Miracle-dz/UniFAR-FTUs huggingface dataset:
Immune responsiveness to Mycobacterium leprae and other mycobacterial antigens throughout the clinical and histopathological spectrum of leprosy.

Immunological responsiveness was studied throughout the clinical and histopathological spectrum of leprosy (Ridley–Jopling scale) by the methods of lymphocyte transformation, leucocyte migration inhibition and delayed skin hypersensitivity, The response to Mycobacterium leprae showed by all methods a continuous decrease from strong responses in the polar tuberculoid (TT) group to virtually negative responses in the polar lepromatous (LL) group. There was a good agreement between the in vitro methods and the lepromin skin test, giving support to the latter as useful tool in the evaluation of immune responsiveness to M. leprae in leprosy patients. The immune response to BCG and PPD on the other hand, decreased only slightly towards the lepromatous pole of the spectrum, confirming the high degree of specificity of the immune defect in lepromatous leprosy. Patients grouped histologically as subpolar tuberculoid (TT/BT) reacted particularly strongly to BCG and PPD. As it is likely that the methods used mainly measured T-lymphocyte function, the clinicopathological manifestations of leprosy appear to reflect the strength of the cellular immune response against M. leprae. Thus the findings give strong support to the concept of a host-determined, immunological diseases pectrum as expressed in the Ridley–Jopling classification.
An unexpected increase of entropy in a sleepwalking disorder patient during propofol and remifentanil anesthesia: a case report

We report a case of increased values of entropy parameters Response Entropy (RE) and State Entropy (SE) during intravenous general anesthesia in a sleepwalking patient. An ASA class II, 64-year-old woman with stress incontinence underwent mid-urethral sling surgery. Prior to surgery, the patient had been administered paroxetine, valproic acid and clonazepam for the treatment of sleepwalking disorder. After 10 min of target-controlled infusion of propofol and remifentanil, entropy values increased up to 94 (RE) and 88 (SE) for 10 min. The target effect-site concentrations of anesthetics increased from 4 to 7 µg/ml propofol and 4 ng/ml remifentanil, at which point values fell back to adequate anesthesia levels. Episodes of recall or of explicit memories did not occur during the anesthesia. In conclusion, sleepwalking patients with long-term use medications may need increment of anesthetic dose caused by the anesthetic drug metabolism activation or impairment or immaturity of inhibitory circuits in brain.
Stories, Studies, and Suggestions About Reading

This article is based on the presidential address I delivered at the 12th annual meeting of the Society for the Scientific Study of Reading, held in June 2005 in Toronto. I trace the development of my interest in instructional research in, first, beginning reading and, more recently, in comprehension, and I describe studies designed to improve the reading of children with learning disabilities and others at risk for academic failure. I conclude with reflections about what our field has accomplished over the last few decades and with suggestions about what might profitably be given further attention at the present time.
Online Outlier Exploration Over Large Datasets

Traditional outlier detection systems process each individual outlier detection request instantiated with a particular parameter setting one at a time. This is not only prohibitively time-consuming for large datasets, but also tedious for analysts as they explore the data to hone in on the appropriate parameter setting and desired results. In this work, we present the first online outlier exploration platform, called ONION, that enables analysts to effectively explore anomalies even in large datasets. First, ONION features an innovative interactive anomaly exploration model that offers an "outlier-centric panorama" into big datasets along with rich classes of exploration operations. Second, to achieve this model ONION employs an online processing framework composed of a one time offline preprocessing phase followed by an online exploration phase that enables users to interactively explore the data. The preprocessing phase compresses raw big data into a knowledge-rich ONION abstraction that encodes critical interrelationships of outlier candidates so to support subsequent interactive outlier exploration. For the interactive exploration phase, our ONION framework provides several processing strategies that efficiently support the outlier exploration operations. Our user study with real data confirms the effectiveness of ONION in recognizing "true" outliers. Furthermore as demonstrated by our extensive experiments with large datasets, ONION supports all exploration operations within milliseconds response time.
On the “Demystification” of Insight: A Critique of Neuroimaging Studies of Insight

Psychologists studying problem solving have, for over 100 years, been interested in the question of whether there are two different modes of solving problems. One mode—problem solving based on analysis—depends on application of past experience to the problem at hand and proceeds incrementally toward solution. The second mode—problem solving based on insight—involves breaking away from what one knows, typically after one has reached an impasse, and entails solution occurring suddenly, in a leap beyond what one knows. A number of recent studies have used neuroscientific methods (e.g., fMRI; EEG) to demystify insight, i.e., to dispel what is seen as the mystery of insight in problem solving. This research has been summarized by Lehrer (2008), in the context of examination of a real-life example of insightful problem solving: R. Wagner Dodge's creation of an escape fire to avoid near-certain death from a forest fire. This article presents a critical review of neuroscientific studies of insight, which indicates that methodological flaws in those studies have precluded their furthering the understanding of insight. Tentative proposals are presented concerning the design of a study that would allow one to determine the brain states underlying insight. In addition, an analysis of Dodge's insight indicates that there may not be that much mystery standing in the way of our understanding what he did.
Changes in epidemiology of leptospirosis in 2003–2004, a two El Niño Southern Oscillation period, Guadeloupe archipelago, French West Indies

SUMMARY Our study aimed at analysing the changes in epidemiological features of leptospirosis cases from the hospital of Pointe à Pitre in Guadeloupe in 2003–2004 compared to reliable data in 1994–2001. Leptospirosis incidence increased fourfold during 2002–2004, a period with two El Niño events. Whereas the main risk factors were unchanged (male gender, occupational exposure, contact with cattle or pigs) a major role of rodent exposure emerged (52%, P=0·02, multivariate analysis). Interestingly, mean age of cases shifted to the older population (51·7 years vs. 43 years, P<0·05). Moreover, the Ballum serogroup rose dramatically (36% of incidence) competing with the Icterohaemorragiae serogroup (62%). However, severe forms were less recorded. Our data suggest that the changes in leptospirosis features could be related to exceptional meteorological events and their consequences on rodent populations. We propose the monitoring of rodent population and climatic data as a tool of management of leptospirosis in Guadeloupe.
Expression of the gag-pol fusion protein of Moloney murine leukemia virus without gag protein does not induce virion formation or proteolytic processing

A mutant of Moloney murine leukemia virus was generated in which the UAG termination codon at the 3' end of the gag gene was changed to a CAG codon encoding glutamine. Cells carrying the mutant provirus constitutively express the gag-pol fusion protein and no detectable gag protein. The precursor is stable, is not processed by the protease domain within the precursor, and does not induce assembly and release of virion particles.
Assessment and Treatment of Patients with Borderline Personality Disorder in the College and University Population

The assessment and treatment of students with borderline personality traits or disorders poses specific challenges for clinicians at college and university mental health centers complicated, frequently, by a model of brief treatment frameworks and high patient volumes. Students with borderline pathology will be well represented in student health centers and will likely generate unusually complex and concerning situations for clinicians and administrators. Accurate diagnosis of borderline pathology, avoidance of iatrogenic complications related to misdiagnosis, and referral to informed and evidence-based interventions can guide clinicians’ management. Risk management concerns are best addressed by a clear and realistic understanding of the borderline pathology. The author proposes a variety of interventions for college and university mental health clinicians with the goal of accurate diagnosis of borderline personality, management focusing on safety for both students and clinicians, and targeted referrals for both borderline symptomatology and co-occurring conditions.
3-D Face Recognition Using Local Appearance-Based Models

In this paper, we present a local appearance-based approach for 3-D face recognition. In the proposed algorithm, we first register the 3-D point clouds to provide a dense correspondence between faces. Afterwards, we analyze two mapping techniques-the closest-point mapping and the ray-casting mapping, to construct depth images from the corresponding well-registered point clouds. The depth images that are obtained are then divided into local regions where the discrete cosine transformation is performed to extract local information. The local features are combined at the feature level for classification. Experimental results on the FRGC version 2.0 face database show that the proposed algorithm performs superior to the well-known face recognition algorithms.
Title: a Mathematical Analysis of Development of Oriented Receptive Fields in Linsker's Model

Abstract. We consider Linsker’s neural network model, in particular, development of oriented receptive fields of cells on layer G, and investigate which features in this model are crucial for the development. We assume that the correlation function is a Mexican-hat shape function while we introduce the arbor function explicitly and discuss its role in the development. We compute the Fourier transform of the modification rule of synaptic weights to analyze its modification process. Through our mathematical analysis, we obtain the following observations. (1) the Fourier transform of the correlation function extracts a set of Fourier coefficients of a certain frequency, (2) the Fourier transform of the set of those coefficients consists of a finite number of its components, (3) among those components, the arbor function extracts only some of those and others degenerate, (4) thus, the shape of a receptive field can be described as a combination of a certain Fourier cosine components and Fourier sine components, (5) the arbor function determines one of the set of the Fourier cosine components and that of the Fourier sine components dominates the other. We consider two types of the arbor function and analyze when oriented (e.g., bi-lobed) receptive fields are developed. These observations are also justified by computer simulations. Finally we discuss the role of Linsker’s parameters k1 and k2.
Subject-clitic inversion and inflectional hierarchies

Abstract This paper attributes the effects of subject-clitic inversion to a reversal of the normal hierarchy between Tense (T) and Mood (M) projections which is induced by certain modal or illocutionary features. The simple inversion pattern results from raising of the verb to M, while the subject raises to Spec TP. This structure provides a position (Spec MP) for the lexical subject in the case of complex inversion, without the need for multiple specifiers or additional functional categories. By raising to this position, the lexical subject binds a surrogate clitic in Spec TP, creating an argument Chain which contains a single theta-position and a single Case position. The implications of this analysis for subject questions and the phenomenon of stylistic inversion are also discussed in some detail.
A three dimensional localization algorithm for underwater acoustic sensor networks

Although many localization protocols have been proposed for terrestrial sensor networks in recent years, the unique characteristics of the underwater acoustic communication channel, such as high and variable propagation delay and the three dimensional volume of the environment make it necessary to design and develop new localization algorithms. In this paper, a localization algorithm called three-dimensional underwater localization (3DUL) is introduced. 3DUL achieves networkwide robust 3D localization by using a distributed and iterative algorithm. Most importantly, 3DUL exploits only three surface buoys for localization initially. The sensor nodes leverage the low speed of sound to accurately determine the inter-node distances. Performance evaluations show that 3DUL algorithm provides high accuracy in underwater localization, which does not degrade with network size.
A stable intermediate in the thermal unfolding process of a chimeric 3‐isopropylmalate dehydrogenase between a thermophilic and a mesophilic enzymes

The thermal unfolding process of a chimeric 3‐isopropylmalate dehydrogenase made of parts from an extreme thermophile, Thermus thermophilus, and a mesophile, Bacillus subtilis, enzymes was studied by CD spectrophotometry and differential scanning calorimetry (DSC). The enzyme is a homodimer with a subunit containing two structural domains. The DSC melting profile of the chimeric enzyme in 20 mM NaHCO3, pH 10.4, showed two endothermic peaks, whereas that of the T. thermophilus wild‐type enzyme had one peak. The CD melting profiles of the chimeric enzyme under the same conditions as the DSC measurement, also indicated biphasic unfolding transition. Concentration dependence of the unfolding profile revealed that the first phase was protein concentration‐independent, whereas the second transition was protein concentration‐dependent. When cooled after the first transition, the intermediate was isolated, which showed only the second transition upon heating. These results indicated the existence of a stable dimeric intermediate followed by the further unfolding and dissociation in the thermal unfolding of the chimeric enzyme at pH 10–11. Because the portion derived from the mesophilic isopropylmalate dehydrogenase in the chimeric enzyme is located in the hinge region between two domains of the enzyme, it is probably responsible for weakening of the interdomain interaction and causing the decooperativity of two domains. The dimeric form of the intermediate suggested that the first unfolding transition corresponds to the unfolding of domain 1 containing the N‐ and C‐termini of the enzyme, and the second to that of domain 2 containing the subunit interface.
Moving out of conflict into reconciliation – Bildung through philosophical dialogue in intercultural and interreligious education

The empirical basis of this article is the reconciliation process in a destructive conflict between students of different cultural and religious backgrounds in upper secondary education in Norway. The Dialogos approach to dialogical philosophizing was tried out through an action research process in order to bring about reconciliation, letting the students explore existential, ethical, religious and emotional topics together. The empirical reconciliation process is discussed in relation to elements of the philosophical concept Bildung, aiming at answering the following overarching questions: how did the movement from conflict to reconciliation come about through the action research process; to what extent might the Reconciliation Project be understood as a process of Bildung towards human maturity and wisdom; and how might philosophical dialogues become an institutionalized part of interreligious and intercultural education?
Attribution Required: Stack Overflow Code Snippets in GitHub Projects

Stack Overflow (SO) is the largest Q&A website for developers, providing a huge amount of copyable code snippets. Using these snippets raises various maintenance and legal issues. The SO license requires attribution, i.e., referencing the original question or answer, and requires derived work to adopt a compatible license. While there is a heated debate on SO's license model for code snippets and the required attribution, little is known about the extent to which snippets are copied from SO without proper attribution. In this paper, we present the research design and summarized results of an empirical study analyzing attributed and unattributed usages of SO code snippets in GitHub projects. On average, 3.22% of all analyzed repositories and 7.33% of the popular ones contained a reference to SO. Further, we found that developers rather refer to the whole thread on SO than to a specific answer. For Java, at least two thirds of the copied snippets were not attributed.
Modified Full Bayesian Networks Classifiers for Medical Diagnosis

This paper is present a modified Bayesian Network (BN) for Full Bayesian Classifier (FBC) for used it to diagnoses the condition of a patient from some of symptoms and medical history. The conditions are the heart diseases and the nervous diseases. Modified for FBC is depended on common structure known as naïve Bayes. Determining the network structure is D-separated by the variable. Each variable has CPT and each disease (table) has Probability. By modified the equation for find CPT for each variable and Probability for each disease (table) in Modified-FBC (M-FBC) structure, the system for diagnosis is designed. The experimental resulted show that the successful ratio of heart diseases (93%) and nervous system diseases (98%) approximately.
A New Performance Measure Using  $k$-Set Correlation for Compressed Sensing Matrices

In this letter, a new performance measure for compressed sensing matrices is proposed. This new measure is based on the k-set correlation vectors whose components consist of the correlation values between two columns in the k-column submatrices of a sensing matrix. This measure is highly related to the restricted isometry property (RIP). And the proposed measure has less computational complexity than the condition number approach which is a typical approach for performance prediction with RIP check. It is shown by simulation that the proposed scheme works well as a performance measure for the compressed sensing matrices.
Genetic Factors Influence the Clustering of Depression among Individuals with Lower Socioeconomic Status

Objective To investigate the extent to which shared genetic factors can explain the clustering of depression among individuals with lower socioeconomic status, and to examine if neuroticism or intelligence are involved in these pathways. Methods In total 2,383 participants (1,028 men and 1,355 women) of the Erasmus Rucphen Family Study were assessed with the Center for Epidemiologic Studies Depression Scale (CES-D) and the Hospital Anxiety and Depression Scale (HADS-D). Socioeconomic status was assessed as the highest level of education obtained. The role of shared genetic factors was quantified by estimating genetic correlations (ρG) between symptoms of depression and education level, with and without adjustment for premorbid intelligence and neuroticism scores. Results Higher level of education was associated with lower depression scores (partial correlation coefficient −0.09 for CES-D and −0.17 for HADS-D). Significant genetic correlations were found between education and both CES-D (ρG = −0.65) and HADS-D (ρG = −0.50). The genetic correlations remained statistically significant after adjusting for premorbid intelligence and neuroticism scores. Conclusions Our study suggests that shared genetic factors play a role in the co-occurrence of lower socioeconomic status and symptoms of depression, which suggest that genetic factors play a role in health inequalities. Further research is needed to investigate the validity, causality and generalizability of our results.
Cognitive Architectures and Autonomy: A Comparative Review

Abstract One of the original goals of artificial intelligence (AI) research was to create machines with very general cognitive capabilities and a relatively high level of autonomy. It has taken the field longer than many had expected to achieve even a fraction of this goal; the community has focused on building specific, targeted cognitive processes in isolation, and as of yet no system exists that integrates a broad range of capabilities or presents a general solution to autonomous acquisition of a large set of skills. Among the reasons for this are the highly limited machine learning and adaptation techniques available, and the inherent complexity of integrating numerous cognitive and learning capabilities in a coherent architecture. In this paper we review selected systems and architectures built expressly to address integrated skills. We highlight principles and features of these systems that seem promising for creating generally intelligent systems with some level of autonomy, and discuss them in the context of the development of future cognitive architectures. Autonomy is a key property for any system to be considered generally intelligent, in our view; we use this concept as an organizing principle for comparing the reviewed systems. Features that remain largely unaddressed in present research, but seem nevertheless necessary for such efforts to succeed, are also discussed.
An approach to Adaptive E-learning Hypermedia System based on Learning Styles (AEHS-LS): Implementation and evaluation

This paper presents an approach to integrate learning styles into Adaptive E-learning Hypermedia. The main objective was to develop an adaptive e-learning system and assess the effect of adapting educational materials individualized to the student’s learning style. The proposed approach utilized adaptive hypermedia technology to improve learning process by adapting course content presentation to student learning styles. The combination of Apache, MySQL and PHP were used to implement the system based on learning styles to present the appropriate subject matter, including the content, format and media type. The system was organized into 3 models; domain model, learner model and adaptation model. The 3 models interact together to perform adaptively. An experiment between 2 groups of students was conducted to evaluate the impact on learning achievement. Inferential statistics were applied to make inferences from the sample data to more general conditions. Descriptive statistics were applied simply to describe what's going on in the sample data. Results showed that students taught using learning style adaptive system performed significantly better in academic achievement (p<0.05) than students taught the same material without adaptation to learning style. The findings support the use of learning styles as guideline for adaptation into the Adaptive E-learning Hypermedia Systems. Key words: E-learning, adaptive hypermedia, learning styles, technology based education, academic achievement.