arrhythmia Disease Diagnosis from ECG Signal Data

Changes in the normal rhythm of a human heart may result in different cardiac arrhythmias, which may be immediately causes irreparable damage to the heart sustained over long periods of time. The ability to automatically identify arrhythmias from ECG recordings is important for clinical diagnosis and treatment. In this paper we proposed an Artificial Neural Network (ANN) based cardiac arrhythmia disease diagnosis system using standard 12 lead ECG signal recordings data. In this study, we are mainly interested in classifying disease in normal and abnormal classes. We have used UCI ECG signal data to train and test three different ANN models. In arrhythmia analysis, it is unavoidable that some attribute values of a person would be missing. Therefore we have replaced these missing attributes by closest column value of the concern class. ANN models are trained by static backpropagation algorithm with momentum learning rule to diagnose cardiac arrhythmia. The classification performance is evaluated using measures such as mean squared error (MSE), classification specificity, sensitivity, accuracy, receiver operating characteristics (ROC) and area under curve (AUC). Out of three different ANN models Multilayer perceptron ANN model have given very attractive classification results in terms of classification accuracy and sensitivity of 86.67% and 93.75% respectively while Modular ANN have given 93.1% classification specificity. General Terms Machine Learning, Pattern Classification.
Compression-based normal similarity measures for DNA sequences

Similarity measures based on compression assess the distance between two objects based on the number of bits needed to describe one, given a description of the other. Theoretically, compression-based similarity depends on the concept of Kol-mogorov complexity, which is non-computable. The implementations require compression algorithms that are approximately normal. The approach has important advantages (no signal features to identify and extract, for example) but the compression method must be normal. This paper proposes normal algorithms based on mixtures of finite context models. Normality is attained by combining two new ideas: the use of least-recently-used caching in the context models, to allow deeper contexts, and data interleaving, to better explore that cache. Examples for DNA sequences are given (at the human genome scale).
The N-Terminal UND Motif of the Arabidopsis U-Box E3 Ligase PUB18 Is Critical for the Negative Regulation of ABA-Mediated Stomatal Movement and Determines Its Ubiquitination Specificity for Exocyst Subunit Exo70B1

The N-terminal UND motif of PUB18 is critical for the negative regulation of ABA-mediated stomatal closure and ubiquitination specificity to Exo70B1, a subunit of the exocyst complex. The Arabidopsis thaliana U-box E3 ligases PUB18/PUB19 and PUB22/PUB23 are negative regulators of drought stress responses. PUB18/PUB19 regulate the drought stress response in an abscisic acid (ABA)-dependent manner, whereas PUB22/PUB23 regulate this response in an ABA-independent manner. A major structural difference between PUB18/PUB19 and PUB22/PUB23 is the presence of the UND (U-box N-terminal domain). Here, we focused on elucidating the molecular mechanism that mediates the functional difference between PUB18 and PUB22 and found that the UNDPUB18 was critically involved in the negative regulation of ABA-mediated stomatal movements. Exo70B1, a subunit of the exocyst complex, was identified as a target of PUB18, whereas Exo70B2 was a substrate of PUB22. However, the ∆UND-PUB18 derivative failed to ubiquitinate Exo70B1, but ubiquitinated Exo70B2. By contrast, the UNDPUB18-PUB22 chimeric protein ubiquitinated Exo70B1 instead of Exo70B2, suggesting that the ubiquitination specificities of PUB18 and PUB22 to Exo70B1 and Exo70B2, respectively, are dependent on the presence or absence of the UNDPUB18 motif. The ABA-insensitive phenotypes of the pub18 pub19 exo70b1 triple mutant were reminiscent of those of exo70b1 rather than pub18 pub19, indicating that Exo70B1 functions downstream of PUB18. Overall, our results suggest that the UNDPUB18 motif is crucial for the negative regulation of ABA-dependent stomatal movement and for determination of its ubiquitination specificity to Exo70B1.
Rethinking inhibition theory: explaining forgetting without inhibition

The aim of the present thesis is to investigate whether the inhibition theory provides a better explanation for the retrieval-induced forgetting effect than the strength-based models. We examine the three main properties of the inhibition theory and conclude that inhibition is not necessary to explain retrieval-induced forgetting and hence forgetting can still be explained without recourse to the concept of inhibition.
A multi-purpose control and power electronic architecture for active magnetic actuators

This paper shows the results related with the design and implementation of a multi-purpose electronic architecture used to drive magnetic actuators by means of a three-phase independent-legs module in place of the commonly used H-bridge modules. The typical application is the magnetic actuators drive used in active magnetic bearings. The architecture is composed of a control unit with a floating point Digital Signal Processor (DSP), a power board with six independent phase legs and a carrier board to interconnect them. When more than one module is required by the application, the communication between them is guaranteed by means of CAN bus interconnection. The proposed system allows to drive two pairs of opposite electromagnets, such as those typically used to control active magnetic bearings. The study is motivated by the opportunity of reducing the amount of power and control electronic components resulting in a more straightforward, efficient and cost reduction design.
Optical Flow Focusing: Light-Induced Destabilization of Stable Liquid Threads

Confinement of flowing liquid threads by solid walls makes them stable with respect to the Rayleigh–Plateau instability. We demonstrate here that light can break this stability, by forcing locally the deformation of the liquid interface through thermally-induced Marangoni stresses. Depending upon the confining conditions and fluid properties, this optocapillary deformation either pinches or inflates the thread, which may in both cases lead to its localized fragmentation into droplets. In the pinching regime, the laser beam behaves as a wall-free constriction that flow fo-cuses the thread, leading to successive regimes of single and multiple periodicity. Light-driven local Marangoni stresses may prove an elegant contactless alternative to control reversibly the thread-to-droplet transition for digital microfluidics.
Image Motion Estimation From Motion Smear-A New Computational Model

Motion smear is an important visual cue for motion perception by the human vision system (HVS). However, in image analysis research, exploiting motion smear has been largely ignored. Rather, motion smear is usually considered as a degradation of images that needs to be removed. In this paper, the authors establish a computational model that estimates image motion from motion smear information-"motion from smear". In many real situations, the shutter of the sensing camera must be kept open long enough to produce images of adequate signal-to-noise ratio (SNR), resulting in significant motion smear in images. The authors present a new motion blur model and an algorithm that enables unique estimation of image motion. A prototype sensor system that exploits the new motion blur model has been built to acquire data for "motion-from-smear". Experimental results on images with both simulated smear and real smear, using the authors' "motion-from-smear" algorithm as well as a conventional motion estimation technique, are provided. The authors also show that temporal aliasing does not affect "motion-from-smear" to the same degree as it does algorithms that use displacement as a cue. "Motion-from-smear" provides an additional tool for motion estimation and effectively complements the existing techniques when apparent motion smear is present.
Mechanisms, models and biomarkers in amyotrophic lateral sclerosis

Abstract The last 30 years have seen a major advance in the understanding of the clinical and pathological heterogeneity of amyotrophic lateral sclerosis (ALS), and its overlap with frontotemporal dementia. Multiple, seemingly disparate biochemical pathways converge on a common clinical syndrome characterized by progressive loss of upper and lower motor neurons. Pathogenic themes in ALS include excitotoxicity, oxidative stress, mitochondrial dysfunction, neuroinflammation, altered energy metabolism, and most recently RNA mis-processing. The transgenic rodent, overexpressing mutant superoxide dismutase-1, is now only one of several models of ALS pathogenesis. The nematode, fruit fly and zebrafish all offer fresh insight, and the development of induced pluripotent stem cell-derived motor neurons holds promise for the screening of candidate therapeutics. The lack of useful biomarkers in ALS contributes to diagnostic delay, and the inability to stratify patients by prognosis may be an important factor in the failure of therapeutic trials. Biomarkers sensitive to disease activity might lessen reliance on clinical measures and survival as trial endpoints and reduce study length. Emerging proteomic markers of neuronal loss and glial activity in cerebrospinal fluid, a cortical signature derived from advanced structural and functional MRI, and the development of more sensitive measurements of lower motor neuron physiology are leading a new phase of biomarker-driven therapeutic discovery.