Miracle-dz/UniFAR-FTUs huggingface dataset:
A generic particle filtering approach for multiple polyhedral object tracking in a distributed active sensor network

This paper presents a method for multi-target tracking in a multisensor system composed of several distributed active sensors (rangefinders). The final goal is to deliver a complete reconstruction of the environment of a vehicle. The originality of this work relies on the joint exploitation of geometric invariance properties of objects avoiding any loss of optimality and on an efficient management of transitions when the objects of interest move from one field-of-view to another.
Impact of website information design factors on consumer ratings of web-based auction sites

Web-based auctions are now regarded as among the most successful business models on the Internet. Buyers who are invited to a web-based auction site make decisions based on a wealth of on-line information. In such circumstances, commercial transactions tend to be influenced not only by the information content of the website, but also by its design. However, little effort has been made to analyse the relationships between transaction behaviour and these design factors. The aim of this paper is to identify information design factors and to analyse how these factors influence intention to bid in web-based auction sites. Our empirical study shows that information design factors and the specific characteristics of products are significantly related to a buyer's evaluations of an auction website and intention to bid.
Unity Power Factor Control for Three-Phase Three-Level Rectifiers Without Current Sensors

Three-level rectifiers with reduced number of switches (such as the Vienna rectifier) to improve the input power quality of rectifier systems have been receiving wide interest in the past years. In this paper, a new carrier-based pulsewidth-modulation control algorithm is proposed for such converters to eliminate the low-frequency harmonics in the line current while achieving unity power factor at the rectifier input terminals. The operating constraints of the Vienna rectifier with the carrier-based modulation strategy are examined carefully, and the proposed control algorithm ensures that appropriate voltage/current directional constraints are met. A promising cost-reduction opportunity can be seen with the elimination of input current sensing to operate the Vienna rectifier. The control algorithm is verified via Saber simulation and experimental results.
Minimum Variance Control Over a Gaussian Communication Channel

We consider the problem of minimizing the response of a plant output to a stochastic disturbance using a control law that relies on the output of a noisy communication channel. We discuss a lower bound on the performance achievable at a specified terminal time using nonlinear time-varying communication and control strategies and show that this bound may be achieved using strategies that are linear. We also consider strategies that are defined over an infinite horizon that may achieve better transient response that those that are optimal for the terminal time problem.
Engaging scientometrics in Information Systems: Combining the Quantitative and Qualitative

The goal of this study is to stimulate a broader and deeper application of scientometric theory in information systems (IS) research, specifically to emphasize the benefits of scientometrics in the conceptual development of the IS field. The study reviews the underlying theories of scientometrics, specifically how they combine both quantitative and qualitative approaches towards research evaluation. Based on the analysis of selected scientometric studies in IS, this study finds significant room for future research in the virtually untouched landscape of scientometric theories.
Factors Associated With Poor Glycemic Control or Wide Glycemic Variability Among Diabetes Patients in Hawaii, 2006–2009

Introduction Although glycemic control is known to reduce complications associated with diabetes, it is an elusive goal for many patients with diabetes. The objective of this study was to identify factors associated with sustained poor glycemic control, some glycemic variability, and wide glycemic variability among diabetes patients over 3 years. Methods This retrospective study was conducted among 2,970 diabetes patients with poor glycemic control (hemoglobin A1c [HbA1c] >9%) who were enrolled in a health plan in Hawaii in 2006. We conducted multivariable logistic regressions to examine factors related to sustained poor control, some glycemic variability, and wide glycemic variability during the next 3 years. Independent variables evaluated as possible predictors were age, sex, type of insurance coverage, morbidity, diabetes duration, history of cardiovascular disease, and number of medications. Results Longer duration of diabetes, being under age 35, and taking 15 or more medications were significantly associated with sustained poor glycemic control. Preferred provider organization and Medicare (vs health maintenance organization) enrollees and patients with high morbidity were less likely to have sustained poor glycemic control. Wide glycemic variability was significantly related to being younger than age 50, longer duration of diabetes, having coronary artery disease, and taking 5 to 9 medications per year. Conclusion Results indicate that duration of diabetes, age, number of medications, morbidity, and type of insurance coverage are risk factors for sustained poor glycemic control. Patients with these characteristics may need additional therapies and targeted interventions to improve glycemic control. Patients younger than age 50 and those with a history of coronary heart disease should be warned of the health risks of wide glycemic variability.
New Compact 3-Dimensional Shape Descriptor for a Depth Camera in Indoor Environments

This study questions why existing local shape descriptors have high dimensionalities (up to hundreds) despite simplicity of local shapes. We derived an answer from a historical context and provided an alternative solution by proposing a new compact descriptor. Although existing descriptors can express complicated shapes and depth sensors have been improved, complex shapes are rarely observed in an ordinary environment and a depth sensor only captures a single side of a surface with noise. Therefore, we designed a new descriptor based on principal curvatures, which is compact but practically useful. For verification, the CoRBS dataset, the RGB-D Scenes dataset and the RGB-D Object dataset were used to compare the proposed descriptor with existing descriptors in terms of shape, instance, and category recognition rate. The proposed descriptor showed a comparable performance with existing descriptors despite its low dimensionality of 4.
Did the reporting of prognostic studies of tumour markers improve since the introduction of REMARK guideline? A comparison of reporting in published articles

Although biomarkers are perceived as highly relevant for future clinical practice, few biomarkers reach clinical utility for several reasons. Among them, poor reporting of studies is one of the major problems. To aid improvement, reporting guidelines like REMARK for tumour marker prognostic (TMP) studies were introduced several years ago. The aims of this project were to assess whether reporting quality of TMP-studies improved in comparison to a previously conducted study assessing reporting quality of TMP-studies (PRE-study) and to assess whether articles citing REMARK (citing group) are better reported, in comparison to articles not citing REMARK (not-citing group). For the POST-study, recent articles citing and not citing REMARK (53 each) were identified in selected journals through systematic literature search and evaluated in same way as in the PRE-study. Ten of the 20 items of the REMARK checklist were evaluated and used to define an overall score of reporting quality. The observed overall scores were 53.4% (range: 10%-90%) for the PRE-study, 57.7% (range: 20%-100%) for the not-citing group and 58.1% (range: 30%-100%) for the citing group of the POST-study. While there is no difference between the two groups of the POST-study, the POST-study shows a slight but not relevant improvement in reporting relative to the PRE-study. Not all the articles of the citing group, cited REMARK appropriately. Irrespective of whether REMARK was cited, the overall score was slightly higher for articles published in journals requesting adherence to REMARK than for those published in journals not requesting it: 59.9% versus 51.9%, respectively. Several years after the introduction of REMARK, many key items of TMP-studies are still very poorly reported. A combined effort is needed from authors, editors, reviewers and methodologists to improve the current situation. Good reporting is not just nice to have but is essential for any research to be useful.
How hard is this query? Measuring the Semantic Complexity of Schema-agnostic Queries

The growing size, heterogeneity and complexity of databases demand the creation of strategies to facilitate users and systems to consume data. Ideally, query mechanisms should be schema-agnostic, i.e. they should be able to match user queries in their own vocabulary and syntax to the data, abstracting data consumers from the representation of the data. This work provides an informationtheoretical framework to evaluate the semantic complexity involved in the query-database communication, under a schema-agnostic query scenario. Different entropy measures are introduced to quantify the semantic phenomena involved in the user-database communication, including structural complexity, ambiguity, synonymy and vagueness. The entropy measures are validated using natural language queries over Semantic Web databases. The analysis of the semantic complexity is used to improve the understanding of the core semantic dimensions present at the query-data matching process, allowing the improvement of the design of schema-agnostic query mechanisms and defining measures which can be used to assess the semantic uncertainty or difficulty behind a schema-agnostic querying task.
The influence of stevia glycosides on the growth of Lactobacillus reuteri strains

Use of stevia‐derived sweeteners was recently officially approved by the European Commission, and their application in the food industry has increased, especially in functional foods. However, there are scarce data about the influence of stevia on probiotic bacteria, which are important both as an inhabitant of the human gut and as a functional food additive. Taking into consideration the broad application of Lactobacillus reuteri in functional foods, the aim of the research was to evaluate the influence of stevia glycosides on its growth. Six Lact. reuteri strains were tested for their ability to grow in the presence of stevioside and rebaudioside A (0·2–2·6 g l−1). The effect of stevia glycosides on biomass concentration, cell count, pH and lactic and acetic acid synthesis was analysed. Both glycosides impaired the growth of analysed strains. However, the inhibitory effect was strain specific, and the concentration‐dependent effect was not observed for all parameters. The most pronounced concentration‐dependent effect was on lactic and acetic acid production. Taking into account the observed strain‐specific inhibitory effect of stevia glycosides, it could be suggested to evaluate the influence of them on each strain employed before their simultaneous application in functional foods.
Unsupervised Machine Learning Application to Perform a Systematic Review and Meta-Analysis in Medical Research

When trying to synthesize information from multiple sources and perform a statistical review to compare them, particularly in the medical research field, several statistical tools are available, most common are the systematic review and the meta-analysis. These techniques allow the comparison of the effectiveness or success among a group of studies. However, a problem of these tools is that if the information to be compared is incomplete or mismatched between two or more studies, the comparison becomes an arduous task. On a parallel line, machine learning methodologies have been proven to be a reliable resource, such software is developed to classify several variables and learn from previous experiences to improve the classification. In this paper, we use unsupervised machine learning methodologies to describe a simple yet effective algorithm that, given a dataset with missing data, completes such data, which leads to a more complete systematic review and meta-analysis, capable of presenting a final effectiveness or success rating between studies. Our method is first validated in a movie ranking database scenario, and then used in a real life systematic review and meta-analysis of obesity prevention scientific papers, where 66.6% of the outcomes are missing.
Wavelet feature based SVM and NAIVE BAYES classification of glaucomatous images using PCA and Gabor filter

The increase in intraocular pressure within the eye causes degradation of optic nerves which results in glaucoma. It is an eye disease in which no early symptoms will be detected until some vision loss has occurred. Therefore diagnosing of glaucoma is very essential to minimize the risk of vision loss. In this paper, the input retinal images are enhanced by using Principal Component Analysis and the blood vessels are removes by Gabor filter, morphological operation and thresholding techniques. Glaucomatous image classification is performed using texture features of an image. The texture features are obtained using 2-D discrete wavelet transform (DWT). The filters used in this paper are symlet3 (sym3) and bi-orthogonal (bio3.3, bio3.5). The extracted features are validated by support vector machine and Naive Bayes classifier. Finally the performance measures of the two classifiers are compared.
Handling samples correlation in the Horus system

We present an autoregressive model for modelling samples autocorrelation from the same access point in WLAN location determination systems. Our work is in the context of the Horus system, which is a probabilistic WLAN location determination system. We show that the autocorrelation between consecutive samples from the same access point can be as high as 0.9. Using our model, we describe a technique to use multiple signal strength samples from each access point, taking the high autocorrelation into account, to achieve better accuracy. Implementation of the technique in the Horus system shows that the average system accuracy is increased by more than 50%. Our results show that assuming independence of samples from the same access point can lead to degraded performance as the number of samples used in the estimation algorithm is increased, due to the wrong independence assumption. We also discuss how to incorporate the new technique with other algorithms for enhancing the performance of WLAN location determination systems.
A Distributed Learning Method for ℓ1-Regularized Kernel Machine over Wireless Sensor Networks

In wireless sensor networks, centralized learning methods have very high communication costs and energy consumption. These are caused by the need to transmit scattered training examples from various sensor nodes to the central fusion center where a classifier or a regression machine is trained. To reduce the communication cost, a distributed learning method for a kernel machine that incorporates ℓ1 norm regularization (ℓ1-regularized) is investigated, and a novel distributed learning algorithm for the ℓ1-regularized kernel minimum mean squared error (KMSE) machine is proposed. The proposed algorithm relies on in-network processing and a collaboration that transmits the sparse model only between single-hop neighboring nodes. This paper evaluates the proposed algorithm with respect to the prediction accuracy, the sparse rate of model, the communication cost and the number of iterations on synthetic and real datasets. The simulation results show that the proposed algorithm can obtain approximately the same prediction accuracy as that obtained by the batch learning method. Moreover, it is significantly superior in terms of the sparse rate of model and communication cost, and it can converge with fewer iterations. Finally, an experiment conducted on a wireless sensor network (WSN) test platform further shows the advantages of the proposed algorithm with respect to communication cost.
Effects of cognitive demands on postmovement motor cortical deactivation

Postmovement &bgr;-rebounds induced by different intermovement intervals were investigated using magnetoencephalography in 14 healthy participants to test the hypothesis that postmovement motor cortical deactivation over the primary motor cortex depends on movement-related cognitive demands. Shorter latency and lower amplitude in postmovement &bgr;-rebounds over the contralateral primary motor cortex were noted in the short-movement interval movement (repetitive finger lifting). Greater latency span of postmovement &bgr;-rebounds jittering using single-trial analysis in the long-movement interval movement (discrete finger lifting) was observed. The study elucidates that the temporal interval between two adjacent movements reflecting different degrees of cognitive demands can affect postmovement motor cortical deactivation in terms of postmovement &bgr;-rebounds latency and amplitude, and latency span of postmovement &bgr;-rebounds jittering. Postmovement motor cortical deactivation can reflect cognitive demands in addition to motor and somatosensory processing.
SCY-635, a Novel Nonimmunosuppressive Analog of Cyclosporine That Exhibits Potent Inhibition of Hepatitis C Virus RNA Replication In Vitro

ABSTRACT SCY-635 is a novel nonimmunosuppressive cyclosporine-based analog that exhibits potent suppression of hepatitis C virus (HCV) replication in vitro. SCY-635 inhibited the peptidyl prolyl isomerase activity of cyclophilin A at nanomolar concentrations but showed no detectable inhibition of calcineurin phosphatase activity at concentrations up to 2 μM. Metabolic studies indicated that SCY-635 did not induce the major cytochrome P450 enzymes 1A2, 2B6, and 3A4. SCY-635 was a weak inhibitor and a poor substrate for P-glycoprotein. Functional assays with stimulated Jurkat cells and stimulated human peripheral blood mononuclear cells indicated that SCY-635 is a weaker inhibitor of interleukin-2 secretion than cyclosporine. A series of two-drug combination studies was performed in vitro. SCY-635 exhibited synergistic antiviral activity with alpha interferon 2b and additive antiviral activity with ribavirin. SCY-635 was shown to be orally bioavailable in multiple animal species and produced blood and liver concentrations of parent drug that exceeded the 50% effective dose determined in the bicistronic con1b-derived replicon assay. These results suggest that SCY-635 warrants further investigation as a novel therapeutic agent for the treatment of individuals who are chronically infected with HCV.
Decreased 1,25-Dihydroxyvitamin D3 level is involved in the pathogenesis of Vogt-Koyanagi-Harada (VKH) disease

Purpose 1,25-Dihydroxyvitamin D3 [1,25(OH)2D3] has recently been found to be involved in the development of autoimmune diseases. This study was to investigate the expression and potential role of 1,25(OH)2D3 in the pathogenesis of Vogt-Koyanagi-Harada (VKH) disease. Methods Blood samples were obtained from VKH patients and healthy individuals. Serum 1,25(OH)2D3 levels were measured using ELISA. Peripheral blood mononuclear cells (PBMCs) or cluster of differentiation (CD) 4+ T cells were cultured with or without 1,25(OH)2D3 in the presence of anti-CD3 and anti-CD28 for the measurement of cell proliferation and cytokines. The cell proliferation was detected using the Cell Counting Kit. The levels of interleukin (IL)-17 and interferon (IFN)-γ levels in the supernatants of PBMCs or CD4+ T cells were detected by ELISA. Results 1,25(OH)2D3 was significantly decreased in the serum of active VKH patients as compared with inactive VKH patients and controls. It significantly inhibited PBMCs proliferation and CD4+ T cell proliferation. It was also able to significantly inhibit the production of IL-17 and IFN-γ by both PBMCs and CD4+ T cells from VKH patients and controls. Conclusions These findings suggest that decreased expression of 1,25(OH)2D3 may be involved in the development of VKH disease. 1,25(OH)2D3 may be potentially used in the treatment of this disease.
Community pharmacy-based implementation and evaluation of an osteoporosis self-assessment tool for Asians.

OBJECTIVES To implement an osteoporosis screening and referral program in community pharmacies and evaluate the use of the Osteoporosis Self-Assessment Tool for Asians (OSTA) as the screening instrument. DESIGN Uncontrolled study. SETTING Three community pharmacies in Bangkok, Thailand. PATIENTS 51 women aged 50 years or older without prior diagnosis of osteoporosis; three community pharmacists; six hospital-based physicians. INTERVENTION OSTA assessment by community pharmacists of the risks of osteoporosis in patients; counseling of patients about diet and exercise; referral of patients at high risk (OSTA index value less than -4) to hospitals where pharmacists had made arrangements in advance; and assessment of satisfaction and opinions of participating patients and physicians. RESULTS Of the 51 patients, 32 (62.7%) were categorized as low risk (OSTA index value > -1) and 19 (37.3%) as intermediate risk (OSTA index value range, -4 to -1). The majority of patients (97%) were satisfied with the program and the knowledge gained. Even though no high-risk patients were identified and referred for medical care, all six participating physicians agreed with having risk assessment service in community pharmacies and the prearranged referral system, and five of six physicians believed that OSTA results were valuable in the management of osteoporosis. CONCLUSION Community pharmacy-based osteoporosis risk assessment services using OSTA were well accepted by the patients and participating physicians. Public health benefits may result from the provision of osteoporosis risk screening services in community pharmacies in Thailand and other Asian countries.