Miracle-dz/UniFAR-FTUs huggingface dataset:
Stimulation of Endothelin B Receptors in Astrocytes Induces cAMP Response Element-Binding Protein Phosphorylation and c-fos Expression Via Multiple Mitogen-Activated Protein Kinase Signaling Pathways

The vasoconstrictor peptide endothelin (ET-1) exerts its physiological and pathological effects via activation of ETA and ETB receptor (ET-R) subtypes. In this study, we demonstrate that both ET-R subtypes are highly expressed in rat astrocytes in vivo, indicating that these cells are potential targets of the biological effects of ET-1 in the brain. In cultured cortical astrocytes, both ET-R subtypes are expressed, and selective stimulation of ETB-R with ET-1 induces phosphorylation of cAMP response element-binding protein (CREB). The signal transduction pathway activated by ET-1 includes the Rap1/B-Raf and the Ras/Raf-1 complexes, protein kinase C (PKC) together with extracellular signal-regulated kinases (ERK), and the ribosomal S6 kinase (RSK) isoforms RSK2 and RSK3, two kinases that lie immediately downstream of ERK and are able to phosphorylate CREB. Moreover, ET-1 activates the p38 mitogen-activated protein kinase (MAPK)-dependent, but not the c-jun N-terminal kinase (JNK)-dependent pathway. By using selective protein kinase inhibitors and expression of dominant-negative Rap1 protein, we also found that the Rap1/PKC/ERK-dependent pathway induces the phosphorylation of activating transcription factor-1, CREB, and Elk-1, whereas the p38MAPK-dependent pathway only causes CREB phosphorylation. ET-1-induced transcription of the immediate early genec-fos requires the concomitant activation of both the PKC/ERK- and p38MAPK-dependent pathways, because inhibitors of either pathway block the ET-1-induced increase of c-fos mRNA. Our findings indicate that changes in the expression of cAMP response element-dependent immediate and delayed response genes could play a pivotal role in the physiological effects elicited by ET-1 in astrocytes.
The head detection method based on binocular stereo vision

This paper is dedicated to the research of head detection method based on binocular stereo vision. In the first stage, we correct the acquired images, and in the second stage calculate the target parallax in binocular vision. According to the feature of the head contour, different depth distribution of person and the scene in depth map by binocular stereo image, the relationship between head's geometric features and depth information can be obtained. And then, the method of depth stratification to obtain the depth layers of head information can be used. The second part is to regard the geometric features of contour as the decision condition of round head, and then combined with the stereo matching algorithms of binocular vision to recognize the target under the binocular vision. Finally, whether the contour is the head or not can be distinguished. Experimental results show that the algorithm can be adapted to detect the head effectively in complex situation and has high accuracy.
Use of text syntactical structures in detection of document duplicates

This is the first paper on a set of experiments addressing issues related to the determination of text similarity using a combined syntactical representation and string alignment techniques. The suggested approach takes advantage of document syntactical structure manifested in Part of Speech (POS) tags and uses it as a basis for further processing. Documents, including the query, are pre-processed using a POS tagger converting them into a reduced string that captures some of the writing style of authors and some of the semantics of the written text. This provides means of representing a document on a higher level of abstraction that captures the different alterations that can be done on documents that are similar in origin and possibly in style. This in turn enables processing of such documents using many of the available string manipulation and matching algorithms. This work is inspired and driven by the parallel between text processing and sequence alignment in computational biology. Sequence alignment techniques are used to analyze and establish the utility of using strings produced as a result of this syntactical representation of content.
Cryptanalysis of Two Dynamic ID-Based Remote User Authentication Schemes for Preserving User Privacy

Remote user authentication is an essential part in electronic commerce to identify legitimate users over the Internet. However, how to protect user privacy in the authentication has become an important issue recently. Therefore, many secure authentication schemes with smart cards have been proposed. In this paper, we will analyze the security weaknesses of two recently proposed authentication schemes for preserving user privacy. First, Chang et al. (2011) proposed a robust and efficient remote user authentication scheme to provide user anonymity. However, this scheme fails to protect user privacy in terms of anonymity and traceability. In addition, it is vulnerable to the server counterfeit attack and it does not provide perfect forward secrecy for session keys. Furthermore, if the smart card is lost, it will suffer from the offline password guessing attack as well as the user impersonation attack. Second, Wen and Li (2012) recently presented an improved dynamic ID-based authentication scheme with key agreement. However, this scheme is vulnerable to traceability. In addition, it does not support perfect forward secrecy for session keys. Furthermore, the insecure offline password change phase and online secret renewal phase will result in the denial of service attack.
Application of improved PSO algorithm to hydropower station optimal operation

The long term optimal operation of hydropower stations involves non-linear optimization with high dimensionality. An improved particle swarm optimization is presented in this article to solve the problem. The capacity of solving nonlinear problems is enhanced effectively through adjusting inertia factor dynamically in the algorithm of particle swarm optimization. In order to test the performance of the algorithm, it is applied to solve the long term optimal operation of hydropower station. The results showed that this algorithm is feasible for the problems of complex non-linear systems with rapid speed of convergence and superior precision.
Virtual Reality Technology and Its Application in Prevention of Coal and Gas Outburst

This paper discussed the application of virtual reality technology and its application on prevention of coal and gas outburst in coal mine. With the help of virtual reality technology, the vivid and process of coal and gas outburst in coal mine could be obtained. The application of virtual reality technology on prevention of coal and gas outburst included development such as system requirements, data preparation and organization, the configuration for virtual reality software and the custom of the client are discussed. The study and development of virtual reality technology were much important to relieve the catastrophic accident. The problems existing in prevention of coal and gas outburst was pointed out and corresponding countermeasures were put forward.
ABC Model of Team Innovation Behavior

This paper analyzes the influences of team innovation atmosphere and empowering leadership on team innovation behavior. It discusses the effect of team efficacy and put forward the ABC model of medium mechanism of team efficacy between innovation atmosphere and team innovation behavior and empowering leadership and innovation behavior. We test the hypotheses of the model with 104 innovation teams.
The future of fuzzy logic based wind energy conversion system with solid oxide fuel cell and the passions of radical pedagogy

This paper presents a novel control system for wind energy conversion system integrated with Solid oxide fuel cell (SOFC). In recent years the Double-Fed Induction Generator (DFIG) gaining more popular due to their variable speed and variable pitch control. A dynamic model of SOFC fuel cell integrated with a doubly fed induction generator to maintain grid voltage constant 440 V and 50 Hz. The conventional vector control technique is used in the variable speed DFIG to maintain constant frequency. Existing literature used PI controller based vector control technique for the control of DFIG. In this work, fuzzy logic controller is proposed to decrease total harmonic distortion in grid current. The performance of the system for sudden load changes with PI control and proposed control technique has been obtained and compared, by using MATLAB SIMULINK.
Using neural network categorization method to develop an innovative knowledge management technology for patent document classification

In order to process huge amount of explicit knowledge documents in an organized manner, automatic document categorization is an important research area in the R&D knowledge management domain. In this paper, we propose a new document classification methodology based on neural network technology. We first extract key phrases from the document set by means of text processing and determine the significance of key phrases by their appearance frequency. After significant phrases are extracted, a keyword correlation analysis model is applied to compute similarity between key phrases. Then, synonyms are extracted from highly similar terms. The backpropagation neural network model is adopted as a classifier. The target output is to identify a document's proper category based on the hierarchical document classification scheme, i.e., the international patent classification (IPC) standard. In this research, patents related to designs of innovative power hand-tools are studied in their IPC classification scheme. Any related patent can be automatically and accurately classified using the pretrained neural network models. In the prototype system, we provide two modules for explicit knowledge management. The automatic classification module helps the user classify patent documents and the search module helps users find the correct patent documents quickly. The result shows a very significant improvement in document classification and identification in explicit knowledge management.
Metamaterial-Based Electrically Small Wide Band L-Shaped Monopole Antenna

A wide band metamaterial based electrically small L-shaped monopole antenna is proposed for the application of Wimax and Wifi. It is easy to fabricate due to planar and compact structure. The coplanar waveguide (CPW) feed is used to provide better bandwidth. The bandwidth of the proposed antenna is 2.5789 GHz. Compactness of antenna is achieved by using ring resonator having a metamaterial property.
Anti-inflammatory effect of a methanolic extract of leaves of Ocimum Sanctum

Basak et al. Anti-inflammatory effect of a methanolic extract of leaves of Ocimum Sanctum, ABSTRACT Aim of study: The aim of this study was to establish the anti-inflammatory activity of the methanolic extract of Ocimum sanctum leaves (MEOS) with its fractions and to delineate the possible mechanism of action for MEOS. Materials and methods: The anti-inflammatory activities of MEOS along with its petroleum ether and chloroform fractions were evaluated in a Carrageenan induced model of acute inflammation. The effect of MEOS on lipopolysaccharide induced production of nitric oxide (NO) in macrophages was also studied. Results: MEOS (100, 200 and 400 mg/kg body weight) significantly reduced Carrageenan induced paw edema; chloroform fraction was most potent (66%, p < 0.001). MEOS was non-toxic up to 125microgm/ml in mouse peritoneal macrophages wherein it (0–100microgm/ml) reduced lipopolysaccharide induced NO production. Conclusion: MEOS possesses significant anti-inflammatory activity. Chloroform fraction of MEOS showed best anti-inflammatory activity. Abbreviation: MEOS-Methanolic Extract of Ocimum sanctum.
Significant impact of the +93 C/T polymorphism in the apolipoprotein(a) gene on Lp(a) concentrations in Africans but not in Caucasians: confounding effect of linkage disequilibrium.

Lipoprotein(a) [Lp(a)] is a quantitative genetic trait in human plasma associated with atherothrombotic disease. The major determinant of Lp(a) concentration is the apolipoprotein(a) [apo(a)] gene locus. Variation in the number of kringle IV repeats (K-IV VNTR) in apo(a) has a direct effect on Lp(a) concentrations but explains only a fraction of the large intra- and inter-population variance in Lp(a) levels. Effects on Lp(a) of other intragenic polymorphisms including a pentanucleotide repeat (PNRP) in the promoter likely reflect allelic associations with as yet unidentified sequence variation in the apo(a) gene. We have studied a candidate C-->T transition in two European and two African populations. This polymorphism in the 5' region of the apo(a) gene creates an ATG start codon thereby reducing apo(a) translation in vitro by 60%. All samples were also analyzed for the K-IV VNTR and the PNRP to stratify for their effects and to consider allelic associations. Consistent with the in vitro effect the C-->T transition was associated with a significant reduction in Lp(a) levels in both African populations ( P < 0.0056). In Caucasians, however, the effect was not significant. This was explained by linkage disequilibrium of the +93 T with apo(a) alleles of intermediate length (K-24-K-34) and with nine PNRs. In Europeans these alleles are associated with low Lp(a) which makes any potential effect of the +93 T undetectable in the total sample. From our results we conclude (i) that the +93 C/T polymorphism is the second known intragenic apo(a) polymorphism which affects Lp(a) levels directly in vivo ; (ii) that allelic associations may mask the effect of a mutation; and (iii) that heterogeneity of an effect of a mutation across populations does not disprove causality.
Real-time government policy monitoring framework using expert guided topic modeling

The user generated data on social online platforms is a very resourceful medium for building applications. It provide an easy, cheap and efficient way to address the opinions expressed by millions of users. There are various commercial applications developed that analyze the products based on user reviews. However, no considerable research work is carried out at building applications to consume this data for good governance. Topic models are successfully used for various text analysis tasks and are employed here. In order to improve accuracy of the model as government policies is a specialized domain, the model is extended with expert guidance by following a semi-supervised approach. POS tagging is used to identify user opinions which is evaluated through WordNet dictionary. In order to perform real-time analysis, the model is tuned to streaming tweets data which is analyzed to produce real-time analysis about the top government policies. The model is trained on print media articles and is tested on twitter data that accurately recognized policies and represented their sentiment scores for different time spans.
Perspectives on “Disease” and “Disability” in Child Health: The Case of Childhood Neurodisability

Chronic health conditions are often associated with what is termed disability. Traditional thinking has focused on diagnosis and treatment of chronic diseases and disorders, with less attention to people’s functional abilities and their contextual determinants. Understanding all of these factors is integral to addressing the predicaments and needs of persons with chronic conditions. However, these complementary yet distinct “worldviews” reflected in what we call disease and disability perspectives often remain, at best, only vaguely articulated. In this paper, we explore and expand on these perspectives in light of conceptual advances, specifically the framework of the World Health Organization’s International Classification of Functioning, Disability and Health, and their epistemic underpinnings with reference to Wilhelm Windelband’s notions of nomothetic and idiographic types of knowledge. Our primary focus is the children with neurodisability – life-long conditions that onset early in life and have functional consequences that impact developmental trajectories. We critically review and analyze conceptual material, along with clinical and research evidence relevant to the experiential and clinical realities of this population, to demonstrate the limitations of a biomedically based diagnostic–therapeutic paradigm at the expense of a developmental and disability-oriented perspective. Our main aim in this paper is to argue for an explicit recognition of both disease and disability perspectives, and a more balanced and appropriate deployment of these concepts across the continuum of clinical services, research, policy-making and professional and public education in relation to children with neurodisability; we also provide concrete recommendations to advance this progressive strategy. The relevance of these aims and strategies, however, extends beyond this particular population.
Cell Planning and Deployment for IEEE 802.11p\/WAVE Network

In order to support the mobility of vehicles and reliable services in the Institute of Electrical and Electronics Engineers (IEEE) 802.11p/wireless access in vehicular environments (WAVE) network, cell planning and coverage optimization are critical issues. In light of this, we employed the IEEE 802.11p/WAVE test-bed located at the Chungju campus of the Korea National University of Transportation (KNUT). We proposed a prediction model by using a 3D ray-tracing tool with geographic information system (GIS) data for cell planning and coverage optimization. Furthermore, we developed the WAVE geometric measurement studio (WGMS), which can be used as a tool for the cell planning and deployment of IEEE 802.11p/WAVE wireless networks. By comparing the measurement campaign results with the simulated results, it is confirmed that the proposed prediction model and the developed WGMS can together be used as a general solution tool to reduce the cost and time consumption for the cell planning and optimization of IEEE 802.11p/WAVE wireless networks.
Optimization and Evaluation of an Energy-Efficient MAC Protocol for WASNs

A Wireless Ad hoc Sensor Network (WASN) is an autonomous collection of low cost devices that communicate over wireless links. This devices are often powered by limited energy resources, and it is expensive and sometimes infeasible to recharge or replace them. Hence, energy efficiency is the main design concern for such a network. In literature, several energy-efficient Medium Access Control (MAC) protocols have been proposed, because the primary sources of energy waste are collision, overhearing, idle listening and overhead. %Nevertheless, most of these works In this paper, we propose a novel adaptive MAC layer protocol, which uses a model-based duty-cycle adaptation strategy based on traffic load predictions. Specifically, a stochastic model is used by a state estimator to predict the network's future conditions. The predicted network conditions are then used by an optimizer to derive an optimal wake-up time schedule which reduces the end-to-end latency while saving energy. The performance of our protocol is then compared to the most widely duty-cycle MAC protocols such are S-MAC and T-MAC. Our experimental results on a simulated WASN reveals that under heavy as well as light traffic conditions our solution results in an improvement in the balance between end-to-end latency and energy consumption.
Novel Approach For Online Learning Through Affect Recognition

Online learning is commonly accepted as a support tool for educators as well as a medium of delivery of any-time, any-where content of a wide range of study programs to a widely dispersed learner community. Web-based learning environments are a relatively new medium of learning to Sri Lankan universities. There are predictions of a near future boom of digital learning in Asian educational context, challenging the conventional face to face learning environments. Like any learning process, digital learning depends on effective communication of human knowledge, whether this occurs in a face-to-face classroom or across the internet. Within the state university settings, learners experience varied emotions and interest towards learning. Although both emotions and interest can increase learners’ likelihood to engage in traditional learning, little is known about the influence of emotions and interest in learning activities in a digital environment. Moreover, recent research on the emotional response to digital learning has focused on the importance of learners’ feelings in relation to the community of learning. Major objective of this research study is to introduce a new model of online learning with relevance to the emotional response of the learning community.
Private Information and High-Frequency Stochastic Volatility

We study the effect of privately informed traders on measured high frequency price changes and trades in asset markets. We use a standard market microstructure framework where exogenous news is captured by signals that informed agents receive. We show that the entry and exit of informed traders following the arrival of news accounts for high-frequency serial correlation in squared price changes (stochastic volatility) and trades. Because the bid-ask spread of the market specialist tends to shrink as individuals trade and reveal their information, the model also accounts for the empirical observation that high-frequency serial correlation is more pronounced in trades than in squared price changes. A calibration test of the model shows that the features of the market microstructure, without serially correlated news, accounts qualitatively for the serial correlation in the data, but predicts less persistence than is present in the data.
AN EQUIVARIANT WHITEHEAD ALGORITHM AND CONJUGACY FOR ROOTS OF DEHN TWIST AUTOMORPHISMS

Abstract Given finite sets of cyclic words $\{u_1,\dots,u_k\}$ and $\{v_1,\dots,v_k\}$ in a finitely generated free group $F$ and two finite groups $A$ and $B$ of outer automorphisms of $F$, we produce an algorithm to decide whether there is an automorphism which conjugates $A$ to $B$ and takes $u_i$ to $v_i$ for each $i$. If $A$ and $B$ are trivial, this is the classic algorithm due to Whitehead. We use this algorithm together with Cohen and Lustig’s solution to the conjugacy problem for Dehn twist automorphisms of $F$ to solve the conjugacy problem for outer automorphisms which have a power which is a Dehn twist. This settles the conjugacy problem for all automorphisms of $F$ which have linear growth. AMS 2000 Mathematics subject classification: Primary 20F32. Secondary 57M07
Long-term X-ray variability in Blazars and its multiwaveband context

The accumulation of well-sampled X-ray, optical, and radio light curves of blazars and coredominated radio galaxies allows analysis of the long-term variability properties and crossfrequency correlations. Armed with this rich database, we are starting to be able to determine where in the jet the nonthermal flares take place. We find that these can occur in at least two locations: in the core seen on millimeter-wave VLBI images and in a region with a helical magnetic field well upstream of the core. The latter is consistent with the jet acceleration and collimation zone according to the magnetohydrodynamical models favored by most theorists. In this picture, the jet of a blazar, which points within several degrees of the line of sight, produces the bulk of its radiation near the end of this zone and in standing shocks or other compressions downstream. The outbursts and superluminal radio knots are connected with events in the central engine signalled by dips in the X-ray flux. However, a model detailing how the accretion-disk/black-hole system couples with the jet still needs to be developed.