Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Ginkgo biloba Extract EGb761 on Hippocampal Neuronal Injury and Carbonyl Stress of D-Gal-Induced Aging Rats

Background Ginkgo biloba extract is widely studied for antiaging activities, but little is known about its antiaging mechanism of protein carbonylation. In order to verify carbonyl toxification (stress) hypothesis of aging, we have investigated the effects of EGb761 on hippocampal neuronal injury and carbonyl stress of aging rats. Methods Seventy-two Wister male rats were randomly assigned into six groups (n = 12), normal control (NC), model control (MC), vitamin E (VE, 60 mg/kg) group, EGb761 low doses (GBEL, 8.75 mg/kg), EGb761 moderate doses (GBEM, 17.5 mg/kg), and EGb761 high doses (GBEH, 35 mg/kg). Except the NC, the other groups were subject to subcutaneous administration of 0.5% D-gal (10 ml/kg/day) for 6 weeks to induce aging model. The study detected cognitive impairment in rats by Morris water maze test and the contents of superoxidase dismutase (SOD), malondialdehyde (MDA), total antioxidant capacity (T-AOC) by the related kits. The level of 4-hydroxy-2-nonenal (4-HNE) protein adducts in rat brain was detected, and the ultrastructure of hippocampus was observed. Results The EGb761 treatment groups significantly improved the spatial learning and memory of rats. Moreover, EGb761 treatment could reduce hippocampal neuronal damage based on histopathological and ultrastructural observation. Further studies have proved that these activities are remarkably related with the reducing level of MDA, protein carbonyl and lipofuscin, and 4-HNE protein expression, as well as the increasing of SOD and T-AOC content. Furthermore, EGb761 improves telomerase activity by detecting telomerase activity in the brain of aging rats. Conclusion Our data indicate that EGb761 is an effective agent against D-gal-induced hippocampal neuronal loss owing to its antioxidative as well as carbonyl stress properties. Meanwhile, the carbonylation hypothesis is confirmed that the high level of 4-HNE may cause age-related neurodegenerative disorders.
Spruce Snowshoe Hare Red Squirrel Lynx Coyote Red Fox Ground Squirrel Zooplankton Krill Pelagic Fish Orca Seal Baleen Whale

This work provides the first unifying theoretical framework for node (positional) embeddings and structural graph representations, bridging methods like matrix factorization and graph neural networks. Using invariant theory, we show that the relationship between structural representations and node embeddings is analogous to that of a distribution and its samples. We prove that all tasks that can be performed by node embeddings can also be performed by structural representations and vice-versa. We also show that the concept of transductive and inductive learning is unrelated to node embeddings and graph representations, clearing another source of confusion in the literature. Finally, we introduce new practical guidelines to generating and using node embeddings, which fixes significant shortcomings of standard operating procedures used today.
A Correlation Study between Performance-Based Tests with the WOMAC Index and SF-36 in Pre-operative Total Hip Arthroplasty Patients

INTRODUCTION: The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) is a self-administered questionnaire that assesses pain, joint stiffness and disability in patients suffering from osteoarthritis of the hip and knee. The WOMAC index is validated for patients with osteoarthritis and is endorsed by the American Academy of Orthopaedic Surgeons’ Committee on Outcome Studies for lower extremity arthoplasty evaluation. However, the WOMAC index has limitations; it does not measure the actual function of patients. Standardized functional testing of patients with osteoarthritis undergoing total hip arthroplasty (THA) has never been established and is currently being evaluated via the physical functioning domain of the WOMAC and Short Form 36 questionnaire (SF-36). Accordingly, this study aims to evaluate the relationship between pre-operative performance-based tests with the WOMAC index and SF-36 questionnaire of those patients undergoing THA.
Multilevel Analysis of PISA 2003 with Influence on Achievement from Education Index of Countries and Time Studying of Students

Starting from 2000, the Programme on International Student Assessment (PISA) is held by the Organization for Economic Co-operation and Development (OECD) for the 15-year-old every three years. The sample includes over 270,000 participants of 41 countries in the PISA 2003 database aimed at evaluating mathematics and problem-solving ability. Most of the studies on the database are analyses of descriptive statistics, however, the database has the characteristics of hierarchical properties. It is necessary to use hierarchical linear model (HLM) of two levels to analyze the relation between the variables of countries and students. The unit in level-1 is students. The variables belonging to the level-1 are the score of mathematics cognition and the time studying mathematics homework outside the regular mathematics classes. As to the level-2, the unit is countries and the variable is Education Index (EI) from Human Development Reports (HDR) of United Nations Development Programme (UNDP). Also, in considering of the differences between OECD countries and non-OECD countries, the database is divided into two groups. Therefore, the purpose of this study is to investigate the PISA 2003 database by HLM of two levels analysis and to provide some suggestions in education and recommendations for future research. Key-Words: PISA, HLM, mathematics achievement, education index, mathematics homework.
Impact of Land Cover Types on Riverine CO2 Outgassing in the Yellow River Source Region

Under the context of climate change, studying CO2 emissions in alpine rivers is important because of the large carbon storage in these terrestrial ecosystems. In this study, riverine partial pressure of CO2 (pCO2) and CO2 emission flux (FCO2) in the Yellow River source region (YRSR) under different landcover types, including glaciers, permafrost, peatlands, and grasslands, were systematically investigated in April, June, August, and October 2016. Relevant chemical and environmental parameters were analyzed to explore the primary controlling factors. The results showed that most of the rivers in the YRSR were net CO2 source, with the pCO2 ranging from 181 to 2441 μatm and the FCO2 ranging from −50 to 1574 mmol m−2 d−1. Both pCO2 and FCO2 showed strong spatial and temporal variations. The highest average FCO2 was observed in August, while the lowest average was observed in June. Spatially, the lowest FCO2 were observed in the permafrost regions while the highest FCO2 were observed in peatland. By integrating seasonal changes of the water surface area, total CO2 efflux was estimated to be 0.30 Tg C year−1. This indicates that the YRSR was a net carbon source for the atmosphere, which contradicts previous studies that conclude the YRSR as a carbon sink. More frequent measurements of CO2 fluxes, particularly through several diel cycles, are necessary to confirm this conclusion. Furthermore, our study suggested that the riverine dissolved organic carbon (DOC) in permafrost (5.0 ± 2.4 mg L−1) is possibly derived from old carbon released from permafrost melting, which is equivalent to that in peatland regions (5.1 ± 3.7 mg L−1). The degradation of DOC may have played an important role in supporting riverine CO2, especially in permafrost and glacier-covered regions. The percent coverage of corresponding land cover types is a good indicator for estimating riverine pCO2 in the YRSR. In view of the extensive distribution of alpine rivers in the world and their sensitivity to climate change, future studies on dynamics of stream water pCO2 and CO2 outgassing are strongly needed to better understand the global carbon cycle.
Honor among Thieves: Towards Understanding the Dynamics and Interdependencies in IoT Botnets

In this paper, we analyze the Internet of Things (IoT) Linux malware binaries to understand the dependencies among malware. Towards this end, we use static analysis to extract endpoints that malware communicates with, and classify such endpoints into targets and dropzones (equivalent to Command and Control). In total, we extracted 1,457 unique dropzone IP addresses that target 294 unique IP addresses and 1,018 masked target IP addresses. We highlight various characteristics of those dropzones and targets, including spatial, network, and organizational affinities. Towards the analysis of dropzones' interdependencies and dynamics, we identify dropzones chains. Overall, we identify 56 unique chains, which unveil coordination (and possible attacks) among different malware families. Further analysis of chains with higher node counts reveals centralization. We suggest a centrality-based defense and monitoring mechanism to limit the propagation and impact of malware.
Addiction is a brain disease, and it doesn’t matter: Prior choice in drug use blocks leniency in criminal punishment.

Our aim was to explore how (neuro)scientific understanding of addiction as a brain-disease impacts criminal sentencing decisions in courts in England and Wales, where legal rules concerning intoxication, prior-fault and mental disease conflict, and sentencing guidelines lack clarity. We hypothesized that despite significant neuropsychiatric overlap of addiction and other brain-disorders, variables in relation to etiology would moderate magistrates’ sentencing decisions in cases involving addicted offenders. Using a questionnaire-based, quantitative design, and combining frequentist and Bayesian analysis approaches, we probed court magistrates’ sentencing decisions, and underlying rationale, for defendants presenting with brain damage resulting from a (fictional) disease, addiction to heroin, or more complex, mixed etiologies. When identical neuropsychiatric profiles resulted from disease, but not heroin addiction, prison sentences were significantly reduced. Study 1 (N=109) found the pivotal factor preventing addiction from mitigating sentences was perceived choice in its acquisition; removing choice from addiction increased the odds of sentence reduction (~20- fold) and attaching choice to disease aggravated or reversed earlier leniency. Study 2 (N=276) replicated these results and found that when heroin use led to disease or vice versa, magistrates found middle ground. These differences were independent of the age of first drug use. Finally, evidence of addiction was more likely to evoke punishment considerations by magistrates, rather than rehabilitation. Consistent with legal rules relating to intoxication but running counter to norms around mental-illness and choice, our results demonstrate the need for greater clarity in sentencing guidance on addiction specifically, and mental disorders more generally.
“And the winner is...” – Representing awards on the Web of Data

Awards are a particular kind of events happening in domains as various as entertainement, sport, and even scientific conferences. Here, we present an approach to model events on the Web of Data, and to extract event information about music artists from Wikipedia categories, combining (1) data extraction using background knowledge, and (2) machine learning with the Google Prediction API.
Systematic Literature Review Protocol: Data Dissemination in Large-cardinality Social Graphs

In the problem area of real-time message delivery there are very strict requirements on what is considered to be "real time" [1]. These requirements are especially hard to uphold for large-scale systems which social media applications usually are. As the overall amount of Internet traffic continues to increase [2], the load on social media applications also increases, meaning that new problems arise over time. One of these problems is the clusterization of social graphs, the concept that interactions in social media applications are built on. Clusterization happens when select producers start to attract many consumers, forming clusters, or large-cardinality local social graphs. Therefore, even though the requirements for data dissemination through all the social graphs are the same, the laws governing message delivery through small and large cardinality graphs are completely different. While these laws have not yet been clearly defined, their effect on the architecture of social media applications is great. As a result, the problem was recognized by companies in industry [3], and multiple solutions were proposed and developed [4]–[6]. This study applies the Systematic Literature Review (SLR) methodology [7] to investigate the challenges of data dissemination in large-cardinality social graphs. Since no past SLR has been found regarding the topic, it was chosen to conduct a systematic review as a reliable tool [8] aimed at identifying gaps in previous research, summarizing existent evidence and positioning future research.
Reducing Computational Time using Radix-4 in 2’s Complement Rectangular Multipliers

This paper presents a method to spped up Booth encoded multipliers by cing the size of Partial product array using Radix – 4 Modified Booth encoded multiplier . This method is used for higher radices encoding for any size of mxn multiplications This reduction may allow for a faster compression of the partial product array and regular layouts. This technique is of particular interest in all multiplier designs, but especially in short bit-width two’s complement multipliers for high-performance embedded cores. With the extra hardware of a (short) 3-bit addition, and the simpler generation of the first partial product row, we have been able to achieve a delay for the proposed scheme within the bound of the delay of a standard partial product row generation. We evaluated the proposed approach by comparison with some other possible solutions; the results based on a rough theoretical analysis and on logic synthesis showed its efficiency in terms of both area and delay.
Subformula Caching for Model Counting and Quantitative Program Analysis

Quantitative program analysis is an emerging area with applications to software reliability, quantitative information flow, side-channel detection and attack synthesis. Most quantitative program analysis techniques rely on model counting constraint solvers, which are typically the bottleneck for scalability. Although the effectiveness of formula caching in expediting expensive model-counting queries has been demonstrated in prior work, our key insight is that many subformulas are shared across non-identical constraints generated during program analyses. This has not been utilized by prior formula caching approaches. In this paper we present a subformula caching framework and integrate it into a model counting constraint solver. We experimentally evaluate its effectiveness under three quantitative program analysis scenarios: 1) model counting constraints generated by symbolic execution, 2) reliability analysis using probabilistic symbolic execution, 3) adaptive attack synthesis for side-channels. Our experimental results demonstrate that our subformula caching approach significantly improves the performance of quantitative program analysis.
University of Southern Denmark Three Tails of Organizational Innovation: from the Value Creation Perspective

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Multidimensionality of Spirituality: A Qualitative Study among Secular Individuals

This study examines the multidimensionality of spirituality by comparing the applicability of two models—the five-dimensional model of religiosity by Huber that we have extended with a sixth dimension of ethics and the three-dimensional spirituality model by Bucher. This qualitative study applied a semi-structured interview guideline of spirituality to a stratified sample of N = 48 secular individuals in Switzerland. To test these two models, frequency, valence, and contingency analysis of Mayring’s qualitative content analysis were used. It could be shown that Bucher’s three-dimensional model covers only about half of the spirituality codes in the interviews; it is especially applicable for implicit and salient spiritual aspects in general, as well as for spiritual experience in specific. In contrast, the extended six-dimensional model by Huber could be applied to almost all of the spirituality-relevant codes. Therefore, in principle, the scope of this six-dimensional model can be expanded to spirituality. The results are discussed in the context of future development of a multidimensional spirituality scale that is based on Huber’s Centrality of Religiosity by extending the religiosity concept to spirituality without mutually excluding these concepts from each other.
Modeling Trends of Airborne Particulate Matter by using Support Vector Machines

Monitoring, modeling and forecasting of air quality parameters are important topics in environmental and health research due to their impact caused by exposing to air pollutants in urban environments. The aim of this article is to show that forecast of daily airborne pollution using support vector machines (SVM) is feasible in regression mode. Results are presented using data measurements of Particulate Matter of aerodynamical size on the order of 10 and 2.5 micrograms (PMx) in London-Bloomsbury at south England.
A network-based approach to evaluate the performance of football teams

The striking proliferation of sensing technologies that provide high-fidelity data streams extracted from every game, induced an amazing evolution of football statistics. Nowadays professional statistical analysis firms like ProZone and Opta provide data to football clubs, coaches and leagues, who are starting to analyze these data to monitor their players and improve team strategies. Standard approaches in evaluating and predicting team performance are based on history-related factors such as past victories or defeats, record in qualification games and margin of victory in past games. In contrast with traditional models, in this paper we propose a model based on the observation of players’ behavior on the pitch. We model a the game of a team as a network and extract simple network measures, showing the value of our approach on predicting the outcomes of a long-running tournament such as Italian major league.
Neural Tree Kernel Learning

We propose an interpretable and scalable kernel, Neural Tree Kernel , which combines neural networks with the principles of decision trees for developing kernel methods which are both, highly ﬂexible and interpretable. Speciﬁcally, the Neural Tree Kernel transforms the inputs of base kernels, such as RBF kernels, through the designed neural trees. The proposed kernel operates as an independent unit and can be easily applied as a drop-in replacement for any base kernel in a kernel-based model, such as a Gaussian Process (GP). To validate the effectiveness of our Neural Tree Kernel , we conduct classiﬁcation experiments on 20 datasets from the UCI repository and show the promising performance of our model. We also demonstrate the interpretability of our kernel in a classiﬁcation task and its practical usefulness in automating machine learning for natural language tasks (Appendix A).
New perspectives on lagomorph and rodent biochronology in the Anza-Borrego Desert of southern California, USA

Faunal compilations and biochronologies of the late Pliocene to early Pleistocene often include some or all of the Anza-Borrego Desert records of Lepus, Microtus with five closed triangles, Microtus meadensis, and Lasiopodomys, especially because they are among the oldest, if not the oldest, reported records for those taxa in North America. The purported Lepus specimens are represented by three partial dentaries with incomplete dentitions, each retaining the third premolar, one of which is incomplete. The arvicoline specimens include one edentulous dentary and three isolated lower first molars, one of which is incomplete. We provide a detailed review of background documentation and identify inaccuracies in taxonomic assignment, stratigraphic origin, and general curatorial documentation that affect the identity and reliability of the individual specimens and have important ramifications for Pliocene-Pleistocene biochronology. As a result of our review, we reassign all Lepus records to Leporinae, genus and species indeterminate. The specimen of Microtus with five closed triangles cannot be placed in a reliable stratigraphic context, and the edentulous jaw is diagnosable only to Arvicolinae, genus and species indeterminate. The locality that produced the Microtus meadensis specimen is stratigraphically higher and in a different section of the AnzaBorrego Desert than previously reported, lowering the age of the specimen by nearly a million years. We retain the Lasiopodomys designation although we are hesitant to accept 'Lasiopodomys' as a higher order taxon; the specimen is from reversed polarity sediments dating to between 1.77 and 1.07 Ma, making it the oldest reported specimen of the Lasiopodomys morphotype. Lyndon K. Murray. Jackson School of Geosciences, Vertebrate Paleontology Laboratory, Texas Natural Science Center, The University of Texas at Austin R7600, J.J. Pickle Research Campus PRC 6, 10100 Burnet Road. Austin, Texas 78758 USA Current address: Colorado Desert District, 200 Palm Canyon Drive. Borrego Springs, California 92004 USA. lkmurray@parks.ca. gov Dennis R. Ruez, Jr. Department of Environmental Studies, One University Plaza, PAC 308, University of Illinois at Springfield, Springfield, Illinois 62703-5407druez2@uis.edu Christopher J. Bell. Jackson School of Geosciences, Department of Geological Sciences, 1 University Station, C 1100, The University of Texas at Austin, Austin, Texas 78712-0254 USA, cjbell@mail.utexas. edu PE Article Number: 14.3. 36A Copyright: Society of Vertebrate Paleontology November 2011 Submission: 15 June 2007. Acceptance: 27 March 2011 Murray, Lyndon K. , Ruez, Dennis R. Jr., and Bell, Christopher J. 2011. New perspectives on lagomorph and rodent biochronology in the Anza-Borrego Desert of southern California, USA. Palaeontologia Electronica Vol. 14, Issue 3; 36A:53p; palaeo-electronica.org/2011_3/12_murray/index.html MURRAY, RUEZ, AND BELL: CALIFORNIA BIOCHONOLOGY
Reformation of higher education in the EaP countries: cultural dimensions under the shadow

Dipartimento di Studi Politici e Sociali UNIVERSITÀ DEGLI STUDI DI SALERNO ABSTRACT In the article, the complexity and interconnection of the cultural characteristics that impact higher education institutions in the Eastern Partnership countries are presented. The six countries, united in 2009 by Brussels in one block, have a similar policy of the reformation of their higher education systems which has a distinct European vector. The paper is designed to study the higher education reforms and higher through the prism of cultural dimensions portrayed at national and institutional levels. To perform this task Geert Hofstede’s cultural value dimensions and World Value Survey database (2010-2014) were employed as well as findings of the individual researchers. In short, this paper aims to discuss the culture implication in academic environment and changes occurring within the higher education institutions of the six countries of Eastern partnership and to explain them by use of G. Hofstede’s cultural dimensions. Considering higher education institutions performance with the help of cross-cultural analysis can facilitate analysis of the education practices, teaching and learning methods, readiness to institutional change and external challenges, policies and practices undertaken by academic systems to cope with the external and internal academic environment and modes of the implementing the reformation strategies in the selected countries.