Miracle-dz/UniFAR-FTUs huggingface dataset:
Autonomic regulation of brown adipose tissue thermogenesis in health and disease: potential clinical applications for altering BAT thermogenesis

From mouse to man, brown adipose tissue (BAT) is a significant source of thermogenesis contributing to the maintenance of the body temperature homeostasis during the challenge of low environmental temperature. In rodents, BAT thermogenesis also contributes to the febrile increase in core temperature during the immune response. BAT sympathetic nerve activity controlling BAT thermogenesis is regulated by CNS neural networks which respond reflexively to thermal afferent signals from cutaneous and body core thermoreceptors, as well as to alterations in the discharge of central neurons with intrinsic thermosensitivity. Superimposed on the core thermoregulatory circuit for the activation of BAT thermogenesis, is the permissive, modulatory influence of central neural networks controlling metabolic aspects of energy homeostasis. The recent confirmation of the presence of BAT in human and its function as an energy consuming organ have stimulated interest in the potential for the pharmacological activation of BAT to reduce adiposity in the obese. In contrast, the inhibition of BAT thermogenesis could facilitate the induction of therapeutic hypothermia for fever reduction or to improve outcomes in stroke or cardiac ischemia by reducing infarct size through a lowering of metabolic oxygen demand. This review summarizes the central circuits for the autonomic control of BAT thermogenesis and highlights the potential clinical relevance of the pharmacological inhibition or activation of BAT thermogenesis.
Coping With Dynamic Syntactic Strategies: An Experimental Environment for an Experimental Parser

An environment built around WEDNESDAY 2, a chart based parser is introduced. The environment is in particular oriented towards exploring dynamic aspects of parsing. It includes a number of specialized tools that consent an easy, graphics-based interaction with the parser. It is shown in particular how a combination of the characteristics of the parser(based on the lexicon and on dynamic unification) and of the environment allow a nonspecialized user to explore heuristics that may alter the basica control of the system. In this way, for instance, a psycholinguist may explore ideas on human parsing strategies, or a "language engineer" may find useful heuristics for parsing within a particular application.
Orientasi matlamat dan kebimbangan pra pertandingan di kalangan atlet hoki bawah 18 tahun / Rosli Saadan

The purpose of this research was to identify differences between goal orientation and pre-competition anxiety among under 18 hockey athletes. In addition, the differences of the level of goal orientation and pre-competition anxiety between groups were also analyzed. This study employed a quasi-experimental approach. 144 participants were selected as sample for this study. This study involved four groups in which three groups were experimental groups and one group was the control group. There were 36 respondents in each group. Experimental groups were given intervention before, while and after training session, while the control group was not given any intervention. Data were collected twice ; immediately before the training and an hour before the competition using Task and Ego Orientation in Sport Questionnaire (TEOSQ; Duda & Nicholls, 1992) and Revised Competitive State Anxiety Inventory-2 (CSAI-2R; Cox et al., 2003) survey. MANOVA analysis showed that there was significant difference between genders and dependent variables. This could be clearly seen from the values of Pillai’s trace = 0.260 and F value [(10, 127) = 4.453, p < 0.05]. Findings also showed that there were significant difference among groups in all the dependent variables as the value of Pillai’s trace = 0.527 and F value [(30, 387) = 2.746, p < 0.05]. Findings also showed that there were interaction between variables when the value of Pillai’s trace = 0.614 and F value [(30, 387) = 3.319, p < 0.05]. Findings also showed that there were significant difference between gender for pre-test orientation subscale [F (1,136) = 10.84, p < 0.05], pre-test ego orientation [F (1,136) = 9.117, p < 0.05], pre-test cognitive anxiety [F (1,136) = 16.23, p < 0.05] and post-test self-confidence [F (1,136) = 3.983, p < 0.05]. Post-hoc analysis comparison between groups revealed a significant difference between Task & Ego group and Ego group [F (3,136) = 0.010, p < 0.05], Task & Ego and Control group [F (3,136) = 0.006, p < 0.05]. For post-test task orientation subscale, there was significant difference between Task & Ego group and Task group [F (3,136) = 0.008, p < 0.05], Task group and Ego group [F (3,136) = 0.003, p < 0.05] and Task group and Control group [F (3,136) = 0.002, p < 0.05]. For pre-test ego orientation subscale, there was significant difference between Task & Ego group and Task group [F (3,136) = 0.001, p < 0.05], Task & Ego group and Ego group [F (3,136) = 0.038, p < 0.05]; Task & Ego group and Control group [F (3,136) = 0.001, p < 0.05] and Ego group and Control group [F (3,136) = 0.035, p < 0.05]. On the other hand, for post-test ego orientation subscale, there was significant difference between Task & Ego group and Task group [F (3,136) = 0.013, p < 0.05].
Photochemical production of ozone in Beijing during the 2008 Olympic Games

Abstract. As a part of the CAREBeijing-2008 campaign, observations of O 3 , oxides of nitrogen (NO x and NO y ), CO, and hydrocarbons (NMHCs) were carried out at the air quality observatory of the Peking University in Beijing, China during August 2008, including the period of the 29th Summer Olympic Games. The measurements were compared with those of the CAREBeijing-2006 campaign to evaluate the effectiveness of the air pollution control measures, which were conducted for improving the air quality in Beijing during the Olympics. The results indicate that significant reduction in the emissions of primary air pollutants had been achieved; the monthly averaged mixing ratios of NO x , NO y , CO, and NMHCs decreased by 42.2, 56.5, 27.8, and 49.7 %, respectively. In contrast to the primary pollutants, the averaged mixing ratio of O 3 increased by 42.2 %. Nevertheless, it was revealed that the ambient levels of total oxidant (O x = O 3 +NO 2 +1.5 NO z ) and NO z were reduced by 21.3 and 77.4 %, respectively. The contradictions between O 3 and O x were further examined in two case studies. Ozone production rates of 30–70 ppbv h −1 and OPEx of ~8 mole mole −1 were observed on a clear-sky day in spite of the reduced levels of precursors. In that case, it was found that the mixing ratio of O 3 increased with the increasing NO 2 /NO ratio, whereas the NO z mixing ratio leveled off when NO 2 /NO>8. Consequently, the ratio of O 3 to NO z increased to above 10, indicating the shift from VOC-sensitive regime to NO x -sensitive regime. However, in the other case, it was found that the O 3 production was inhibited significantly due to substantial reduction in the NMHCs. According to the observations, it was suggested that the O 3 and/or O x production rates in Beijing should have been reduced as a result of the reduction in the emissions of precursors during the Olympic period. However, the nighttime O 3 levels increased due to a decline in the NO-O 3 titration, and the midday O 3 peak levels were elevated because of the shift in the photochemical regime and the inhibition of NO z formation.
Using LSA and Association Rules to Enhance Web Image Annotation

Traditionally, image annotation was conducted by person, but this processing consumes huge amounts of human efforts. Moreover, it tends to have inconsistent explanations of the same image by different persons. To effectively automate the annotation procedure, we used latent semantic analysis (LSA) method to analyze the context of the accompanying web pages to obtain anecdotal vocabulary as a semantic enrichment of the target image. To enhance the pertinence of image annotation, we conducted a series of incremental treatments on LSA in order to evaluate the effectiveness of image annotation. The treatments included: LSA, Position Factor (PS) + LSA, clustering + LSA, PS + clustering + LSA and association rules. Results show that the adoption of position factors, and clustering has positive effects on image annotation. In particular, the application of association rules significantly increase precision value from 50 percent to 79 percent.
UML-based enhanced rich form generation

The Model Driven Development (MDD) has provided a new way of engineering today's rapidly changing requirements into the implementation. However, the development of the user interface (UI) part of an application has not benefited much from MDD although today's UIs are complex software components and play an essential role in the usability of an application. It is a common practice that developers create view forms manually by referring to entity beans to determine their content. However, such kind of manual creation is very error-prone and thus makes the system maintenance difficult. One promise in MDD is that we can generate code from UML models, but existing design models in MDD does not capture enough information that are required to generate desired UI fragments. This paper presents our approach addressing these issues. The approach makes it possible to generate complex UIs, rich view forms, that fully satisfy both designers and end-users and to enforce system access control.
Geographic Information System ( GIS ) Analysis of Ecosystem Response to Industrial Pollution in the Niepolomice Forest in Southern Poland 1

Years A nn ua l e m is si on , t on x 1 00 0 Abstract The Niepolomice Forest is located near the city of Krakow in southern Poland. Since the erection of large iron works in the 1950’s, the forest has suffered from heavy pollution with SO2 and industrial dusts containing heavy metals. During the past 10 years, the ecology of the Niepolomice Forest has been intensively studied and the impact of industrial pollution has been significantly reduced. With the advent of modern computer intensive techniques, data gathered in the past have been reanalyzed with respect to the spatial and temporal variations of the forest ecosystem response to industrial pollution. In addition, the effects of natural conditions (soil, vegetation) and industrial pollution (heavy metals, sulfur dioxide) upon the pine stands (tree volume increment, crown injuries) in the Niepolomice Forest were studied by using a geographic information system. Procedures of statistical analysis involving bootstrapping were developed. Results suggest the apparent fertilization of forest stands as a result of industrial pollution—an effect not revealed in former studies.
OPE-algebras and their modules

Vertex algebras formalize the subalgebra of holomorphic fields of a conformal field theory. OPE-algebras were proposed as a generalization of vertex algebras that formalizes the algebra of all fields of a conformal field theory. We prove some basic results about them: The state-field correspondence is an OPE-algebra isomorphism and Dong's lemma and the existence theorem hold for multiply local OPE-algebras; locality implies skew-symmetry; if skew-symmetry holds then duality implies locality for modules and they are equivalent for algebras. We define modules over OPE-algebras.
ISIL: Instant search-based indoor localization

As GPS signals may not be available indoor and can be blocked easily by obstacle, several localization techniques based on Wi-Fi have been proposed. Most of them require a pre-training step for known locations which is time-consuming and not practical for wide-scale deployment. This paper proposes an alternative approach for indoor localization based on the SSID of nearby access points (APs) at a specific location. The idea of this work is based on the observation that many AP's names contain information related to the location. Thus, the observable APs' names are mined via a search engine as a location indicator. The returned search results are analyzed and aggregated to predict the position of the location. Unlike existing localization algorithm, our approach is simple, yet requires no training time and is nearly independent of either Wi-Fi signals changes or mobile devices. To verify our approach, we conduct an experiment consisting of more than 3,000 locations spreading over 60,000 meters around Ho Chi Minh City (HCMC). This method can achieve an accuracy of up to 70 percent for exact address matching and up to 88 percent for nearby location with radius less than 100 meters.
A Distributed Cache Management Architecture for Mobile Computing Environments

In mobile computing caching plays a vital role owing to its ability to alleviate the performance and availability limitations of weakly-connected and disconnected operations. An efficient way to reduce query delay, save bandwidth and improve system performance is to cache the frequently accessed data objects at the local buffer of a mobile. Owing to the disconnection and mobility of the mobile clients, classical cache management strategies may be inappropriate for mobile environments. Generally, cache placement, cache discovery, cache consistency and cache replacement techniques constitute cache management in mobile environment. In this paper, we design a distributed cache management architecture which includes all the above techniques. The architecture also includes a location update procedure for a moving mobile client. The simulation results illustrate that our proposed architecture achieves lower latency and packet loss, reduced network bandwidth consumption, and reduced data server workload.
A DSL-Supported Workflow for the Automated Assembly of Large Stochastic Models

Dependability and performance analysis of modern systems is facing great challenges: their scale is growing, they are becoming massively distributed, interconnected, and evolving. Such complexity makes model-based assessment a difficult and time-consuming task. For the evaluation of large systems, reusable sub models are typically adopted as an effective way to address the complexity and improve the maintanability of models. Approaches based on Stochastic Petri Nets often compose sub models by state-sharing, following predefined "patterns", depending on the scenario of interest. However, such composition patterns are typically not formalized. Clearly defining libraries of reusable sub models, together with valid patterns for their composition, would allow complex models to be automatically assembled, based on a high-level description of the scenario to be evaluated. The contribution of this paper to this problem is twofold: on one hand we describe our workflow for the automated generation of large per formability models, on the other hand we introduce the TMDL language, a DSL to concretely support the workflow. After introducing the approach and the language, we detail their implementation within the Eclipse modeling platform, and briefly show its usage through an example.
Stress, Sleep, and Performance on Standardized Tests: Understudied Pathways to the Achievement Gap

Stress exposure, and subsequent biological responses to stress exposure, can negatively affect cognitive functioning and test performance. Stress exposure affects multiple biological systems, including sleep and the activity of the hypothalamic-pituitary-adrenal (HPA) axis and its primary hormonal product, cortisol. Sleep and cortisol interact with each other, and both affect cognitive performance. Stress, sleep, and cortisol also vary by race-ethnicity and socioeconomic status, and as a result, they may serve as potential pathways contributing to racial-ethnic and socioeconomic achievement gaps. Effects of stress on academic performance could occur either during the learning process or in response to the acute stress of testing. Interventions to limit stress exposure, reduce perceived stress, and promote optimal stress hormone levels and sleep may help students arrive in the classroom prepared to learn and to perform well on tests. These measures may particularly benefit low-income and minority students and may play a role in reducing achievement gaps.
k-Liveness With Disjunctive Stabilization : A Communication Fabric Case Study

We present a liveness verification framework that extendskLiveness algorithm with disjunctive stabilization constraints. We demonstrate effectiveness of our algorithm for verification of responseproperty for communication fabrics. We also provide an open-source impl ementation of our algorithm in the ABC framework. This framework can be used as a general model checker for liveness properties on any seque ntial circuit. Experiments are performed on industrially relevant public benchmarks, and preliminary results are very encouraging.
Composition analysis of A , C , G , T nucleotides in genes responsible for the Long QT Syndrome

Long QT syndrome (LQTS) is a congenital disorder characterized by a prolongation of the QT interval on ECG and a propensity to ventricular tachyarrhythmia, which may lead to syncope, cardiac arrest, or sudden death. LQTS is caused by mutations of the genes for cardiac potassium and sodium or calcium ion channels. 8 genes have been identified.LQT1 (KCNQ1), LQT2 (KCNH2), and LQT3 (SCN5A) account for most cases of LQTS, with estimated prevalence of 45%, 45%, and 7%, respectively. We have used the analogy of genome analysis and VIRUS (vital information recourse under siege) and analyzed Since KCNQ1, KCNH2 and SCN5A genes are playing an important role in LQTS disease, we have taken their nucleotide sequences in FASTA format and submitted them in Geneboy(www.dnai.org). And studied their composition of nucleic acids (A,C,T,G),and we have received results for genes KCNQ1,KCNH2 such that their nucleic acid composition approximately same, being their prevalence percentage is same
IP Traceback Based Probabilistic Packet Marking and Randomized Network Coding

A novel approach for IP traceback is proposed, which combines probabilistic packet marking and network coding techniques. Dissimilar to prior PPM schemes, our approach stores random linear combinations of router labels instead of overwriting to further decrease the convergence time for attack path reconstruction. Based on the coupon collector problem with unequal probability, we also present accurate models for convergence time of the proposed approach as well as that of prior schemes. Simulation results and analysis indicate that our approach can effectively improve the traceback performance
Adaptive Domotic System in Green Buildings

This paper presents an adaptive domotic system in green buildings. In our case, the data of sensor and devices were controlled in CIESOL center. The adaptive domotic system uses a Fuzzy Lattice Reasoning classifier for predicting building energy performance depending on the user condition. Training and testing of classifiers were carried out with temperature condition data acquired for 4 months (February, May, July and November) in the case building called CIESOL. The results show a high accuracy rates with a mean absolute error between 0% and 0.21%.
Evaluation of Sleep Scheduling Method for Data Collection from Sensor Networks Divided into Local Areas

Various sleep scheduling methods have been proposed to achieve energy efficiency in wireless sensor networks. Although these methods can make most nodes sleep to save energy, they do not give adequate consideration to the amount of data originating in specific areas of the network. The authors proposed a sleep scheduling method that divided a sensor network into an adjustable number of areas to ensure that more than one node remained active in each area, but which required all nodes to be able to access the sink node. However, the conditions of simulation experiments displayed a problem in that all the active sensor nodes sent packets to the sink node at the same time. This paper reports how the problem was solved in fresh evaluations of the proposed method and shows that the proposed method also extends the network lifetime.
Optimal technology mapping for single output cells

This paper presents a new approach to technology mapping for arbitrary technologies with single output cells. It overcomes the restrictions of tree-mapping based methods. Optimal algorithms for special cases of DAG-mapping are presented: for minimum delay mapping and for duplication-free mapping under a class of simple cost functions (including area and delay). Heuristics for duplication of logic and for AT-tradeoffs are developed and applied to LUT-FPGAs.
Model and evaluation of a new Honeynet

To present a solution to problem of bad collaboration and weak real-time performance in former Honeynet, based on citing Realm, a new Honeynet Model - BRHNS(Based Realm Honeynet) is presented. BRHNS makes use of cooperation between Realms, shares knowledge of new intrusion rules, IDS rule-lib is updated in real time, the detection efficiency of IDS is improved and the workload of Honeynet is effectively reduced, consequently, the efficiency of Honeynet is improved. After BRHNS has been implemented preliminarily, the efficiency of Honeynet is analyzed from response time, it is found that the efficiency of BRHNS is improved greatly than formal Honeynet.
Notch and Neural Progenitors Neocortical Development Notch, Neural Stem Cells, and Brain Tumors

Notch pathway regulates many different processes during mammalian development. Notch signaling has been particularly heavily studied in the developing nervous system, where Notch receptor activation inhibits neu-ronal differentiation and maintains the neural stem/ progenitor cell pool. Notch signaling has also been found to promote glial character, and in light of findings that certain glial cells possess neural stem cell character, the ability of Notch to maintain progenitor character and to promote glial character is likely to be mechanistically related (Gaiano and Fishell 2002). In addition to its role in development, Notch signaling has been implicated in many human cancers, including those in the brain. Because Notch pathway activation is well known for contributing to the maintenance of a prolif-eratively active cell state, the notion that aberrant Notch signaling could contribute to tumor formation is not surprising. The mechanisms by which Notch regulates neural stem cells in the developing nervous system are likely to be similar to those used during the regulation of putative brain tumor stem cells. As such, understanding parallels between both the signaling mechanisms and the cellular hetero-geneity present in both settings (e.g., stem cell vs. transit-amplifying progenitor) will provide valuable insight. In the first part of this chapter, we focus on Notch's role in embryonic neural stem/progenitor cells in the developing mammalian neocortex. Ongoing work in the field has focused on understanding how the Notch signal transduc-tion cascade is regulated and also on the nature of cell–cell interactions that mediate signaling. In the second part of this chapter, we address Notch signaling in brain tumor formation and growth and how this signaling pathway may regulate the maintenance and behavior of brain tumor stem cells. We also consider parallels between Notch function in embryonic neural stem/progenitor cells and in brain tumor stem cells. The mammalian neocortex is a highly organized six-layered structure that develops at the anterior end of the neural tube. The first neural stem/progenitor cells (simply referred to as progenitors hereafter, unless otherwise noted) line the ventricles in a germinal area referred to as the ventricular zone (VZ). A second germinal area, termed the subventricular zone (SVZ), forms just beneath the VZ after the onset of neurogenesis. The VZ and SVZ both contain highly proliferative neural progenitor cells that undergo symmetric and asymmetric cell divisions to either maintain the proliferative pool or produce the neu-rons of the different cortical layers (Noctor et al. 2004). In the …