Miracle-dz/UniFAR-FTUs huggingface dataset:
Support Vectors Selection for Supervised Learning Using an Ensemble Approach

Support Vector Machines (SVMs) are popular for pattern classification. However, training a SVM requires large memory and high processing time, especially for large datasets, which limits their applications. To speed up their training, we present a new efficient support vector selection method based on ensemble margin, a key concept in ensemble classifiers. This algorithm exploits a new version of the margin of an ensemble-based classification and selects the smallest margin instances as support vectors. Our experimental results show that our method reduces training set size significantly without degrading the performance of the resulting SVMs classifiers.
Design and Fabrication of LC-Oscillator Tool Kits Based Op-Amp for Engineering Education Purpose

In this paper, a proposed design, fabrication and testing of sine wave oscillator “LC” type (Hartley and Colpitts oscillator) has been performed using five approaches. The first approach proposed design is done theoretically using the basic theorems used to generate oscillations, such as the condition of oscillation criteria and determine the values of capacitor (C) and inductor (L) component, Secondly it is done using simulation technique (LTSpice IV), Thirdly the simulated design is implemented practically using IC OP-AMP 741 with passive elements such as resistors, capacitors and inductors by oscilloscope and frequency generator. Fourthly design the Hartley and colpitts tool kit by 2-D and 3-D, layouting the circuit by Eagle PCB design software then package into tool box which integrated each other. Finaly, the LC-oscillator tool kit was tested such as resistor, capasitor and inductor module and write the result into tables (for jobsheet data).
Exploiting Discourse Analysis for Article-Wide Temporal Classification

In this paper we classify the temporal relations between pairs of events on an article-wide basis. This is in contrast to much of the existing literature which focuses on just event pairs which are found within the same or adjacent sentences. To achieve this, we leverage on discourse analysis as we believe that it provides more useful semantic information than typical lexico-syntactic features. We propose the use of several discourse analysis frameworks, including 1) Rhetorical Structure Theory (RST), 2) PDTB-styled discourse relations, and 3) topical text segmentation. We explain how features derived from these frameworks can be effectively used with support vector machines (SVM) paired with convolution kernels. Experiments show that our proposal is effective in improving on the state-of-the-art significantly by as much as 16% in terms of F1, even if we only adopt less-than-perfect automatic discourse analyzers and parsers. Making use of more accurate discourse analysis can further boost gains to 35%.
Finding Optimal Bayesian Network Structures with Constraints Learned from Data

Several recent algorithms for learning Bayesian network structures first calculate potentially optimal parent sets (POPS) for all variables and then use various optimization techniques to find a set of POPS, one for each variable, that constitutes an optimal network structure. This paper makes the observation that there is useful information implicit in the POPS. Specifically, the POPS of a variable constrain its parent candidates. Moreover, the parent candidates of all variables together give a directed cyclic graph, which often decomposes into a set of strongly connected components (SCCs). Each SCC corresponds to a smaller subproblem which can be solved independently of the others. Our results show that solving the constrained subproblems significantly improves the efficiency and scalability of heuristic search-based structure learning algorithms. Further, we show that by considering only the top p POPS of each variable, we quickly find provably very high quality networks for large datasets.
Clinical Assessment of Anti-Viral CD8+ T Cell Immune Monitoring Using QuantiFERON-CMV® Assay to Identify High Risk Allogeneic Hematopoietic Stem Cell Transplant Patients with CMV Infection Complications

The reconstitution of anti-viral cellular immunity following hematopoietic stem cell transplantation (HSCT) is crucial in preventing cytomegalovirus (CMV)-associated complications. Thus immunological monitoring has emerged as an important tool to better target pre-emptive anti-viral therapies. However, traditional laboratory-based assays are too cumbersome and complicated to implement in a clinical setting. Here we conducted a prospective study of a new whole blood assay (referred to as QuantiFERON-CMV®) to determine the clinical utility of measuring CMV-specific CD8+ T-cell responses as a prognostic tool. Forty-one evaluable allogeneic HSCT recipients underwent weekly immunological monitoring from day 21 post-transplant and of these 21 (51.2%) showed CMV reactivation and 29 (70.7%) developed acute graft-versus-host disease (GvHD). Patients with acute GvHD (grade≥2) within 6 weeks of transplant showed delayed reconstitution of CMV-specific T-cell immunity (p = 0.013) and a higher risk of CMV viremia (p = 0.026). The median time to stable CMV-specific immune reconstitution was 59 days and the incidence of CMV reactivation was lower in patients who developed this than those who did not (27% versus 65%; p = 0.031). Furthermore, a failure to reconstitute CMV-specific immunity soon after the onset of CMV viraemia was associated with higher peak viral loads (5685 copies/ml versus 875 copies/ml; p = 0.002). Hence, QuantiFERON-CMV® testing in the week following CMV viremia can be useful in identifying HSCT recipients at risk of complicated reactivation.
Validity and reliability of the Short Physical Performance Battery ( SPPB ) : a pilot study on mobility in the Colombian Andes

Abstract Objectives: To assess the validity (convergent and construct) and reliability of the Short Physical Performance Battery (SPPB) among non-disabled adults between 65 to 74 years of age residing in the Andes Mountains of Colombia. Methods: Design: Validation study; Participants: 150 subjects aged 65 to 74 years recruited from elderly associations (day-centers) in Manizales, Colombia. Measurements: The SPPB tests of balance, including time to walk 4 meters and time required to stand from a chair 5 times were administered to all participants. Reliability was analyzed with a 7-day interval between assessments and use of repeated ANOVA testing. Construct validity was assessed using factor analysis and by testing the relationship between SPPB and depressive symptoms, cognitive function, and self rated health (SRH), while the concurrent validity was measured through relationships with mobility limitations and disability in Activities of Daily Living (ADL). ANOVA tests were used to establish these associations. Results: Test-retest reliability of the SPPB was high: 0.87 (CI95%: 0.77-0.96). A one factor solution was found with three SPPB tests. SPPB was related to self-rated health, limitations in walking and climbing steps and to indicators of disability, as well as to cognitive function and depression. There was a graded decrease in the mean SPPB score with increasing disability and poor health. Conclusion: The Spanish version of SPPB is reliable and valid to assess physical performance among older adults from our region. Future studies should establish their clinical applications and explore usage in population studies. Original Articles
Mechanism for the selection of nuclear polypeptides in Xenopus oocytes. II. Two-dimensional gel analysis

The role of the nuclear envelope in controlling intracellular protein exchanges was investigated in vivo, by determining the effect of altering nuclear permeability on (a) the protein composition of the nucleoplasm and (b) the nuclear uptake rates of specific endogenous proteins. The nuclear envelopes were disrupted by puncturing oocytes in the region of the germinal vesicle by use of glass needles. Nuclear proteins were analyzed in punctured and control cells by two- dimensional gel electrophoresis, fluorography, and double-labeling techniques. Over 300 nuclear polypeptides were identified in the fluorographs. Of this number, only approximately 10-15 were found to vary between punctured and control nuclei; furthermore, different polypeptides varied in each experiment. These qualitative studies indicate that specific binding within the nucleoplasm, and not selection by the envelope, is the main factor in maintaining the protein composition of the nucleus. The nuclear uptake rates of five individual polypeptides, ranging in molecular weight from 43,000 to 100,000, were analyzed by use of double-labeling procedures. Only one of the polypeptides (actin) entered the nuclei more rapidly after disruption of the envelope. That the nuclear uptake of certain endogenous proteins is unaffected by puncturing demonstrates that passage across the envelope is not a rate-limiting step in the nucleocytoplasmic exchange of these molecules.
r-Learning services for elementary school students with a teaching assistant robot

The r-Learning paradigm with educational robots is emerging as a part of e-Learning, which means using technology for learning. This study on using robots as a teaching assistant robot opened the possibility of r-Learning for English in classroom. We found that children like robot services for personal relationship in class and teachers prefer them related to their convenience to manage the lesson. Related robot services such as praising and cheering up or calling the roll are the effective way for motivating children to learn, enhancing the relationship between TIRO and children. We are going on conducting further field trials for new scenarios and services that motivate children and make them concentrate on class with teachers, pre-teachers, children, parents, robotic researchers, social scientists, etc.
Organization and reorganization of autonomous oceanographic sampling networks

As robots and other autonomous agents become more widespread, there will be a greater need for them to work cooperatively to accomplish complex, that is, agents will enter or leave the system while the task is being performed. This presents a formidable problem for organizing and controlling the agents. We present an approach to this problem for autonomous oceanographic sampling networks, which are groups of robots and sensor platforms that cooperate to sample an area over a long period of time. The approach uses two organizations to control the agents. A task-level organization (TLO) controls the system during the actual mission, and a meta-level organization (MLO) is responsible for self-organization of the system, design of the TLO to fit the situation, and reorganization as necessary. This approach allows the TLO to be highly efficient, while allowing the MLO to give the overall system a great deal of flexibility in adapting to change.
The Measurement of the Q‐T Interval of the Electrocardiogram

The sources of error in determination of the beginning of QRS and the end of T during measurement of the Q-T duration are analyzed. An important error is confusion of an elevated U wave with the T wave, resulting in the diagnosis of a prolonged Q-T. In such cases, some of the precordial leads usually show a notch or kink between T and U which indicates approximately the end of T. If these criteria are used, the true corrected Q-T duration in hypopotassemia without hypocalcemia is not prolonged, but normal or shortened, corresponding to an earlier appearance of the second heart sound.
Striatal astrocytes produce neuroblasts in an excitotoxic model of Huntington's disease

In the adult brain, subsets of astrocytic cells residing in well-defined neurogenic niches constitutively generate neurons throughout life. Brain lesions can stimulate neurogenesis in otherwise non-neurogenic regions, but whether local astrocytic cells generate neurons in these conditions is unresolved. Here, through genetic and viral lineage tracing in mice, we demonstrate that striatal astrocytes become neurogenic following an acute excitotoxic lesion. Similar to astrocytes of adult germinal niches, these activated parenchymal progenitors express nestin and generate neurons through the formation of transit amplifying progenitors. These results shed new light on the neurogenic potential of the adult brain parenchyma. Highlighted article: Brain lesion in mice reveals a latent neurogenic potential in striatal astrocytes, which can proliferate and generate new neuroblasts.
Bifurcation Analysis of Ultrashort Self-Acting Gas Journal Bearings for MEMS

The development of microrotational devices in microelectromechanical systems (MEMS) has introduced a kind of ultrashort self-acting gas journal bearing with low length-to-diameter ratios. The bifurcation of ultrashort self-acting gas journal bearing-rotor systems is studied in this paper. The system is modeled as a rigid rotor supported by bearing forces as a result of gas viscosity and rotational speed. The spectral collection method is employed to discretize the nonlinear Reynolds equation describing the pressure distribution of the working fluid of the bearing. A system of nonlinear partial differential equations, which couples the fluid equation and the equations of the rotor motion, is presented and solved using the Runge-Kutta method. The bifurcation diagram, rotor center orbits, phase portraits, frequency spectra, and Poincare maps are utilized to analyze the dynamic characteristics of the rotor-bearing system for different operating conditions. The effects of the rotational speed and length-to-diameter ratio on the system dynamic behaviors are investigated with both low and high initial eccentricity ratios. The analyses show that the system exhibits complicated behaviors at low eccentricity ratios as a result of the self-excited whirl motion. For high eccentricity ratios, the bearing behavior comprises synchronous and subharmonic motions. A further understanding of the nonlinear dynamics of gas journal bearing in MEMS is given by the analysis results.
Regional Style Automatic Identification for Chinese Folk Songs

The Regional style is one of the basic characteristic of Chinese folk songs. Because of the distinctive regional characteristics of Chinese folk songs, lots of folk songs lovers search for music by regional style. Therefore, geographical style automatic identification for folk songs is an important topic both for academic and industrial area. This paper studies geographical style automatic identification with different machine learning methods. An active feature selection method is proposed to improve the classification accuracy, and discover the most important feature for regional style classification. The experiments results show that SVM with active feature selection is an approximate best method. The classification accuracy of this method is 82.97%, and the features are reduced to 35 dimensions. Moreover, an improved combining multiple classifiers method can get the highest classification accuracy, that is 84.29%. Relative works show that our methods are also very efficient in other areas like genre classification.
Flow resistance in gravel bed open channel flows case: intense transport condition

Abstract Gravel bed can be categorised into three bed load conditions, i.e. no load, moderate and intense. An experimental investigation was carried out in an open channel flow with gravel bed surface of grain size of D50 values 6.5 mm intense load conditions. The investigation of the roughness characteristics of gravel bed open channel flows under intense load conditions over various discharges and flow depths are presented. Variation of friction factor for the roughness conditions for different flow depths is estimated. The intensity of the bed load is calculated with the help of sediment transport rate. The bed load transport rate for the intense load conditions is also determined from experimentation on gravel beds of 6.5 mm gravel size for different flow depths. Using the data-set of other researchers and present experimental data, a new model as a function of intensity of the bed load transport with respect to Shield’s parameter is formulated. The modified model gives satisfactory results as compared to previous works, which is displayed through error analysis.
The LuxR Family Quorum-Sensing Activator MrtR Requires Its Cognate Autoinducer for Dimerization and Activation but Not for Protein Folding

ABSTRACT MrtR, a LuxR homolog in Mesorhizobium tianshanense, is important for symbiosis. We found that MrtR requires its cognate N-acylhomoserine lactone for forming dimers, binding to a single DNA site and activating the downstream promoter. However, MrtR is able to fold independently of its ligand.
VMM-independent graphics acceleration

We have designed and implemented VMGL, a virtual machine monitor (VMM) independent, graphics processing unit (GPU) independent, and cross-platform OpenGL virtualization solution. VMGL allows applications executing within virtual machines (VMs) to leverage hardware rendering acceleration, thus solving a problem that has limited virtualization of a growing class of graphics-intensive applications. VMGL also provides applications running within VMs with suspend and resume capabilities across GPUs from different vendors. Our experimental results from a number of graphics-intensive applications show that VMGL provides excellent rendering performance, within 14% or better of that obtained with native graphics hardware acceleration. Further, VMGL's performance is two orders of magnitude better than that of software rendering, the commonly available alternative today for graphics-intensive applications running in virtualized environments. Our results confirm VMGL's portability across VMware Workstation and Xen (on VT and non-VT hardware), and across Linux (with and without paravirtualization), FreeBSD, and Solaris. Our results also show that the resource demands of VMGL align well with the emerging trend of multi-core processors.
An Optimum Architecture for Continuous-Flow Parallel Bit Reversal

With the aim of minimizing memory and latency, this letter presents a novel bit-reversal architecture for continuous-flow parallel pipelined FFT processors. It harnesses the theory that any permutation can be decomposed to a series of elementary bit-exchanges. The main contribution of this letter are twofold. First, it achieves continuous-flow bit reversal in parallel with the minimum memory and minimum latency. Second, the architecture, composed of memory and 2-to-1 multiplexers, are simple and regular for general power-of-2 parallelism. Furthermore, it supports different common radices, including radix-2,radix-4, and radix-8.
Pay as you browse: microcomputations as micropayments in web-based services

Currently, several online businesses deem that advertising revenues alone are not sufficient to generate profits and are therefore set to charge for online content. In this paper, we explore a complement to the current advertisement model; more specifically, we propose a micropayment model for non-specialized commodity web-services based on microcomputations. In our model, a user that wishes to access online content offered by a website does not need to register or pay to access the website; instead, he will accept to run microcomputations on behalf of the website in exchange for access to the content. These microcomputations can, for example, support ongoing computing projects that have clear social benefits (e.g., projects relating to HIV, dengue, cancer, etc.) or can contribute towards commercial computing projects. We argue that this micropayment model is economically and technically viable and that it can be integrated in existing distributed computing frameworks (e.g., the BOINC platform). We implement a preliminary prototype of a system based on our model through which we evaluate its performance and usability. Finally, we analyze the security and privacy of our proposal and we show that it ensures payment for the content while preserving the privacy of users.
Deep Learning Based Syndrome Diagnosis of Chronic Gastritis

In Traditional Chinese Medicine (TCM), most of the algorithms used to solve problems of syndrome diagnosis are superficial structure algorithms and not considering the cognitive perspective from the brain. However, in clinical practice, there is complex and nonlinear relationship between symptoms (signs) and syndrome. So we employed deep leaning and multilabel learning to construct the syndrome diagnostic model for chronic gastritis (CG) in TCM. The results showed that deep learning could improve the accuracy of syndrome recognition. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice.
APC mutations lead to cytokinetic failures in vitro and tetraploid genotypes in Min mice

Previous research has proposed that genomic instability contributes to cancer progression, with its initiation linked to tetraploid cell formation (Duesberg, P., and R. Li. 2003. Cell Cycle. 2:202–210; Ganem, N.J., Z. Storchova, and D. Pellman. 2007. Curr. Opin. Genet. Dev. 17:157–162). However, there is little direct evidence linking cancer-causing mutations with such events, and it remains controversial whether genomic instability is a cause or an effect of cancer. In this study, we show that adenomatous polyposis coli (APC) mutations found in human colorectal cancers dominantly inhibit cytokinesis by preventing mitotic spindle anchoring at the anaphase cortex and, thus, blocking initiation of the cytokinetic furrow. We find that dividing crypt cells in the small intestines of APCMin/+ mice exhibit similar mitotic defects, including misoriented spindles and misaligned chromosomes. These defects are observed in normal crypt cells with wild-type levels of β-catenin and, importantly, are associated with tetraploid genotypes. We provide direct evidence that the dominant activity of APC mutants induces aneuploidy in vivo. Our data support a model whereby tetraploid cells represent a first step in the onset of genomic instability and colorectal cancer.
An EST-SSR Linkage Map of Raphanus sativus and Comparative Genomics of the Brassicaceae†

Raphanus sativus (2n = 2x = 18) is a widely cultivated member of the family Brassicaceae, for which genomic resources are available only to a limited extent in comparison to many other members of the family. To promote more genetic and genomic studies and to enhance breeding programmes of R. sativus, we have prepared genetic resources such as complementary DNA libraries, expressed sequences tags (ESTs), simple sequence repeat (SSR) markers and a genetic linkage map. A total of 26 606 ESTs have been collected from seedlings, roots, leaves, and flowers, and clustered into 10 381 unigenes. Similarities were observed between the expression patterns of transcripts from R. sativus and those from representative members of the genera Arabidopsis and Brassica, indicating their functional relatedness. The EST sequence data were used to design 3800 SSR markers and consequently 630 polymorphic SSR loci and 213 reported marker loci have been mapped onto nine linkage groups, covering 1129.2 cM with an average distance of 1.3 cM between loci. Comparison of the mapped EST-SSR marker positions in R. sativus with the genome sequence of A. thaliana indicated that the Brassicaceae members have evolved from a common ancestor. It appears that genomic fragments corresponding to those of A. thaliana have been doubled and tripled in R. sativus. The genetic map developed here is expected to provide a standard map for the genetics, genomics, and molecular breeding of R. sativus as well as of related species. The resources are available at http://marker.kazusa. or.jp/Daikon.