Miracle-dz/UniFAR-FTUs huggingface dataset:
Curing Residual Strain Monitoring of Carbon Fiber Reinforced Polymer Composite Using Notched Long-Period Fiber Grating

Composite materials are widely used in the aerospace industry and structural engineering owing to their advantageous mechanical properties. The curing monitoring of composite material is important to ensure the quality of the curing process, especially for the characterization of residual strains after manufacturing. In this study, we present a notched long-period fiber grating (NLPFG) with a period of 650 μm and a diameter of 66 μm that can be used in the curing monitoring of composite materials. This NLPFG was embedded into the middle layers of composite materials in order to determine the curing residual stress exhibited by the materials. The experimental results showed that the residual stress was about 107 MPa and the axial residual strain was 1490 με. Therefore, the proposed NLPFG has potential as a strain sensor for composite materials.
Circadian rhythms and gene expression during mouse molar tooth development

Abstract Objectives: Incremental markings in dental enamel suggest that the circadian clock may influence the molecular underpinnings orchestrating enamel formation. The aim of this study was to investigate whether the genes and microRNAs (miRNAs) oscillate in a circadian pattern during tooth and enamel development. Material and methods: Comparative gene and miRNA expression profiling of the first mandibular molar tooth germ isolated at different time-points during the light and night period was performed using microarrays and validated using real-time RT-PCR. Bioinformatic analysis was carried out using Ingenuity Pathway Analysis (IPA), and TargetScan software was used in order to identify computationally predicted miRNA–mRNA target relationships. Results: In total, 439 genes and 32 miRNAs exhibited significantly different (p < 0.05) levels of expression in the light phase compared with the night phase tooth germs. Genes involved in enamel formation, i.e. Amelx, Ambn, Amtn, and Odam, oscillated in a circadian pattern. Furthermore, the circadian clock genes, in particular Clock and Bmal1, oscillated in mouse molar tooth germ during 24-h intervals. The expression of Clock and Bmal1 was inversely correlated with the expression of miR-182 and miR-141, respectively. Conclusions: MiRNAs, including miR-182 and miR-141, are involved in the control of peripheral circadian rhythms in the developing tooth by regulating the expression of genes coding for circadian transcription factors such as CLOCK and BMAL1. Regulation of circadian rhythms may be important for enamel phenotype, and the morphology of dental enamel may vary between individuals due to differences in circadian profiles.
Advancements of Data Anomaly Detection Research in Wireless Sensor Networks: A Survey and Open Issues

Wireless Sensor Networks (WSNs) are important and necessary platforms for the future as the concept “Internet of Things” has emerged lately. They are used for monitoring, tracking, or controlling of many applications in industry, health care, habitat, and military. However, the quality of data collected by sensor nodes is affected by anomalies that occur due to various reasons, such as node failures, reading errors, unusual events, and malicious attacks. Therefore, anomaly detection is a necessary process to ensure the quality of sensor data before it is utilized for making decisions. In this review, we present the challenges of anomaly detection in WSNs and state the requirements to design efficient and effective anomaly detection models. We then review the latest advancements of data anomaly detection research in WSNs and classify current detection approaches in five main classes based on the detection methods used to design these approaches. Varieties of the state-of-the-art models for each class are covered and their limitations are highlighted to provide ideas for potential future works. Furthermore, the reviewed approaches are compared and evaluated based on how well they meet the stated requirements. Finally, the general limitations of current approaches are mentioned and further research opportunities are suggested and discussed.
Presynaptic Function during Muscle Remodeling in Insect Metamorphosis

During metamorphosis the leg neuromuscular system of the mothManduca sexta undergoes an extensive remodeling as the larval muscles degenerate and are replaced by new muscles in the adult. The terminal processes of persistent leg motoneurons undergo severe regression followed by regrowth (Consoulas et al., 1996), accompanied, as shown here, by the loss and re-establishment of functional presynaptic specializations. Before and shortly after the degeneration of the larval muscle, immunoreactivity for the vesicular protein synaptotagmin was localized to the presynaptic varicosities of the motoneurons. Similarly localized were distinct sites of Ca2+-dependent uptake of the fluorescent dye FM1-43. During myoblast migration and accumulation about the re-expanding motor axons, synaptotagmin immunoreactivity was widely distributed in axons, and specific FM1-43 staining revealed vesicle exocytosis in distal axon branches. During myoblast proliferation and fusion, and myotube formation, synaptotagmin staining remained widely distributed in nerve branches, whereas FM1-43 staining was more localized to subdomains of these nerve branches. These initial presynaptic active sites were transient and were replaced by new sites in more distal nerve processes as the muscle anlage increased in size and additional myotubes formed. After myotube separation, synaptotagmin staining disappeared from primary branches but remained distributed within secondary and high-order nerve branches. FM1-43 staining was detected in high-order branches only. During muscle fiber striation, growth, and maturation, both FM1-43 staining and synaptotagmin immunoreactivity became localized to terminal varicosities. Thus, presynaptic function can persist after the loss of the target and occurs transiently in axon shafts before becoming restricted to terminal domains as the underlying muscle fibers mature.
SMO AND LAZY CLASSIFIERS FOR HEART DISEASE PREDICTION

Data mining and machine learning technique are rapidly developed for many kinds of applications. One of the important applications is in medical diagnosis field. The aim of this paper is to compare the different classifiers for heart disease classification. In this paper, SMO classifier and two lazy classifiers (IBK and KStar) are used for prediction of heart disease. The results of each classifiers are compared and analysis. The experiments results proved that SMO classifier is better than other classifiers for heart disease prediction.
Three-dimensional reconstruction and analysis of mitotic spindles from the yeast, Schizosaccharomyces pombe

Mitotic spindles of Schizosaccharomyces pombe have been studied by EM, using serial cross sections to reconstruct 12 spindles from cells that were ultrarapidly frozen and fixed by freeze substitution. The resulting distributions of microtubules (MTs) have been analyzed by computer. Short spindles contain two kinds of MTs: continuous ones that run from pole to pole and MTs that originate at one pole and end in the body of the spindle. Among the latter there are three pairs of MT bundles that end on fibrous, darkly staining structures that we interpret as kinetochores. The number of MTs ending at each putative kinetochore ranges from two to four; all kinetochore-associated MTs disappear as the spindle elongates from 3-6 microns. At this and greater spindle lengths, there are no continuous MTs, only polar MTs that interdigitate at the spindle midzone, but the spindle continues to elongate. An analysis of the density of neighboring MTs at the midzone of long spindles shows that their most common spacing is approximately 40 nm, center to center, and that there is a preferred angular separation of 90 degrees. Only hints of such square-packing are found at the midzone of short spindles, and near the poles there is no apparent order at any mitotic stage. Our data suggest that the kinetochore MTs (KMTs) do not interact directly with nonkinetochore MTs, but that interdigitating MTs from the two spindle poles do interact to form a mechanically stable bundle that connects the poles. As the spindle elongates, the number of MTs decreases while the mean length of the MTs that remain increases. We conclude that the chromosomes of S. pombe become attached to the spindle by kinetochore MTs, that these MTs disappear as the chromosomes segregate, that increased separation of daughter nuclei is accompanied by a sliding apart of anti-parallel MTs, and that the mitotic processes of S. pombe are much like those in other eukaryotic cells.
Comparison of Prognostic Genomic Predictors in Colorectal Cancer

Background Although several prognostic genomic predictors have been identified from independent studies, it remains unclear whether these predictors are actually concordant with respect to their predictions for individual patients and which predictor performs best. We compared five prognostic genomic predictors, the V7RHS, the ColoGuideEx, the Meta163, the OncoDX, and the MDA114, in terms of predicting disease-free survival in two independent cohorts of patients with colorectal cancer. Study Design Using original classification algorithms, we tested the predictions of five genomic predictors for disease-free survival in two cohorts of patients with colorectal cancer (n = 229 and n = 168) and evaluated concordance of predictors in predicting outcomes for individual patients. Results We found that only two predictors, OncoDX and MDA114, demonstrated robust performance in identifying patients with poor prognosis in 2 independent cohorts. These two predictors also had modest but significant concordance of predicted outcome (r>0.3, P<0.001 in both cohorts). Conclusions Further validation of developed genomic predictors is necessary. Despite the limited number of genes shared by OncoDX and MDA114, individual-patient outcomes predicted by these two predictors were significantly concordant.
Design, simulation and implementation of bidirectional converter using synchronous switching for microgrid application

This work is mainly dedicated to implementation of bidirectional DC-DC converter for DC storage systems in medium power Microgrid applications. Microgrids are gaining immense popularity in present day scenario due to availability of flexible power management strategies and cost effectiveness. DC Microgrid mainly consists of PV system and Battery system. Battery system plays very important role in improving dynamic response of the microgrid. While designing power modulators for DC storage system, efficiency is a major concern. This work is dedicated to increase the efficiency of power modulators used for DC storage in microgrid [4]. In the battery system, a bidirectional converter is needed to facilitate bidirectional power flow. For that purpose we have selected two quadrant buck-boost topology instead of using conventional H-bridge or cuk topologies. Also instead of using conventional switching, we have used synchronous switching technique. Synchronous switching eliminates the power diode loss which constitutes major part of total losses in converter resulting into increased efficiency [2]. The corresponding MATLAB simulation results confirming the improved response are also included.
Ceftolozane/tazobactam pharmacokinetic/pharmacodynamic‐derived dose justification for phase 3 studies in patients with nosocomial pneumonia

Ceftolozane/tazobactam is an antipseudomonal antibacterial approved for the treatment of complicated urinary tract infections (cUTIs) and complicated intra‐abdominal infections (cIAIs) and in phase 3 clinical development for treatment of nosocomial pneumonia. A population pharmacokinetic (PK) model with the plasma‐to‐epithelial lining fluid (ELF) kinetics of ceftolozane/tazobactam was used to justify dosing regimens for patients with nosocomial pneumonia in phase 3 studies. Monte Carlo simulations were performed to determine ceftolozane/tazobactam dosing regimens with a >90% probability of target attainment (PTA) for a range of pharmacokinetic/pharmacodynamic targets at relevant minimum inhibitory concentrations (MICs) for key pathogens in nosocomial pneumonia. With a plasma‐to‐ELF penetration ratio of approximately 50%, as observed from an ELF PK study, a doubling of the current dose regimens for different renal functions that are approved for cUTIs and cIAIs is needed to achieve >90% PTA for nosocomial pneumonia. For example, a 3‐g dose of ceftolozane/tazobactam for nosocomial pneumonia patients with normal renal function is needed to achieve a >90% PTA (actual 98%) for the 1‐log kill target against pathogens with an MIC of ≤8 mg/L in ELF, compared with the 1.5‐g dose approved for cIAIs and cUTIs.
A Fuzzy Associative Classification Approach for Recommender Systems

Despite the existence of dierent methods, including data mining techniques, available to be used in recommender systems, such systems still contain numerous limitations. They are in a constant need for personalization in order to make effective suggestions and to provide valuable information of items available. A way to reach such personalization is by means of an alternative data mining technique called classification based on association, which uses association rules in a prediction perspective. In this work we propose a hybrid methodology for recommender systems, which uses collaborative altering and content-based approaches in a joint method taking advantage from the strengths of both approaches. Moreover, we also employ fuzzy logic to enhance recommendations quality and eectiveness. In order to analyze the behavior of the techniques used in our methodology, we accomplished a case study using real data gathered from two recommender systems. Results revealed that such techniques can be applied eectively in recommender systems, minimizing the eects of typical drawbacks they present.
Determination of effective elastic properties of microcracked rocks based on asymptotic approximation

In this paper, we present a study on the effective elastic properties of finely fractured rock based on the concept of energy equivalence. The effective elastic properties a rock body weakened by many penny-shaped microcracks, such as the apparent Young’s modulus, shear modulus and Poisson’s ratio, are particularly important in many applications. To determine these macroscopic parameters, we first adopt the dilute solution approach outlined in Kachanov (1992), where a crack compliance tensor is defined and used extensively to express the energy perturbation caused by the presence of the cracks. In parallel, a self-consistent method is employed where an asymptotic form of the Eshelby’s tensor (Eshelby, 1957) is developed to treat a penny-shaped microcrack as an extreme case of a spheroid-shaped inhomogeneity. The asymptotic approximation permits the local Eshelby tensor as well as its global expression to be derived analytically, and to be further used to construct an equivalent eigenstrain problem based on energy equivalence. The effective values for the parameters of interest can then be evaluated. The formulation and results obtained through the asymptotic self-consistent approach are compared to those predicted using a non-interacting scheme.
An Integrated Location Management Scheme for Seamless Access in B3G Systems

Over the last decade there has been a rapid growth of wireless communication technology. Among numerous wireless network architectures, the personal communication services (PCS) networks and wireless local area networks (WLAN) have attracted lots of attention. One of the core functionalities in wireless networks is the location service that provides location information for subscriber services, emergency services, and various mobile networks internal operations. In this paper, an integrated location management mechanism is proposed for heterogeneous wireless networks that combine PCS networks and WLAN. Three major functionalities in the integrated location management scheme are the determination of the WLAN connectivity for a mobile terminal, the development of a local area location scheme for WLAN, and the location prediction module for PCS networks. This mechanism not only determines the location of a mobile client more precisely, but also reduces the cost of locating. The performance evaluation is conducted to demonstrate the effectiveness of the proposed mechanism for heterogeneous wireless networks.
Diagnosis of asynchronous discrete event systems: datalog to the rescue!

We consider query optimization techniques for data intensive P2P applications. We show how to adapt an old technique from deductive databases, namely Query-Sub-Query (QSQ), to a setting where autonomous and distributed peers share large volumes of interelated data.We illustrate the technique with an important telecommunication problem, the diagnosis of distributed telecom systems. We show that (i) the problem can be modeled using Datalog programs, and (ii) it can benefit from the large battery of optimization techniques developed for Datalog. In particular, we show that a simple generic use of the extension of QSQ achieves an optimization as good as that previously provided by dedicated diagnosis algorithms. Furthermore, we show that it allows solving efficiently a much larger class of system analysis problems.
Psyc home tr ic Assess me nt of Computing Undergraduates

This paper describes three studies of students in computer science, information technology, and software engineering degree courses. Aim. The aim of these studies was to evaluate the usefulness of aptitude testing as a means of recruiting undergraduate students into these courses. Method. At the start of the academic year, student volunteers were invited to complete a demographic survey and/or part of the Aptitude Profile Test Series (APTS) developed by the Australian Council for Education Research. At the end of the year, the survey and APTS data were combined with examination results, and a statistical analysis was performed. Results. The demographic survey yielded several potential predictors of academic performance. Furthermore, the APTS was a statistically significant predictor of academic performance (p < 0.001). Conclusions. The results suggest that the APTS could be used to recruit students into computing degree courses, reducing the withdrawal and termination rates, and increasing the number and quality of graduates from these courses.
CONSERVATION GENETICS OF THE ENDANGERED COACHELLA VALLEY FRINGE-TOED LIZARD (UMA INORNATA)

We used microsatellite loci to examine rangewide population structure and interpopulation gene flow in the federally threatened Coachella Valley fringe-toed lizard (Uma inornata). Our results indicate low population differentiation consistent with high gene flow, recent colonization and range expansion, and/or frequent local extirpation/recolonization events. Given high historical gene flow among populations and current isolation of remaining populations, conservation planning for this species should include monitoring of potential deleterious effects that may result from reduction in gene flow, such as inbreeding and loss of genetic variation, to ensure maintenance of ecological and evolutionary population processes adequate for long-term survival of the species.
Low-biased fiber-optic link for microwave downconversion

Downconversion of microwave signals using fiber-optic links is investigated while low-biasing one modulator in a cascaded pair. Enhancement of the downconverted signal and variation of intermodulation distortion terms as a function of phase bias are studied theoretically and experimentally. Distortion is significant at high local oscillator powers needed to minimize conversion loss.
Nonparametric estimation via empirical risk minimization

A general notion of universal consistency of nonparametric estimators is introduced that applies to regression estimation, conditional median estimation, curve fitting, pattern recognition, and learning concepts. General methods for proving consistency of estimators based on minimizing the empirical error are shown. In particular, distribution-free almost sure consistency of neural network estimates and generalized linear estimators is established. >
A Binding Mode Hypothesis of Tiagabine Confirms Liothyronine Effect on γ-Aminobutyric Acid Transporter 1 (GAT1)

Elevating GABA levels in the synaptic cleft by inhibiting its reuptake carrier GAT1 is an established approach for the treatment of CNS disorders like epilepsy. With the increasing availability of crystal structures of transmembrane transporters, structure-based approaches to elucidate the molecular basis of ligand–transporter interaction also become feasible. Experimental data guided docking of derivatives of the GAT1 inhibitor tiagabine into a protein homology model of GAT1 allowed derivation of a common binding mode for this class of inhibitors that is able to account for the distinct structure–activity relationship pattern of the data set. Translating essential binding features into a pharmacophore model followed by in silico screening of the DrugBank identified liothyronine as a drug potentially exerting a similar effect on GAT1. Experimental testing further confirmed the GAT1 inhibiting properties of this thyroid hormone.
Distance Approximating Dimension Reduction of Riemannian Manifolds

We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geodesic distances between data points on the Riemannian manifold while preserving discrimination ability. Existing algorithms, e.g., ISOMAP, that try to learn an isometric embedding of data points on a manifold have a non-satisfactory discrimination ability in practical applications such as face and gait recognition. In this paper, we propose a two-stage algorithm named tensor-based Riemannian manifold distance-approximating projection (TRIMAP), which can quickly compute an approximately optimal projection for a given tensor data set. In the first stage, we construct a graph from labeled or unlabeled data, which correspond to the supervised and unsupervised scenario, respectively, such that we can use the graph distance to obtain an upper bound on an objective function that preserves pairwise geodesic distances. Then, we perform some tensor-based optimization of this upper bound to obtain a projection onto a low-dimensional subspace. In the second stage, we propose three different strategies to enhance the discrimination ability, i.e., make data points from different classes easier to separate and make data points in the same class more compact. Experimental results on two benchmark data sets from the University of South Florida human gait database and the Face Recognition Technology face database show that the discrimination ability of TRIMAP exceeds that of other popular algorithms. We theoretically show that TRIMAP converges. We demonstrate, through experiments on six synthetic data sets, its potential ability to unfold nonlinear manifolds in the first stage. Index Terms-Gait recognition, linear discriminant analysis, manifold learning, multilinear tensor learning.
Relative bearing estimation from commodity radios

Relative bearing between robots is important in applications like pursuit-evasion [11] and SLAM [7]. This is also true in sensor networks, where the bearing of one sensor node relative to another has been used for localization [5], [18], [20] and topology control [14], [21], [6]. Most systems use dedicated sensors like an IR array or a camera to obtain relative bearing. We study the use of radio signal strength (RSS) in commodity radios for obtaining relative bearing. We show that by using the robot's mobility, commodity radios can be used to obtain coarse relative bearing. This measurement can be used for a suite of applications that do not require very precise bearing measurement. We analyze signal strength variations in simulation and experiment and also show an algorithm that uses this coarse bearing computation in a practical setting.