Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Protein Immunogenicity with a Dendritic Cell Line-Derived Endolysosomal Degradome

Background The growing number of novel candidate molecules for the treatment of allergic diseases imposed a dramatic increase in the demand for animal experiments to select immunogenic vaccines, a pre-requisite for efficacy. Because no in vitro methods to predict the immunogenicity of a protein are currently available, we developed an in vitro assay that exploits the link between a protein's immunogenicity and its susceptibility to endolysosomal proteolysis. Methodology We compared protein composition and proteolytic activity of endolysosomal fractions isolated from murine bone marrow- and human blood- derived dendritic cells, and from the dendritic cell line JAWS II. Three groups of structurally related antigen variants differing in their ability to elicit immune responses in vivo (Bet v 1.0101 and Bet v 1.0401, RNases A and S, holo- and apo-HRP) were subjected to in vitro simulated endolysosomal degradation. Kinetics and patterns of generated proteolytic peptides were evaluated by gel electrophoresis and mass spectrometry. Results Antigens displaying weak capacity of T cell priming in vivo were highly susceptible to endolysosomal proteases in vitro. As proteolytic composition, activity, and specificity of endolysosomal fractions derived from human and murine dendritic cells were comparable, the JAWS II cell line could be used as a substitute for freshly isolated human or murine cells in in vitro degradation assays. Conclusions Endolysosomal fractions prepared from the JAWS II cell line provide a reliable tool for in vitro estimation of protein immunogenicity. The rapid and simple assay described here is very useful to study the immunogenic properties of a protein, and can help to replace, reduce, and refine animal experiments in allergy research and vaccine development in general.
Base J and H3.V Regulate Transcriptional Termination in Trypanosoma brucei

Trypanosoma brucei is a protozoan parasite that lacks many transcription factors found in other eukaryotes, such as those whose binding demarcates enhancers. T. brucei retains histone variants and modifications, however, and it is hypothesized that it relies on epigenetic marks to define transcription-related boundaries. The histone H3 variant (H3.V) and an alternate nucleotide, base J (ß-D-glucosyl-hydroxymethyluracil), are two chromatin marks found at both transcription termination sites (TTSs) and telomeres. Here, we report that the absence of both base J and H3.V result in transcription readthrough and the appearance of antisense transcripts near TTSs. Additionally, we find that maintaining the transcriptional silencing of pol I-transcribed telomeric Variant Surface Glycoprotein (VSG) genes appears to be dependent on deposition of H3.V alone. Our study reveals that gene expression depends on different epigenetic cues depending on chromosomal location and on the transcribing polymerase. This work provides insight into how these signals may have evolved into the more nuanced and fine-tuned gene regulatory mechanisms observed in other model systems.
Learning a Multi-class Discriminative Dictionary with Nonredundancy Constraints for Visual Classification

Recent studies have demonstrated advantages of sparse representation in providing an appealing paradigm for visual classification tasks. However, how to effectively learn a compact dictionary of superior reconstruction and discrimination power is still a challenging problem. In this paper, we concurrently exploit both the intra-class and the inter-class visual correlations to learn a multi-class discriminative dictionary. The intra-nonredundancy constraint prevents zero entities from appearing in the class-specific bases, thereby making the learned dictionary more stable. The inter-nonredundancy constraint effectively separates the common visual patterns from all the class-specific bases, yielding a more compact dictionary. Combining nonredundancy constraints with the reconstruction error and the classification error to form a unified objective function, our method can learn a superior dictionary and an optimal linear classifier simultaneously. Extensive experimental results demonstrate that the proposed algorithm achieves notable improvement over the state-of-the-art methods in image classification and visual tracking tasks.
Multiplication using Normal Bases

Fast algorithms for multiplication in finite fields are required for several cryptographic applications, in particular for implementing elliptic curve operations over the NIST recommended binary fields. In this paper we present new software algorithms for efficient multiplication over the binary fieldF2m that use a Gaussian normal basis representation. Two approaches are presented, direct normal basis multiplication, and a method that exploits a mapping to a ring where fast polynomial-based techniques can be employed. Our analysis including experimental results on an Intel Pentium family processor shows that the new algorithms are faster and can use memory more efficiently than previous methods. Despite significant improvements, we conclude that the penalty in multiplication is still sufficiently large to discourage the use of normal bases in software implementations of elliptic curve systems.
Process variation robust clock tree routing

As the minimum feature sizes of VLSI circuits get smaller while the clock frequency increases, the effects of process variations become significant. We propose a UST/DME based approach to perform simultaneous nonzero clock skew scheduling and clock tree routing, taking into consideration the effects of process variations on clock skews. Our approach ensures that the generated clock tree has a high tolerance to process variations while minimizing the total capacitance of the clock tree, which is proportional to the total wirelength and the total number of buffers. Monte Carlo simulations show that our approach generates clock trees that are highly tolerant to process variations.
Gestational diabetes mellitus: is a diagnosis associated with an increase in maternal anxiety and stress in the short and intermediate term?

OBJECTIVE To examine anxiety levels of women diagnosed with gestational diabetes mellitus (GDM) and to compare these with glucose-tolerant (GT) women at similar stages of pregnancy. RESEARCH DESIGN AND METHODS Prospective longitudinal study conducted on 50 women with GDM and 50 GT women. All women completed the Mental Health Inventory (MHI-5) forms and the Speilberger State-Trait Anxiety Inventory (STAI) at the beginning of the third trimester, antepartum, and 6 weeks postpartum. Specific questions were also assessed using a Likert scale. RESULTS Women with GDM, compared with GT women, had a higher level of anxiety (state rather than trait) at the time of the first assessment. However, before delivery and in the postpartum period, there were no significant differences in anxiety scores between the two groups. Women in both groups were positive about being tested for GDM and wished to be tested during future pregnancies. CONCLUSIONS There were no sustained increased levels of anxiety for women diagnosed with GDM. Concerns expressed about causing sustained maternal anxiety by testing for GDM could not be substantiated.
Preschool Teachers’ Perspectives on Aggressive Behaviors in Children: A Qualitative Study

The main aim of this study was to qualitatively analyze preschool teachers’ opinions about the aggressive behaviors of children in the classroom. The phenomenology design, one of the qualitative research methods, was used in the study. 46 preschool teachers selected by the maximum diversity sampling method constituted the study group. The data of the study were collected using the semi-structured interview technique, and the data were analyzed using the descriptive analysis technique. According to the results of the study, preschool teachers generally described the aggressive behavior as “damaging friends,” mentioned that the type of aggression they mostly encountered in the classroom was “physical aggression” and stated that the most important factor affecting aggression in the preschool period was “parental attitudes. ” Furthermore, preschool teachers indicated that aggressive behaviors generally emerged “during game activities,” that the communication of children exhibiting aggressive behaviors with their peers was usually negatively affected, and that they mostly used the “verbal warning” and “punishment” method to cope with aggressive behaviors in the classroom, however, they also emphasized that they felt inadequate in coping with aggressive behaviors. The activities that will allow children to express themselves and their feelings, to properly communicate with their surroundings and to get rid of their energy can be included in preschool education institutions. Teachers can be provided with applied in-service training seminars on how they can cope with aggressive behaviors and what kinds of effective methods they should use. Furthermore, it is also considered useful to organize information seminars on how parents should approach their children’s aggressive behaviors.
Susceptibility to Kindling and Neuronal Connections of the Anterior Claustrum

The claustrum has been implicated in the kindling of generalized seizures from limbic sites. We examined the susceptibility of the anterior claustrum itself to kindling and correlated this with an anatomical investigation of its afferent and efferent connections. Electrical stimulation of the anterior claustrum resulted in a pattern of rapid kindling with two distinct phases. Early kindling involved extremely rapid progression to bilaterally generalized seizures of short duration. With repeated daily kindling stimulations, early-phase generalized seizures abruptly became more elaborate and prolonged, resembling limbic-type seizures as triggered from the amygdala. We suggest that the rapid rate of kindling from the anterior claustrum is an indication that the claustrum is functionally close to the mechanisms of seizure generalization. In support of our hypothesis, we found significant afferent, efferent, and often reciprocal connections between the anterior claustrum and areas that have been implicated in the generation of generalized seizures, including frontal and motor cortex, limbic cortex, amygdala, and endopiriform nucleus. Additional connections were found with various other structures, including olfactory areas, nucleus accumbens, midline thalamus, and brainstem nuclei including the substantia nigra and the dorsal raphe nucleus. The anatomical connections of the anterior claustrum are consistent with its very high susceptibility to kindling and support the view that the claustrum is part of a forebrain network of structures participating in the generalization of seizures.
The Moderating Effects of Organisational Culture on the Relationship Between Leadership Style and Employee Commitment to Change of Public Sector in Yemen

Employee commitment to change is a crucial factor of a successful change process that can be enhanced by having effective leadership and supportive organisational culture. The present study was designed to examine the relationship between leadership style and employee commitment to change with organisational culture as a moderating variable. The study was carried-out in public sector in Yemen. The study used transformational and transactional model of leadership to determine employee commitment to change. A quantitative approach was mainly conducted in this study. In order to achieve the main objectives of this study, data were collected from employees of public sector in Yemen. Hierarchical regression analysis was then conducted to examine the moderating effects of the organisational culture on the relationship between leadership style and employee commitment to change dimensions. The results from the regression analysis revealed that transformational and transactional leadership were positively associated with all the dimensions of employee commitment to change; namely affective, continuance and normative. Moreover, the findings showed that transactional leadership had stronger effect on the employee commitment to change compared to transformational leadership. Furthermore, the results also showed that organisational culture plays an important role, which it moderated the relationship between leadership style and employee commitment to change. The study may contribute to the body of knowledge on the change management, and on both leadership and organisational culture perspective. Furthermore, the originality of the research lies in the change management area particularly on the human elements. It is also provided comprehensive practical recommendations for organisations, employees, and leaders to guide them to manage change successfully
Identifying the density-dependent structure underlying ecological time series

A central problem in ecology is explaining the causes of population fluctuations, and an important step in the solution is determining the structure of the negative feedback (density dependent) process regulating population dynamics. The conventional way to determine the dimension or order of density dependence in a time series is to calculate the partial autorcorrelation function (PACF). We maintain, however, that PACF is not designed with biological populations in mind and has the wrong null model for detecting the structure of density dependence. We suggest an alternative diagnostic, the partial rate correlation function (PRCF), which is specifically designed for biological populations and has an appropriate null model for detecting their density dependent structures. Tests with simulated data show PRCF to be superior to PACF in detecting the underlying density dependent structure of two simple mathematical models.
Lipid-lowering effect of simvastatin in patients of type 2 diabetes mellitus.

BACKGROUND Dyslipidemia is an important factor in causation of macrovascular disease in type 2 diabetics. The role of simvastatin in the management of dyslipidemia in patients with type 2 diabetes mellitus is not very well elucidated, particularly in the context of the recent American Diabetes Association criteria 2001. The American Diabetes Association suggests that aggressive therapy of diabetic dyslipidemia will reduce the risk of coronary heart disease in diabetics and that optimal levels are serum low-density lipoprotein cholesterol <2.60 mmol/L (< 100 mg/dl), high-density lipoprotein cholesterol >1.1 5 mmol/L (>45 mg/dl) and triglycerides <2.30 mmol/L, (<200 mg/dl). This study was planned to compare the effect of simvastatin together with behavioral modification and behavioral modification alone, in age, sex and body mass index matched patients with type 2 diabetes mellitus with dyslipidemia, in reaching the target levels of various lipids as suggested by the American Diabetes Association criteria 2001. METHODS AND RESULTS An open-label, prospective study was conducted on 80 patients with type 2 diabetes mellitus, who had fair to moderate glycemic control with a total glycated hemoglobin < 10%. The patients in the control group (n=40) were treated with only behavioral modifications like calorie control and daily walking for 30 minutes, and no lipid-lowering agent was given. The lipid profile was re-evaluated after 6 and 12 weeks. The patients in the test group (n=40) were advised behavioral modification and given simvastatin. The starting dose was 10 mg at bed time. After 6 weeks of simvastatin therapy, a lipid profile was done. If the goal of low-density lipoprotein cholesterol < 100 mg/dl and/or triglycerides <200 mg/dl and/or high-density lipoprotein cholesterol >45 mg/dl was not achieved, the dose of simvastatin was increased to 20 mg at bedtime for another 6 weeks. It was observed that low-density lipoprotein dyslipidemia was most prevalent. In the control group, a favorable alteration in lipid levels was brought about but none was statistically significant and the American Diabetes Association goals were not achieved in any of the patients. In the test group, there was a significant and favorable alteration in all lipid moieties, and the target levels were achieved in 80% of patients after 12 weeks. There was no significant alteration in glycemic control and liver functions. Myopathy and epigastric pain were seen in 1 patient in each group. CONCLUSIONS In our study, behavioral modification alone did not achieve the target levels of various lipids in diabetic dyslipidemia as per the American Diabetes Association guidelines. Hence, pharmacological therapy with statins should be resorted to in patients with type 2 diabetes mellitus who carry a high risk of coronary heart disease. Simvastatin is a safe and efficacious lipid-lowering drug.
Reduced complexity automatic face recognition algorithm based on Local Binary Patterns

This paper proposes an adaptation of the Local Binary Patterns operator for the design of an automatic face recognition algorithm. The automatic face recognition process is divided into three main stages: face detection, face localization and face recognition. The authors developed an approach for the realization of all these stages based on a single Local Binary Pattern (LBP) transformation. An innovative LBP-based eye-pupil detection technique for precise face localization is also presented in this paper. The simplicity of the proposed methodology makes it potentially well suited to embedded solutions with limited computational power and memory. The parameters of the algorithms are evaluated on a color FERET database.
A latency-elastic and fault-tolerant cache for improving performance and reliability on low voltage operation

The ever-increasing transistor threshold-voltage (Vth) variation caused by process technologies shrink brings the performance and reliability issues in SRAM cells. To keep power limitations, scaling down the supply voltage is inevitable in mobile devices and future chips. However, caches become susceptible even fail in low voltages, and the distribution of access latencies increases in new technology nodes. To deal with the respectable power of SRAM in modern processors, the memory reliability wall poses a major challenge in cache design nowadays and continues for years to come. This thesis proposes a latency-elastic and fault-tolerant cache not only for fault-tolerant, but aiming at the performance issues. It varies the latency of cache access to achieve better-than-worst-case designs for improving performance.
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research, and how new findings are integrated with existing knowledge. The essay explores these barriers in order to give a sociological account of this new knowledge domain. While the ethical and social implications of big data currently dominate, the essay argues that over the longer term, it is likely that the forces that promote cumulation or hinder it will play a stronger role in shaping social scientific knowledge. The essay will proceed as follows: first, it will elaborate why the scientific nature of the social sciences is being revisited in the light of big data approaches. Next, it will provide definitions of big data (and of data) and argue that the conditions for social scientific knowledge have recently changed with access to readily manipulable data. Data sources are only one part of this change, and another goes to the heart of how cumulation takes place in science, which is the use of mathematics and of research technologies. Hence, too, new directions in thinking about causal explanations are emerging and there is a renewed emphasis on quantitative and statistical methods. The combination of these two factors – data, and how they are analyzed – has led some areas in the social sciences to develop into a rapidly moving research frontier. There have been many novel findings which have also redrawn the relations between traditional social science disciplines and newer specialisms such as computational social science. The essay concludes with a discussion of this realignment among disciplines and in knowledge, and why there are also limits to how big data approaches are transforming social science. Before tackling these topics, it will be useful discuss labels, since big data is still a controversial term and there are a number of competing ones, including computational social science and social data science. For consistency's sake, this essay will use social data science throughout, but nothing hinges on this. ‘Big data approaches in the social sciences’ could be used instead if it were not so clumsy. Big data and data will nevertheless be defined shortly because one argument will be that knowledge is being
CONVERGENCE OF TRUNCATED HALF-QUADRATIC AND NEWTON ALGORITHMS, WITH APPLICATION TO IMAGE RESTORATION.

We address the minimization of penalized least squares (PLS) criteria customarily used for edge-preserving restoration and reconstruction of signals and images. The minimization of PLS criteria can be addressed using a half-quadratic (HQ) scheme, according either to Geman & Reynolds (1992) or to Geman & Yang (1995) constructions. In the case of large-scale problems, the cost of the HQ approach is usually too high. In practice, it is rather proposed to implement an inexact HQ algorithm using a truncated conjugate gradient (TCG) method. This principle echoes that of truncated-Newton algorithms. Our contribution is to establish the convergence of the resulting truncated algorithms (HQ or Newton), under the same conditions required for the exact HQ scheme. Indeed, convergence is granted whatever the number of performed iterations of TCG. According to our experimental study on a deconvolution problem, the fastest versions correspond to severe truncation. This reinforces the interest for the truncated schemes, as fully valid algorithms in the field of image restoration.
Face and Human Detection Using Gradient Pattern with Binary Histogram Technique

— Detecting and classifying the image is an important topic of computer technology that determines the sizes in digital images. It is mainly used for authentication and identification purpose. Intensity transform features convert the intensity (pixel color) into an encoded value by comparing the pixel. Normally, detection methods take the pixel color directly as information cues. These schemes are more sensitive to noise, variations in pose and changes in illumination. To tackle these effects by using GP (Gradient pattern) and SNOW algorithm. Gradient feature makes the variation of edges. SNOW reduces the variations of misclassified area. The images are classified by using Background variations. The proposed approach is to rectify the intensity differences at various locations, provides a minimum processing time and the misdetections are prevented in crowd environment
'MASTerful' Matchmaking in Service Transactions: Inferred Abilities, Needs and Interests versus Activity Histories

Timebanking is a growing type of peer-to-peer service exchange, but is hampered by the effort of finding good transaction partners. We seek to reduce this effort by using a Matching Algorithm for Service Transactions (MAST). MAST matches transaction partners in terms of similarity of interests and complementarity of abilities and needs. We present an experiment involving data and participants from a real timebanking network, that evaluates the acceptability of MAST, and shows that such an algorithm can retrieve matches that are subjectively better than matches based on matching the category of people's historical offers or requests to the category of a current transaction request.