Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Sperm Conjugation and Dissociation on Sperm Viability In Vitro

Sperm conjugation is an unusual variation in sperm behavior where two or more spermatozoa physically unite for motility or transport through the female reproductive tract. Conjugation has frequently been interpreted as sperm cooperation, including reproductive altruism, with some sperm advancing their siblings toward the site of fertilization while ostensibly forfeiting their own ability to fertilize through damage incurred during conjugate break-up. Conversely, conjugation has been proposed to protect sensitive regions of spermatozoa from spermicidal conditions within the female reproductive tract. We investigated the possibility of dissociation-induced sperm mortality and tested for a protective function of conjugation using the paired sperm of the diving beetle, Graphoderus liberus. Sperm conjugates were mechanically dissociated and exposed to potentially damaging tissue extracts of the female reproductive tract and somatic tissue. We found no significant difference in viability between paired sperm and dissociated, single sperm. The results further indicate that the reproductive tract of female G. liberus might not be spermicidal and conjugation is not protective of sperm viability when damaging conditions do exist. Our results support the interpretation that, at least in some taxa, sperm conjugation is neither protective nor damaging to sperm viability.
Comparison between multi-class classifiers and deep learning with focus on industry 4.0

Growing amounts of data will be one of consequences in Industry 4.0. This paper deals about mining frequent patterns and important factors in data. Classification is one of the most common assignments in data analytics. We used letter recognition data from the UCI repository as data set for our experiment. Data set contains more than 20000 instances of 26 classes. In our case, it represents multi-class classification. This idea can be transformed into industrial environment. Deep learning is a new area of machine learning research. We decided to use Deep learning from open source H2O machine learning framework and compare it with four multi-class classification algorithms available as services on Microsoft Azure. We are focusing this idea on Industrial systems, cloud architecture and data analytics, which will be fundamental pillars of Industry 4.0.
What Should a Social Psychology for Social Change Look Like in Asia? Reflections on Scientific Research, Aimed at Solving Social Problems and Generating New Knowledge With ‘a Theory of Culture Change at Its Centre’

In late 2013, the Asian Association of Social Psychology (AASP) signed an agreement with the Journal of Pacific Rim Psychology (JPRP) to annually produce one themed issue in accordance with both organisations’ missions, for a period of 5 years. For AASP, the annual publication of a themed issue on ‘The Social Psychology of Social Change: Science and Practice in Asia’ was the end result of 2 years of member consultation, undertaken by President-Elect James Liu from 2012 to 2013. This resulted in a Mission Statement, and a directive from members to develop a second publications outlet with an SSCI impact factor, but more focused on applied research, to complement AASP's eponymous flagship journal the Asian Journal of Social Psychology (which is more basic in its research orientation).
Key Amino Acids in the Bacterial (6-4) Photolyase PhrB from Agrobacterium fabrum

Photolyases can repair pyrimidine dimers on the DNA that are formed during UV irradiation. PhrB from Agrobacterium fabrum represents a new group of prokaryotic (6–4) photolyases which contain an iron-sulfur cluster and a DMRL chromophore. We performed site-directed mutagenesis in order to assess the role of particular amino acid residues in photorepair and photoreduction, during which the FAD chromophore converts from the oxidized to the enzymatically active, reduced form. Our study showed that Trp342 and Trp390 serve as electron transmitters. In the H366A mutant repair activity was lost, which points to a significant role of His366 in the protonation of the lesion, as discussed for the homolog in eukaryotic (6–4) photolyases. Mutants on cysteines that coordinate the Fe-S cluster of PhrB were either insoluble or not expressed. The same result was found for proteins with a truncated C-terminus, in which one of the Fe-S binding cysteines was mutated and for expression in minimal medium with limited Fe concentrations. We therefore assume that the Fe-S cluster is required for protein stability. We further mutated conserved tyrosines that are located between the DNA lesion and the Fe-S cluster. Mutagenesis results showed that Tyr424 was essential for lesion binding and repair, and Tyr430 was required for efficient repair. The results point to an important function of highly conserved tyrosines in prokaryotic (6–4) photolyases.
Implications of polyploidy events on the phenotype, microstructure, and proteome of Paulownia australis

Polyploidy events are believed to be responsible for increasing the size of plant organs and enhancing tolerance to environmental stresses. Autotetraploid Paulownia australis plants exhibit superior traits compared with their diploid progenitors. Although some transcriptomics studies have been performed and some relevant genes have been revealed, the molecular and biological mechanisms regulating the predominant characteristics and the effects of polyploidy events on P. australis remain unknown. In this study, we compared the phenotypes, microstructures, and proteomes of autotetraploid and diploid P. australis plants. Compared with the diploid plant, the leaves of the autotetraploid plant were longer and wider, and the upper epidermis, lower epidermis, and palisade layer of the leaves were thicker, the leaf spongy parenchyma layer was thinner, the leaf cell size was bigger, and cell number was lower. In the proteome analysis, 3,010 proteins were identified and quantified, including 773 differentially abundant proteins. These results may help to characterize the P. australis proteome profile. Differentially abundant proteins related to cell division, glutathione metabolism, and the synthesis of cellulose, chlorophyll, and lignin were more abundant in the autotetraploid plants. These results will help to enhance the understanding of variations caused by polyploidy events in P. australis. The quantitative real-time PCR results provided details regarding the expression patterns of the proteins at mRNA level. We observed a limited correlation between transcript and protein levels. These observations may help to clarify the molecular basis for the predominant autotetraploid characteristics and be useful for plant breeding in the future.
Automatic image hanging protocol for chest radiographs in PACS

Chest radiography is one of the most widely used techniques in diagnostic imaging. It comprises at least one-third of all diagnostic radiographic procedures in hospitals. However, in the picture archive and communication system, images are often stored with the projection and orientation unknown or mislabeled, which causes inefficiency for radiologists' interpretation. To address this problem, an automatic hanging protocol for chest radiographs is presented. The method targets the most effective region in a chest radiograph, and extracts a set of size-, rotation-, and translation-invariant features from it. Then, a well-trained classifier is used to recognize the projection. The orientation of the radiograph is later identified by locating the neck, heart, and abdomen positions in the radiographs. Initial experiments are performed on the radiographs collected from daily routine chest exams in hospitals and show promising results. Using the presented protocol, 98.2% of all cases could be hung correctly on projection view (without protocol, 62%), and 96.1% had correct orientation (without protocol, 75%). A workflow study on the protocol also demonstrates a significant improvement in efficiency for image display
Automation tool to deploy Simulink models into programmable system-on-chip

In this article we present a computational tool called MS2PSoC to automate the deployment of applications developed in Matlab/Simulink environment in PSoC hardware. The purpose of this automation is to assist the project development process described in Simulink and translated to PSoC Creator environment. The proposed methodology is to translate the digital or analog designs described in the Matlab/Simulink environment to programming language and hardware supported by PSoC hardware. Two case studies were used to assess the proposed methodology. The first case it is a digital case consisting of the MLT-3 line code. The second case is reported to a D/A converter of 4 bits employing the model Ladder R-2R. Both cases have been described in Simulink environment and then implemented in hardware PSoC using the MS2PSoC tool. The results show the feasibility of the methodology developed in the tool.
Generalized histogram shifting-based reversible data hiding with an adaptive binary-to-q-ary converter

This paper increases the flexibility of generalized histogram shifting-based reversible data hiding (HS-RDH). An RDH method modifies an original image to hide data to the image, and the method not only extracts the hidden data but also restores the original image from the distorted image which conveys the hidden data. A generalized HS-RDH method increases (or decreases) particular pixel values in an original image by (q - 1), based on its tonal distribution, to hide q-ary data symbols, whereas an ordinary HS-RDH method shifts a part of the histogram by one to embed binary symbols. This paper introduces an adaptive binary-to-q-ary watermark converter and a tonal distribution analysis to increase conveyable hidden data size, whereas a conventional generalized HS-RDH method with an arithmetic decoder-based converter cannot always convert the extracted q-ary strings to original binary strings correctly and the other method embeds q̂-symbols instead of q-ary symbols where q̂ is a power of two equal to or less than q. In addition, histogram packing technique is introduced in this paper to further increase q. Experimental results show the effectiveness of the proposed method.
Road Traffic Noise and Annoyance: A Quantification of the Effect of Quiet Side Exposure at Dwellings

Previous studies indicate that residents may benefit from a “quiet side” to their dwellings. The influence of the level of road traffic noise exposure at the least exposed side on road traffic noise annoyance was studied in Amsterdam, The Netherlands. Road traffic noise exposure was assessed at the most and least exposed façade (Lden,most and Lden,least respectively) of dwellings for subjects in a population based survey (N = 1,967). It was investigated if and to what extent relative quietness at the least exposed façade affected the level of road traffic noise annoyance by comparing two groups: (1) The subgroup with a relatively quiet façade; (2) the subgroup without a relatively quiet façade (large versus small difference in exposure between most and least exposed façade; DIF ≥ 10 dB and DIF < 10 dB respectively). In addition, it was investigated if and to what extent Lden,least affected the level of road traffic noise annoyance. Results indicate a significantly lower road traffic noise annoyance score at a given Lden,most, in the subgroup with DIF ≥ 10 dB versus DIF < 10 dB. Furthermore, results suggest an effect of Lden,least independent of Lden,most. The estimated size of the effect expressed in an equivalent change in Lden,most approximated 5 dB for both the difference between the two subgroups (DIF ≥ 10 dB and DIF < 10 dB), and for a 10 dB change in Lden,least.
Computer science/informatics in secondary education

Computer Science (CS) Education research, specifically when focusing on secondary education, faces the difficulty of regionally differing political, legal, or curricular constraints. To date, many different studies exist that document the specific regional situations of teaching CS in secondary schools. This ITiCSE working group report documents the process of collecting, evaluating, and integrating research findings about CS in secondary schools from different countries. As an outcome, it presents a category system (Darmstadt Model), as a first step towards a framework that sup-ports future research activities in this field and that supports the transfer of results between researchers and teachers in CS education (CSE) across regional or national boundaries. Exemplary application of the Darmstadt model shows in several important categories how different the situation of CSE in secondary education in various countries can be. The Darmstadt Model (DM) is now ready for discussion and suggestions for improvement by the CSE-community.
The nonlocal model of short-range wetting

Recently, a Nonlocal Model of short-range wetting was proposed that seems to overcome problems with simpler interfacial models. In this thesis we explore this model in detail, laying the foundations for its use. We show how it can be derived from a microscopic Hamiltonian by a careful coarse-graining procedure, based on a previous recipe proposed by Fisher and Jin. In the Nonlocal Model the substrate-interface interaction is described by a binding potential functional with an elegant diagrammatic expansion: W = a1 + b1 + · · · . This model has the same asymptotic renormalisation group behaviour as the simpler model but with a much smaller critical region, explaining the mystery of 3D critical wetting. It also has the correct form to satisfy the covariance relation for wedge filling. We then proceed to check the robustness of the structure of the Nonlocal Model using perturbation theory to study the consequences of the use of a more general microscopic Hamiltonian. The model is robust to such generalisations whose only relevant effect is the change of the values of the coefficients of the Nonlocal Model. These same remarks are valid for the inclusion of a surface field: the generalised model still has the same structure, albeit with different coefficients. Another important extension is the inclusion of a longer-range substrate-fluid interaction or a bulk field. We finalise with a chapter exploring the structure of the correlation function at meanfield level. This allows us to prove that the Nonlocal Model obeys a sum-rule for complete wetting, and shed light on why the critical region is so small in the Nonlocal Model. The study of correlations at a capillary slit can provide a direct test of the Nonlocal Model.
Integrating the Actin and Vimentin Cytoskeletons

Cells adhere to the substratum through specialized structures that are linked to the actin cytoskeleton. Recent studies report that adhesion also involves the intermediate filament (IF) and microtubule cytoskeletons, although their mechanisms of interaction are unknown. Here we report evidence for a novel adhesion-dependent interaction between components of the actin and IF cytoskeletons. In biochemical fractionation experiments, fimbrin and vimentin coprecipitate from detergent extracts of macrophages using vimentin- or fimbrin-specific antisera. Fluorescence microscopy confirms the biochemical association. Both proteins colocalized to podosomes in the earliest stages of cell adhesion and spreading. The complex is also found in filopodia and retraction fibers. After detergent extraction, fimbrin and vimentin staining of podosomes, filopodia, and retraction fibers are lost, confirming that the complex is localized to these structures. A 1:4 stoichiometry of fimbrin binding to vimentin and a low percentage (1%) of the extracted vimentin suggest that fimbrin interacts with a vimentin subunit. A fimbrin-binding site was identified in the NH2-terminal domain of vimentin and the vimentin binding site at residues 143–188 in the CH1 domain of fimbrin. Based on these observations, we propose that a fimbrin–vimentin complex may be involved in directing the assembly of the vimentin cytoskeleton at cell adhesion sites.
Selection Combining of Signals with Different Modulation Levels in Nakagami-m Fading

Conventionally, the BER analysis of selection combining schemes is performed under the assumption that the signals to be combined belong to the same modulation level. This is not necessarily the case in cooperative relaying, where the source and relay may use different modulation levels. Recently, a closed-form BER expression was derived for selection combing of signals with different modulation levels, under the assumption that the source-relay, source-destination, and relay-destination links are all modeled as Rayleigh fading channels. In this letter, we extend the analysis to the asymmetric Nakagami-m fading channel, which is a more versatile channel model. We derive the closed-form BER expression which is expressed in terms of elementary functions. The derived BER expression generalizes many existing expressions in the literature. Simulation results are also presented to confirm the accuracy of the derived results.
A Neural Predictor of Cultural Popularity

How can we predict popularity? Although superficially a trivial question, the desire for popularity consumes a great portion of the lives of many youths and adults. Being popular is a marker for social status, and consequently, would seem to confer a reproductive advantage in the evolution of the human species, thus explaining the importance of popularity to humans. Such importance extends to economic success as well because goods and services that are popular command higher prices. Here, we are interested in predicting cultural popularity – something that is popular in the broadest sense and appeals to a large number of individuals. Neuroeconomic research suggests that activity in reward-related regions of the brain, notably the orbitofrontal cortex and ventral striatum 1-4, is predictive of future purchasing decisions, but it is unknown whether the neural signals of a small group of individuals are predictive of the purchasing decisions of the population at large. For neuroimaging to be useful as a measure of widespread popularity, these neural responses would have to generalize to a much larger population that is not the direct subject of the brain imaging itself. Moreover, to be useful as a predictor, such a test would need to be done prospectively. Here, we test the possibility of using functional magnetic resonance imaging (fMRI) to predict the relative popularity of a common good: music. We used fMRI to measure the brain responses of a focus group of adolescents while listening to songs of relatively unknown artists 5. As a measure of popularity, the sales of these songs were totaled for the three years following scanning, and brain responses were then correlated with these “future” earnings. Although subjective likability of the songs was not predictive of sales, activity within the ventral striatum was significantly correlated with the number of units sold. These results suggest that the neural responses to goods are not only predictive of purchase decisions for those individuals actually scanned, but such responses generalize to the population at large and may be used to predict cultural popularity.
Fractal Complexity in Spontaneous EEG Metastable-State Transitions: New Vistas on Integrated Neural Dynamics

Resting-state EEG signals undergo rapid transition processes (RTPs) that glue otherwise stationary epochs. We study the fractal properties of RTPs in space and time, supporting the hypothesis that the brain works at a critical state. We discuss how the global intermittent dynamics of collective excitations is linked to mentation, namely non-constrained non-task-oriented mental activity.
’ s repository of research publications and other research outputs Exploring scholarly data with Rexplore . Conference Item

Despite the large number and variety of tools and s ervices available today for exploring scholarly data, current support is still very limited in the context of sensemaking tasks, which go beyond stand ard search and ranking of authors and publications, and focus instead on i) u derstanding the dynamics of research areas, ii) relating authors ‘semantically’ (e.g., in terms of common interests or shared academic trajectories), or iii) performing fine-grained academic expert search along multiple dimensions. T o address this gap we have developed a novel tool, Rexplore, which integrates s atistical analysis, semantic technologies, and visual analytics to provide effec tiv support for exploring and making sense of scholarly data. Here, we describe t he main innovative elements of the tool and we present the results from a taskcentric empirical evaluation, which shows that Rexplore is highly effective at pro viding support for the aforementioned sensemaking tasks. In addition, thes e r ults are robust both with respect to the background of the users (i.e., expert analysts vs. ‘ordinary’ users) and also with respect to whether the tasks a re elected by the evaluators or proposed by the users themselves.
GIRL CHILD WORKERS AND HOUSEHOLD POVERTY: A CASE STUDY

Child worker though a product of multiple factors viz. social, economic, cultural etc., girl child worker is the result of poverty. Parents in many families still consider girl child as a liability, as the girl after marriage would leave them, and hence they are not concerned about their education and skill formation. The low value placed on the girl child within the family is itself a major concern. As soon as the girl child starts walking and is able to understand language, work is entrusted to her as a routine affair. The girl child has to undertake a variety of tasks in and outside the house depending upon the nature and type of family and customs in society. Mothers without realizing the consequences, slowly inducts the girl child to shoulder many responsibilities by prescribing do’s and don’ts. She also prepares the girls to behave in a different way from the boys. An attempt is made in this research paper to present the household poverty of child workers both girls and boys with regard to their caste-communities. This paper also examines the per capita income requirement of child workers in the study area.
Adaptive preconditioning in neurological diseases -- therapeutic insights from proteostatic perturbations

neurons adapt to these proteostatic perturbations by activating a range of cellular protective and repair responses, thus maintaining cell function. These interconnected adaptive mechanisms comprise a ‘proteostasis network’ and include the unfolded protein response, the ubiquitin proteasome system and autophagy. Interestingly, several recent studies have shown that these adaptive responses can be stimulated by preconditioning treatments, which confer resistance to a subsequent toxic challenge – the phenomenon known as hormesis. In this review we discuss the impact of adaptive stress responses stimulated in diverse human neuropathologies including Parkinson's disease, Wolfram syndrome, brain ischemia, and brain cancer. Further, we examine how these responses and the molecular pathways they recruit might be exploited for therapeutic gain. This article is part of a Special Issue entitled SI:ER stress. & 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). -lyon.fr (B. Mollereau). et al., Adaptive preconditioning in neurological diseases – therapeutic insights from ch (2016), http://dx.doi. org/10.1016/j.brainres. 2016.02. 033