Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of the hydrogen sulfide donor GYY4137 on platelet activation and microvascular thrombus formation in mice

Abstract This study evaluates the effect of the H2S donor GYY4137 (GYY) on adhesion molecule expression, protein S-sulfhydration and morphology of platelets in vitro and on kinetics of microvascular thrombus formation in vivo. Using flowcytometry, untreated resting, TRAP-activated, or TRAP-activated and GYY-exposed human platelets were studied for expression of P-selectin, GPIb and GPIIb/IIIa as well as for fibrinogen binding. By means of electron microscopy, platelet morphology and intracellular granule numbers were assessed. Platelet shape change was studied using immunohistochemistry for P-selectin, NSF and F-actin by SR-SIM. Biotin switch assay served for the analysis of platelet protein S-sulfhydration by GYY. Using the FeCl3 and the light/dye model in dorsal skinfold chamber-equipped mice, the effect of GYY and its vehicle DMSO was studied on venular thrombus formation and tail-vein bleeding time. Soluble (s)P-selectin plasma concentrations were measured in GYY- or DMSO-treated animals. Exposure to GYY increased the S-sulfhydration of platelet proteins. GYY reduced dose-dependently the TRAP-induced adhesion molecule expression and attenuated the morphological signs of TRAP-associated platelet activation. In mice, GYY caused a significant prolongation of venular thrombus formation and tail-vein bleeding time. Application of an anti-P-selectin antibody in DMSO-exposed animals prolonged thrombosis formation comparably as GYY did. GYY reversed the TRAP-induced distribution of P-selectin at the plasma membrane of platelets. This indicates reduced exocytosis and shedding of P-selectin, which is supported by significantly lower sP-selectin concentrations in GYY- vs. DMSO-treated mice. H2S acts anti-thrombotic and seems to regulate thrombogenesis by interference with platelet activation and adhesion molecule-mediated aggregation.
Appropriability, Technological Opportunity, Market Demand and Technical Change, Empirical evidence from Switzerland

The purpose of this paper is to analyze both theoretically and empirically those factors which underlay the - empirically observable - inter-industry differences in technical progress. At the theoretical level economists agree more and more that technical progress can be explained at the industry level by the following three factors: (1) the technological opportunities, (2) the appropriability conditions, meaning the ability to capture and protect the results of technical innovations and (3) the market demand conditions. The basic theoretical model was tested with the help of two sets of Swiss data. One set was made available by Swiss Federal Office of Statistics and consists of quantitative information on RD 358 of them, or 38%, covering 127 industries, completed the questionnaire. The items on the questionnaire were related to the two supply-side determinants of technical progress - items (1) and (2) above. For the empirical specification of the theoretical model, technical progress (as the dependent variable) was measured by three indicators: an output indicator, representing the introduction rate of innovations since 1970; two input indicators, "share of R&D expenditures in sales" and "share of R&D personnel in total employment". All data were aggregated at the industry-level (4-digit SIC). Three equations were estimated individually, using the OLS, GLS and Tobit methods. The most important results of the empirical analysis can be summarized as follows: - The ability to appropriate the results of innovations exerts a positive impact on technical progress in all three models. In this context, the non-patent related means of appropriability "secrecy", "lead time", "moving downward on the learning curve" and "superior sales and service efforts" prove to be more important for the innovation process than the means "patents to protect against imitation" and "patents to secure royalty income". - Of all external sources of technological opportunities, domestic and foreign university research makes the largest quantitative and statistically most significant contribution to technical progress. -Science (i.e. education in 14 science fields) is on the whole relevant for technical progress. But its contribution to technical progress would increase, if at the R&D level its application could be better targeted. - Of the six fields of basic science, only in mathematics and in theoretical computer science is education relevant for technical progress. - The relevance of education and training in the applied sciences for technical progress is high and significant in the fields of medical science and electronics. - The impact of sales as an indicator for market demand is negative. Industries with relatively low sales are relatively more innovative than those with a higher level of sales.
Hemiplegic Limb Synergies in Stroke Patients

Welmer AK, Widén Holmqvist L, Sommerfeld DK: Hemiplegic limb synergies in stroke patients. Am J Phys Med Rehabil 2006;85:112–119. Objective:To describe the extent to which the voluntary movements of hemiparetic stroke patients are restricted to the hemiplegic limb synergies (which are marked by the inability to master individual joint movements) described by Brunnström. The study also aimed to describe the extent to which the synergies are related to functioning. Design:In a prospective observational study design, 64 consecutive hemiparetic stroke patients were assessed with Brunnström’s hemiplegic limb synergies, the modified Ashworth scale for spasticity, the Rivermead mobility index, and the Barthel ADL index. Results:Three months after stroke, 8 of the 64 patients were moving completely or partly within the synergies. All patients whose movements were restricted to the synergies also exhibited spasticity. Hemiparetic patients whose movements were restricted to the synergies had significantly worse functioning scores than hemiparetic patients whose movements were not restricted to the synergies although severe disabilities were seen in both groups. Conclusions:Three months after stroke, the voluntary movements of only 13% of hemiparetic stroke patients were restricted to the synergies. The synergies were associated with spasticity and activity limitations. The use of the synergies might only be suitable for a small fraction of hemiparetic patients—namely, those displaying spasticity.
Automatic Protocol Compliance Checking of SystemC TLM-2.0 Simulation Behavior Using Timed Automata

The increasing complexity of todays digital circuit designs led to the increased usage of abstract models. In particular, the Electronic System Level (ESL) has emerged as an area of active research. For ESL design, SystemC and its Transaction Level Modeling (TLM) framework have become the standard tools for abstract modeling. The resulting models represent both, an executable specification and a reference model for the hardware design. The correctness of these designs is important as undetected errors may propagate to less abstract levels in the design process, increasing the potential amount of work required to fix them. To quickly ensure that implementations and reference emit the same behavior, the comparison between these abstractions needs to be both, flexible and automated. This paper presents a method to verify the simulation behavior of a given System TLM-2.0 design against TLM-2.0 protocols. The system's structural description and its run-time behavior are translated to a single, consistent formal model. This is then used to verify that a simulation run adheres to a given protocol. The protocol compliance checks are performed using the UPPAAL model checker and applied to several TLM models.
A Deep Ranking Model for Spatio-Temporal Highlight Detection from a 360 Video

We address the problem of highlight detection from a 360◦ video by summarizing it both spatially and temporally. Given a long 360◦ video, we spatially select pleasantly-looking normal field-of-view (NFOV) segments from unlimited field of views (FOV) of the 360◦ video, and temporally summarize it into a concise and informative highlight as a selected subset of subshots. We propose a novel deep ranking model named as Composition View Score (CVS) model, which produces a spherical score map of composition per video segment, and determines which view is suitable for highlight via a sliding window kernel at inference. To evaluate the proposed framework, we perform experiments on the Pano2Vid benchmark dataset (Su, Jayaraman, and Grauman 2016) and our newly collected 360◦ video highlight dataset from YouTube and Vimeo. Through evaluation using both quantitative summarization metrics and user studies via Amazon Mechanical Turk, we demonstrate that our approach outperforms several state-of-the-art highlight detection methods.We also show that our model is 16 times faster at inference than AutoCam (Su, Jayaraman, and Grauman 2016), which is one of the first summarization algorithms of 360◦ videos.
Deep Modeling of Social Relations for Recommendation

Social-based recommender systems have been recently proposed by incorporating social relations of users to alleviate sparsity issue of user-to-item rating data and to improve recommendation performance. Many of these social-based recommender systems linearly combine the multiplication of social features between users. However, these methods lack the ability to capture complex and intrinsic non-linear features from social relations. In this paper, we present a deep neural network based model to learn non-linear features of each user from social relations, and to integrate into probabilistic matrix factorization for rating prediction problem. Experiments demonstrate the advantages of the proposed method over state-of-the-art social-based recommender systems.
Amyloid-β Annular Protofibrils Evade Fibrillar Fate in Alzheimer Disease Brain*♦

Annular protofibrils (APFs) represent a new and distinct class of amyloid structures formed by disease-associated proteins. In vitro, these pore-like structures have been implicated in membrane permeabilization and ion homeostasis via pore formation. Still, evidence for their formation and relevance in vivo is lacking. Herein, we report that APFs are in a distinct pathway from fibril formation in vitro and in vivo. In human Alzheimer disease brain samples, amyloid-β APFs were associated with diffuse plaques, but not compact plaques; moreover, we show the formation of intracellular APFs. Our results together with previous studies suggest that the prevention of amyloid-β annular protofibril formation could be a relevant target for the prevention of amyloid-β toxicity in Alzheimer disease.
Improved prostate cancer detection with a human kallikrein 11 and percentage free PSA-based artificial neural network

Abstract Human kallikrein 11 (hK11) was evaluated in a percentage free PSA-based artificial neural network (ANN) to reduce unnecessary prostate biopsies. Serum samples from 357 patients with (n=132) and without (n=225) prostate cancer (PCa) were analyzed and ANN models were constructed and compared to all parameters. The discriminatory power of hK11 was lower than that of PSA, but receiver operator characteristic (ROC) analyses demonstrated significantly larger areas under the curves for the ANN compared to all other parameters. ANNs with hK11 may lead to a further reduction in unnecessary prostate biopsies, especially when analyzing patients with less than 15% free PSA.
Human-system cooperative hybrid augmented intelligence based dynamic dispatching framework of semiconductor wafer fabrication facility

Modern semiconductor manufacturing is in urgent need of the dynamic intelligent dispatching method which can make real-time response to uncertain operating environment, meet the complex process constraints, collaborate a variety types of scheduling, achieve the desired performance, and especially guide the real production lines. To meet the requirements above, combining human knowledge with artificial intelligence is a promising direction for semiconductor dispatching. Therefore, a dynamic intelligent dispatching framework of “human-in-the-loop” with the abilities of prediction and self-optimization is proposed in the paper, which defines the roles of human and machine intelligence as well as their collaborative manner. What's more, the realization process of semiconductor manufacturing dynamic intelligent dispatching method based on hybrid human-system collaboration and data driven is demonstrated in detail.
Multilabel statistical shape prior for image segmentation

Statistical shape models have been widely used to guide the segmentation in an image, thus overcoming noise and occlusions. In this study, the authors present a graph cut-based segmentation framework, in which multiple objects can be segmented. They design a specific multilabel shape prior, which is integrated into the graph cost function. They also want to enforce spatial constraint between the objects. Towards this aim, they propose a local constraint to forbid the inclusion of an object into another, which is enforced in the regularisation term of the graph energy. They apply the authors’ method to cardiac magnetic resonance images, in which left and right ventricles, and the myocardium are segmented and for which encouraging results are obtained.
Functional and Structural Responses of Hyporheic Biofilms to Varying Sources of Dissolved Organic Matter

ABSTRACT Headwater streams are tightly connected with the terrestrial milieu from which they receive deliveries of organic matter, often through the hyporheic zone, the transition between groundwater and streamwater. Dissolved organic matter (DOM) from terrestrial sources (that is, allochthonous) enters the hyporheic zone, where it may mix with DOM from in situ production (that is, autochthonous) and where most of the microbial activity takes place. Allochthonous DOM is typically considered resistant to microbial metabolism compared to autochthonous DOM. The composition and functioning of microbial biofilm communities in the hyporheic zone may therefore be controlled by the relative availability of allochthonous and autochthonous DOM, which can have implications for organic matter processing in stream ecosystems. Experimenting with hyporheic biofilms exposed to model allochthonous and autochthonous DOM and using 454 pyrosequencing of the 16S rRNA (targeting the “active” community composition) and of the 16S rRNA gene (targeting the “bulk” community composition), we found that allochthonous DOM may drive shifts in community composition whereas autochthonous DOM seems to affect community composition only transiently. Our results suggest that priority effects based on resource-driven stochasticity shape the community composition in the hyporheic zone. Furthermore, measurements of extracellular enzymatic activities suggest that the additions of allochthonous and autochthonous DOM had no clear effect on the function of the hyporheic biofilms, indicative of functional redundancy. Our findings unravel possible microbial mechanisms that underlie the buffering capacity of the hyporheic zone and that may confer stability to stream ecosystems.
The Simplest Chronoscope V

Extending work by Montare, visual simple reaction time, choice reaction time, discriminative reaction time, and overall reaction time scores obtained from college students by the simplest chronoscope (a falling meterstick) method were significantly faster as well as significantly less variable than scores of the same individuals from electromechanical reaction timers (machine method). Results supported the existence of dual reaction time systems: an ancient primary reaction time system theoretically activating the V5 parietal area of the dorsal visual stream that evolved to process significantly faster sensory-motor reactions to sudden stimulations arising from environmental objects in motion, and a secondary reaction time system theoretically activating the V4 temporal area of the ventral visual stream that subsequently evolved to process significantly slower sensory-perceptual-motor reactions to sudden stimulations arising from motionless colored objects.
Shell companies as IPO alternatives: an analysis of trading activity around reverse mergers

While shell companies are convenient vehicles for small private firms to go public via a reverse merger, they are also often mentioned in the popular press in conjunction with stock price manipulation. Recently the Securities and Exchange Commission (SEC) has imposed stricter rules on these companies to speed up disclosure of financial information and curb potential abuses. Our article looks at the trading activity around reverse mergers. Clearly, the merger is taken as significant news as the trading activity increases immediately following the merger announcement. This observation suggests that the SEC may have had good reason to speed up the required filings and provide timely information to the public. We find sporadic, but statistically significant positive returns surrounding the merger reflecting the increase in value of the shell companies that is also evidenced in the (statistically insignificant) positive CARs following merger announcements. However, our results do not show any evidence of persistent insider trading or price manipulation in these stocks.
Relation of hepatolithiasis to helminthic infestation

Background and Aim: The relation of helminthic infestation to hepatolithiasis is a subject of dispute. This case–control study was undertaken to evaluate the prevalence of helminthiasis in hepatolithiasis patients and to compare the clinicopathological features of hepatolithiasis between patients with and without helminthiasis.
Ability, families, education and earnings in Britain

The paper estimates the returns to education for a cohort of individuals born in Britain in March 1958 who have been followed since birth until the age of 33. The data used has a wealth of information on family background including parental education, social class and interest shown in the child's education as well as measures of ability. These variables are typically missing in studies looking at the returns to schooling. In the paper we Ud that the return to an additional year of full-time education for the UK population as a whole is somewhere between 5 to 7 per cent for men and 8 to 10 per cent for women even after correcting for the ehcts of measurement error. The paper also presents evidence that the returns to an additional year of schooling in the UK are heterogeneous. The results from the paper suggest that individuals undertaking education involving some sort of formal qualification have significantly larger rates of return to an additional year of education than individuals who have obtained no formal education. Individuals whose highest educational qualification is an A level (the highest schooling qualification in the UK) appear to have the highest average return to an additional year of education at around 15 per cent for both men and women. There is also some evidence that individuals with lower tastes for education, have significantly higher marginal returns to education. The results of the paper suggest that recent IV estimates of the returns to schooling in the UK, which exceed typical OLS estimates, may overestimate the average marginal return for the population as a whole.
Using Syntax to Ground Referring Expressions in Natural Images

We introduce GroundNet, a neural network for referring expression recognition---the task of localizing (or grounding) in an image the object referred to by a natural language expression. Our approach to this task is the first to rely on a syntactic analysis of the input referring expression in order to inform the structure of the computation graph. Given a parse tree for an input expression, we explicitly map the syntactic constituents and relationships present in the tree to a composed graph of neural modules that defines our architecture for performing localization. This syntax-based approach aids localization of both the target object and auxiliary supporting objects mentioned in the expression. As a result, GroundNet is more interpretable than previous methods: we can (1) determine which phrase of the referring expression points to which object in the image and (2) track how the localization of the target object is determined by the network. We study this property empirically by introducing a new set of annotations on the GoogleRef dataset to evaluate localization of supporting objects. Our experiments show that GroundNet achieves state-of-the-art accuracy in identifying supporting objects, while maintaining comparable performance in the localization of target objects.
Salvage of nicotinamide adenine dinucleotide plays a critical role in the bioenergetic recovery of post‐hypoxic cardiomyocytes

Ischaemic heart disease can lead to serious, life‐threatening complications. Traditional therapies for ischaemia aim to increase oxygen delivery and reduce the myocardial ATP consumption by increasing the coronary perfusion and by suppressing cardiac contractility, heart rate or blood pressure. An adjunctive treatment option for ischaemia is to improve or optimize myocardial metabolism.
Participatory research as a tool for community development

In Third World countries, where resources are scarce, social scientists are confronted with the challenge of providing knowledge and services relevant to national development. This paper attempts to address this ‘relevance’ question by exploring the relationship between participatory research (as a social science research paradigm) and community development. The assumption is that people possess indigenous skills and knowledge, but that these need to be harnessed and refined in order that they can be effectively utilised in the planning and implementation of development processes. It is argued that human capacity building and empowerment are core components of participatory research and a prerequisite for appropriate development. A participatory research project in a rural resettlement village in the Ciskei is presented to illustrate the implementation of participatory research as a tool for community development.
Cyber crime influencing businesses in South Africa

This study shows that cyber crime is a recent addition to the list of crimes that can adversely affec tbusinesses directly or indirectly. This phenomenon was not directly prosecutable in South Africa until the enactment of the ECT Act in July 2002. However this Act also prevents businesses to fully prosecute a hacker due to incompleteness. Any kind of commercially related crime can be duplicated as cyber crime. Therefore very little research appears or has been documented about cyber crime in South African companies before 2003. The motivation to do this study was that businesses often loose millions in cyber attacks, not necessarily through direct theft but by the loss of service and damage to the image of the company. Most of the companies that were approached for interviews on cyber crime were reluctant to share the fact that they were hacked or that cyber crime occurred at their company as it violates their security policies and may expose their fragile security platforms. The purpose of this study was to attempt to get an overall view on how South African businesses are affected by cyber crime in the banking and short term insurance sector of the South African industry and also to determine what legislation exist in this country to protect them. The case study approach was used to determine the affect of cyber crime on businesses like banks and insurance companies and higher education institutions. Each case was interviewed, monitored and was observed over a period of a year. This study discloses the evaluation of the results of how cyber crime affected the cases, which were part of this study. The banks and higher education institutions felt that they were at an increased risk both externally and internally, which is likely to increase as the migration towards electronic commerce occurs. The insurance industry felt that they are not yet affected by external cyber crime attacks in this country.