Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient parallel algorithm for multiple sequence alignments with regular expression constraints on graphics processing units

Multiple sequence alignments with constraints has become an important problem in computational biology. The concept of constrained sequence alignment is proposed to incorporate the biologist's domain knowledge into sequence alignments such that the user-specified residues/segments are aligned together in the alignment results. Over the past decade, a series of constrained multiple sequence alignment tools were proposed in the literature. RE-MuSiC is the newest tool with the regular expression constraints and useful for a wide range of biological applications. However, the computation time of REMuSiC is large for a large amount of sequences or long sequences and this problem limits the application usage. Therefore, in this paper, a tool, GPU-REMuSiC v1.0, is proposed to reduce the computation time of RE-MuSiC by using the graphics processing units with CUDA. GPU-REMuSiC v1.0 can achieve 29× speedups for overall computation time by the experimental results.
A Survey of Model Comparison Strategies and Techniques in Model Driven Engineering

This Survey paper shows the recent state of model comparison as it’s applies to Model Driven engineering. In Model Driven Engineering to calculate the difference between the models is a very important and challenging task. There are number of tasks involved in Model differencing that firstly starts with identifying and matching the elements of the model. In this paper we discuss how model matching is accomplished, the strategies, techniques and the types of the model. In this paper we also discuss the future direction. We find out that many of the latest model comparison strategies are geared near enabling Meta model and similarity based matching. Therefore model versioning is the most dominant application of the model comparison. Recently to work on comparison for versioning has begun to deteriorate, giving way to different applications. Ultimately there is wide change among the tools in the measure of client exertion needed to perform model comparisons, as some require more push to encourage more sweeping statement and expressive force. Full Text: PDF DOI: http://dx.doi. org/10.11591/ijset.v1i3. 4579
Crystallization of a Glass‐Ceramic by Epitaxial Growth

The crystallization mechanism in a modified Li/sub 2/O-Al/sub 2/O/sub 3/-SiO/sub 2/ glass containing P/sub 2/O/sub 5/ nucleating agent was investigated by transmission electron microscopy, X-ray diffraction, and differential thermal analysis. During an initial 1000/sup 0/C treatment P/sub 2/O/sub 5/ and Li/sub 2/O react to precipitate Li/sub 3/PO/sub 4/ crystallites. At lower temperatures cristobalite, lithium metasilicate, and lithium disilicate crystallize by epitaxial growth on those Li/sub 3/PO/sub 4/ crystallites. Crystallographic orientation relations for epitaxy were determined by electron diffraction, and lattice misfits were found to be in the range -5.3 to +3.8%. These results provide the first direct proof that glass-ceramics can crystallize by epitaxial growth on heterogeneous nuclei formed from intentionally added nucleating agents.
Information supervisory control of human behavior — Experiments and formal modeling

A type of services that requires human physical actions and intelligent decision making can be found in various real fields, such as services by floor staff in hotels/restaurants and caregiving by nurses in hospitals/nursing homes. The authors' group calls such a type of services “the physical and adaptive intelligent service,” and is developing an ICT-based system, called the smart voice messaging (SVM) system, that assists staff in cooperation, knowledge sharing and recording events and observations. We have already proposed the concept of information supervisory control (ISC) and its implementation on the SVM system. In this scheme, there is a central commander, called the information supervisor, and it provides a group of persons with appropriate information at appropriate timing. Toward realization of ISC, we conduct experiments in order to know how human activity changes by providing information. Moreover, we introduce formal models that simulate human decision making in the experiments. Finally, we discuss realization of ISC based on the results of the experiments and the simulation.
Time-varying parametric system multiresolution identification by wavelets

In this paper, the problem of time-varying parametric system identification by wavelets is discussed. Employing wavelet operator matrix representation, we propose a new multiresolution least squares (MLS) algorithm for time-varying AR (ARX) system identification and a multiresolution least mean squares (MLMS) algorithm for the refinement of parameter estimation. These techniques can achieve the optimal tradeoff between the over-fitted solution and the poorly represented identification. The main features of time-varying model parameters are extracted in a multiresolution way, which can be used to represent the smooth trends as well as track the rapidly changing components of time-varying parameters simultaneously and adaptively. Further, a noisy time-varying AR (ARX) model can also be identified by combining the total least squares algorithm with the MLS algorithm. Based on the proposed AR (ARX) model parameter estimation algorithm, a novel identification scheme for time-varying ARMA (ARMAX) system is presented. A higher-order time-varying AR (ARX) model is used to approximate the time-varying ARMA (ARMAX) system and thus obtain an initial parameter estimation. Then an iterative algorithm is applied to obtain the consistent and efficient estimates of the ARMA (ARMAX) system parameters. This ARMA (ARMAX) identification algorithm requires linear operations only and thus greatly saves the computational load. In order to determine the time-varying model order, some modified AIC and MDL criterions are developed based on the proposed wavelet identification schemes. Simulation results verify that our methods can track the rapidly changing of time-varying system parameters and attain the best balance between parsimonious modelling and accurate identification.
DroidVulMon -- Android Based Mobile Device Vulnerability Analysis and Monitoring System

The use of Android platform based mobile terminals has been growing high. On the down side, the number of attacks by malicious application is also increasing because Android platform is vulnerable to private information leakage. These malicious applications are easily distributed to users through open market or internet. An attacker inserts malicious code into mobile app which could be harmful tool to steal private data. To cope with security threats more actively, it is necessary to develop countermeasure system that enables to detect security vulnerability existing in mobile terminal and take an appropriate action to protect the system against malicious attacks. Therefore, this paper investigates security-related vulnerability for mobile terminal and suggests 'DroidVulMon' system to detect and respond attacks in order to prevent information leakage caused by malicious app.
Microblog Analysis as a Program of Work

Inspired by a European project, PHEME, that requires the close analysis of Twitter-based conversations in order to look at the spread of rumors via social media, this article has two objectives. The first of these is to take the analysis of microblogs back to first principles and lay out what microblog analysis should look like as a foundational program of work. The other is to describe how this is of fundamental relevance to human-computer interaction's interest in grasping the constitution of people's interactions with technology within the social order. Our critical finding is that, despite some surface similarities, Twitter-based conversations are a wholly distinct social phenomenon requiring an independent analysis that treats them as unique phenomena in their own right, rather than as another species of conversation that can be handled within the framework of existing conversation analysis. This motivates the argument that microblog analysis be established as a foundationally independent program, examining the organizational characteristics of microblogging from the ground up. We articulate how aspects of this approach have already begun to shape our design activities within the PHEME project.
ICG-001 Exerts Potent Anticancer Activity Against Uveal Melanoma Cells

Purpose Uveal melanoma (UM) is uniformly refractory to all available systemic chemotherapies, thus creating an urgent need for novel therapeutics. In this study, we investigated the sensitivity of UM cells to ICG-001, a small molecule reported to suppress the Wnt/β-catenin–mediated transcriptional program. Methods We used a panel of UM cell lines to examine the effects of ICG-001 on cellular proliferation, migration, and gene expression. In vivo efficacy of ICG-001 was evaluated in a UM xenograft model. Results ICG-001 exerted strong antiproliferative activity against UM cells, leading to cell cycle arrest, apoptosis, and inhibition of migration. Global gene expression profiling revealed strong suppression of genes associated with cell cycle proliferation, DNA replication, and G1/S transition. Gene set enrichment analysis revealed that ICG-001 suppressed Wnt, mTOR, and MAPK signaling. Strikingly, ICG-001 suppressed the expression of genes associated with UM aggressiveness, including CDH1, CITED1, EMP1, EMP3, SDCBP, and SPARC. Notably, the transcriptomic footprint of ICG-001, when applied to a UM patient dataset, was associated with better clinical outcome. Lastly, ICG-001 exerted anticancer activity against a UM tumor xenograft in mice. Conclusions Using in vitro and in vivo experiments, we demonstrate that ICG-001 has strong anticancer activity against UM cells and suppresses transcriptional programs critical for the cancer cell. Our results suggest that ICG-001 holds promise and should be examined further as a novel therapeutic agent for UM.
A Symmetrical Cascaded Compact-Module Multilevel Inverter (CCM-MLI) With Pulsewidth Modulation

Cascaded H-bridge (CHB) multilevel inverters (MLIs) have been widely used for power electronics systems. While high-voltage blocking across power switches is not a constraint for low voltage applications, the research trend has been oriented to the design of more compact module topologies as an alternative for CHB. Despite the generation of more voltage levels with reduced switch count, the existing module topologies in recent literature take no account of the freewheeling current path during dead-time, thus, inducing multistep jumps in voltage levels and giving rise to undesirable voltage spikes. Addressing this concern, this paper proposes two symmetrical compact-module topologies for cascaded MLI, where freewheeling current path during dead-time is provided for smooth transition between voltage levels to prevent voltage spikes. The proposed 7-level and 13-level compact-modules demonstrated low number of conducting switches for all voltage levels. Comprehensive analysis and comparison with the latest module topologies are conducted. To validate the operation of the proposed compact-module topologies, simulation and experimental results are presented.
Replicate Phylogenies and Post-Glacial Range Expansion of the Pitcher-Plant Mosquito, Wyeomyia smithii, in North America

Herein we tested the repeatability of phylogenetic inference based on high throughput sequencing by increased taxon sampling using our previously published techniques in the pitcher-plant mosquito, Wyeomyia smithii in North America. We sampled 25 natural populations drawn from different localities nearby 21 previous collection localities and used these new data to construct a second, independent phylogeny, expressly to test the reproducibility of phylogenetic patterns. Comparison of trees between the two data sets based on both maximum parsimony and maximum likelihood with Bayesian posterior probabilities showed close correspondence in the grouping of the most southern populations into clear clades. However, discrepancies emerged, particularly in the middle of W. smithii's current range near the previous maximum extent of the Laurentide Ice Sheet, especially concerning the most recent common ancestor to mountain and northern populations. Combining all 46 populations from both studies into a single maximum parsimony tree and taking into account the post-glacial historical biogeography of associated flora provided an improved picture of W. smithii's range expansion in North America. In a more general sense, we propose that extensive taxon sampling, especially in areas of known geological disruption is key to a comprehensive approach to phylogenetics that leads to biologically meaningful phylogenetic inference.
Scaled fixed-point frequency selective extrapolation for fast image error concealment

Image and video signal processing demands in many areas for error concealment algorithms, whereby the execution time plays an important role. Within this paper, we introduce the scaled fixed-point Frequency Selective Extrapolation for fast image error concealment. This algorithm is based on the complex-valued Frequency Selective Extrapolation, but reduces computational complexity. It is shown that a fixed-point realization of the state-of-the-art algorithm requires an impracticable word-length, which makes it necessary to design a novel, scaled Frequency Selective Extrapolation that reduces the required word-length. Regarding the new approach, execution time can be reduced on average by 22.84 % and at best by up to 40.45 % compared to the state-of-the-art floating point Frequency Selective Extrapolation at the same reconstruction quality. Moreover, platforms can be exploited, which support fixed-point arithmetic only.
Plasmodium vivax Biology: Insights Provided by Genomics, Transcriptomics and Proteomics

During the last decade, the vast omics field has revolutionized biological research, especially the genomics, transcriptomics and proteomics branches, as technological tools become available to the field researcher and allow difficult question-driven studies to be addressed. Parasitology has greatly benefited from next generation sequencing (NGS) projects, which have resulted in a broadened comprehension of basic parasite molecular biology, ecology and epidemiology. Malariology is one example where application of this technology has greatly contributed to a better understanding of Plasmodium spp. biology and host-parasite interactions. Among the several parasite species that cause human malaria, the neglected Plasmodium vivax presents great research challenges, as in vitro culturing is not yet feasible and functional assays are heavily limited. Therefore, there are gaps in our P. vivax biology knowledge that affect decisions for control policies aiming to eradicate vivax malaria in the near future. In this review, we provide a snapshot of key discoveries already achieved in P. vivax sequencing projects, focusing on developments, hurdles, and limitations currently faced by the research community, as well as perspectives on future vivax malaria research.
Relationship between somatic cell count, polymorphonuclear leucocyte count and quality parameters in bovine bulk tank milk

The somatic cell count (SCC) in bovine bulk tank milk is presently used as an indicator of raw milk quality, reflecting the udder health status of the herd. During mastitis, SCC increases, mostly owing to an influx of polymorphonuclear leucocytes (PMN) from blood into milk, with a concomitant change in milk composition. Bulk tank milk samples were categorized according to their SCC, as well as polymorphonuclear leucocyte count (PMNC), to study relationships between SCC, PMNC and various raw milk quality traits, i.e. contents of total protein, whey protein, casein, fat and lactose, casein number, proteolysis and rheological properties. The proportion of PMN, obtained by direct microscopy, was significantly higher in samples with high SCC compared with low SCC samples. SCC and PMNC were strongly correlated, yielding a correlation coefficient of 0·85. High SCC samples had lower lactose and casein contents, lower casein number and more proteolysis than low SCC samples. Samples with high PMNC had a lower casein number than low PMNC samples. Samples with high and low SCC or PMNC did not differ in respect to rheological properties. Our results do not indicate that PMNC is a better biomarker than SCC for raw bulk tank milk quality, as previously proposed.
Mitigation of Byzantine Attacks on Distributed Detection Systems Using Audit Bits

This paper considers the problem of distributed detection in the presence of Byzantines who seek to degrade detection performance by falsifying data. This paper proposes a novel mechanism to mitigate Byzantine attacks by partitioning sensors into groups. Local decisions from sensors in each group are sent to the Fusion Center (FC) via multiple paths, which enable the FC to assess (i.e., to audit) the information that reaches it to improve detection performance. We introduce a weighted Kullback–Leibler Divergence (KLD) metric to measure the detection performance of the FC and show that the proposed mechanism is more robust against Byzantine attacks than previously proposed schemes. We prove that, using the proposed mechanism, the FC becomes blind (i.e., no useful information reaches the FC) only if all the nodes in the network are Byzantines. This paper also characterizes optimal Byzantine attacks in the scenario when the FC cannot be made blind. Further, the paper conducts game theoretic analysis to investigate the scenario when both the Byzantines and the FC act strategically against each other and prove the existence of a Nash Equilibrium. Extensive numerical results are provided throughout the paper that provide insights into the proposed distributed detection mechanism.
Open-Label Pilot Study to Compare the Safety and Immunogenicity of Pentavalent Rotavirus Vaccine (RV5) Administered on an Early Alternative Dosing Schedule with Those of RV5 Administered on the Recommended Standard Schedule

This study compares the safety and immunogenicity of pentavalent rotavirus vaccine (RV5) administered on an alternative schedule (initiated at 2-5 weeks of age) with those of RV5 administered on the recommended standard schedule. Our findings support the future conduct of larger clinical trials to confirm the safety and efficacy of rotavirus vaccination in the neonatal period.
An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach

Melanoma is the deadliest type of skin cancer with highest mortality rate. However, the annihilation in early stage implies a high survival rate therefore, it demands early diagnosis. The accustomed diagnosis methods are costly and cumbersome due to the involvement of experienced experts as well as the requirements for highly equipped environment. The recent advancements in computerized solutions for these diagnoses are highly promising with improved accuracy and efficiency. In this article, we proposed a method for the classification of melanoma and benign skin lesions. Our approach integrates preprocessing, lesion segmentation, features extraction, features selection, and classification. Preprocessing is executed in the context of hair removal by DullRazor, whereas lesion texture and color information are utilized to enhance the lesion contrast. In lesion segmentation, a hybrid technique has been implemented and results are fused using additive law of probability. Serial based method is applied subsequently that extracts and fuses the traits such as color, texture, and HOG (shape). The fused features are selected afterwards by implementing a novel Boltzman Entropy method. Finally, the selected features are classified by Support Vector Machine. The proposed method is evaluated on publically available data set PH2. Our approach has provided promising results of sensitivity 97.7%, specificity 96.7%, accuracy 97.5%, and F‐score 97.5%, which are significantly better than the results of existing methods available on the same data set. The proposed method detects and classifies melanoma significantly good as compared to existing methods.
Exploring alternative security warning dialog for attracting user attention: evaluation of "Kawaii" effect and its additional stimulus combination

One of security functions is a security warning dialog (SWdialog). However, the effect for ensuring security is questionable because of the habituation. This means that users tend to disregard of it through repeated encounters. In this paper, we propose an alternative security warning dialog using the effect of "Kawaii", which means "cute" in Japanese. We also propose a combination of additional effects with "Kawaii" to the dialog. We conducted an evaluation experiment with a small number of subjects in order to verify whether the proposed dialog has a potential of expected affection to users. From the results of the experiment, we find that the proposed dialog could obtain user attention better than the conventional dialogs. Moreover, one of proposed dialog that is applied the effect combined additional effects with "Kawaii" would have a potential to suppress disregarding action to the dialog even if a user is habituated.
Disability associated with mental disorders

Background: Disability associated with mental illness is a major contributor to the global burden of disease. The present study looks at some aspects of disability associated with 7 psychiatric disorders: schizophrenia, bipolar affective disorder, anxiety disorders, depression, obsessive–compulsive disorder, dementia, and mental and behavioural disorders due to the use of alcohol. Aims: (i) To evaluate the nature and quantity of disabilities in the study groups; (ii) to compare the degree of disability with the severity of the disorder; (iii) to compare disability among various disorders; and (iv) to study the longitudinal stability of disability in the disease groups. Methods: A total of 228 patients attending the OPD, Department of Psychiatry, Assam Medical College, Dibrugarh, between July 2003 and June 2004, who were diagnosed as per ICD-10 guidelines and SCAN, were included in the study. Severity was assessed by the application of some commonly used rating scales for each specific disorder. The level of disability was assessed by using the Indian Disability Evaluation and Assessment Scale (IDEAS). Patients were followed up at 6 and 12 months. Statistical analysis was done on SPSS version 10. Results: All the 7 disorders under study are associated with significant disability; schizophrenia being maximally disabling. Disability associated with alcohol use disorder and anxiety is comparable to disability on account of OCD. Over a period of 12 months, disability due to depression, alcohol use disorder and anxiety tend to remain significant.
Integral augmented nonlinear differentiator for noisy signals

This paper proposed an arctangent function based integral augmented nonlinear differentiator (IAND) for obtaining of the noise-less derivative signal from a noisy measurement signal. The basic idea of proposed IAND with high noise-attenuation effect is to establish the differentiator by expanding the signal dynamics with extra state variable representing the integrated noisy measurement, then with the integral of measurement as input, the IAND is formulated to achieve better noise suppression ability without appreciable delay. Moreover, the convergence characteristic and anti-noise property in the frequency domain are analyzed via singular perturbation theory and describing function method, respectively. The simulation comparison results with other differentiators show the superiority of IAND in noise suppression.