Miracle-dz/UniFAR-FTUs huggingface dataset:
Suppression of Inflammation and Arthritis by Orally Administrated Cardiotoxin from Naja naja atra

Cardiotoxin (CTX) from Naja naja atra venom (NNAV) reportedly had analgesic effect in animal models but its role in inflammation and arthritis was unknown. In this study, we investigated the analgesic, anti-inflammatory, and antiarthritic actions of orally administered CTX-IV isolated from NNAV on rodent models of inflammation and adjuvant arthritis. CTX had significant anti-inflammatory effects in models of egg white induced nonspecific inflammation, filter paper induced rat granuloma formation, and capillary osmosis tests. CTX significantly reduced the swelling of paw induced by egg white, the inflammatory exudation, and the formation of granulomas. CTX reduced the swelling of paw, the AA clinical scores, and pathological alterations of joint. CTX significantly decreased the number of the CD4 T cells and inhibited the expression of relevant proinflammatory cytokines IL-17 and IL-6. CTX significantly inhibited the secretion of proinflammatory cytokine IL-6 and reduced the level of p-STAT3 in FLS. These results suggest that CTX inhibits inflammation and inflammatory pain and adjuvant-induced arthritis. CTX may be a novel therapeutic drug for treatment of arthritis.
Model selection to enhance prediction performance in the presence of missing data

Most nonlinear modelling approaches focus on solving a model selection problem with complete data, and in many cases original data are pre-processed with some nonlinear transforms such as Box-Tidwell and fractional polynomial transformation. Often these approaches can lead to models that are better than traditional models (for example, logistic model and quadratic model). However, in the case of missing data, it is not easy to predict the relationship between the predictor and dependent variables; traditional nonlinear models in some cases of missing data analysis give poor results. This paper explains nonlinear model selection techniques for missing data. It includes an overview of nonlinear model selection with complete data, and provides accessible descriptions of Box-Tidwell and fractional polynomial methods for model selection. In particular, this paper focuses on a fractional polynomial method for nonlinear modelling in cases of missing data and presents analysis examples to illustrate performance of the method.
Enhancement of bioactivity of titanium carbonitride nanocomposite thin films on steels with biosynthesized hydroxyapatite

Thin films of titanium carbonitride (TiCN) were fabricated by DC magnetron sputtering on medical grade steel. The biocompatibility of the coating was further enhanced by growing hydroxyapatite crystals over the TiCN-coated substrates using biologically activated ammonia from synthetic urine. The coatings were characterized using X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy (SEM)-energy dispersive spectroscopy, and Raman spectroscopy. The electrochemical behavior of the coatings was determined in simulated body fluid. In addition, hemocompatibility was assessed by monitoring the attachment of platelets on the coating using SEM. The wettability of the coatings was measured in order to correlate with biocompatibility results. Formation of a coating with granular morphology and the preferred orientation was confirmed by SEM and X-ray diffraction results. The hydroxyapatite coating led to a decrease in thrombogenicity, resulting in controlled blood clot formation, hence demonstrating the hemocompatibility of the coating.
Robust localization of furniture parts by integrating depth and intensity data suitable for range sensors with varying image quality

In this paper we present an approach to localize planar furniture parts in 3D range camera data for autonomous robot manipulation, that estimates both their six degree of freedom (DoF) poses and their dimensions. Range cameras are a promising sensor category for mobile robotics. Unfortunately, many of them come with a considerable measurement noise, that leads to difficulties when trying to detect objects or their parts e.g. using canonical methods for range image segmentation. In contrast, our approach is able to overcome these issues by combining concepts of 2D and 3D computer vision as well as integrating intensity and depth data on several levels of abstraction. Therefore it is not restricted to range sensors with high image quality and scales on cameras with lower image quality, too. This concept is generic and has been implemented for elliptical object parts as a proof of concept.
Background subtraction based on a combination of texture, color and intensity

A new background subtraction algorithm based on a combination of texture, color and intensity information is presented. The texture is depicted by DLBP, a modified version of LBP, color is a local template in HS color space and intensity the pixel intensity value. The approach works robustly both on rich texture areas and uniform areas even with noise and can deal with weak cast shadows effectively. The comparative experiments show that the overall performance of our method is better than other methods in most scenes.
Definitions of bloodstream infection in the newborn

Objective: To develop definitions of bloodstream infections in the newborn that would enable clinicians to identify infection early, so patients can be enrolled in clinical trials. The definitions should be useful for surveillance and epidemiologic purposes. Method: Search of EMBASE, MEDLINE, and Cochrane Library using age and English language limited key words sepsis, septicemia, and shock. Extensive study of textbook of neonatology and discussions with experts in the field. Results: The search identified >2,000 references. The most appropriate were selected and reviewed. Definitions of bloodstream infection were developed after consultation with an international faculty. Conclusion: Current definitions of neonatal infection (and associated categories) used by neonatal clinicians and researchers have been either adapted/modified from definitions developed for adults or generated by individuals to suit their local needs or the needs of a particular study. It is clear that definitions generated for adults are not applicable to children or to newborn infants. In addition, developing and using unique definitions to suit individual or local needs make comparisons of outcome data and result of studies very difficult. This article proposes a set of definitions that are based as much as possible on current evidence. These definitions may be applicable widely for daily management of an infant with an infection and for research and epidemiologic studies.
The Growth of Government Expenditure: A Review of Quantitative Analysis

This paper reviews the extensive empirical literature on the growth and determinants of government expenditure. Although the coverage does not aim to be exhaustive, the authors provide an overview of the quantitative approaches to analyzing the growth in government expenditure. The main debates in the literature are described, and the authors present a few tests of some theories and describe one or two of their own experiments in others. The paper highlights the data problems and the technical difficulties of hypothesis testing and model estimation in this area, many arising from the nature of the problem studied. It is contended that the quantitative analysis of government expenditure growth has often improved the formulation of hypotheses, but that data and theoretical limitations have meant that the methods employed have not always been justified.
Dual Band Edge Serrated Microstrip Antenna on FR 4 Substrate for L & S Band Applications

With the advancements in optical and satellite communications for high speed long range data transmissions, serrated antennas plays a vital role. In this work we have designed a Edge Serrated Microstrip Patch antenna used for these applications has been modeled on FR4 substrate as a dielectric medium which has a relative permittivity value of 4.4. The proposed antenna was resonating at two different frequencies in L & S band Microwave frequency ranges. This antenna was fed with coaxial feeding and was designed in a software HFSS.
A novel Matching Pursuit algorithm with adaptive subdictionary

Sparse decomposition of a signal can be obtained by decomposing the signal in an over complete dictionary. Matching Pursuit (MP) is a greedy algorithm to realize such decompositions, and has been widely studied in many signal processing researches. Through exploiting the structure shared by these so-called adaptive decomposition dictionaries, we propose a novel MP algorithm which can reduce computation and storage requirement dramatically.
Web services choreography and orchestration in Reo and constraint automata

Currently web services constitute one of the most important topics in the realm of the World Wide Web. Composition of web services lets developers create applications on top of service-oriented computing platforms. Current web services choreography and orchestration proposals, such as BPELAWS, WSCDL, and WSCI, provide notations for describing the message flows in web service interactions. However, such proposals remain at the description level, without providing any kind of formal reasoning mechanisms or tool support for checking the compatibility of web services based on the proposed notations. In this paper, we present our work on compositional construction of web services using the Reo coordination language and constraint automata. Reo is an exogenous coordinational language based on channels. We investigate the possibility of representing the behaviour of web services using constraint automata as black-box components within Reo circuits. We describe the orchestration of web services by the product of corresponding constraint automata, and use Reo circuits for choreography of web services. We investigate the issues of description, orchestration, and choreography of web services at a unifying abstract level, based on constraint automata, which have been used as the semantics of the coordination language Reo, allowing us to derive a natural correspondence relationship between orchestration and choreography.
A novel approach to improve background subtraction method for fall detection system

The fall detection system composed in general from three models, the first is a detection moving object, the second is tracking moving object and the third is recognition person's behavior. In this paper, we will deal out the first module which is the main unit in the fall detection system, because it is where we detect the person in the image. There are a lot of approaches in this way, but their results are not perfect due to the change of the background model. Many works propose to improve those results, but these approaches are not satisfied in some states. In this way, we propose a novel approach by using the optical flow which can improve The result to extract the foreground human body without errors.
Bank Reputation in Australia: A View from the Inside

This paper investigates management perceptions of bank reputational problems. Interviews with senior bank officials identified several factors that were recognised as impacting negatively on bank reputation; including profits, fees and charges, executive salaries and reactions to changes in monetary policy. Together with media and political commentary these have contributed to the poor public view of banks and increased reputational risk, which can only be mitigated by improving the bank/customer relationship. Measures to increase customer satisfaction ratings, such as fee reductions, improved environmental and social responsibility performance along with community engagement have been employed within the banking industry and have been successful in realigning community expectations.
Hybrid forecasting model research on stock data mining

The synergy effect's benefit is widely accepted. The object of this paper is to investigate whether a hybrid approach combining different stock prediction approaches together can dramatically outperform the single approach and compare the performance of different hybrid approaches. The hybrid model includes three well-researched algorithms: back propagation neural network (BPNN), adaptive network-based fuzzy neural inference system (ANFIS) and support vector machine (SVM). First, we utilize them independently to single-step forecast the stock price, and then integrate the three forecasts into a final result by a combining strategy. Two different combining methods are investigated. The first method is a linear combination of the three forecasts. The second method combines them by a neural network. We have all of the algorithms experiment on the S&P500 Index. The experiment verifies that by combining the single algorithm appropriately, better performance can be achieved.
Occurrence and genetic characterization of Toxoplasma gondii in naturally infected pigs

The protozoan Toxoplasma gondii is an obligate intracellular parasite that infects a wide range of warm-blooded vertebrates. The data about the occurrence of toxoplasmosis in slaughter pigs in the Slovak Republic are still missing. The aim of our study was to estimate the prevalence of toxoplasmosis in pigs from Slovakia during the period of 2006–2010 by ELISA and PCR methods. In sera of 970 slaughter pigs, 2.16% seropositivity to T. gondii was detected. In tissue samples of seropositive pigs the presence of T. gondii DNA was confirmed. In six monitored Slovak regions the seropositivity varied between 1.11 and 3.48%. The statistically significant differences were recorded between the Košice and Prešov region. The seroprevalence of toxoplasmosis in sows (4.26%) was two times higher than that in slaughter pigs (2.06%) (OR = 2.12; 95% CI = 0.48–9.36). Presence of Toxoplasma gondii in tissues of seropositive pig isolates was confirmed by TGR1E and B1 genes and analysis of DNA polymorphism at SAG2 and ROP1 genes revealed the presence of virulent strain of genotype I in 85.7% of infected pigs and an avirulent strain (genotype II) in 14.3% of pigs.
Temporal Partitioning on Multicore Platform

This paper addresses the problem of ensuring temporal partitioning according to the ARINC-653 standard for integrating multiple applications on the same multicore platform. To employ temporal partitioning, we propose the design and analysis of a hierarchical scheduling framework (HSF) for multicore platform. In HSF, each application has a server task, which is mapped to one of the physical cores of the multicore platform. The HSF framework is based on scheduling at two-levels: (i) a system-level scheduler for each core schedules the server tasks that are mapped to that core, and (ii) a task-level scheduler for each application schedules the tasks of the application. This paper presents the design and analysis of this two-level HSF that can be used to ensure temporal partitioning and meeting all the deadlines of each application tasks. The effectiveness of our technique is demonstrated using real-world space applications provided by RUAG Space Sweden AB.
Keratinized Gingiva Determines a Homeostatic Behavior of Gingival Sulcus through Transudation of Gingival Crevice Fluid

Objective. To shed light on the role of KG, its influence on periodontal behavior was investigated. Methods. Tissue fluid transudation was assessed in alveolar mucosa (P1A), outer gingival margin (P1B), at entrance of (P2) and within gingival sulcus (P3), before and after chewing of fibrous food in 16 patients portraying ≥2 mm KG at one tooth (group 1), and <2 mm at another homologous tooth (group 2). Results. There was a significant increase in GCF after chewing at P1B and P3 in group 1 and at P1A in group 2 (t-test, P < 0.05). Conclusions. The results suggest that KG plays a role in marginal periodontal homeostasis.
Neuroscience and Biobehavioral Reviews Person Recognition and the Brain: Merging Evidence from Patients and Healthy Individuals

Recognizing other persons is a key skill in social interaction, whether it is with our family at home or with our colleagues at work. Due to brain lesions such as stroke, or neurodegenerative disease, or due to psychiatric conditions, abilities in recognizing even personally familiar persons can be impaired. The underlying causes in the human brain have not yet been well understood. Here, we provide a comprehensive overview of studies reporting locations of brain damage in patients impaired in person-identity recognition, and relate the results to a quantitative meta-analysis based on functional imaging studies investigating person-identity recognition in healthy individuals. We identify modality-specific brain areas involved in recognition from different person characteristics, and potential multimodal hubs for person processing in the anterior temporal, frontal, and parietal lobes and posterior cingulate. Our combined review is built on cognitive and neuroscientific models of face-and voice-identity recognition and revises them within the multimodal context of person-identity recognition. These results provide a novel framework for future research in person-identity recognition both in the clinical as well as basic neurosciences.
Statically detect invalid pointer dereference vulnerabilities in binary software

The invalid pointer dereference vulnerabilities exist in binary software result from inadequate security check, and these vulnerabilities can be grouped by specific characteristics. In this paper, we have extracted three typical invalid pointer dereference vulnerability patterns from real-world vulnerabilities, and then we put forward a novel method to detect these vulnerabilities for binary software which builds upon pattern-matched static analysis. We also implemented our prototype system and the evaluation results show that our detection method can detect the invalid pointer dereference vulnerabilities that exist in binary software effectively.
Antimicrobial Sensitivity Pattern of Pseudomonas fluorescens after Biofield Treatment

Global emergence of Pseudomonas fluorescens (P. fluorescens) displays a mechanism of resistance to all existing antimicrobials. Due to its strong ability to acquire resistance, there is a need of some alternative treatment strategy. Objective of this study was to investigate the effect of biofield treatment on antimicrobial sensitivity pattern of P. fluorescens. P. fluorescens cells were procured from MicroBioLogics in sealed packs bearing the American Type Culture Collection (ATCC 49838) number. Two sets of ATCC samples were taken in this experiment and denoted as A and B. ATCC-A sample was revived and divided into two groups (Gr) i.e. Gr.I (control) and Gr.II (revived); likewise, ATCC-B was labeled as Gr.III (lyophilized). Gr.II and III were given biofield treatment and were measured by MicroScan Walk-Away® system before and after treatment. Parameters studied in experiment were antimicrobial sensitivity, minimum inhibitory concentration (MIC), biochemical reactions, and biotype number of both control and treatment groups using MicroScan Walk-Away® system. Experimental results showed antimicrobials such as cefepime, cefotaxime, ceftazidime, ceftriaxone, ciprofloxacin, piperacillin, tetracycline, and tobramycin showed altered sensitivity and MIC values in treated group as compared to control. Biochemical reactions showed positive reaction in malonate, melibiose, nitrate, galactosidase, ornithine, raffinose, sorbitol, sucrose, tobramycin and Voges-Proskauer in Gr.II. Arabinose, colistin, glucose, and rhaminose also showed positive reactions in Gr.II on day 10 while arginine and cetrimide showed negative reaction in Gr.III as compared to control. Biochemical tests results revealed a change in biotype number in Gr.II (34101173, day 5), (77103177, a very rare biotype on day 10) and Gr.III (40000043) as compared to control (02041722). Organism was identified as Enterobacter cloacae (GrII, day 10) and Vibrio fluvialis (Gr.III, day 10) with respect to control. These findings suggest that biofield treatment made significant alteration in sensitivity pattern, MIC values, and biotype number of P. fluorescens.
Answer Comparison : Analysis of Relationships between Answers to ‘ Where ’-Questions

For many reasons, Question Answering must deal with questions that have multiple answers. To this end, we have built a framework for answer comparison based on a technique using information fusion that has successfully been applied in automated summarization. The architecture of this system is a direct application of the Model-View-Controller design pattern which allows us to define an answer in terms of content, structure and rendering. We present an experiment using this system on TREC ‘where‘-questions and analyse relationships discovered between potential answers. We show that this approach is robust and a first step towards complex/structred answer generation.
No-show rates to a sleep clinic: drivers and determinants.

STUDY OBJECTIVES Attendance to sleep clinic appointments is imperative to diagnose sleep-related disorders and to offer appropriate treatment. As part of our quality assurance program, we assessed predictors of no-show rates at our sleep clinic. We hypothesize that no-show rates can be predicted by demographics, appointment type (new vs established) and timing, and insurance status. METHODS We performed a 10-month, retrospective chart review of patients scheduled at Saint Louis University's SLUCare Sleep Disorders Center. Multivariable logistic regression was used to determine which factors were independently associated with no-show. RESULTS A total of 2,532 clinical visits were reviewed, and the overall no-show rate was 21.2%. Factors associated with a higher incidence of no-show rates included younger age (17-40 years: 21.5%; 41-64 years: 23.5%; ≥65 years: 14.0%; P < .0001), appointment type (new: 30.5% vs established: 18.3%; P < .0001), and insurance status (no insurance: 24.6% vs public: 22.6% vs private: 15.9%; P < .0001). Multivariable logistic regression confirmed the independent association between no-show and age ≤ 40 years (adjusted odds ratio = 1.72; 95% confidence interval: 1.44, 2.20), new patient status (adjusted odds ratio = 1.78; 95% confidence interval: 1.44, 2.20), and absence of health insurance (adjusted odds ratio = 1.62; 95% confidence interval: 1.24, 2.11). Sex, appointment time, day of the week, and season did not significantly influence no-show rates. CONCLUSIONS Independent predictors of no-show appointments included younger age, new patient status, and lack of health insurance. Our findings will aid future efforts to identify patients with high predictors of nonadherence. Further studies are needed to develop methods to decrease no-show rates once high-risk appointments have been identified.