Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of Magmas in protein transport and human mitochondria biogenesis

Magmas, a conserved mammalian protein essential for eukaryotic development, is overexpressed in prostate carcinomas and cells exposed to granulocyte-macrophage colony-stimulating factor (GM-CSF). Reduced Magmas expression resulted in decreased proliferative rates in cultured cells. However, the cellular function of Magmas is still elusive. In this report, we have showed that human Magmas is an ortholog of Saccharomyces cerevisiae Pam16 having similar functions and is critical for protein translocation across mitochondrial inner membrane. Human Magmas shows a complete growth complementation of Δpam16 yeast cells at all temperatures. On the basis of our analysis, we report that Magmas localizes into mitochondria and is peripherally associated with inner mitochondrial membrane in yeast and humans. Magmas forms a stable subcomplex with J-protein Pam18 or DnaJC19 through its C-terminal region and is tethered to TIM23 complex of yeast and humans. Importantly, amino acid alterations in Magmas leads to reduced stability of the subcomplex with Pam18 that results in temperature sensitivity and in vivo protein translocation defects in yeast cells. These observations highlight the central role of Magmas in protein import and mitochondria biogenesis. In humans, absence of a functional DnaJC19 leads to dilated cardiac myophathic syndrome (DCM), a genetic disorder with characteristic features of cardiac myophathy and neurodegeneration. We propose that the mutations resulting in decreased stability of functional Magmas:DnaJC19 subcomplex at human TIM23 channel leads to impaired protein import and cellular respiration in DCM patients. Together, we propose a model showing how Magmas:DnaJC19 subcomplex is associated with TIM23 complex and thus regulates mitochondrial import process.
A Methodology for Evaluating Whether Web Sites Support Their Organizational Critical Activities

Organizational critical activities (OCAs) are activities which must receive constant management attention in order for that organization to be successful in its industry. Some empirical studies have shown that all of these activities may not be well supported by organizations’ websites. This research attempts to develop the evaluation methodology which can be used to assess how well an organization’s website supports the organization’s OCAs if the OCAs are identified. Based on a review of relevant literature, a prototype was proposed, and then evolved and tested through eight case studies in New Zealand universities. In total, more than two thousands web pages were evaluated and 37 semi-structured interviews were conducted. The final methodology includes five operational stages and seven forms. The results of final case were presented in order to show how the methodology can be utilized in the website evaluation. Some implications and future research are also provided.
A Structural SVM Based Approach for Optimizing Partial AUC

The area under the ROC curve (AUC) is a widely used performance measure in machine learning. Increasingly, however, in several applications, ranging from ranking and biometric screening to medical diagnosis, performance is measured not in terms of the full area under the ROC curve, but instead, in terms of the partial area under the ROC curve between two specified false positive rates. In this paper, we develop a structural SVM framework for directly optimizing the partial AUC between any two false positive rates. Our approach makes use of a cutting plane solver along the lines of the structural SVM based approach for optimizing the full AUC developed by Joachims (2005). Unlike the full AUC, where the combinatorial optimization problem needed to find the most violated constraint in the cutting plane solver can be decomposed easily to yield an efficient algorithm, the corresponding optimization problem in the case of partial AUC is harder to decompose. One of our key technical contributions is an efficient algorithm for solving this combinatorial optimization problem that has the same computational complexity as Joachims' algorithm for optimizing the usual AUC. This allows us to efficiently optimize the partial AUC in any desired false positive range. We demonstrate the approach on a variety of real-world tasks.
Strength of the respiratory and lower limb muscles and functional capacity in chronic stroke survivors with different physical activity levels.

BACKGROUND The assessment of strength and its relationships with functional capacity could contribute to more specific and effective disability management of stroke survivors. OBJECTIVE To compare and investigate associations between measures of strength and functional capacity of 98 chronic stroke survivors, stratified into three groups, according to their physical activity levels. METHOD The physical activity levels were classified as impaired, moderately active, and active, based on their Human Activity Profile (HAP) scores. Strength was assessed by the maximal inspiratory (MIP) and expiratory (MEP) pressures and by the residual deficits (RDs) of work of the lower limb and trunk muscles, whereas functional capacity was evaluated by the distance covered during the six-minute walking test (6MWT). RESULTS One-way analyses of variance revealed significant differences between the groups, except between the active and moderately active groups regarding the RDS of the hip and knee flexors/extensors and ankle dorsiflexors (2.91<F<8.62; 0.001<p<0.01). Differences between the groups were found for the 6MWT (F=10.75; p<0.001), but no differences were found for the MIP and MEP measures (0.92<F<2.13; 0.13<p<0.40). Significant, negative, and fair correlations were observed between the RDS of the hip and knee muscles and the 6MWT (0.30<r<-0.43; p<0.01) and the HAP (-0.28<r<-0.41; p<0.01). Moderate to good correlations were found between the 6MWT and the HAP (r=0.50; p<0.0001). There were no significant correlations between measures of respiratory strength and any of the investigated variables (-0.11<r<0.12; 0.26<p<0.56). CONCLUSIONS Lower strength deficits and higher functional capacity were associated with higher physical activity levels. However, the moderately active and active groups demonstrated similar strength deficits.
Disaggregation of SMOS Soil Moisture in Southeastern Australia

Disaggregation based on Physical And Theoretical scale Change (DisPATCh) is an algorithm dedicated to the disaggregation of soil moisture observations using high-resolution soil temperature data. DisPATCh converts soil temperature fields into soil moisture fields given a semi-empirical soil evaporative efficiency model and a first-order Taylor series expansion around the field-mean soil moisture. In this study, the disaggregation approach is applied to Soil Moisture and Ocean Salinity (SMOS) satellite data over the 500 km by 100 km Australian Airborne Calibration/validation Experiments for SMOS (AACES) area. The 40-km resolution SMOS surface soil moisture pixels are disaggregated at 1-km resolution using the soil skin temperature derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data, and subsequently compared with the AACES intensive ground measurements aggregated at 1-km resolution. The objective is to test DisPATCh under various surface and atmospheric conditions. It is found that the accuracy of disaggregation products varies greatly according to season: while the correlation coefficient between disaggregated and in situ soil moisture is about 0.7 during the summer AACES, it is approximately zero during the winter AACES, consistent with a weaker coupling between evaporation and surface soil moisture in temperate than in semi-arid climate. Moreover, during the summer AACES, the correlation coefficient between disaggregated and in situ soil moisture is increased from 0.70 to 0.85, by separating the 1-km pixels where MODIS temperature is mainly controlled by soil evaporation, from those where MODIS temperature is controlled by both soil evaporation and vegetation transpiration. It is also found that the 5-km resolution atmospheric correction of the official MODIS temperature data has a significant impact on DisPATCh output. An alternative atmospheric correction at 40-km resolution increases the correlation coefficient between disaggregated and in situ soil moisture from 0.72 to 0.82 during the summer AACES. Results indicate that DisPATCh has a strong potential in low-vegetated semi-arid areas where it can be used as a tool to evaluate SMOS data (by reducing the mismatch in spatial extent between SMOS observations and localized in situ measurements), and as a further step, to derive a 1-km resolution soil moisture product adapted for large-scale hydrological studies.
Criminal History and Future Offending of Juveniles Convicted of the Possession of Child Pornography

Most child pornography is distributed online. It is estimated that 3% to 15% of child pornography consumers are juveniles. The present study analyzed a consecutive sample of 54 male juveniles convicted of the possession of child pornography. Demographic characteristics, criminal history, and subsequent offending were assessed from criminal files and official reports. Juvenile possessors of child pornography were compared to three different groups of juveniles: Juvenile possessors of other illegal pornography (n = 42), juveniles who committed a sexual contact offense against a child (n = 64), and juveniles who committed a sexual contact offense against a peer or adult (n = 104). Juvenile possessors of child pornography were found to have downloaded the illegal material more frequently and over a longer time period than juvenile possessors of other illegal pornography. Furthermore, juvenile possessors of child pornography differed from juveniles who had committed a sexual contact offense in terms of demographics and showed fewer previous and subsequent offending than juveniles who sexually offended against a peer or adult. We conclude that juvenile possessors of child pornography need a specific target intervention focusing on dysfunctional Internet use and sexually deviant arousal.
The Eyes of the Beholder: Gender Prediction Using Images Posted in Online Social Networks

Identifying user attributes from their social media activities has been an active research topic. The ability to predict user attributes such as age, gender, and interests from their social media activities is essential for personalization and recommender systems. Most of the techniques proposed for this purpose utilize the textual content created by a user, while multimedia content has gained popularity in social networks. In this paper, we propose a novel algorithm to infer a user's gender by using the images posted by the user on different social networks.
Online Multi-Target Tracking Using Recurrent Neural Networks

We present a novel approach to online multi-target tracking based on recurrent neural networks (RNNs). Tracking multiple objects in real-world scenes involves many challenges, including a) an a-priori unknown and time-varying number of targets, b) a continuous state estimation of all present targets, and c) a discrete combinatorial problem of data association. Most previous methods involve complex models that require tedious tuning of parameters. Here, we propose for the first time, an end-to-end learning approach for online multi-target tracking. Existing deep learning methods are not designed for the above challenges and cannot be trivially applied to the task. Our solution addresses all of the above points in a principled way. Experiments on both synthetic and real data show promising results obtained at ~300 Hz on a standard CPU, and pave the way towards future research in this direction.
An Empirical Investigation of Virtual Communities and Trust

In the midst of promising perceived benefits, the electronic commerce (EC) environment entails greater challenges than those posed by conventional trade. In addition to privacy and security concerns, researchers and businesses alike are increasingly aware that the lack of trust for online vendors experienced by consumers constitutes a serious barrier to the widespread adoption and successful proliferation of EC. The process of building trust between consumers and vendors in the online environment thus becomes of paramount importance. This study seeks to examine how online vendors can develop trusting relationships with consumers through the establishment of virtual communities (VCs), fast becoming a notably successful online business model with relationship-enhancing and trust-building capabilities. By integrating multi-disciplinary theories, we propose and empirically validate a model, which proposes that increased levels of involvement in VCs enhances trust building among members and vendors, in turn encouraging greater EC participation in light of lower perceived risks and greater perceived benefits of online transactions. Results indicate that these relationships as proposed in the model are significant. There is empirical support that VCs constitute a successful business model of building trust, reducing perceived risks of purchase, improving customer relationships, reducing search costs, and retaining customers, leading us to conclude that increased involvement in VCs indeed has a positive effect on EC participation.
Online matching: haste makes waste!

This paper studies a new online problem, referred to as min-cost perfect matching with delays (MPMD), defined over a finite metric space (i.e., a complete graph with positive edge weights obeying the triangle inequality) M that is known to the algorithm in advance. Requests arrive in a continuous time online fashion at the points of M and should be served by matching them to each other. The algorithm is allowed to delay its request matching commitments, but this does not come for free: the total cost of the algorithm is the sum of metric distances between matched requests plus the sum of times each request waited since it arrived until it was matched. A randomized online MPMD algorithm is presented whose competitive ratio is O (log2 n + logΔ), where n is the number of points in M and Δ is its aspect ratio. The analysis is based on a machinery developed in the context of a new stochastic process that can be viewed as two interleaved Poisson processes; surprisingly, this new process captures precisely the behavior of our algorithm. A related problem in which the algorithm is allowed to clear any unmatched request at a fixed penalty is also addressed. It is suggested that the MPMD problem is merely the tip of the iceberg for a general framework of online problems with delayed service that captures many more natural problems.
Organochlorine Pesticides Residues in the Breast Milk of Some Primiparae Mothers in La Community, Accra, Ghana

This study was conducted to determine the types and levels of Organochlorine pesticide residues in the breast milk of 21 primiparae mothers in La, a suburb of Accra an urban community in the Greater Accra region of Ghana. Liquid-liquid extraction procedure was employed and extract clean-up was done using silica gel solid phase extraction. Fourteen (14) different organochlorine pesticides residues namely p,p'-DDT, p,p'-DDE, gamma-HCH, delta-HCH, heptachlor, aldrin, Endrin, endrin-aldehyde, endrin-ketone, alpha-endosulphan, endosulphan-sulphate, gamma-chlordane, dieldrin, and methoxychlor were identified and quantified in the individual breast milk samples using a Gas Chromatograph (GC) with an Electron Capture detector. The GC recoveries of spiked samples were between 89 to 97%. P,p'- DDE recorded 100% incidence ratio. Also p,p'-DDT, delta-HCH, gamma-HCH, and endosulfan sulfate recorded incidence ratios of 76.79, 95.25, 80.95 and 85.71%, respectively for the breast milk samples. The concentrations of organochlorine pesticide residues in the human breast milk samples ranged from 1.839 to 99.05 :g/kg fats. With the exception of Endosulphan Sulphate whose mean concentration (99.052 :g/kg) was above the Australian Maximum Residue Limit (MRL) of 20 :g/kg for milk, the mean concentrations for all the other organochlorines detected were below their respective limits.
A trait‐based approach reveals the feeding selectivity of a small endangered Mediterranean fish

Abstract Functional traits are growing in popularity in modern ecology, but feeding studies remain primarily rooted in a taxonomic‐based perspective. However, consumers do not have any reason to select their prey using a taxonomic criterion, and prey assemblages are variable in space and time, which makes taxon‐based studies assemblage‐specific. To illustrate the benefits of the trait‐based approach to assessing food choice, we studied the feeding ecology of the endangered freshwater fish Barbus meridionalis. We hypothesized that B. meridionalis is a selective predator which food choice depends on several prey morphological and behavioral traits, and thus, its top‐down pressure may lead to changes in the functional composition of in‐stream macroinvertebrate communities. Feeding selectivity was inferred by comparing taxonomic and functional composition (13 traits) between ingested and free‐living potential prey using the Jacob's electivity index. Our results showed that the fish diet was influenced by 10 of the 13 traits tested. Barbus meridionalis preferred prey with a potential size of 5–10 mm, with a medium–high drift tendency, and that drift during daylight. Potential prey with no body flexibility, conical shape, concealment traits (presence of nets and/or cases, or patterned coloration), and high aggregation tendency had a low predation risk. Similarly, surface swimmers and interstitial taxa were low vulnerable to predation. Feeding selectivity altered the functional composition of the macroinvertebrate communities. Fish absence favored taxa with weak aggregation tendency, weak flexibility, and a relatively large size (10–20 mm of potential size). Besides, predatory invertebrates may increase in fish absence. In conclusion, our study shows that the incorporation of the trait‐based approach in diet studies is a promising avenue to improve our mechanistic understanding of predator–prey interactions and to help predict the ecological outcomes of predator invasions and extinctions.
HIV gp41 C-terminal Heptad Repeat Contains Multifunctional Domains

T20 (Fuzeon), a novel anti-human immunodeficiency virus (HIV) drug, is a peptide derived from HIV-1 gp41 C-terminal heptad repeat (CHR). Its mechanism of action has not yet been defined. We applied Pepscan strategy to determine the relationship between functional domains and mechanisms of action of five 36-mer overlapping peptides with a shift of five amino acids (aa): CHR-1 (aa 623–658), C36 (aa 628–663), CHR-3 (aa 633–668), T20 (aa 638–673), and CHR-5 (aa 643–678). C36 is a peptide with addition of two aa to the N terminus of C34. Peptides CHR-1 and C36 contain N-terminal heptad repeat (NHR)- and pocket-binding domains. They inhibited HIV-1 fusion by interacting with gp41 NHR, forming stable six-helix bundles and blocking gp41 core formation. Peptide T20 containing partial NHR- and lipid-binding domains, but lacking pocket-binding domain, blocked viral fusion by binding its N- and C-terminal sequences with gp41 NHR and cell membrane, respectively. Peptide CHR-3, which is located in the middle between C36 and T20, overlaps >86% of the sequences of these two peptides, and lacks pocket- and lipid-binding domains, exhibited marginal anti-HIV-1 activity. These results suggest that T20 and C36 contain different functional domains, through which they inhibit HIV-1 entry with distinct mechanisms of action. The multiple functional domains in gp41 CHR and their binding partners may serve as targets for rational design of new anti-HIV-1 drugs and vaccines.
A New Process-Based Approach for Implementing an Integrated Management System: Quality, Security, Environment

This paper presents a new approach for implementing an integrating quality, environment and security management system on the basis of three aspects: process-based approach, risk management and a global monitoring system used as integrating factors to satisfy three important levels of integra- tion, namely, correspondence, coordination and in- tegration. The different steps of the proposed ap- proach cover the whole PDCA (Plan, Do, Check, Act) scheme.
Pathogenicity and cytadherence of Mycoplasma imitans in chicken and duck embryo tracheal organ cultures

Two strains of the avian organism Mycoplasma imitans were examined for pathogenicity and cytadherence in chicken and duck embryo tracheal organ cultures, and a virulent strain of the related pathogen Mycoplasma gallisepticum was included for comparison. All consistently cause ciliostasis in tracheal explants from both hosts, and examination of infected tissues by immunofluorescence and transmission electron microscopy demonstrated that M. imitans proliferated on the epithelial surface and adhered to the respiratory epithelium by means of its terminal tip structure in the same manner as M. gallisepticum. These observations endorse the striking phenotypic similarities between M. imitans and M. gallisepticum and suggest that M. imitans may have pathogenic potential in vivo.
Analysis of long-term and large-scale experiments on robot dialogues using a cloud robotics platform

To build conversational robots, roboticists are required to have deep knowledge of both robotics and spoken dialogue systems. Unlike using stand-alone speech recognition/ synthesis toolkits, a cloud robotics platform for human-robot communication enables high-quality speech recognition and synthesis that is optimized to human-robot interactions. This is challenging because we need to build a wide variety of functionalities ranging from a stable cloud platform to high-quality multilingual speech recognition and synthesis engines. From this background, we constructed rospeex [1], which is a cloud robotics platform for multilingual spoken dialogues with robots. Over 20,000 unique users have used rospeex in the two years since it was launched. In this paper, we propose a method to reduce the response time in rospeex; and analyze its effectiveness. We also analyze the server logs of rospeex that we have collected.
Three-Dimensional Effective Property and Strength Prediction of Thick Laminated Composite Media.

Abstract : An analytical model appropriate for the analysis and design of thick laminated composite media is presented. The model is based on the theoretical work of Chou, Carleone, and Hsu (1972) and predicts the effective three-dimensional thermo-mechanical properties and ultimate strength of thick laminated composite media under applied mechanical and thermal loadings. Various types of lamina constitutive models and lamina failure criteria (including progressive ply failure) have been incorporated in the analysis. A major result of this work is the codification of a three-dimensional laminated media model into a user-friendly computer program environment (LAM3D) for implementation as an engineering design tool for thick laminated composite structures. LAM3D predictions are validated with comparisons between results in the published literature and available experimental data. Several illustrative examples are presented to demonstrate the utility of the code for predicting the effective properties and ultimate strength of laminated composite media. This work represents an important step toward the development of a computationally efficient engineering tool which will significantly enhance the design and analysis capability for the development of a wide range thick composite structures currently being investigated for military and commercial applications. (MM)