Miracle-dz/UniFAR-FTUs huggingface dataset:
Men’s Report of Domestic Violence Perpetration in Bangladesh

This study provides an examination of the antecedents of domestic violence perpetration among a nationally representative sample of men in Bangladesh using an ecological model. Secondary analysis of survey data from nationally representative Bangladesh Demographic and Health Survey is used to examine potential antecedents of perpetration of domestic violence in a sample of 3,371 ever-married men between the ages of 15 and 54 years. Outcome measure is perpetration of domestic violence as measured by a modified Conflict Tactics Scale (CTS), and predictor variables include maternal domestic violence, egalitarianism, marital age, number of household members, wealth index, marital duration, and demographic variables. Men who reported maternal domestic violence had 0.13 greater probability of perpetrating domestic violence compared with men who did not report maternal domestic violence, men who were egalitarian had 0.04 greater probability of perpetrating domestic violence compared with men who were not egalitarian, men in larger households were less likely to report domestic violence. At the same time, the probability of domestic violence perpetration was 0.07 smaller for men who were married at age 36 years and older, as compared with men who were married between the ages of 16 and 20 years, as well as men who were married for more than 5 years when compared with men married for 0 to 4 years. Finally, the probability of domestic violence perpetration was 0.17 smaller for men who were married between the ages of 21 and 25 years and 0.10 smaller for men married between the ages of 26 and 35 years, compared with men who married below the legal marital age of 21. This study provides support for the use of an ecological model to explain domestic violence perpetration in the context of Bangladesh to suggest a multipronged holistic effort to address this insidious social problem and prevent its intergenerational transmission.
Recognition of E-Shopper Behavior Pattern Based on a Dynamic Architecture Neural Networks and Genetic Algorithm

With the rapid development of online shopping, the ability to intelligently collect and analyze information about E-shoppers has become a key source of competitive advantage for firms. This paper presents an optimal algorithm of modeling dynamic architecture for artificial neural networks (ANN) and a novel machine-learning algorithm for extracting rules from databases via using genetic algorithm. Classical architecture of ANN is arbitrary. Before training ANN, the number of hidden layers and hidden nodes has already been fixed. In the dynamic architecture, the number of hidden layers and the number of hidden nodes are sequentially and dynamically generated until a level of performance accuracy is reached. In addition, in this paper, a new genetic algorithm is proposed, which does not need the computational complexity. The genetic algorithm is used to find the optimal values of input attributes(chromosome), Xm, which maximizes output function phiK of output node k. The optimal chromosome is decoded and used to obtain a rule belonging to class k. The better result is achieved by applying the two new algorithms to a given database for customers buying computer.
Obstacle avoidance algorithm using gradient based Swarm techniques

In this paper, a hybrid approach to obstacle avoidance, based on Particle Swarm Optimisation is proposed. This method provides significantly faster convergence, compared to classical approaches using potential fields and gradient descent. The potential functions being used are presented, along with the results, one would obtain by employing gradient descent, for comparison. The results obtained by using hybrid-algorithm, clearly show the significant reduction in number of iterations taken for convergence, in comparison to the exponential time, typically taken by gradient descent. The penultimate section explains the approach taken to adapt the algorithm being proposed, for applications with GPS coordinates. Experimental results for the same are also presented herewith.
Metabolism of the tryptamine-derived new psychoactive substances 5-MeO-2-Me-DALT, 5-MeO-2-Me-ALCHT, and 5-MeO-2-Me-DIPT and their detectability in urine studied by GC-MS, LC-MSn , and LC-HR-MS/MS.

Many N,N-dialkylated tryptamines show psychoactive properties and were encountered as new psychoactive substances. The aims of the presented work were to study the phase I and II metabolism and the detectability in standard urine screening approaches (SUSA) of 5-methoxy-2-methyl-N,N-diallyltryptamine (5-MeO-2-Me-DALT), 5-methoxy-2-methyl-N-allyl-N-cyclohexyltryptamine (5-MeO-2-Me-ALCHT), and 5-methoxy-2-methyl-N,N-diisopropyltryptamine (5-MeO-2-Me-DIPT) using gas chromatography-mass spectrometry (GC-MS), liquid chromatography coupled with multistage accurate mass spectrometry (LC-MSn ), and liquid chromatography-high-resolution tandem mass spectrometry (LC-HR-MS/MS). For metabolism studies, urine was collected over a 24 h period after administration of the compounds to male Wistar rats at 20 mg/kg body weight (BW). Phase I and II metabolites were identified after urine precipitation with acetonitrile by LC-HR-MS/MS. 5-MeO-2-Me-DALT (24 phase I and 12 phase II metabolites), 5-MeO-2-Me-ALCHT (24 phase I and 14 phase II metabolites), and 5-MeO-2-Me-DIPT (20 phase I and 11 phase II metabolites) were mainly metabolized by O-demethylation, hydroxylation, N-dealkylation, and combinations of them as well as by glucuronidation and sulfation of phase I metabolites. Incubations with mixtures of pooled human liver microsomes and cytosols (pHLM and pHLC) confirmed that the main metabolic reactions in humans and rats might be identical. Furthermore, initial CYP activity screenings revealed that CYP1A2, CYP2C19, CYP2D6, and CYP3A4 were involved in hydroxylation, CYP2C19 and CYP2D6 in O-demethylation, and CYP2C19, CYP2D6, and CYP3A4 in N-dealkylation. For SUSAs, GC-MS, LC-MSn , and LC-HR-MS/MS were applied to rat urine samples after 1 or 0.1 mg/kg BW doses, respectively. In contrast to the GC-MS SUSA, both LC-MS SUSAs were able to detect an intake of 5-MeO-2-Me-ALCHT and 5-MeO-2-Me-DIPT via their metabolites following 1 mg/kg BW administrations and 5-MeO-2-Me-DALT following 0.1 mg/kg BW dosage. Copyright © 2017 John Wiley & Sons, Ltd.
Relevance of Host Cell Surface Glycan Structure for Cell Specificity of Influenza A Viruses

Influenza A viruses (IAVs) initiate infection via binding of the viral hemagglutinin (HA) to sialylated glycans on host cells. HA’s receptor specificity towards individual glycans is well studied and clearly critical for virus infection, but the contribution of the highly heterogeneous and complex glycocalyx to virus–cell adhesion remains elusive. Here, we use two complementary methods, glycan arrays and single-virus force spectroscopy (SVFS), to compare influenza virus receptor specificity with virus binding to live cells. Unexpectedly, we found that HA’s receptor binding preference does not necessarily reflect virus–cell specificity. We propose SVFS as a tool to elucidate the cell binding preference of IAVs, thereby including the complex environment of sialylated receptors within the plasma membrane of living cells.
Human Recognition in RGBD Combining Object Detectors and Conditional Random Fields

This paper addresses the problem of detecting and segmenting human instances in a point cloud. Both fields have been well studied during the last decades showing impressive results, not only in accuracy but also in computational performance. With the rapid use of depth sensors, a resurgent need for improving existing state-of-the-art algorithms, integrating depth information as an additional constraint became more ostensible. Current challenges involve combining RGB and depth information for reasoning about location and spatial extend of the object of interest. We make use of an improved deformable part model algorithm, allowing to deform the individual parts across multiple scales, approximating the location of the person in the scene and a conditional random field energy function for specifying the object’s spatial extent. Our proposed energy function models up to pairwise relations defined in the RGBD domain, enforcing label consistency for regions sharing similar unary and pairwise measurements. Experimental results show that our proposed energy func- tion provides a fairly precise segmentation even when the resulting detection box is imprecise. Reasoning about the detection algorithm could potentially enhance the quality of the detection box allowing capturing the object of interest as a whole.
A framework for knowledge security in aerospace inter-organizational Network

The design of complex new aerospace products requires wide and deep collaborations among firms and in many cases also with competitors collaborating and, at the same time, protecting the valuable knowledge assets. In this context, knowledge protection means defining which knowledge assets must be shared and introducing policies and systems to protect them. Framed in the above premises, this paper presents the preliminary results of an on-going innovative research project i-Design Foundation (iDF) aimed to develop methodologies and technologies to support collaborative product design in aerospace value networks. Findings suggest an integrated organisational and technological framework describing: a) the modelling of collaboration's scenarios of a network of companies involved in innovative projects; b) an architectural framework to protect the codified knowledge assets shared. The paper is of value for managers that can get insights in knowledge security mechanisms and technological solutions supporting the collaboration in wider innovative projects.
Improve Affective Learning with EEG Approach

With the development of computer science, cognitive science and psychology, a new paradigm, affective learning, has emerged into e-learning domain. Although scientists and researchers have achieved fruitful outcomes in exploring the ways of detecting and understanding learners affect, e.g. eyes motion, facial expression etc., it sounds still necessary to deepen the recognition of learners affect in learning procedure with innovative methodologies. Our research focused on using bio-signals based methodology to explore learner's affect and the study was primarily made on Electroencephalography (EEG). After the EEG signals were collected from EEG equipment, we tidied the EEG data with signal processing algorithms and then extracted some features. We applied k-Nearest-Neighbor classifier and Naive Bayes classifier to these features to find out a combination, which may mostly contribute to reflect learners' affect, for example, Attention. In the classification algorithm, we presented a different way of using the Self-Assessment Manikin (SAM) model to classify and analyze learners attention, although the SAM was normally used for classifying emotions, for example, happiness etc. For the purpose of evaluating our findings, we also developed an affective learning prototype based on university e-learning web site. A real time EEG feedback window and an attention report were integrated into the system. The result of the experiment was encouraging and further discussion was also included in this paper.
Conjunctival Malignant Melanoma-Associated Pseudomelanoma of the Apposing Tarsal Conjunctiva

Purpose: To describe a case of conjunctival malignant melanoma associated with pseudomelanomatous alteration of the apposing tarsal conjunctiva. Methods: A 93-year-old woman presented with an elevated, pigmented mass on her superior bulbar conjunctiva. The tumor was associated with increased pigmentation of the apposing superior tarsal conjunctiva. An excisional biopsy of the epibulbar melanoma and pigmented tarsal conjunctiva was performed. Results: Histopathologic evaluation of the epibulbar tumor revealed epithelioid melanocytes diagnostic of malignant melanoma. Histopathologic evaluation of the pigmented tarsal lesion showed large areas of ulceration and foci of granulation tissue composed of neovascular sprouts arising in the background of a loose connective tissue, with a moderate chronic inflammatory infiltrate. The infiltrate was composed of mature lymphocytes, plasma cells, and scattered histiocytes. Densely packed intracytoplasmic, brown pigment granules that stained positive with HMB 45 were found, attesting to adjacent melanocytes' releasing melanin-laden granules. There was no evidence of malignancy in the pigmented tarsal specimen. Conclusion: Noncontiguous pigmented conjunctival tumor can be found in apposition to an epibulbar melanoma. Although a limited biopsy could be considered, only a complete resection and histopathologic evaluation can determine whether the entire lesion is free of malignant melanoma.
Fabrication and characterization of photonic crystal microcavities in quasi-single crystal diamond films

Single crystal diamond has become an attractive material for quantum information processing [1] due to the extraordinary properties of optically active defect centers, including Silicon (SiV), Nickel and Nitrogen (NV) complexes. The NV-center is the most investigated color center due to its outstanding properties such as very long spin lifetimes at room temperature and its suitability for single photon sources. There have been a number of recent proposals for the employment of color centers as cavity enhanced single photon sources, for cavity enhanced spin measurements or as optical qubits in quantum networks. All these proposals require a direct coupling of an emitter to a cavity with long photon lifetime (high quality factor Q) as well as strong spatial light confinement (small modal volume V). Photonic crystal microcavities etched in a diamond slab are being considered as an attractive architecture to manipulate and control light-matter interaction between an individual defect center and a resonator.
A recommender System for Restaurant Reviews Based on Consumer Segment

Previous research shows that consumers use online reviews for a variety of reasons. For many products / services, there are a large number of reviews which makes it difficult for consumers to decide which reviews to pay attention to. Hence, previous research has suggested that online reviews websites can provide a customized review sorting system for each individual consumer. Consequently, drawing upon five consumer segments as well as 10 restaurant characteristics found in the literature, we propose a content-filtering recommender system that evaluates individual online reviews and assigns a numeric score to each review for each of the five consumer segments. The numeric scores can later be used to sort online reviews for individual consumers according to their taste for restaurants
Low‐complexity high‐rate irregular QC‐LDPC codes with applications to PR2 and EPR2 channels

In this paper, we propose a modified high rate (3,L) quasi‐cyclic low‐density parity‐check (QC‐LDPC) code based on circulant permutation matrices for efficient encoder implementation. The structure of the code is modified from a (3,L) regular QC‐LDPC code to be an approximate lower triangular matrix and a linear independent form. We present two novel efficient encoding techniques for generating redundant parity bits. The complexity of the encoder implementation depends on the number of redundant parity bits of the code for one‐stage encoding and the length of the code for two‐stage encoding. The advantage of both encoding techniques is that few XOR gates are used in encoder implementation. The simulation results show that the proposed codes at code rate 0.884 and 0.953 have good bit error rate performance compared with other LDPC codes over PR2 and EPR2 channels. European Transactions on Telecommunications. Copyright © 2012 John Wiley & Sons, Ltd.
Optimal Broadcast Scheduling in Packet Radio Networks via Branch and Price

Packet radio networks use spatial time-division multiple-access to enable multiple network stations to communicate via the same frequency within the same time slot. Stations in close proximity are not allowed to use the same frequency, as their signals would interfere with each other. In this context, an important design problem is that of scheduling access to the high-speed communications channel in such a way as to maximize the utilization while avoiding interference and keeping the frame length to a minimum. This is frequently referred to as the broadcast scheduling problem and is known to be NP-hard. It is often formulated as a nonlinear discrete optimization problem for a given frame length and solved via heuristic approaches by parametrically varying the length of the frame. Despite this, the sizes of the problems solved have been small, with the solution times becoming prohibitive with increasing problem size. This paper introduces a set covering formulation for the problem and solves it optimally using branch and price. Columns are generated using a simple pricing heuristic whenever possible. A branching strategy adapted from [Vance, P. 1998. Branch-and-price algorithms for the one-dimensional cutting stock problem. Computational Optim. Appl.9 211--228] is used, while branching first on the number of time slots used. Extensive computational results show that this approach is very effective, identifying optimal solutions quickly even on problems significantly larger than those solved previously.
Grid connected solar PV fed cascaded multilevel inverter implementation using XSG platform

A photovoltaic (PV) supported cascaded H-Bridge multilevel inverter can be used to transfer the bulk solar power to the grid. It is considered that the dc link of the H-bridges is supplied from the PV array. The five-level cascaded H-bridge inverter enhances the power transfer rating and improves the output quality with carrier phase-shifted method of current control. Under varying radiation level across the PV arrays the DC link voltages across H-bridges varies. As a result the total PV power generated also varies. A grid connected current control method is proposed which transfers the PV generated power into the grid which depends upon the radiation level. The proposed control is verified through Xilinx System Generator (XSG) platform for implementation of FPGA control algorithm and realization of multilevel inverter and PV system. The maximum power point tracking (MPPT) is also incorporated across each PV array and realized in XSG. The conversion stage of VHDL program from XSG based simulation is also discussed.
BIOMETRIC SIGNATURE VERIFICATION USING PEN POSITION, TIME, VELOCITY AND PRESSURE PARAMETERS

The paper describes the development of a handwritten signature verification system incorporating pen pressure of signature path, time duration of the signing procedure, velocity profile of signature and position of signature shape. The handwritten signals have been captured and digitized using a tablet. The main features of the proposed signature verification system are the dynamically update of handwritten signature, retries capability in verification, application of tolerance bands and threshold values, development of user friendly Graphic User Interface, application of Common Time Axes and verification of signatures using a class of a multilayer feed-forward neural network. A novel algorithm has been applied that provides the ability to produce consistent and high accuracy verification result and maintain the speed of verification. The system has yielded 1.33% of False Reject Rate and 0% False Acceptation Rate with the verification using random forgery signatures.
Continuous indices of core data set measures in rheumatoid arthritis clinical trials: lower responses to placebo than seen with categorical responses with the American College of Rheumatology 20% criteria.

OBJECTIVE To describe indices that are continuous counterparts of categorical responses to the American College of Rheumatology 20% improvement criteria (ACR20), ACR50, and ACR70, which extend rheumatoid arthritis (RA) clinical trial results and recognize clinical worsening (as well as improvement) with active and placebo treatments. METHODS Data from a clinical trial of leflunomide, methotrexate, and placebo treatment over 1 year were reanalyzed. Percent change was computed for each of the 7 components of the ACR core set of outcome measures. Four continuous indices were computed: 1) ACR-N (lowest of 3 values: number of swollen joints, number of tender joints, and median of the other 5 measures); 2) composite (median of all 7 measures [3 patient and 3 assessor measures plus erythrocyte sedimentation rate]); 3) patient-only (median of physical function, pain, and global status); and 4) assessor-only (median of number of swollen joints, number of tender joints, and global status). Means, medians, categorical 20%, 50%, and 70% responses, and continuous probability plots were computed according to each index for the 3 treatment groups and were compared with one another and with standard ACR20, ACR50, and ACR70 responses. RESULTS Mean levels of improvement calculated using the different methods, in patients taking leflunomide, placebo, and methotrexate, respectively, were as follows: ACR-N 20%, -12%, and 13%; composite 43%, 9%, and 33%; patient-only 36%, 0%, and 26%; assessor-only 50%, 20%, and 44%; and ACR20 52%, 26%, and 46%. Differences between leflunomide and placebo were 30-36%, and differences between methotrexate and placebo were 24-26%. CONCLUSION Continuous indices may be an informative addition to categorical ACR 20%, 50%, or 70% responses to compare efficacies of various treatments in RA, and to describe lower responses to placebo by recognizing worsening as well as improvement.
The Effects of Target Behavior Choice and Self-Management Skills Training on Compliance with Behavioral Self-Monitoring

Purpose. The purpose of this study was to evaluate two potential methods for increasing participant compliance with behavioral self-monitoring (BSM). Design. A randomized 2 × 2 factorial design was used to evaluate the effects of target behavior choice (choice vs. assigned) and self-management skills training (training vs. no-training) on BSM compliance. In the choice manipulation, participants either chose or were assigned one of seven types of healthful or safe behaviors to self-monitor. In the training manipulation, participants either completed computer-based self-management skills training or received no training. Participants were then asked to complete daily BSM for 2 weeks. Setting. The study was conducted at a university and teaching hospital. Subjects. Participants (N = 60) were predominantly university and hospital employees. Measures. The primary dependent measure was percent compliance with BSM. Analysis. A factorial analysis of variance of compliance scores was performed. Results. Mean compliance with prescribed BSM was 52.6% (SD = 31.8). The main effect for choice was significant, with choice participants showing 18% higher BSM compliance than those in no-choice conditions (d = .59; p < .05). The effects of self-management skills training and the interaction term were both nonsignificant. Conclusion. Although self-management skills training did not appear to affect BSM compliance, offering individuals a choice in target behavior substantially increased both BSM compliance and self-reported behavior change. (Am J Health Promot 2011;25[5]:319-324.)