Miracle-dz/UniFAR-FTUs huggingface dataset:
Delayed Inhibition of VEGF Signaling after Stroke Attenuates Blood–Brain Barrier Breakdown and Improves Functional Recovery in a Comorbidity-Dependent Manner

Diabetes is a common comorbidity in stroke patients and a strong predictor of poor functional outcome. To provide a more mechanistic understanding of this clinically relevant problem, we focused on how diabetes affects blood–brain barrier (BBB) function after stroke. Because the BBB can be compromised for days after stroke and thus further exacerbate ischemic injury, manipulating its function presents a unique opportunity for enhancing stroke recovery long after the window for thrombolytics has passed. Using a mouse model of Type 1 diabetes, we discovered that ischemic stroke leads to an abnormal and persistent increase in vascular endothelial growth factor receptor 2 (VEGF-R2) expression in peri-infarct vascular networks. Correlating with this, BBB permeability was markedly increased in diabetic mice, which could not be prevented with insulin treatment after stroke. Imaging of capillary ultrastructure revealed that BBB permeability was associated with an increase in endothelial transcytosis rather than a loss of tight junctions. Pharmacological inhibition (initiated 2.5 d after stroke) or vascular-specific knockdown of VEGF-R2 after stroke attenuated BBB permeability, loss of synaptic structure in peri-infarct regions, and improved recovery of forepaw function. However, the beneficial effects of VEGF-R2 inhibition on stroke recovery were restricted to diabetic mice and appeared to worsen BBB permeability in nondiabetic mice. Collectively, these results suggest that aberrant VEGF signaling and BBB dysfunction after stroke plays a crucial role in limiting functional recovery in an experimental model of diabetes. Furthermore, our data highlight the need to develop more personalized stroke treatments for a heterogeneous clinical population.
Intraday Analysis of the Limit Order Bias on the Ex-Dividend Day of U.S. Common Stocks

This study places Dubofsky’s (1992) “limit order adjustment hypothesis” under the microscope of an intraday analysis, which employs a minute-by-minute trade and quote data recorded during the ex-dividend days of common stocks listed on NYSE, AMEX and NASDAQ. Dufosky’s (1992) model concluded that the asymmetric adjustment of open limit orders for cash dividend payments under the NYSE and AMEX rules is sufficient to create abnormal returns on the ex-dividend day. Empirical evidence shows that the limit order bias incurred due to the asymmetric adjustment of open limit orders seems to dominate the overnight ex-day returns but at the same time, it is significantly corrected via active trading up until the close of the ex- dividend day. As a result, the significant association of the ex-day price drop discrepancy with the opening limit order bias eventually disappears before the ex-dividend day close. Finally, it is found that the reversal of the limit order bias is in fact quicker in stocks which are more liquid or listed on NASDAQ where strong competition among dealers is envisaged to drive stale quotes closer to the fair adjustment of the dividend.
Segmental lumbar spine instability at flexion-extension radiography can be predicted by conventional radiography.

AIM To identify plain radiographic findings that predict segmental lumbar spine instability as shown by functional flexion-extension radiography. MATERIALS AND METHODS Plain radiographs and flexion-extension radiographs of 215 patients with clinically suspected lumbar spine instability were analysed. Instability was classified into anterior or posterior sliding instability. The registered plain radiographic findings were traction spur, spondylarthrosis, arthrosis of facet joints, disc degeneration, retrolisthesis, degenerative spondylolisthesis, spondylolytic spondylolisthesis and vacuum phenomena. Factors reaching statistical significance in univariate analyses (P < 0.05) were included in stepwise multiple logistic regression analysis. RESULTS Degenerative spondylolisthesis (P = 0.004 at L3-4 level and P = 0.017 at L4-5 level in univariate analysis and odds ratio 16.92 at L4-5 level in multiple logistic regression analyses) and spondylolytic spondylolisthesis (P = 0.003 at L5-S1 level in univariate analyses) were the strongest independent determinants of anterior sliding instability. Retrolisthesis (odds ratio 10.97), traction spur (odds ratio 4.45) and spondylarthrosis (odds ratio 3.20) at L3-4 level were statistically significant determinants of posterior sliding instability in multivariate analysis. CONCLUSION Sliding instability is strongly associated with various plain radiographic findings. In mechanical back pain, functional flexion-extension radiographs should be limited to situations when symptoms are not explained by findings of plain radiographs and/or when they are likely to alter therapy.
Lexical Based Method for Opinion Detection on Tripadvisor Collection

—The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difﬁculty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classiﬁer is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a ﬁnal score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.
Magnetic resonance imaging-guided focused ultrasound to increase localized blood-spinal cord barrier permeability

Spinal cord injury (SCI) affects thousands of people every year in the USA, and most patients are left with some permanent paralysis. Therapeutic options are limited and only modestly affect outcome. To address this issue, we used magnetic resonance imaging-guided focused ultrasound (MRgFUS) as a non-invasive approach to increase permeability in the blood-spinal cord barrier (BSCB). We hypothesize that localized, controlled sonoporation of the BSCB by MRgFUS will aid delivery of therapeutics to the injury. Here, we report our preliminary findings for the ability of MRgFUS to increase BSCB permeability in the thoracic spinal cord of a normal rat model. First, an excised portion of normal rat spinal column was used to characterize the acoustic field and to estimate the insertion losses that could be expected in an MRgFUS blood spinal cord barrier opening. Then, in normal rats, MRgFUS was applied in combination with intravenously administered microbubbles to the spinal cord region. Permeability of the BSCB was indicated as signal enhancement by contrast administered prior to T1-weighted magnetic resonance imaging and verified by Evans blue dye. Neurological testing using the Basso, Beattie, and Breshnahan scale and the ladder walk was normal in 8 of 10 rats tested. Two rats showed minor impairment indicating need for further refinement of parameters. No gross tissue damage was evident by histology. In this study, we have opened successfully the blood spinal cord barrier in the thoracic region of the normal rat spine using magnetic resonance-guided focused ultrasound combined with microbubbles.
Preprocessi Features Learning Feature Weights using Training Document Machine Learnin g Lables New Text Document Preprocessi ng Features Extractio Predictive Model Expected Label

The huge amount of documents in the internet led to the rapid need of text classification (TC). TC is used to organize these text documents. In this research paper, a new model is based on Extreme Machine learning (EML) is used. The proposed model consists of many phases including: preprocessing, feature extraction, Multiple Linear Regression (MLR) and ELM. The basic idea of the proposed model is built upon the calculation of feature weights by using MLR. These feature weights with the extracted features introduced as an input to the ELM that produced weighted Extreme Learning Machine (WELM). The results showed a great competence of the proposed WELM compared to the ELM.
Moving Towards High-Fidelity RANS Calculations Of Maneuvering Surface Vessels Using Unstructured Grids

Simulations of maneuvering surface ships using high-fidelity viscous computational fluid dynamics requires the capability to model the conservation of mass and momentum via the unsteady Reynoldsaveraged Navier-Stokes, along with appropriate turbulence modeling, the capability to rotate and deflect appendages, accurate force and moment predictions and robust and efficient unsteady nonlinear free surface capabilities. Simulations of flow around transom sterns for naval combatants introduces additional complexities due to grid generation issues arising from wetted or unwetted conditions. Finally, to simulate flow for fully-appended configurations with struts, rudders, shafts and propellers, unstructured grids offer much promise due to the geometric complexities. In this research, a three-dimensional unstructured mixed-element flow solver of the incompressible Reynolds-averaged Navier-Stokes equations with various turbulence models and nonlinear free surface capabilities is studied with the goal of addressing some preliminary issues for rudder-induced, propeller driven, six-degree-of-freedom maneuvers. The research presented herein is divided into three topics, each focused on numerical simulations of the DTMB Model 5415 series hullform. The first topic concerns the accuracy of the free surface and of the forces and moments generated by the unstructured flow solver. Results from a grid refinement study is used to determine the level of grid refinement that are required for accurate predictions of the forces and moments for this code. The second topic covers two different types of steady-state maneuvers, the constant drift case and the constant turn case. Flow around the Model 5415 hullform at drift angles from 1 to 5 degrees are presented, as well as flow for turns of constant radius ranging from 6 to 24 ship lengths. The third topic is a prescribed maneuver for the model 5415 hullform with a linear free surface. Simulation data from a rudder-induced, propeller-driven maneuver with no free surface (i.e., the free surface was a symmetry plane) is used to prescribe a maneuver for the Model 5415 hullform. Due to the complexities of moving the grid at each time step, only a linear free surface was used, so that the grid movement algorithm is ignored.
Chronic Interleukin-1β Expression in Mouse Brain Leads to Leukocyte Infiltration and Neutrophil-Independent Blood–Brain Barrier Permeability without Overt Neurodegeneration

The proinflammatory cytokine interleukin-1β (IL-1β) plays a significant role in leukocyte recruitment to the CNS. Although acute effects of IL-1β signaling in the mouse brain have been well described, studies elucidating the downstream effects of sustained upregulation have been lacking. Using the recently described IL-1βXAT transgenic mouse model, we triggered sustained unilateral hippocampal overexpression of IL-1β. Transgene induction led to blood–brain barrier leakage, induction of MCP-1 (monocyte chemoattractant protein 1) (CCL2), ICAM-1 (intercellular adhesion molecule 1), and dramatic infiltration of CD45-positive leukocytes comprised of neutrophils, T-cells, macrophages, and dendritic cells. Despite prolonged cellular infiltration of the hippocampus, there was no evidence of neuronal degeneration. Surprisingly, neutrophils were observed in the hippocampal parenchyma as late as 1 year after transgene induction. Their presence was coincident with upregulation of the potent neutrophil chemotactic chemokines KC (keratinocyte-derived chemokine) (CXCL1) and MIP-2 (macrophage inflammatory protein 2) (CXCL2). Knock-out of their sole receptor CXCR2 abrogated neutrophil infiltration but failed to reduce leakage of the blood–brain barrier.
Intergenerational Long Term Effects of Preschool-Estimates from a Structural Dynamic Programming Model ∗

Using theNLSY79 (National Longitudinal Study ofYouths, 1979) and theNLSY79 Children and Young Adults datasets, this paper formulates and then empirically estimates an altruistic model of parental preschool investment within a structural dynamic programming framework. The paper provides conditions for identification of the structural parameters of the dynamic programming model and carries out a Lucas-Critique free policy analysis using the estimated structural parameters. The paper empirically estimates the production processes for social, motivational and cognitive skills of a child and the role that the parental preschool investment plays in such production processes. It then examines the effect of a publicly provided preschool policy to disadvantaged children on their educational and labor market achievements, and also on the intergenerational long-term effect on social mobility, schooling mobility, and earnings inequality. The paper calculates the tax burden of such a social contract policy taking into account these intraand inter-generational effects.
Testosterone suppresses oxidative stress in human neutrophils

The in vitro effect of testosterone on human neutrophil function was investigated. Blood neutrophils from healthy male subjects were isolated and treated with 10 nM, 0.1 and 10 µM testosterone for 24 h. As compared with untreated cells, the testosterone treatment produced a significant decrease of superoxide production as indicated by the measurement of extra‐ and intracellular superoxide content. An increment in the production of nitric oxide was observed at 0.1 and 10 µM testosterone concentrations, whereas no effect was found for 10 nM. Intracellular calcium mobilization was significantly increased at 10 nM, whereas it was reduced at 10 µM testosterone. There was an increase in phagocytic capacity at 10 nM and a decrease of microbicidal activity in neutrophils treated with testosterone at 10 µM. Glutathione reductase activity was increased by testosterone treatment, whereas no effect was observed in other antioxidant enzyme activities. An increase in the content of thiol groups was observed at all testosterone concentrations. Lipid peroxidation in neutrophils evaluated by levels of TBARS was decreased at 10 nM and 0.1 µM testosterone. These results indicate the antioxidant properties of testosterone in neutrophils as suggested by reduction of superoxide anion production, and lipid peroxidation, and by the increase in nitric oxide production, glutathione reductase activity and the content of thiol groups. Therefore, the plasma levels of testosterone are important regulators of neutrophil function and so of the inflammatory response. Copyright © 2010 John Wiley & Sons, Ltd.
Optimal Tuning of PID Controller for PMBLDC Motor using Cat Swarm Optimization

This paper proposes the optimal tuning of PID controller with Cat Swarm Optimization (CSO) algorithm for the speed control of Brushless DC Motor. Proportional Integral Derivative controllers are most popular controllers because of their effectiveness and easy to implement. However, in PID controller it is difficult to obtain the proper values of the controlling parameters Kp, Ki and Kd. In this paper, CSO is proposed to adjust the parameters of the controller in order to improve the performance of the system and run the BLDC motor at desired speed. The speed control of PMBLDC motor is done by the conventional PID controller and the CSO based PID controller. The variation of speed has been tested for both conventional and CSO based PID controller. The results shows a better system performance while using the CSO based PID controller than the conventional PID controller and also the speed of PMBLDC is improved by using the CSO.
Model Based Concept Mining Applied to Information Security Data

Security Operations Center (SOC) analysts are concerned with triaging alarms coming from an Intrusion Detection System quickly but carefully. In most cases, however, scattering of information throughout multiple sources makes it difficult to do so. We introduce a way to capture information from different sources into one structured dataset, by use of EDXML. We define the notion of Model Based Concept Mining to retrieve entities defined by an ontology. By defining the ontology, we add semantics to the data involved with security events, which make it possible for a computer to understand the data. A framework for the process of going from raw data to the presentation of the relevant information consists of four stages, two of which are application dependent. We show how to implement these steps to create a graph yielding the information necessary for an analyst to gather insights into the context of an alarm, and to aid in making a justified decision on the risk an alarm poses. The process of generating a structured data set and presenting the data consists of four steps, which can be tailored to the needs for each application domain. For the SOC domain, time constraints play a key role, and adaptations to the model are necessary. A preliminary evaluation of evidence presented after applying the model on real data has been conducted. This evaluation did not test the model itself, but its use when analysing an alarm. This evaluation showed that there are potential benefits in terms of speed and focus when analysing an alarm.
Table based KNN for Article Classification

In this research, we propose the modified version of KNN (K Nearest Neighbor) as an approach to the text categorization. The fact that there are the three problems in encoding texts into numerical vectors for using the traditional version to the task such as the huge dimensionality, the sparse distribution, and the poor transparency, provided the motivation for doing this research. As the solution to the three problems, the idea of this research is to modify the KNN which is known as the popular and practical classifier into the version where texts are encoded into tables, instead of the numerical vectors. The modified version of KNN which is proposed in this research is expected to classify texts better than the traditional version by solving the three problems. Hence, the goal of this research is to implement the text categorization system, using the proposed approach.
CONSUMER PERCEPTIONS OF THE FAST FOOD INDUSTRY IN SWEDEN.

The fast food industry is one of the important and growing segments of the overall restaurant industry. At the same time, it is a very dynamic and competitive business where too many vendors are chasing too few clients.To maintain sustainable growth and long-term success it is crucial to meet consumer needs and offer value to them. In order to achieve this, fast food providers must first evaluate customer satisfaction level to determine the extent of satisfaction with given products and services, as well as identify the key attributes of value for consumers and evaluate consumer behavior. Eventually, satisfaction with market transaction leads to repeat purchases which benefits the business operators and helps to build loyal consumer base. This paper seeks to investigate perception of the fast food industry by exploring consumer behavior, determining key attributes of perceived value and by assessing customer satisfaction level. To successfully achieve the purpose of the study a quantitative research design was applied to collect the data. I entailed utilizing the survey method which was used to collect the statistical evidence regarding the objects of the study. The results revealed that consumers of local fast food outlets are overall satisfied with their fast food restaurant experience. The primary purpose of a visit to a fast food outlet is for social activities such as friends get together, for convenience or for change and fun. Additionally, consumers exhibited high importance towards certain attributes such as quality and nutritional value of products, cleanliness and hygiene of the dining premise, quality and speed of the service handling, menu variety were amongst perceived important value attributes. Consequently, it is recommended that fast food providers focus on the key attributes of value for consumers and systematically review the customer needs and expectations in order to increase customer satisfaction and deliver value. Moreover, for maintaining loyal consumer base and increasing customer retention, it is important to direct resources towards improving and strengthening the relationship marketing strategy. (Less)
Measuring Central Executive Functioning: What's in a Reading Span?

Although variations of Daneman and Carpenter's (1980) Reading Span Test (RST) have seen increasing use in both cognitive and neuropsychological research, the specific mental operations involved in performing it remain unclear. We tested 80 undergraduates to examine the extent to which speed of processing, manipulation capacity, and susceptibility to interference contributed to RST performance. The results suggest that, rather than unitary central executive or processing speed functions underlying RST performance, at least two factors, manipulation capacity and susceptibility to interference, underlie the task. Further study of RST operations may lead to a better understanding of the nature of the central executive itself.
Agosta libVersioningCompiler : an easy-to-use library for dynamic generation and invocation of multiple code versions

We present libVersioningCompiler, a C++ library designed to support the dynamic generation of multiple versions of the same compute kernel in a HPC scenario. It can be used to provide continuous optimization, code specialization based on the input data or on workload changes, or otherwise to dynamically adjust the application, without the burden of a full dynamic compiler. The library supports multiple underlying compilers but specifically targets the llvm framework. We also provide examples of use, showing the overhead of the library, and providing guidelines for its efficient use.