Miracle-dz/UniFAR-FTUs huggingface dataset:
The Nature and Extent of Collaboration Between Park and Recreation Agencies and Higher Education Institutions

It has long been recognized that collaboration between higher education institutions and community organization has the potential to create win-win situations with both accruing significant benefits. The park and recreation field seems to be particularly well-suited to take advantage of collaborative benefits given the proliferation of academic programs over the past 20 years, along with a subsequent increase in curricula-based field work such as practical, service learning based courses, and student internships. However, despite these potential benefits, collaboration is often viewed as time consuming and difficult to maintain. This paper explores the nature and extent of university-community collaboration in the park and recreation field. A total of 800 recreation practitioners and 411 faculty were asked to rate the importance of 31 areas of collaboration for the field. For each area, subjects were asked whether they were actively collaborating with practitioners or faculty. Respondents to the survey included 307 practitioners (39%) and 174 faculty (42%), for an overall response rate of 40%. Results indicated that 24 of the 31 areas of collaboration were rated at least “somewhat important” for the field of park and recreation. Collaboration on internships, pre-internships, and service learning were the most important areas, as was interaction at conferences and professional workshops. Using park and recreation agencies for field-based research, using practitioners as guest speakers in academic classes, offering/taking advantage of continuing education/professional development opportunities at colleges and universities, and using the park and recreation agency to enhance teaching opportunities were also rated as important for the field. More than half of the subjects in this study reported actively collaborating in these areas. Results revealed that past collaboration was a significant predictor of future intent to collaborate (p<0.0001). There were no significant differences between ratings of importance and performance for any of the 31 areas of collaboration listed. However, less than half of the respondents reported that they were actively collaborating on specific research and evaluation projects, even while reporting that these types of collaborations were somewhat important for the field as a whole. Finally, faculty generally rated collaboration as more important than practitioners, with 17 of the 31 areas of collaboration showing significant differences between the groups (p<0.05).
Adaptive Estimation of Heteroscedastic Money Demand Model of Pakistan

For the problem of estimation of Money demand model of Pakistan, money supply (M1) shows heteroscedasticity of the unknown form. For estimation of such model we compare two adaptive estimators with ordinary least squares estimator and show the attractive performance of the adaptive estimators, namely, nonparametric kernel estimator and nearest neighbour regression estimator. These comparisons are made on the basis standard errors of the estimated coefficients, standard error of regression, Akaike Information Criteria (AIC) value, and the Durban-Watson statistic for autocorrelation. We further show that nearest neighbour regression estimator performs better when comparing with the other nonparametric kernel estimator.
Managing Large Scale Unstructured Data with RDBMS

With the rapid development of information technology, the needs of unstructured data storage and processing is growing rapidly, which develops a new requirement for the database storage. Traditional row-oriented relational databases appear to be inadequate for the data query and analysis. In this paper, we propose a novel approach to store the unstructured data in a relational database. By splitting the VALUE property of the unstructured KEY/VALUE data and recreating the two-dimensional data, the original data can be stored in relational databases. The system introduced in this paper is designed to handle this task. In addition, this system rebuilds the SQL as its query language, which makes it compatible with relational databases. In experiments of the query for unstructured data, the outcomes show that the system is good at decomposing the SQL statement submitted by users, and generating the corrected sub-query statements. The results of the experiments show that the performance of this system is good.
Integrating Entity and Attribute for Object Similarity

In this paper, we propose an object similarity algorithm (OSA) to address the problem of similarity calculation in the complex graph network by integrating the entity and attribute similarity of the graph node. The proposed method can solve the similarity judgment of the objects that are lack of links or missing attributes by accident or intention. Exper- imental results have showed that our proposed object similarity method has the advantage of assessing the similarity of objects comprehensively, which can correct the one-sided judgment errors and improves the ability to distinguish similari- ty of graph objects; the method can also be used for homogeneous or heterogeneous networks.
xLiD-Lexica: Cross-lingual Linked Data Lexica

In this paper, we introduce our cross-lingual linked data lexica, called xLiD-Lexica, which are constructed by exploiting the multilingual Wikipedia and linked data resources from Linked Open Data (LOD). We provide the cross-lingual groundings of linked data resources from LOD as RDF data, which can be easily integrated into the LOD data sources. In addition, we build a SPARQL endpoint over our xLiD-Lexica to allow users to easily access them using SPARQL query language. Multilingual and cross-lingual information access can be facilitated by the availability of such lexica, e.g., allowing for an easy mapping of natural language expressions in different languages to linked data resources from LOD. Many tasks in natural language processing, such as natural language generation, cross-lingual entity linking, text annotation and question answering, can benefit from our xLiD-Lexica.
Midazolam anesthesia protects neuronal cells from oxidative stress-induced death via activation of the JNK-ERK pathway

Midazolam is an anesthetic agent commonly used during clinical and surgical procedures, which has been shown to exert ROS-suppressing and apoptosis-modulating pharmacological activities in various cellular systems. However, the effects of midazolam on oxidative stress in neuronal cells require elucidation. The present study investigated the effects of midazolam on buthionine sulfoximine (BSO)- and hydrogen peroxide (H2O2)-induced oxidative stress in primary cortical neuronal cells. In addition, the effects of midazolam on middle cerebral artery occlusion (MCAO) in mice and on ethanol-induced neuroapoptosis in the brains of neonatal mice were determined. Subsequently, cell viability was detected using the MTT assay; intracellular reactive oxygen species (ROS) generation was determined using the 2′,7′-dichlorodihydrofluorescein diacetate method with confocal microscopy; terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining was conducted to detect apoptotic cells; immunohistochemistry was performed to detect activated caspase-3; neuronal deficit and infarct volume analyses were conducted; and quantitative polymerase chain reaction and western blotting were performed to detect the expression levels of genes and proteins associated with apoptosis and cell survival pathways. The results demonstrated that BSO (10 mM) and H2O2 (1 mM) suppressed proliferation of cortical neuronal cells by inducing apoptosis. These effects were suppressed following treatment with midazolam in a dose-dependent manner. In addition, BSO and H2O2 induced ROS generation in neuronal cells; however, this was effectively suppressed by midazolam (100 µM). Beneficial synergistic effects were detected when midazolam was used in combination with the known antioxidant trolox. BSO and H2O2 also suppressed the protein expression levels of c-Jun N-terminal kinases (JNK), phosphorylated (p)JNK, extracellular signal-regulated kinases (ERK)1/2, pERK1/2, AKT and nuclear factor-κB; however, expression was recovered following treatment with midazolam. Midazolam also activated protein kinase C-ε, which was suppressed by BSO, in cortical neuronal cells. In MCAO mice, midazolam post-conditioning significantly suppressed infarct size and reduced the number of TUNEL-positive cells. In addition, the expression levels of caspase-3 and poly (ADP-ribose) polymerase were suppressed in a dose-dependent manner. In neonatal mice, midazolam reduced ethanol-induced activated caspase-3 staining and apoptotic TUNEL staining. The results of the present study demonstrated that midazolam may protect against neuronal degeneration and neuroapoptosis induced by physiological and oxidative stress.
New connections between 4D and 5D black holes

A simple equality is proposed between the BPS partition function of a general 4D IIA Calabi-Yau black hole and that of a 5D spinning M-theory Calabi-Yau black hole. Combining with recent results then leads to a new relation between the 5D spinning BPS black hole partition function and the square of the N = 2 topological string partition function.
Dual-Stock Structure , Analyst Following , and Corporate Governance

We examine the effects of internal and external corporate governance and monitoring mechanisms on the dual-class status and the firm value of dual-class firms. Employing 736 dual-class firms and 7,027 single-class firms during the period 1996-2002, we find that dual-class firms tend to be larger, and have higher director ownership, higher institutional ownership, lower blockholdings, and a smaller fraction of independent directors on their boards than single-class firms. In addition, we observe that dual-class firms are followed by a smaller number of security analysts. After correcting for endogeneity bias, our results show that not only firms with higher analyst coverage, but also firms with higher analyst following and a lower wedge, measured as the difference between voting rights and cash flow rights, are strongly associated with Tobin’s q. In contrast, blockholders’ ownership, board independence, and institutional ownership play a relatively insignificant role in enhancing dual-class firm value. We interpret these results to suggest that security analysts are one of the most effective monitoring mechanisms that influence both the dual-class choice and firm value. Our results are not attributed either to the difference in firm size or to an industry effect.
The Early Multicolor Afterglow of GRB 050502a: Possible Evidence for a Uniform Medium with Density Clumps

The 2 m robotic Liverpool Telescope reacted promptly to the gamma-ray burst GRB 050502a, discovered by INTEGRAL, and started observing 3 minutes after the onset of the burst. The automatic identification of a bright afterglow with r' ~ 15.8 mag triggered, for the first time, an observation sequence in the BVr'i' filters during the first hour after a GRB. Observations continued for ~1 day using the RoboNet-1.0 network of 2 m robotic telescopes. The light curve in all filters can be described by a simple power law with index of 1.2 ± 0.1. We find evidence for a bump rising at t ~ 0.02 days in all filters. From the spectrum and the light curve, we investigate different scenarios and find possible evidence for a uniform circumburst medium with clumps in density, as in the case of GRB 021004. Other interpretations of such bumps, such as the effect of energy injection through refreshed shocks or the result of a variable energy profile, are less favored. The optical afterglow of GRB 050502a is likely to be the result of slow electron cooling, with the optical bands lying between the synchrotron peak frequency and the cooling frequency.
A Non-Cyclic Prefixed MIMO-OFDM System Based on a Recursive Algorithm of Joint Channel Estimation and Data Detection

We propose in this paper a non-cyclic prefixed multiple-input multiple-output orthogonal frequency division multiplexing (non-cp MIMO-OFDM) system based on a recursive algorithm of joint channel estimation and data detection. Unlike in the traditional cyclic prefixed MIMO-OFDM system, the transmitted sequence of the proposed system is given in the way that block-type pilot sequences and OFDM symbols have been arranged alternately without any cyclic prefix (CP) before each OFDM symbol. Moreover, a recursive algorithm of joint channel estimation and data detection (recursive-JCEDD) based on interference cancellation is proposed for the corresponding receivers. Simulation results show that the proposed system based on the recursive-JCEDD algorithm achieves lower bit error rate (BER) and higher information data rate than the traditional cyclic prefixed MIMO-OFDM system with least square (LS) or iterative LS channel estimation algorithm.
Using time-of-flight range data for occlusion handling in augmented reality

One of the main problems of monoscopic video see-through augmented reality (AR) is the lack of reliable depth information. This makes it difficult to correctly represent complex spatial interactions between real and virtual objects, e.g., when rendering shadows. The most obvious graphical artifact is the incorrect display of the occlusion of virtual models by real objects. Since the graphical models are rendered opaquely over the camera image, they always appear to occlude all objects in the real environment, regardless of the actual spatial relationship. In this paper, we propose to utilize a new type of hardware in order to solve some of the basic challenges of AR rendering. We introduce a depth-of-flight range sensor into AR, which produces a 2D map of the distances to real objects in the environment. The distance map is registered with high resolution color images delivered by a digital video camera. When displaying the virtual models in AR, the distance map is used in order to decide whether the camera image or the virtual object is visible at any position. This way, the occlusion of virtual models by real objects can be correctly represented. Preliminary results obtained with our approach show that a useful occlusion handling based on time-of-flight range data is possible.
Theorizing policy-industry processes: A media policy field approach

This article develops a theoretical perspective to study the conditions for media policy formation under the condition of digitalization – the Media Policy Field approach – building on an organizational field approach in combination with theories of policy development. The theory of strategic action fields offers a meso-level view of how actors in media fields interact and how their respective opportunities for influencing policy are structured by the state of the field and their respective positions. This theory is linked with the Multiple Streams Approach, which maintains that change occurs when policy entrepreneurs connect problem, policy and politics streams, and create policy windows. The Media Policy Field approach proposes three analytical foci for the study of current media policy processes: collective frames, incumbent and challenger roles and policy windows. Empirical strategies for pursuing this theoretical programme are discussed.
Using Genetic Algorithms for 3 D Object Recognition

We investigate the application of genetic algorithms for recognizing 3D objects from two-dimensional intensity images, assuming orthographic projection. The recognition strategy is based on the recently proposed theory of algebraic functions of views. According to this theory, the variety of 2D views depicting a 3D object under the case of orthographic projection can be expressed as a linear combination of a small number of 2D views of the object. This suggests a powerful strategy for performing object recognition: novel 2D views of a 3D object can be recognized by simply matching them to linear combinations of known (reference) 2D views of the object. The main advantage of this strategy is that 3D models are not required. Given an unknown view of an object, the goal of the recognition procedure is to find the coefficients of the linear combination scheme. In this paper, we propose using genetic algorithms for searching the space of coefficients efficiently. Interval arithmetic is used to restrict genetic search in the most feasible regions of the coefficients’ space only. Ke ywords: object recognition, algebraic functions of views, genetic algorithms, interval arithmetic
Deep Learning of Invariant Spatio-Temporal Features from Video

We present a novel hierarchical, distributed model for unsupervised learning of invariant spatio-temporal features from video. Our approach builds on previous deep learning methods and uses the convolutional Restricted Boltzmann machine (CRBM) as a basic processing unit. Our model, called the Space-Time Deep Belief Network (ST-DBN), alternates the aggregation of spatial and temporal information so that higher layers capture longer range statistical dependencies in both space and time. Our experiments show that the ST-DBN has superior performance on discriminative and generative tasks including action recognition and video denoising when compared to convolutional deep belief networks (CDBNs) applied on a per-frame basis. Simultaneously, the ST-DBN has superior feature invariance properties compared to CDBNs and can integrate information from both space and time to fill in missing data in video.
Antithrombotic Treatment for Recurrent Miscarriage

AbstractCombined use of heparin and aspirin is frequently prescribed for treatment of recurrent miscarriage (RM) in patients with antiphospholipid syndrome (APS), or in those without apparent cause of RM other than thrombophilia; however, this strategy is largely based on expert opinion and has not been well studied. The option for the use of different antithrombotic therapies to improve live birth remains unclear. In this network meta-analysis, we incorporated direct and indirect evidence to evaluate effects of different antithrombotic treatments on prevention of pregnancy losses.We searched PubMed and Embase for randomized clinical trials comparing effects of at least 2 antithrombotic treatments on live birth in RM patients published from 1965 through the early of May 2015. Potential risk bias of eligible trials was evaluated according to the Cochrane Collaboration guidelines. Bayesian network meta-analysis was used to estimate relative effects on live birth.A total of 19 trials involving 2391 RM patients with or without thrombophilia and 543 with APS were included. No beneficial effect of antithrombotic treatment was observed either in RM patients with or without thrombophilia or in patients with APS; however, for patients with or without thrombophilia, low molecular weight heparin therapy had the greatest probability (61.48%) of being the best option in terms of live birth; for patients with APS, unfractionated heparin plus aspirin was the superior treatment for RM with the highest possibility (75.15%) of being top 2 places for reducing pregnancy losses. Aspirin was inferior in both groups.Our results do not support the use of combined low molecular weight heparin and aspirin for RM treatment, and suggested aspirin may have negative effects for lowering the risk of pregnancy loss.
Ionospheric plasma density variations observed at Mars by MAVEN/LPW

We report on initial observations made by the Langmuir Probe and Waves relaxation soundingexperiment on board the NASA Mars Atmosphere and Volatile EvolutioN (MAVEN) mission. These measurements yield the ionospheric thermal plasma density, and we use these data here for an initial survey of its variability. Studying orbit‐to‐orbit variations, we show that the relative variability of the ionospheric plasma density is lowest at low altitudes near the photochemical peak, steadily increases toward higher altitudes and sharply increases as the spacecraft crosses the terminator and moves into the nightside. Finally, despite the small volume of data currently available, we show that a clear signature of the influence of crustal magnetic fields on the thermal plasma density fluctuations is visible. Such results are consistent with previously reported remote measurements made at higher altitudes, but crucially, here we sample a new span of altitudes between ∼130 and ∼300 km using in situ techniques.
Strategies for identifying genes underlying drug abuse susceptibility.

It is becoming widely accepted that most, if not all, drug responses are subject to influence by genetic factors. The magnitude, duration, and even the quality or direction of response can differ among individuals with differing genotypes. Most drug responses are not simple genetic traits; rather, multiple genes can be demonstrated to influence a given response. In addition, any gene is likely to affect multiple traits, a condition called pleiotropism. To the extent that two traits are pleiotropically influenced by some of the same genes, they are said to be genetically correlated. Use of genetic animal models has achieved significant progress in the analysis of drug response traits.
Arbitrarily Degenerate Helium White Dwarfs as Donors in AM Canum Venaticorum Binaries

We apply the Deloye & Bildsten isentropic models for donors in ultracompact low-mass X-ray binaries to the AM CVn population of ultracompact, interacting binaries. The mass-radius relations of these systems' donors in the mass range of interest (M2 < 0.1 M⊙) are not single-valued, but parameterized by the donor's specific entropy. This produces a range in the relationships between system observables, such as orbital period Porb and mass transfer rate . For a reasonable range in donor specific entropy, can range over several orders of magnitude at fixed Porb. We determine the unique relation between and M2 in the AM CVn systems with known donor-to-accretor mass ratios q = M2/M1. We use structural arguments, as well as each system's photometric behavior, to place limits on and M2 in each. Most systems allow a factor of about 3 variation in , although V803 Cen, if the current estimates of its q are accurate, is an exception and must have M2 ≈ 0.02 M⊙ and ≈ 10-10 M⊙ yr-1. Our donor models also constrain each donor's core temperature (Tc) range and correlate Tc with M2. We examine how variations in donor specific entropy across the white dwarf family of AM CVn systems affects this population's current Galactic distribution. Allowing for donors that are not fully degenerate produces a shift in systems toward longer Porb and higher , increasing the parameter space in which these systems can be found. This shift increases the fraction of systems whose Porb is long enough that their gravity wave (GW) signal is obscured by the background of detached double white dwarf binaries that dominate the GW spectrum below a frequency of ≈2 mHz.
A Development Process of KMS Based on Systems Engineering Methodology

Based on the Hall three dimensions structure and Knowledge Management Maturity Model, a methodological framework on knowledge systems engineering was analyzed to guide the implementation of knowledge management project. With the theories and methods of project management, organizational management, knowledge management and systems engineering, the development process of knowledge management system was further analyzed and summarized. Finally, the development process of knowledge management system including eight key steps was established based on methodological framework and given a detailed analysis for each key step. The practice has shown this process could provide a clear theoretical basis and method for the research and development of knowledge management system. Keywords-Knowledge Management System; Development Process; Systems Engineering; Methodology