Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanism of focal cerebral ischemic tolerance in rats with ischemic preconditioning involves MyD88- and TRIF-dependent pathways

The aim of this study was to explore the involvement of Toll-like receptor 4 (TLR4) and the downstream myeloid differentiation factor 88 (MyD88)-dependent and -independent pathways in the mechanisms of cerebral ischemic tolerance. Using an improved middle cerebral artery occlusion method, we constructed a preconditioned ischemic brain model in rats. Sham and ischemia-reperfusion groups were also established. The expression levels of proteins in the MyD88/nuclear factor-κB (NF-κB) pathway (MyD88-dependent) were compared with those in the Toll/interleukin-1 receptor-domain-containing adaptor-inducing interferon-β (TRIF)/interferon regulatory factor-3 (IRF-3) pathway (MyD88-independent) by western blot analysis. NF-κB and IRF-3 protein expression levels within cells were determined by immunofluorescence staining of frozen tissue sections. Western blot analysis showed a downregulation of MyD88 protein expression in the brain tissue of ischemic preconditioned rats; however, NF-κB, TRIF and IRF-3 protein expression levels were upregulated. Immunofluorescence staining showed that NF-κB protein was mainly located in the cytoplasm in ischemic preconditioned rats and IRF-3 was predominantly located in the nucleus. The results indicate that changes in the two TLR4 downstream pathways are the main mechanisms involved in the development of brain ischemic tolerance with ischemic pretreatment.
Detecting changes in information diffusion patterns over social networks

We addressed the problem of detecting the change in behavior of information diffusion over a social network which is caused by an unknown external situation change using a small amount of observation data in a retrospective setting. The unknown change is assumed effectively reflected in changes in the parameter values in the probabilistic information diffusion model, and the problem is reduced to detecting where in time and how long this change persisted and how big this change is. We solved this problem by searching the change pattern that maximizes the likelihood of generating the observed information diffusion sequences, and in doing so we devised a very efficient general iterative search algorithm using the derivative of the likelihood which avoids parameter value optimization during each search step. This is in contrast to the naive learning algorithm in that it has to iteratively update the patten boundaries, each requiring the parameter value optimization and thus is very inefficient. We tested this algorithm for two instances of the probabilistic information diffusion model which has different characteristics. One is of information push style and the other is of information pull style. We chose Asynchronous Independent Cascade (AsIC) model as the former and Value-weighted Voter (VwV) model as the latter. The AsIC is the model for general information diffusion with binary states and the parameter to detect its change is diffusion probability and the VwV is the model for opinion formation with multiple states and the parameter to detect its change is opinion value. The results tested on these two models using four real-world network structures confirm that the algorithm is robust enough and can efficiently identify the correct change pattern of the parameter values. Comparison with the naive method that finds the best combination of change boundaries by an exhaustive search through a set of randomly selected boundary candidates shows that the proposed algorithm far outperforms the native method both in terms of accuracy and computation time.
Learning analytics in higher education --- challenges and policies: a review of eight learning analytics policies

This paper presents the results of a review of eight policies for learning analytics of relevance for higher education, and discusses how these policies have tried to address prominent challenges in the adoption of learning analytics, as identified in the literature. The results show that more considerations need to be given to establishing communication channels among stakeholders and adopting pedagogy-based approaches to learning analytics. It also reveals the shortage of guidance for developing data literacy among end-users and evaluating the progress and impact of learning analytics. Moreover, the review highlights the need to establish formalised guidelines to monitor the soundness, effectiveness, and legitimacy of learning analytics. As interest in learning analytics among higher education institutions continues to grow, this review will provide insights into policy and strategic planning for the adoption of learning analytics.
A Natural Fiber Complex Reduces Body Weight in the Overweight and Obese: A Double-Blind, Randomized, Placebo-Controlled Study

A proprietary natural fiber complex (Litramine IQP G‐002AS) derived from Opuntia ficus‐indica, and standardized on lipophilic activity, was previously shown in preclinical and human studies to reduce dietary fat absorption through gastrointestinal (GI) fat binding. Here, we investigated the efficacy and safety of IQP G‐002AS in body weight reduction.
Experiments on in-channel swimming of an untethered biomimetic robot with different helical tails

Experiments are carried out with a cm-scale bio-mimetic swimming robot, which consists of a body and a rigid helical tail and mimics typical eukaryotic micro organisms, inside circular channels filled with viscous fluids. The body of the robot is made of a cylindrical capsule, which includes an onboard power supply, a dedicated DC-motor, and a driving circuitry with IR-receiver for remote control purposes. In experiments geometric parameters of the helical tail, wavelength and amplitude, and the diameter of the circular channels are varied to understand the effect of those parameters on the swimming speed of the robots. Models, based on slender body theory (SBT) and resistive force theory (RFT), are implemented to predict the swimming speeds, which are then compared with experimentally measured values. A simple model for the DC-motor dynamics is included to account for the contact friction effects on the body rotation rates. Model results agree reasonably well with experimental measurements.
Influence of gender and mode of study on examination anxiety among university undergraduates of Ogun State

Tests and examinations at all stages of education, especially at higher education level have been considered an important and powerful tool for decision making in competitive society, with people of all ages being evaluated with respect to their achievement, skills and abilities. The purpose of this study was to investigate the influence of gender and mode of study on examination anxiety among university undergraduates of Ogun State, Nigeria. Descriptive research design of ex-post-facto type was used in the study. One hundred and forty-nine (149) respondents were selected randomly from Olabisi Onabanjo University, Ogun State, Nigeria. The respondents were measured with adapted validated instruments and the data obtained was analyzed using t-test and multiple regression statistical analysis. Three (3) research questions were raised and answered in the study. The result showed that there was significant difference in theexamination anxiety of male and female undergraduate students with male students having higher examination anxiety than their female counterpart, the independent when pulled together have significant effect on examination anxiety of undergraduate students with 58.2% of the variance was accounted for by the predictor variables when taken together and each of the independent variables made a significant contribution to the prediction of examination anxiety of undergraduate students. In term of magnitude of contribution, gender made the most significant contribution to the prediction follow by study mode. In view of these findings, the study recommended that counselling psychologists should intensify their effort in organizing workshops for educational stakeholders on the implications of mode of study and gender on examination anxiety of students in the school and that students should be enlightened on the need to improve their study mode so as to reduce the examination anxiety as proved in the study.
Conjugation-A Bacterially InspiredForm of Genetic RecombinationDr

Bacterial Conjugation is a process that involves the uni-directional transfer of genetic information by direct cellular contact from a donor bacterial cell to a recipient bacterial cell. This paper describes a genetic recombination operator inspired by bacterial conjugation. Three forms of conjugation are described: a simulation of the direct cellular contact using a matrix of forms that exchange genetic material when adjacent in the matrix. Secondly, the simple conjugation operator is described and nally a method of recombination based on tournament selection is introduced.
On the symmetric capacity of the K-user symmetric cyclic Gaussian interference channel

The capacity region of Gaussian interference channel in the weak interference regime is an open problem. Recently, Etkin, Tse and Wang derived an outer bound for the two-user Gaussian interference channel and proved that a simple Han-Kobayashi signaling scheme can achieve within one bit of the capacity region for all values of channel parameters. In this paper, we extend their result to the K-user symmetric cyclic Gaussian interference channel. Our result shows that both the Etkin, Tse and Wang's upper bound and their one-bit achievability result on the symmetric rate continue to hold for the symmetric rate of the K-user symmetric cyclic channel using the same Han-Kobayashi strategy.
Towards Formal Verification of IEC61499: modelling of Data and Algorithms in NCES

This paper aims to demonstrate the modelling details of IEC61499 basic function blocks by means of net condition event systems (NCES). In particular, the paper discusses modelling of basic data types, Boolean algebra and arithmetic operations of unsigned integer, and of simple algorithms in basic function block. The behaviour of the modelled IEC61499 systems can be verified by using model checking tools such as iMATCh and SESA.
Improved Cluster Head Selection for Efficient Data Aggregation in Sensor Networks

Large-scale Wireless Sensor Networks (WSN) is the focus of recent research and development efforts. Due to their benefits in monitoring physical environments, WSN find diverse applications from military usage to agriculture and scientific works. To maximize WSN's network life, data transfer paths are selected so that total energy consumed on the path is minimal. To ensure high scalability and improved data aggregation, sensor nodes are grouped into disjoint, non-overlapping subsets known as clusters. This study proposes improved Cluster Head (CH) selection for efficient sensor networks' data aggregation. The suggested hybrid algorithm is based on Bacterial Foraging Optimization (BFO) and Gravitational Search Algorithm (GSA). The proposed hybrid BFO is incorporated in Lower Energy Adaptive Clustering Hierarchy (LEACH).
Using the Driver Behaviour Questionnaire to predict crashes and demerit point loss: Does it get better with larger sample sizes?

The Driver Behaviour Questionnaire (DBQ) continues to be the most widely utilised self-report scale globally to assess crash risk and aberrant driving behaviours among motorists. However, the scale also attracts criticism regarding its perceived limited ability to accurately identify those most at risk of crash involvement. This study reports on the utilisation of the DBQ to examine the self-reported driving behaviours (and crash outcomes) of drivers in three separate Australian fleet samples (N = 443, N = 3414, & N = 4792), and whether combining the samples increases the toolrs predictive ability. Either on-line or paper versions of the questionnaire were completed by fleet employees in three organisations. Factor analytic techniques identified either three or four factor solutions (in each of the separate studies) and the combined sample produced expected factors of: (a) errors, (b) highway-code violations and (c) aggressive driving violations. Highway code violations (and mean scores) were comparable across the studies. However, across the three samples, multivariate analyses revealed that exposure to the road was the best predictor of crash involvement at work, rather than DBQ constructs. Furthermore, combining the scores to produce a sample of 8649 drivers did not improve the predictive ability of the tool for identifying crashes (e.g., 0.4% correctly identified) or for demerit point loss (0.3%). The paper outlines the major findings of this comparative sample study in regards to utilising self-report measurement tools to identify lat riskr drivers as well as the application of such data to future research endeavours.
Computational cardiac anatomy using MRI

Ventricular geometry and fiber orientation may undergo global or local remodeling in cardiac disease. However, there are as yet no mathematical and computational methods for quantifying variation of geometry and fiber orientation or the nature of their remodeling in disease. Toward this goal, a landmark and image intensity‐based large deformation diffeomorphic metric mapping (LDDMM) method to transform heart geometry into common coordinates for quantification of shape and form was developed. Two automated landmark placement methods for modeling tissue deformations expected in different cardiac pathologies are presented. The transformations, computed using the combined use of landmarks and image intensities, yields high‐registration accuracy of heart anatomies even in the presence of significant variation of cardiac shape and form. Once heart anatomies have been registered, properties of tissue geometry and cardiac fiber orientation in corresponding regions of different hearts may be quantified. Magn Reson Med 52:1167–1174, 2004. Published 2004 Wiley‐Liss, Inc.
Prevalence of occult hepatitis B virus infection in hemodialysis patients in Isfahan, Iran

Background: The absence of a detectable hepatitis B surface antigen (HBsAg) with or without hepatitis B core antibody (anti-HBc) or hepatitis B surface antibody (anti-HBs) in the presence of hepatitis B virus-DNA (HBV-DNA) is defined as occult HBV infection. This study was aimed to evaluate the prevalence of occult HBV infection in patients receiving hemodialysis (HD) in Isfahan, Iran. Materials and Methods: This cross sectional study was done on 400 patients without acute or chronic HBV infection with end-stage renal disease undergoing regular HD. Blood samples were collected prior to the HD session, and serological markers of viral hepatitis B included HBsAg, anti-HBs and anti-HBc were measured using standard third generation commercially avail-able enzyme immunoassays kit, then samples of positive anti-HBc and negative anti-HBs were tested for HBV DNA using quantitative real-time polymerase chain reaction techniques. Data were analyzed by SPSS using t-test and Chi-square test. Results: The mean age of patients was 51.6 ± 11.2 years. Anti-HBc positive was observed in 32 (8%) of 400 studied patients with negative HBsAg. Of 32 patients with anti-HBc positive, 15 were males and 17 were females with mean age of 49.7 ± 12.6 years. Among 32 patients with anti-HBc positive, 10 patients were negative for anti-HBs. All of 10 patients were negative for HBV DNA. The prevalence of occult HBV infection was 0%. Conclusions: The prevalence of occult HBV infection in HBsAg negative patients undergoing HD was 0% and look to be among the lowest worldwide. So, occult HBV infection is not a significant health problem in HD patients in this region.
On the Impact of Time Synchronization on Quality of Information and Network Performance

Time synchronization in wireless sensor networks consumes both limited battery power and bandwidth on the network nodes. We quantify the effect of time synchronization accuracy upon the performance of real time estimation and detection problems. We also quantify the costs and benefits of time synchronization algorithms. We show that the intuitive assumption that using higher stability clocks will automatically improve duty cycling performance, and thus decrease power consumption, does not always hold true. For reasons of space restrictions, we only present summaries of the analyses that show the impact of timing errors for different event durations, target speeds, number of sensors, and sampling frequencies. The analysis framework can also be used to estimate the maximum synchronization error each application can sustain while still achieving the desired Quality of Information (QoI).
Patient monitoring in health care working with robotic assistants

The main objective of this work is to develop a robots' fleet working together to make assistance tasks in a hospital or at home in a collaborative way. This paper presents a method to detect, recognize and track people using mount cameras fixed on a building and an algorithm for collaborative mobile robot localization based on probabilistic methods (Monte Carlo localization). The performance of this system has been tested successfully. Some experimental results and conclusions are presented.
Interest Premium, Sudden Stop, and Adjustment in a Small Open Economy

This article studies the adjustment process of a small open economy to a sudden worsening of external conditions. The sudden stop is modeled by the use of a highly nonlinear specification that captures credit constraints in a convenient way. The advantage of this approach is that the effects of the shock become highly conditional on the external debt position of the economy. A two-sector model with money-in-the-utility is adopted, thereby making it possible to study sectoral asymmetries in the adjustment process, and also the role of currency mismatch. The model is calibrated to the behavior of the Hungarian economy in the 2000s, and its crisis experience in 2008–11 in particular. Four counterfactuals are calculated: two with different exchange rate policies (a more flexible float and a perfect peg), and both of these policy regimes with smaller initial indebtedness. Overall, the model is able to fit the movements of key aggregate and sectoral macroeconomic variables after the crisis by producing a large and protracted deleveraging process. It also offers a meaningful quantification of the policy tradeoff between facilitating the real adjustment by letting the currency depreciate and protecting consumption expenditures by limiting the adverse effect of exchange rate movements on household balance sheets.
AN EXACT PENALTY ALGORITHM FOR NONLINEAR EQUALITY CONSTRAINED OPTIMIZATION PROBLEMS

In this paper we define a trust-region globalization strategies to solve a continuously differentiable nonlinear equality constrained minimization problem. The trust-region approach uses a penalty parameter that is proven to be uniformly bounded. Under rather weak hypotheses and without the usual regularity assumption that the linearized constraints gradients are linearly independent, we prove that the hybrid algorithm is globally convergent Moreover, under the standard hypotheses of the SQP method, we prove that the rate of convergence is q-quadratic.
The Behavioral and Evolutionary Roots of Dynamic Capabilities

Work on dynamic capabilities is proving to be a fruitful direction in understanding the nature of the firm. Despite its popularity, some scholars have attacked the dynamic capability theory as lacking theoretical underpinnings. In this study, we clarify the origins of the dynamics of the dynamic capabilities framework. Standard operating procedures, routines and the concept of routinization are important elements of understanding the contribution of ordinary capabilities and dynamic capabilities within this stream of literature. Based on the insights of the non-strategic model of Cyert and March, through the dynamic evolutionary theory of the firm in Nelson and Winter, then through the efforts by Teece, Pisano and Shuen (1997) and Teece (2007, 2014), dynamic capabilities have evolved into a dominant theory of the field of strategic management. We provide a brief overview of key topics and empirical research, along with some ideas for future research.
Perceptual Texture Space Improves Perceptual Consistency of Computational Features

Perceptual consistency is important in many computer vision applications. Unfortunately, except for color, computational features and similarity measurements for other visual features are not necessarily consistent with human's perception. This paper addresses three critical issues regarding perceptually consistent texture analysis: (1) development of perceptual texture space, (2) assessment of how consistent computational features are to human perception, and (3) mapping computational features to perceptual space. It demonstrates the construction of a reliable perceptual texture space, which can be used as a yardstick for assessing the perceptual consistency of computational features and similarity measurements. Moreover, it is found that commonly used computational texture features are not very consistent with human perception, and mapping them to the perceptual space improves their perceptual consistency.
Analysis of tumor template from multiple compartments in a blood sample provides complementary access to peripheral tumor biomarkers

Targeted cancer therapeutics are promised to have a major impact on cancer treatment and survival. Successful application of these novel treatments requires a molecular definition of a patient's disease typically achieved through the use of tissue biopsies. Alternatively, allowing longitudinal monitoring, biomarkers derived from blood, isolated either from circulating tumor cell derived DNA (ctcDNA) or circulating cell-free tumor DNA (ccfDNA) may be evaluated. In order to use blood derived templates for mutational profiling in clinical decisions, it is essential to understand the different template qualities and how they compare to biopsy derived template DNA as both blood-based templates are rare and distinct from the gold-standard. Using a next generation re-sequencing strategy, concordance of the mutational spectrum was evaluated in 32 patient-matched ctcDNA and ccfDNA templates with comparison to tissue biopsy derived DNA template. Different CTC antibody capture systems for DNA isolation from patient blood samples were also compared. Significant overlap was observed between ctcDNA, ccfDNA and tissue derived templates. Interestingly, if the results of ctcDNA and ccfDNA template sequencing were combined, productive samples showed similar detection frequency (56% vs 58%), were temporally flexible, and were complementary both to each other and the gold standard. These observations justify the use of a multiple template approach to the liquid biopsy, where germline, ctcDNA, and ccfDNA templates are employed for clinical diagnostic purposes and open a path to comprehensive blood derived biomarker access.
A scenario-driven role engineering process for functional RBAC roles

In this paper we present a novel scenario-driven role engineering process for RBAC roles. The scenario concept is of central significance for the presented approach. Due to the strong human factor in role engineering scenarios are a good means to drive the process. We use scenarios to derive permissions and to define tasks. Our approach considers changeability issues and enables the straightforward incorporation of changes into affected models. Finally we discuss the experiences we gained by applying the scenario-driven role engineering process in three case studies.