Miracle-dz/UniFAR-FTUs huggingface dataset:
BS 196 : an old star cluster far from the Small Magellanic Cloud main body

We present B and V photometry of the outlying Small Magellanic Cloud (SMC) star cluster BS 196 with the 4.1-m SOAR telescope. The photometry is deep (to V≈25), showing ≈3 mag below the cluster turnoff point at M V = 2.5 (1.03 M ⊙ ). The cluster is located at the SMC distance. The colour-magnitude diagram and isochrone fittings provide a cluster age of 5.0 ± 0.5 Gyr, indicating that this is one of the 12 oldest clusters so far detected in the SMC. The estimated metallicity is [Fe/H] = - 1.68 ± 0.10. The structural analysis gives by means of the King profile fittings a core radius R c = 8.7 ± 1.1 arcsec (2.66 ± 0.14pc) and a tidal radius R t = 69.4 ± 1.7 arcsec (21.2 ± 1.2pc). BS 196 is rather loose with a concentration parameter c = 0.90. With M V = -1.89 ± 0.39, BS 196 belongs to the class of intrinsically fainter SMC clusters, which have started to be explored as compared to the well-known populous ones.
Summarizing conceptual descriptions using knowledge representations

Summarizing a body of information is a complex task which mainly depends on the ability to distinguish important information and to condense notions through abstraction. Considering a knowledge representation partially ordering concepts into a directed acyclic graph, this study focuses on the problem of summarizing several human descriptions expressed through sets of concepts. We formally define the problem of summarization in this context and we propose a model mimicking a Human-like Intelligence for scoring alternatives with regard to a specific objective. Several interesting theoretical results related to this problem (e.g. for optimization) are also given. Finally, the evaluation of the proposed approach performed in the domain of odor analysis highlights the benefits of our proposal and shows how it could be used to automatize time-consuming expert summarizing processes. Source code implementing the proposed approach as well as datasets are made available to the community.1
Internet of Things Based Free Parking Space Management System

Internet of things is an emerging technology that enables every object of our surroundings to be connected and controlled from a distance. Wireless sensors can be integrated to the internet and the sensor data can be monitored and thus detect events from distance. Reliable free parking-space management system is important to maintain the discipline and better utilization of the parking space. Free parkingspace management system using wireless sensor networks is less expensive and requires less installation requirements. In this paper, we have illustrated a complete implementation of free parking-space management system using wireless sensor networks. We have used sensor motes of Texas Instruments each consisting of ten sensors. We have employed four sensors, magnetic, light, temperature, and ambient temperature sensors of the motes for reliable detection of the free space. We have optimized the operating system, adopted low-powered efficient networking protocol and a lightweight messaging model for data transmission. We have implemented the system and deployed in a parking area. Our experimental results show that the system can detect vehicle presence with an accuracy of 98%.
Molecular characterization of pmbA, an Escherichia coli chromosomal gene required for the production of the antibiotic peptide MccB17

Microcin B17 (MccB17) is a peptide antibiotic produced by Escherichia coli strains harbouring plasmid pMccB17. We have isolated two mutations that strongly reduce the production of MccB17. These mutations, which map at 96 min on the E. coli chromosome, define a new gene that we have caiied pmbA. A chromosomal DNA fragment of about 13kb, including the wild‐type pmbA allele, was cloned into a mini‐Mu piasmid vector. pmbA was located within the cloned DNA fragment by insertional mutagenesis and deletion analysis. The nucleotide sequence of a 1.7 kb DNA region containing the gene was determined. pmbA encodes a hydrophilic protein of 450‐amino‐acid residues with a predicted molecular size of 48375 D, which was visualized in polyacrylamide gels. Protein profiles of cellular envelope and soluble fractions from cells with plasmids overproducing PmbA indicated that it is cytoplasmic. Physiological experiments suggested that pmbA mutants synthesize a molecule (pro‐MccB17) able to inhibit DNA replication but unable to the released from cells. We propose that PmbA facilitates the secretion of the antibiotic by completing its maturation.
Energy-Saving Predictive Resource Planning and Allocation

Predictive resource allocation is an emerging approach to improve the performance of mobile systems as human behavior is reported predictable by leveraging big data analytics. Yet what information can be predicted by big data, what information need to be predicted for wireless access optimization, how to translate the information, and how to exploit the synthetic knowledge for allocating radio resources are not well understood and largely explored. In this paper, we are concerned with the latter two issues. In particular, we devise an energy-saving resource planning and allocation policy for multiple base stations (BSs) to serve mobile users with non-real-time (NRT) traffic by exploiting the user, network, and application levels of context information, where RT traffic may occupy partial resources of each BS. Inspired by the solution from an energy minimization problem with future instantaneous information, a low complexity multi-timescale predictive policy is proposed. Upon the arrival of each NRT user request, the resource planning is made with the user and network level context information, defined as the average channel gains of the NRT users and the statistics of residual bandwidth after serving RT traffic, with which the scheduling, power allocation, and BS sleeping can be accomplished after instantaneous channel information and residual network resource are available at each BS in each time slot. Simulation results show that the proposed policy can dramatically reduce the energy consumed by the BSs for serving the NRT traffic.
ASCA Observations of the Ionized Gas in the Seyfert Galaxy NGC 3783

We present the results from ASCA observations of NGC 3783 carried out during 1993 and 1996. Variability is observed both between the two epochs and within the individual observations, the latter due to a nonstationary process. We find the spectra at both epochs to contain features due to absorption by ionized material, predominantly due to O VII and O VIII. We find the opacity for such material to decrease by a factor ~2 in the ~0.7-1.0 keV band between the epochs while the photoionizing flux increases by ~25%. By comparison with detailed photoionization models we show that this behavior is inconsistent with that expected from a single zone of photoionized gas. A deficit in the data compared to such models, consistent with excess absorption by O VIII, supports the suggestion that the material consists of two or more zones. Significant Fe K shell emission is also observed during both epochs. We show that this emission is dominated by the asymmetric line profile expected from the innermost regions of the accretion flow. We find no evidence that the Fe emission varied in either shape or equivalent width between the two epochs.
An Optimized Business Service Directory for the ESB Platform in SOA

Service Oriented Architecture (SOA) helps toprovide value added services to the user with agility by following a publish-find-compose technique. Business Service Directory is one of the key components of Enterprise Service Bus and its implementation involves many challenges. One of the essential challenges is how to provide a suitable set of service candidates faster. This paper proposes a business service directory which employs ranking based, quality driven publishing and searching. The proposed business service directory is a fuzzy expert system which requires no human intervention. The implementation of optimized business service directory is composed of two steps, first the rule base is designed which contains auto generated rules to rank the web service. Fuzzy clustering and PSO is used to not only generate rules automatically using training dataset but also removing redundant and less effective rules. The next step is to design inference engine which triggers the rules in the rule base. The proposed Business service directory minimizes administrative overhead and increases usability by locating the best web service among the large number of functionally equivalent web services and it’s also adaptive in nature.
Optimal pulsewidth modulation of a dual three-level inverter system operated from a single dc link

Operating a dual three-level inverter system from a single dc link circuit is an economic solution for generating five-level output voltage waveforms and to double the output power compared to a single three-level inverter. Such inverter system is used for feeding a drive motor with open stator windings. A mechanism is then required to reduce the common mode voltage components of the motor voltages. This paper describes an off-line optimization method that minimizes both the harmonic distortion of the motor currents and the common mode voltage components. The optimization permits reducing the switching frequency to a very low value of 200 Hz without compromising on harmonic distortion. High performance operation of the drive system at low switching frequency is experimentally demonstrated.
A pilot study of group cognitive behavioural therapy for depression in a Japanese community.

Aims: This pilot study investigated the effect and feasibility of a group cognitive behavioural therapy program in a Japanese community setting. Methodology: Participants were five patients with major depression. Ten weekly 1-hour sessions of group cognitive behavioural therapy was conducted in a Japanese community setting. Outcomes were assessed using the Beck Depression Inventory-II (BDI-II). Statistical comparison of means was performed using nonparametric Wilcoxon signed-rank test using normal approximation, and effect sizes (d) was used to compare depression scores before and after the Short Communication Asano et al.; BJMMR, 10(4): 1-6, 2015; Article no.BJMMR. 19447 2 intervention. Results: Group cognitive behavioural therapy appears to be significantly efficacious in a Japanese community setting, with an effect size of . 85. The present results are similar to those found in clinical settings. Discussion: Adapting group cognitive behaviour programs to Japanese community settings can contribute to improved mental health in this country. The limitations of this study are the sample size was very small, measurement is self-reported questionnaire and conducted in a community setting as an uncontrolled, naturalistic pilot study. Controlled studies are needed and would provide a more convincing demonstration of the program’s efficacy in Japanese community settings.
Hydrogen peroxide induces p16INK4a through an AUF1‐dependent manner

Elevation of p16INK4a has been described as an important mechanism for hydrogen peroxide (H2O2)‐induced replicative senescence. However, the mechanisms underlying remain unknown. In this study, we demonstrate an important role of RNA‐binding protein AUF1‐mediated mRNA turnover in H2O2‐induced p16INK4a expression. The induction of p16 by H2O2 was accompanied with declined cytoplasmic AUF1 level. Accordingly, exposure of cells to H2O2 remarkably reduced the binding of AUF1 to p16 3′UTR and increased the half‐life of an EGFP‐p16‐3′UTR chimeric transcript. In AUF1‐silenced cells, the effect of H2O2 on p16 induction was abolished. Furthermore, in cells co‐transfected with vectors expressing AUF1s, treatment with H2O2 failed to significantly reduce the expression of AUF1 and subsequently elevate the levels of p16. Moreover, HeLa cells overexpressing AUF1s were resistant to H2O2‐induced senescence. Our results indicate that AUF1 is critical for H2O2‐induced p16 expression and cellular senescence. J. Cell. Biochem. 109: 1000–1005, 2010. © 2010 Wiley‐Liss, Inc.
Performance Comparison of ROAD Statistic Based Nonlinear Filters for Image Denoising

Removal of impulse noise from images without losing their features is an important requirement in image processing applications. The standard median filter is a good candidate for eliminating impulse noise; however, it fails to preserve the image details when the window size is made larger. In this paper, three nonlinear filtering schemes, based on the recently reported rank-ordered absolute difference (ROAD) image statistic, are introduced for cleaning the images confounded by impulse noise. These ROAD based nonlinear filtering techniques perform the filtering function on the basis of sum of rank-ordered absolute differences between central pixel inside the window and its neighboring pixels. Extensive simulation studies have been carried out by applying the proposed filtering schemes on a test image corrupted with different levels of impulse noise and the results obtained are included.
Identity Tableaux: Multimodal Contextual Constructions of Adolescent Identity

Abstract:Mobile and social media are blurring the social spaces in which teens construct and disseminate representations of identity to their peers. We refer to these representations as identity tableaux. In this paper, we present an unexpected finding from a long-term study investigating the use of mobile media, visual art, and civic engagement to reconnect at-risk youth with their education. Using a framework of hybrid spaces and multimodal media literacies, for our analysis, we looked at the processes adolescents utilize to create and share representations of their identity within the social and intimate spaces that they inhabit. From our analysis of social media posts and interviews, we saw that the participating teens defined their social relationships through representations of affective experiences using context-specific multimodal media literacies. Youth identity formation using mobile and social media is a synergetic relationship between the individual and the collective online.
12 bits, 40MS/s, low power pipelined SAR ADC

This paper presents a low power SAR ADC utilizing pipelining to increase the resolution up to 12 bits while maintaining a high speed sampling rate. Novel system level modifications and also new comparator architecture are proposed to optimize the power consumption. The ADC is designed and simulated in 0.18um CMOS technology by 1.2v supply voltage consuming 4.5mW power at 40MS/s sampling rate. The results indicates an effective number of bits (ENOB) of 11.04 bit and a challenging FOM of 54.9 fj/conversion which verifies the competence of proposed method.
THE EFFECTS OF LIFE SKILLS TRAINING ON MARITAL AND SEXUAL SATISFACTION OF YOUNG COUPLES

The aim of this study was to examine the effects of life skills training on marital and sexual satisfaction of young couples. The research method was quisa experimental and a twogroups research design (experimental and control) with pretest and posttest. Statistical population was all couples who referred to a consulting center in Mashhad from whom a convenient sample of 36 couples (72 persons) were selected. The 36 couples were selected based on the four criteria of marital history; education level, age, and psychological health score . Then, couples were randomly assigned to experimental (18 couples) and control (18 couples) groups. Assessment instruments consisted of Enrich Marital Satisfaction Questionnaires (Olson, et al., 1987) and Sexual Satisfaction Questionnaire (Berg-Cross, 1997). At the pre-test stage, all couples filled the 2 the scales. Then, the experimental group participated in 10-sessions, 3 hours each, training program of life skills and sexual skills, while the control group did not receive any training. At the post-test stage, the two groups answered the 2 scales again. The data were analyzed via using ANCOVA. Results of comparing scores in pretest and posttest showed that skills training affected sexual satisfaction and marital satisfaction, and scores of experimental group improved significantly after receiving skills training compared with their pre-test scores and the control group (P<0.01).
Social capital and cigarette smoking among Latinos in the United States

This paper presents the results of analyses conducted to examine if social capital indicators were associated with current cigarette smoking and with quitting smoking among a national representative sample of Latinos living in the United States. Data are from 2540 Mexican Americans, Puerto Ricans, Cuban Americans, and Other Latinos who participated in the National Latino and Asian American Survey. A significant inverse association between neighborhood cohesion and current smoking, and a positive association with quitting smoking, were found only among Mexican Americans. No other significant associations were found except for family conflict being associated with higher odds of current smoking with Cuban Americans. Implications of these findings are discussed to unravel the differences in social capital and smoking behaviors among Latino populations.
Combining local descriptors for 3D object recognition and categorization

Various local descriptors have been used successfully in a variety of tasks including object recognition. Although different descriptors have been shown to have different strengths, they haven¿t been used in combination. In this paper we show that by combining local image descriptors at the feature level, we can significantly improve object recognition performance. Our system uses keyed context patches and SIFT, two descriptors that have been shown to have a somewhat uncorrelated performance [9]. By requiring hypotheses generated by both types of descriptors to satisfy the same consistency constraints, we were able to significantly reduce the error rate on recognition and categorization tasks.
Data fusion of GPS sensors using Particle Kalman Filter for ship dynamic positioning system

Depending on standards and class, dynamically positioned ships make use of different numbers of redundant sensors to determine current ship position. The paper presents a multi-sensor data fusion algorithm for the dynamic positioning system which allows it to record the proper signal from a number of sensors (GPS receivers). In the research, the Particle Kalman Filter with data fusion was used to estimate the position of the vessel. The presented algorithms generate a virtual measurement using three measurements from independent sensors. The performance of the Particle Kalman Filter algorithm was evaluated in simulation tests for two specific cases: in regular operation and when the signal of one sensor disappears.
From subspace clustering to full-rank matrix completion

Subspace clustering is the problem of finding a multi-subspace representation that best fits a collection of points taken from a high-dimensional space. This type of structure occurs naturally in many applications ranging from bioinformatics, image/text clustering to semi-supervised learning. The companion paper [3] shows that robust and tractable subspace clustering is possible with minimal requirements on the orientation of the subspaces and number of samples per subspace. This note summarizes a forthcoming work [1] on subspace clustering when some of the entries in the data matrix are missing. This problem may also be viewed as a generalization of standard low-rank matrix completion to cases where the matrix is of high or potentially full-rank. Synthetic and real data experiments confirm the effectiveness of these methods. 1 Problem formulation and model Consider a real-valued n × N dimensional matrix X. We assume that the columns of X lie in a union of L unknown linear subspaces, of unknown dimensions. A small subset of the entries of such a matrix is revealed. The goal is two fold: 1) partition the columns into different clusters based on subspace of origin and approximate the underlying subspaces. 2) inpute the missing entries. Throughout we assume that the each entry of X is observed with probability 1 − δ. 2 Method Here we explain our method for subspace clustering with missing data. Upon finding the correct clustering, one can apply any one of the low-rank matrix recovery algorithms on each cluster to complete the missing entries. To introduce our method, we first study the problem when all entries are revealed. 2.1 No missing entries Most spectral clustering algorithms follow a two-step procedure: I) Construct a weighted graph W that captures the similarity between any pair of points, II) Select clusters by applying spectral clustering techniques to W. Following [2,3,6] we build the affinity graph in Step I by finding the sparsest expansion of each column x (i) of X as a linear combination every other column. Under some generic conditions, one expects that the sparsest representation of x (i) would only select vectors from the subspace in which x (i) happens to lie in. This leads to the following sequence of optimization problems min β∈R N β 1 subject to Xβ = x (i) and β i = 0. (2.1) One then collects the outcome of these N optimization problems as columns of a matrix B and …
Efficacy of exercise for menopausal symptoms: a randomized controlled trial

ObjectiveThis study aims to determine the efficacy of exercise training for alleviating vasomotor and other menopausal symptoms. MethodsLate perimenopausal and postmenopausal sedentary women with frequent vasomotor symptoms (VMS) participated in a randomized controlled trial conducted in three sites: 106 women randomized to exercise and 142 women randomized to usual activity. The exercise intervention consisted of individual facility-based aerobic exercise training three times per week for 12 weeks. VMS frequency and bother were recorded on daily diaries at baseline and on weeks 6 and 12. Intent-to-treat analyses compared between-group differences in changes in VMS frequency and bother, sleep symptoms (Insomnia Severity Index and Pittsburgh Sleep Quality Index), and mood (Patient Health Questionnaire-8 and Generalized Anxiety Disorder-7 questionnaire). ResultsAt the end of week 12, changes in VMS frequency in the exercise group (mean change, −2.4 VMS/d; 95% CI, −3.0 to −1.7) and VMS bother (mean change on a four-point scale, −0.5; 95% CI, −0.6 to −0.4) were not significantly different from those in the control group (−2.6 VMS/d; 95% CI, −3.2 to −2.0; P = 0.43; −0.5 points; 95% CI, −0.6 to −0.4; P = 0.75). The exercise group reported greater improvement in insomnia symptoms (P = 0.03), subjective sleep quality (P = 0.01), and depressive symptoms (P = 0.04), but differences were small and not statistically significant when P values were adjusted for multiple comparisons. Results were similar when considering treatment-adherent women only. ConclusionsThese findings provide strong evidence that 12 weeks of moderate-intensity aerobic exercise do not alleviate VMS but may result in small improvements in sleep quality, insomnia, and depression in midlife sedentary women.