Miracle-dz/UniFAR-FTUs huggingface dataset:
Coping and Social Support

Coping and social support are among the most widely written about and researched topics in health psychology. Both constructs have been hypothesized as reasons why particular individuals are at increased risk for developing illnesses such as cardiovascular disease and cancer and why some individuals do not adapt well once they develop a disease. More recently, coping and social support have been linked with disease course and survival. In this chapter, I review theories of coping, definitions of social support, evidence supporting the role of coping and social support in health and psychological outcomes, theoretical and methodological challenges to both areas of research, and directions for future research. Keywords: coping; disease progression; disease recovery; illness; psychological adaptation; social support
Pleiotropic Mutations Are Subject to Strong Stabilizing Selection

The assumption that pleiotropic mutations are more deleterious than mutations with more restricted phenotypic effects is an important premise in models of evolution. However, empirical evidence supporting this assumption is limited. Here, we estimated the strength of stabilizing selection on mutations affecting gene expression in male Drosophila serrata. We estimated the mutational variance (VM) and the standing genetic variance (VG) from two well-matched panels of inbred lines: a panel of mutation accumulation (MA) lines derived from a single inbred ancestral line and a panel of inbred lines derived from an outbred population. For 855 gene-expression traits, we estimated the strength of stabilizing selection as s = VM/VG. Selection was observed to be relatively strong, with 17% of traits having s > 0.02, a magnitude typically associated with life-history traits. Randomly assigning expression traits to five-trait sets, we used factor analytic mixed modeling in the MA data set to identify covarying traits that shared pleiotropic mutations. By assigning traits to the same trait sets in the outbred line data set, we then estimated s for the combination of traits affected by pleiotropic mutation. For these pleiotropic combinations, the median s was three times greater than s acting on the individual component traits, and 46% of the pleiotropic trait combinations had s > 0.02. Although our analytical approach was biased toward detecting mutations with relatively large effects, likely overestimating the average strength of selection, our results provide widespread support for the prediction that stronger selection can act against mutations with pleiotropic effects.
The relationship between student's MBTI, preferences and academic performance at a Syrian university

Purpose – The main purpose of this paper is to find whether a correlation exists between students’ natural preferences or what is known as psychological type as determined by the Myers-Briggs Type Indicator (MBTI); the extent of their enthusiasm measured by their level of “like” to the subject, and students’ grade point average (GPA). Design/methodology/approach – Data were collected from 89 students who took the MBTI inventory in five selected faculties at Damascus University in Syria. In order to rate the subjects’ like or dislike level, the students were asked to complete a form prepared for this purpose. The students’ GPAs were also included in the analysis. Findings – Using paired sample t-test, the results indicate a statistically significant correlation between type of student and his/her faculty of study, type of student and overall study subject like, and type of student and his/her GPA. There was, however, a statistically significant correlation between various personality dichotomies of the typ.
AQUA: An Amphibious Autonomous Robot

AQUA, an amphibious robot that swims via the motion of its legs rather than using thrusters and control surfaces for propulsion, can walk along the shore, swim along the surface in open water, or walk on the bottom of the ocean. The vehicle uses a variety of sensors to estimate its position with respect to local visual features and provide a global frame of reference
The Equal Opportunities Handbook: How to Recognise Diversity, Encourage Fairness and Promote Anti-Discriminatory Practice

The Equal Opportunities Handbook is a guide to indentifying and eradicating workplace discrimination through training and guidance. The revised edition of this popular text has been updated to reflect changes in legislation and policy. This up-to-the-minute guide sets out straightforward procedures, relevant to all types of situation, and demonstrates how simple it is to behave with fairness, courtesy and sensitivity to all.
Search, Effort, and Locus of Control

We test the hypothesis that locus of control influences search by affecting beliefs about the efficacy of search effort in a laboratory experiment. Consistent with this hypothesis, we find that reservation wages and effort are increasing in the belief that one's efforts influence outcomes when subjects are not told how search effort affects search outcomes but are unrelated to these locus of control beliefs when subjects know the relationship between effort and search outcomes. This difference in the relationship between locus of control and search behavior across treatments cannot be explained by unmeasured skill or effort costs as the search technology and offer distribution do not vary across treatments. Only the scope for locus of control to influence beliefs differs and can explain the observed difference across treatments.
Surface Integrity Analysis in Machining of Hardened AISI 4140 Steel

This study aimed to analyze the residual stresses and roughness in finishing milling of AISI 4140 steel, quenched and tempered up to hardness of 58 HRC. Machining operations were performed with the use of CBN inserts and by varying three basic cutting parameters (cutting speed, feed per tooth and cutting depth). Hardened materials are typically machined by abrasive processes, which in turn are more expensive and complex to be studied due to the undefined cutting geometry of the grinding wheel. A series of machining tests with milling process and CBN tools was implemented in order to study the resultant condition of the specimen´s surface. An experimental design was used and the results were statistically treated, enabling the generation of a model that aims to obtain roughness values due to the optimization of three adopted cutting parameters. The roughness values found in the range of R
Comparative efficacy of different acute reperfusion therapies for acute ischemic stroke: a comprehensive benefit–risk analysis of clinical trials

Numerous acute reperfusion therapies (RPT) are currently investigated as potential new therapeutic targets in acute ischemic stroke (AIS). We conducted a comprehensive benefit–risk analysis of available clinical studies assessing different acute RPT, and investigated the utility of each intervention in comparison to standard intravenous thrombolysis (IVT) and in relation to the onset‐to‐treatment time (OTT).
Improving Targeting in Image-Guided Frame-Based Deep Brain Stimulation

BACKGROUND: Deep brain stimulation (DBS) is commonly used in the treatment of movement disorders such as Parkinson disease (PD), dystonia, and other tremors. OBJECTIVE: To examine systematic errors in image-guided DBS electrode placement and to explore a calibration strategy for stereotactic targeting. METHODS: Pre- and postoperative stereotactic MR images were analyzed in 165 patients. The perpendicular error between planned target coordinates and electrode trajectory was calculated geometrically for all 312 DBS electrodes implanted. Improvement in motor unified PD rating scale III subscore was calculated for those patients with PD with at least 6 months of follow-up after bilateral subthalamic DBS. RESULTS: Mean (standard deviation) scalar error of all electrodes was 1.4(0.9) mm with a significant difference between left and right hemispheres. Targeting error was significantly higher for electrodes with coronal approach angle (ARC) ≥10° (P < .001). Mean vector error was X: −0.6, Y: −0.7, and Z: −0.4 mm (medial, posterior, and superior directions, respectively). Targeting error was significantly improved by using a systematic calibration strategy based on ARC and target hemisphere (mean: 0.6 mm, P < .001) for 47 electrodes implanted in 24 patients. Retrospective theoretical calibration for all 312 electrodes would have reduced the mean (standard deviation) scalar error from 1.4(0.9) mm to 0.9(0.5) mm (36% improvement). With calibration, 97% of all electrodes would be within 2 mm of the intended target as opposed to 81% before calibration. There was no significant correlation between the degree of error and clinical outcome from bilateral subthalamic nucleus DBS (R2 = 0.07). CONCLUSION: After calibration of a systematic targeting error an MR image-guided stereotactic approach would be expected to deliver 97% of all electrodes to within 2 mm of the intended target point with a single brain pass.
The Algal Meroterpene 11-Hydroxy-1′-O-Methylamentadione Ameloriates Dextran Sulfate Sodium-Induced Colitis in Mice

Inflammatory bowel disease (IBD) is a complex class of immune disorders. Unfortunately, a treatment for total remission has not yet been found, while the use of natural product-based therapies has emerged as a promising intervention. The present study was aimed to investigate the anti-inflammatory effects of the algal meroterpene 11-hydroxy-1′-O-methylamentadione (AMT-E) in a murine model of dextran sodium sulphate (DSS)-induced colitis. AMT-E was orally administered daily (1, 10, and 20 mg/kg animal) to DSS treated mice (3% w/v) for 7 days. AMT-E prevented body weight loss and colon shortening and effectively attenuated the extent of the colonic damage. Similarly, AMT-E increased mucus production and reduced myeloperoxidase activity (marker for anti-inflammatory activity). Moreover, the algal meroterpene decreased the tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-10 levels, and caused a significant reduction of the expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2). Our results demonstrate the protective effects of AMT-E on experimental colitis, provide an insight of the underlying mechanisms of this compound, and suggest that this class of marine natural products might be an interesting candidate for further studies on the prevention/treatment of IBD.
Selection effects in online sharing: consequences for peer adoption

Most models of social contagion take peer exposure to be a corollary of adoption, yet in many settings, the visibility of one's adoption behavior happens through a separate decision process. In online systems, product designers can define how peer exposure mechanisms work: adoption behaviors can be shared in a passive, automatic fashion, or occur through explicit, active sharing. The consequences of these mechanisms are of substantial practical and theoretical interest: passive sharing may increase total peer exposure but active sharing may expose higher quality products to peers who are more likely to adopt. We examine selection effects in online sharing through a large-scale field experiment on Facebook that randomizes whether or not adopters share Offers (coupons) in a passive manner. We derive and estimate a joint discrete choice model of adopters' sharing decisions and their peers' adoption decisions. Our results show that active sharing enables a selection effect that exposes peers who are more likely to adopt than the population exposed under passive sharing. We decompose the selection effect into two distinct mechanisms: active sharers expose peers to higher quality products, and the peers they share with are more likely to adopt independently of product quality. Simulation results show that the user-level mechanism comprises the bulk of the selection effect. The study's findings are among the first to address downstream peer effects induced by online sharing mechanisms, and can inform design in settings where a surplus of sharing could be viewed as costly.
Progressive multilayer reconfiguration for software DSM systems in non-dedicated clusters

This paper is aimed at resolving the reconfiguration problem of software distributed shared memory (DSM) systems in non-dedicated clusters. Different to the past studies focused on dedicated clusters, the goal of this study focuses on prompting system-wide jobs' throughput rather than DSM programs' performance. We invent an approach called progressive multilayer reconfiguration (PMR) for DSM systems. As named, reconfiguration is divided into three different layers, i.e., processor, application, and node in this approach. According to the state transfer of the workload, the three different layer reconfigurations are progressively and respectively performed during the execution of DSM applications. The preliminary results show that PMR can not only utilize abundant CPU cycles available in non-dedicated clusters for DSM applications but also minimize the slowdown of local jobs caused by the disturb from DSM applications.
Expression of activation‐induced cytidine deaminase decreases throughout the life

Activation‐induced cytidine deaminase (AID) is an RNA editing enzyme, which contributes to generation of new functional genes from a restricted number of genes of plant and animal genome. This enzyme was involved in the process of somatic mutation and class switching in vertebrate. Since the rate of somatic mutations is variable throughout ontogeny, we have studied the transcription of AID in 3 to 24 month‐old Balb/c mice. Our results demonstrate a significant decrease of the transcription of the AID gene with aging. The decreased AID activity is not related to variation of phenotypic and functional properties of B cells throughout the life. This observation can explain the low rate of somatic mutation in aged animals.
Understanding the tradeoffs between software-managed vs. hardware-managed caches in GPUs

On-chip caches are commonly used in computer systems to hide long off-chip memory access latencies. To manage on-chip caches, either software-managed or hardware-managed schemes can be employed. State-of-art accelerators, such as the NVIDIA Fermi or Kepler GPUs and Intel's forthcoming MIC “Knights Landing” (KNL), support both software-managed caches, aka. shared memory (GPUs) or near memory (KNL), and hardware-managed L1 data caches (D-caches). Furthermore, shared memory and the L1 D-cache on a GPU utilize the same physical storage and their capacity can be configured at runtime (same for KNL). In this paper, we present an in-depth study to reveal interesting and sometimes unexpected tradeoffs between shared memory and the hardware-managed L1 D- caches in GPU architecture. In our study, the kernels utilizing the L1 D-caches are generated from those leveraging shared memory to ensure that the same optimizations such as tiling are applied equally in both versions. Our detailed analyses reveal that rather than cache hit rates, the following tradeoffs often have more profound performance impacts. On one hand, the kernels utilizing the L1 caches may support higher degrees of thread-level parallelism, offer more opportunities for data to be allocated in registers, and sometimes result in lower dynamic instruction counts. On the other hand, the applications utilizing shared memory enable more coalesced accesses and tend to achieve higher degrees of memory-level parallelism. Overall, our results show that most benchmarks perform significantly better with shared memory than the L1 D-caches due to the high impact of memory-level parallelism and memory coalescing.
Cost-Effectiveness of Intermittent Preventive Treatment of Malaria in Pregnancy in Southern Mozambique

Background Malaria in pregnancy is a public health problem for endemic countries. Economic evaluations of malaria preventive strategies in pregnancy are needed to guide health policies. Methods and Findings This analysis was carried out in the context of a trial of malaria intermittent preventive treatment in pregnancy with sulphadoxine-pyrimethamine (IPTp-SP), where both intervention groups received an insecticide treated net through the antenatal clinic (ANC) in Mozambique. The cost-effectiveness of IPTp-SP on maternal clinical malaria and neonatal survival was estimated. Correlation and threshold analyses were undertaken to assess the main factors affecting the economic outcomes and the cut-off values beyond which the intervention is no longer cost-effective. In 2007 US$, the incremental cost-effectiveness ratio (ICER) for maternal malaria was 41.46 US$ (95% CI 20.5, 96.7) per disability-adjusted life-year (DALY) averted. The ICER per DALY averted due to the reduction in neonatal mortality was 1.08 US$ (95% CI 0.43, 3.48). The ICER including both the effect on the mother and on the newborn was 1.02 US$ (95% CI 0.42, 3.21) per DALY averted. Efficacy was the main factor affecting the economic evaluation of IPTp-SP. The intervention remained cost-effective with an increase in drug cost per dose up to 11 times in the case of maternal malaria and 183 times in the case of neonatal mortality. Conclusions IPTp-SP was highly cost-effective for both prevention of maternal malaria and reduction of neonatal mortality in Mozambique. These findings are likely to hold for other settings where IPTp-SP is implemented through ANC visits. The intervention remained cost-effective even with a significant increase in drug and other intervention costs. Improvements in the protective efficacy of the intervention would increase its cost-effectiveness. Provision of IPTp with a more effective, although more expensive drug than SP may still remain a cost-effective public health measure to prevent malaria in pregnancy. Trial Registration ClinicalTrials.gov NCT00209781
Agent based information aggregation markets

Information Aggregation Markets (IAMs) constitute a mechanism whose purpose is to collect and aggregate information. They are commonly known as 'prediction markets' because they are often used to predict future events. In order for IAMs to efficiently aggregate information, they should attract participants with diversity of opinion, independence of thought and decentralization of knowledge. When participants are typically well-informed, IAM prices will aggregate information into market prices. IAMs can be considered as a large-scale, open, distributed system used by many human participants whose information needs to be aggregated. In this paper we propose a different approach for information aggregation using IAMs. We use autonomous, interacting agents instead of human participants and we show that agent based IAMs can act as an information aggregation mechanism able to perform predictions without human involvement.
Endurance exercise effect on quality of life and menopausal symptoms in Nigerian women.

INTRODUCTION Women in the menopausal stage of life usually have climacteric symptoms of hot flashes, back pain, sleeplessness, night sweats and increased risk of cardiovascular disorders. Although physical exercises have been documented to favourably alleviate some of these problems, there's a paucity of knowledge of their effects on menopausal women in Nigeria. OBJECTIVES This study investigated the effect of a twelve-week Endurance Exercise Programme (EEP) on quality of life(QOL) and menopausal symptoms in these women. METHODS Participants were purposively recruited and assigned into perimenopausal and postmenopausal groups based on history of thier last menstrual period and from each of these groups randomized into: perimenopausal exercise group (PEMEG), postmenopausal exercise group (POMEG), perimenopausal control group (PEMCG) postmenopausal control group (POMCG). Quality of life (QOL), Menopausal symptoms - Back Pain (BP) and hot flashes (HF) among other variables, were evaluated at baseline and 4 weekly intervals. EEP consisted of a 10-station circuit of muscular and cardiovascular endurance, flexibility, coordination, abdominal and pelvic floor muscle exercises. RESULTS One hundred and seventy five menopausal women, mean age 52.3 +/- 4.1 years. Significant changes occurred between baseline and end of 12th week mean values of PEMEG for QOL: 565.9 +/- 108.8 vs 725.0 +/- 42.9 and BP 4.42 +/- 1.7 vs 1.00 +/- 0.0. (p= 0.000). Also, in POMEG: QOL 558.3 +/- 127.7 vs 736.5 +/- 44.8; and BP 5.37 +/- 1.48 vs 1.88 +/- 1.18 (p=0.000). Significant changes in QOL and BP did not occur in the control groups. CONCLUSION Routine participation in endurance exercise programme is recommended for menopausal women for improved QOL.
An intelligent docking station manager for multiple mobile service robots

Robot docking stations are of utmost important for service robots like security robots and automated guided vehicles in warehouses which are in continuous operation, and hence require frequent recharging. While a lot of research has been done on designing the actual hardware of the docking station itself, a practical situation of intelligently managing a limited number of docking stations in case of multiple robots has largely been ignored. We propose a docking station manager for multiple mobile service robots, which intelligently allots a mobile robot to the most appropriate docking station, based on the robot's task priority, location awareness of the robot and the docking station, power left in robot, and request order. We demonstrate, through experiments in real environment, that the proposed manager can function intelligently and resolve conflicts when the docking stations are fully occupied. We experimentally tested the proposed station manager in different conditions of varying task priorities, power levels, and emergency conditions of the robots, and found it to be robust to intelligently allocate the most appropriate robot with the appropriate charging dock.
Comparison of the deep-learning-based automated segmentation methods for the head sectioned images of the virtual Korean human project

This paper presents an end-to-end pixelwise fully automated segmentation of the head sectioned images of the Visible Korean Human (VKH) project based on Deep Convolutional Neural Networks (DCNNs). By converting classification networks into Fully Convolutional Networks (FCNs), a coarse prediction map, with smaller size than the original input image, can be created for segmentation purposes. To refine this map and to obtain a dense pixel-wise output, standard FCNs use deconvolution layers to upsample the coarse map. However, upsampling based on deconvolution increases the number of network parameters and causes loss of detail because of interpolation. On the other hand, dilated convolution is a new technique introduced recently that attempts to capture multi-scale contextual information without increasing the network parameters while keeping the resolution of the prediction maps high. We used both a standard FCN and a dilated convolution based FCN for semantic segmentation of the head sectioned images of the VKH dataset. Quantitative results showed approximately 20% improvement in the segmentation accuracy when using FCNs with dilated convolutions.