Miracle-dz/UniFAR-FTUs huggingface dataset:
ffects of chronic dietary selenomethionine exposure on repeat swimming erformance , aerobic metabolism and methionine catabolism in adult zebrafish

In a previous study we reported impaired swimming performance and greater stored energy in adult zebrafish (Danio rerio) after chronic dietary exposure to selenomethionine (SeMet). The goal of the present study was to further investigate effects of chronic exposure to dietary SeMet on repeat swimming performance, oxygen consumption (MO2), metabolic capacities (standard metabolic rate [SMR], active metabolic rate [AMR], factorial aerobic scope [F-AS] and cost of transport [COT]) and gene expression of energy metabolism and methionine catabolism enzymes in adult zebrafish. Fish were fed SeMet at measured concentrations of 1.3, 3.4, 9.8 or 27.5 g Se/g dry mass (d.m.) for 90 d. At the end of the exposure period, fish from each treatment group were divided into three subgroups: (a) no swim, (b) swim, and (c) repeat swim. Fish from the no swim group were euthanized immediately at 90 d and whole body triglycerides, glycogen and lactate, and gene expression of energy metabolism and methionine catabolism enzymes were determined. Individual fish from the swim group were placed in a swim tunnel respirometer and swimming performance was assessed by determining the critical swimming speed (Ucrit). After both Ucrit and MO2 analyses, fish were euthanized and whole body energy stores and lactate were determined. Similarly, individual fish from the repeat swim group were subjected to two Ucrit tests (Ucrit-1 and Ucrit-2) performed with a 60 min recovery period between tests, followed by determination of energy stores and lactate. Impaired swim performance was observed in fish fed SeMet at concentrations greater than 3 g Se/g in the diet. However, within each dietary Se treatment group, no significant differences between single and repeat Ucrits were observed. Oxygen consumption, SMR and COT were significantly greater, and F-AS was significantly lesser, in fish fed SeMet. Whole body triglycerides were proportional to the concentration of SeMet in the diet. While swimming resulted in lesser concentrations of glycogen in the body, exposure to SeMet in the diet had no significant effect on glycogen content. Exposure to SeMet significantly down-regulated mRNA abundance of protein tyrosine phosphatase 1B (PTP 1B) in muscle, and -hydroxyacyl coenzyme A dehydrogenase (HOAD), sterol regulatory element binding protein 1 (SREBP 1) and methionine adenosyltransferase 1 alpha (MAT 1A) in liver of adult zebrafish. Overall the results of this study suggest chronic exposure of adult zebrafish to SeMet in the diet can cause both ffects cellular and organismal e
A Multi-Viewpoint Human Tracking Based on Face Detection Using Haar-like Features and a Mean-Shift Tracker

Human tracking is an important function for an automatic surveillance system using a vision sensor. However, it is difficult to identify a human exactly in an image due to the variety of poses. This paper describes a method for automatic human tracking based on face detection using Haar-like features and mean-shift tracking. The method increases its trackability by using multi-viewpoint images. Experimental results showed the validity of the method.
Enabling Deliberations in a Political Party Using Large-Scale Argumentation : A Preliminary Report

THE CHALLENGE: ENABLING DELIBERATION AT SCALE Humanity now finds itself faced with a range of highly complex and controversial challenges – such as climate change, the spread of disease, international security, scientific collaborations, product development, and so on that call upon us to bring together large numbers of experts and stakeholders to deliberate collectively on a global scale. Collocated meetings can however be impractically expensive and are prone to serious dysfunctions, especially at large scales. Social media such as email, blogs, wikis, chat rooms, and web forums provide unprecedented opportunities for interacting on a massive scale, but typically generate vast, poorly-organized, unsystematic and highly redundant corpuses of widely varying quality. Argumentation systems represent a promising approach for addressing these challenges, by virtue of providing a simple systematic structure that radically reduces redundancy and encourages clarity, but these have been used almost exclusively for small-scale deliberations.
Capacity Analysis of Cooperative Relaying Networks with Adaptive Relaying Scheme Selection

In the present paper, the performance of cooperative relaying networks with adaptive relaying scheme selection is analyzed. Cooperative relaying is a new technique to achieve spatial diversity gain by using neighboring stations. However, when multiple stations transmit simultaneously, the number of interference signals increases. Therefore, the introduction of cooperative relaying in radio communication systems does not always increase the network capacity due to the co-channel interference. Therefore, in order to achieve high spectral efficiency, it is necessary to select cooperative relaying or non-cooperative relaying adaptively. Assuming both centralized and decentralized adaptive controls, the spectrum efficiency is evaluated. The performance under decentralized control is evaluated using a game-theoretic approach. Simulation results show that the introduction of cooperative relaying with centralized control always increases the spectral efficiency. On the other hand, Simulation results also show that, when each source selects a relaying scheme independently and selfishly to maximize its own spectral efficiency, the introduction of the cooperative relaying may reduce the spectral efficiency due to the increase in the number of interference signals.
Handling mobile clients: a case for indirect interaction

Networking protocols are being modified to handle mobility of hosts. This paper argues that there is a need to make mobility explicit at every level of the OSI model - even above the network level through user or application level. Further, it is proposed that the mobile host and the first hop (wireless link) of communication be handled differently than the rest of the network. Hence, in networks with mobile hosts, we propose a radical approach of indirect interaction between clients and servers. <<ETX>>
Coregulation of Glutamate Uptake and Long-Term Sensitization in Aplysia

In Aplysia, long-term facilitation (LTF) at sensorimotor synapses of the pleural-pedal ganglia is mediated by an increase in the release of a neurotransmitter, which appears to be glutamate. Glutamate uptake also is increased in sensory neurons 24 hr after the induction of long-term sensitization (Levenson et al., 2000b). The present study investigated whether the same signaling pathways were involved in the long-term increase in glutamate uptake as in the induction of LTF. Thus, roles for cAMP, PKA (cAMP-dependent protein kinase), MAPK (mitogen-activated protein kinase), and tyrosine kinase in the regulation of glutamate uptake were tested. We found that 5-HT increased cAMP and activated PKA in sensory neurons. Exposure of pleural-pedal ganglia to analogs of cAMP or forskolin increased glutamate uptake 24 hr after treatments. Inhibitors of PKA (KT5720), MAPK (U0126 and PD98059), and tyrosine kinase (genistein) blocked the long-term increase in glutamate uptake produced by 5-HT. In addition, bpV, a tyrosine phosphatase inhibitor, facilitated the ability of subthreshold levels of 5-HT to increase glutamate uptake. Inhibition of PKC, which is not involved in LTF, had no effect on the long-term increase in glutamate uptake produced by 5-HT. Furthermore, activation of PKC by phorbol-12,13-dibutyrate did not produce long-term changes in glutamate uptake. The results demonstrate that the same constellation of second messengers and kinases is involved in the long-term regulation of both glutamate release and glutamate uptake. These similarities in signaling pathways suggest that regulation of glutamate release and uptake during formation of long-term memory are coordinated through coregulation of these two processes.
Analysis of Machine Translation Systems’ Errors in Tense, Aspect, and Modality

Errors of the translation of tense, aspect, and modality by machine translation systems were analyzed for six translation systems on the market and our new systems for translating tense, aspect, and modality. The results showed that our systems outperformed the other systems. They also showed that the other systems often produced progressive forms rather than the correct present forms. Our systems rarely made this mistake. Translation systems on the market could thus be improved by incorporating the methods used in our systems. Moreover, error analysis of the translation systems on the market identified information that would be useful for improving them.
Long non-coding RNA FEZF1-AS1 facilitates cell proliferation and migration in colorectal carcinoma

Long non-coding RNAs (lncRNA) have been shown to play important roles in the development and progression of cancer. Here, we discovered a novel long noncoding RNA (lncRNA) FEZF1 antisense RNA1 (FEZF1-AS1) is markedly upregulated in human primary colorectal carcinoma (CRC) and associated with CRC metastasis and poor prognosis. Moreover, the downregulation of FEZF1-AS1 expression significantly inhibited the CRC cells proliferation, migration and invasiveness, suppressed S-phase entry in vitro, and repressed tumor growth and metastasis in vivo. In contrast, overexpression of FEZF1-AS1 could promote the aggressive behaviors of CRC cells. We further discovered that the downregulation of FEZF1-AS1 reduced its sense-cognate gene FEZF1 mRNA and protein expression in CRC cells. There was a positive correlation between FEZF1-AS1 and FEZF1 expression in CRC. Moreover, FEZF1 knockdown also significantly suppressed CRC cell proliferation, migration, and invasion. Our findings indicate that the dysregulation of FEZF1-AS1 participates in colorectal tumorigenesis and progression, which might be achieved, at least in part, through FEZF1 induction.
The Case for Early Psychotherapy in Aging Combat Veterans Experiencing Late Onset Stress Symptomatology

Rajdip Barman1 and Mark B. Detweiler2-5 1Virginia Tech-Carilion Psychiatry Residency Program, Roanoke, Virginia 2Staff Psychiatrist, Salem Veterans Affairs Medical Center, Salem, Virginia 3Geriatric Research Group, Salem Veterans Affairs Medical Center, Salem, Virginia 4Virginia Tech-Carilion School of Medicine, Department of Psychiatry and Behavioral Medicine, Roanoke, Virginia 5Edward via College of Osteopathic Medicine Department of Psychiatry, Blacksburg, Virginia
HKC: A Dictionary Training Algorithm for Sparse Representation

In recent years, research on dictionary design for sparse representation(SR) has changed from pre-defined to training. A Hierarchical K-means Clustering (HKC) dictionary training algorithm is proposed in this paper. The algorithm presents a framework for SR for a class of images. HKC used K-means clustering to generate atoms which is one to one corresponding to hyperplanes for approximating hyperspherical cap. Compared with conventional algorithms, this algorithm is more flexible and efficiency. Finally, experimental results show that this algorithm can be used for compressive sensing and denoising.
The Tpl 2 Mutation Sluggish Impairs Type I IFN Production and Increases Susceptibility to Group B Streptococcal Disease 1

V ia the TLRs, the innate immune system senses conserved molecules of microbial origin and triggers innate immune responses that include production of inflammatory cytokines, chemokines, and type I IFNs. Most of the TLRs signal through the MyD88 adaptor protein, while TLR3 signals through a MyD88-independent pathway and TLR4 signals through both MyD88-dependent and independent processes (reviewed in Refs. 1 and 2). Cytokines produced in response to TLR signaling, including TNF-␣ and IFNs, are critical for controlling microbial infections. The production of type I IFNs by plasmacytoid dendritic cells (pDCs) 4 in response to the stimulation of TLR7 (which senses ssRNA) and/or TLR9 (which senses CpG DNA) is necessary for the host defense against certain viruses (3), while both TNF-␣ and type I IFNs play important roles in the host response to bacterial infections (4 – 6). For instance, Tnf Ϫ/Ϫ and Tnfr1 Ϫ/Ϫ mice are highly susceptible to infection with the intracellular pathogen Listeria monocytogenes (5, 6), and TNF production has been shown to be an important component of the immune response to extra-cellular group B streptococcus (GBS) infection (7, 8). Mice deficient in type I IFN signaling display impaired immune responses to a variety of bacterial infections including GBS (9), but display increased resistance to L. monocytogenes (10 –12). Tpl2 (tumor progression locus 2)/Cot (cancer Osaka thyroid)/ MAP3K8 is a serine/threonine protein kinase that is a member of the MEK kinase (MAP3K) family of proteins. In vitro, Tpl2 can activate important immune response factors including the JNK, p38, and ERK protein kinases, as well as NF-␬B and NFAT (13– 15). Tpl2-deficient mice are resistant to LPS-induced shock, due to low levels of circulating TNF-␣ (16), and Tpl2-deficient macro-phages demonstrate impaired ERK activation and TNF-␣ production in response to multiple TLR ligands (17, 18). We have identified an N-ethyl-N-nitrosourea (ENU)-induced mutation, termed Sluggish, resulting in defective splicing of the Map3k8-encoded Tpl2 transcript. Animals homozygous for the mutation show impaired TNF-␣ secretion in response to all TLR stimuli, while heterozygotes displayed intermediate responses to some TLR ligands. Macrophages isolated from homozygous Map3k8 Sluggish/Sluggish mice showed impaired type I IFN production, specifically in response to TLR7 and TLR9 stimulations, but were able to control viral infections. In addition, Map3k8 Sluggish/Sluggish mice were resistant to mouse cytomegalovirus (MCMV) infection. Although these animals displayed resistance to infection by L. mono-cytogenes, they were highly susceptible to GBS infection. Macro-phages isolated from Map3k8 Sluggish/Sluggish mice …
Empirical Study on Web Content Consistency

In this paper, we would like to perform detail analysis on the consistency situation of current Web content. Both data and the associated attributes of Web objects on replica/CDN (content delivery network) are monitored over the Internet and the correctness and appropriateness of various headers are discussed. It is found that there are lots of discrepancies in data object and attributes found by comparing the original copy and the retrieved copy of the content. This result is important to content delivery and distribution because incorrect headers can easily lead into wrong decision in network and content presentation related functions such as caching, content adaptation and personalization
Efeitos do nascimento pré-termo nas funções cognitivas de crianças: revisão sistemática

Resumo: Deficits cognitivos em criancas sao relacionados ao nascimento pre-termo, e grande parte destas dificuldades sao observadas apenas quando as criancas atingem a idade escolar. Por meio de uma revisao sistematica, o estudo buscou investigar dados empiricos acerca dos efeitos do nascimento pre-termo nos desfechos cognitivos (Quociente de Inteligencia Geral e/ou Funcoes Executivas) em criancas nascidas pre-termo, com idade entre 9 e 12 anos. Foram selecionados manuscritos publicados entre 2004 a 2014, escritos em ingles, portugues ou espanhol. A busca foi realizada nas bases PsycINFO, PubMed e Scopus. No total, 13 estudos satisfizeram os criterios de inclusao. Os resultados indicaram diferencas estatisticamente significativas entre os grupos pre-termo e a termo, visto que as criancas pre-termo apresentaram os escores mais baixos. Entretanto, na maioria dos estudos, as criancas nascidas pre-termo tiveram escores dentro da media no que diz respeito ao Quociente de Inteligencia Geral. Implicacoes clinicas e limitacoes metodologicas sao discutidas. Palavras-chave: pre-termo; quociente de inteligencia geral; funcoes executivas; criancas; idade escolar.
Detecting license plate based on top-hat transform and wavelet transform

In a vehicle license plate identification system, plate region detection is the key step before the final recognition. This paper presents a license plate detection algorithm from complex background based on top-hat transform and wavelet transform. First, the vertical gradient of gray image is calculated and the region of license plate is standed out by using top-hat transformation. Then the horizontal projection of gradient variance is obtained and horizontal candidates are located by using threshold. Multiresolution feature of candidates are extracted by using wavelet transformation in the following. Finally, accurate vertical position of license plate is detected and license plate is extracted from image. In order to show the effectiveness of the proposed method, experiments have been conducted on 360 images taken from various scenes and different conditions. The algorithm can quickly and correctly detect the region of license plate and the license plate detecting rate of success is 98.61%.
Network coding for TCP throughput enhancement over a multi-hop wireless network

The poor performance of TCP over multi-hop wireless networks is well known. In this paper we explore to what extent network coding can help to improve the throughput performance of TCP controlled bulk transfers over a chain topology multi-hop wireless network. The nodes use a CSMA/CA mechanism, such as IEEE 802.11psilas DCF, to perform distributed packet scheduling. The reverse flowing TCP ACKs are sought to be X-ORed with forward flowing TCP data packets. We find that, without any modification to the MAC protocol, the gain from network coding is negligible. The inherent coordination problem of carrier sensing based random access in multi-hop wireless networks dominates the performance. We provide a theoretical analysis that yields a throughput bound with network coding. We then propose a distributed modification of the IEEE 802.11 DCF, based on tuning the back-off mechanism using a feedback approach. Simulation studies show that the proposed mechanism when combined with network coding, improves the performance of a TCP session by more than 100%.
EMOTION-SENSITIVE HUMAN-COMPUTER INTERFACES

People are polite to their computers. They are flattered by them, form teams with them and even interact emotionally with them. In their experiments, Reeves and Nass (The Media Equation, 1996) showed that humans impose their interpersonal behavioral patterns onto their computers. Thus, the design of humancomputer interfaces should reflect this observation in order to facilitate an effective communication. In order to build a human-computer interface that is sensitive to the user's expressed emotion, we investigated spectral, prosodic, and verbal cues in the user's utterance. Based on these cues, we showed that the classification system achieved accuracies comparable to human performance. Finally, we demonstrate how to integrate information about the expressed emotion into a dialog system. The dialog system employs different discourse strategies depending on the expressed emotion allowing for a natural and effective communication between the user and the system.
OBLIGATION BLACKWELL GAMES AND P-AUTOMATA

Abstract We generalize winning conditions in two-player games by adding a structural acceptance condition called obligations. Obligations are orthogonal to the linear winning conditions that define whether a play is winning. Obligations are a declaration that player 0 can achieve a certain value from a configuration. If the obligation is met, the value of that configuration for player 0 is 1. We define the value in such games and show that obligation games are determined. For Markov chains with Borel objectives and obligations, and finite turn-based stochastic parity games with obligations we give an alternative and simpler characterization of the value function. Based on this simpler definition we show that the decision problem of winning finite turn-based stochastic parity games with obligations is in NP∩co-NP. We also show that obligation games provide a game framework for reasoning about p-automata.
An Overview on Privacy Preserving Data Mining Methodologies

Recent interest in the collection and monitoring of data using data mining technology for the purpose of security and business-related applications has raised serious concerns about privacy issues. For example, mining health care data for the detection of disease outbreaks may require analyzing clinical records and pharmacy transaction data of many individuals over a certain area. However, releasing and gathering such diverse information belonging to different parties may violate privacy laws and eventually be a threat to civil liberties. Privacy preserving data mining strives to provide a solution to this dilemma. It aims to allow useful data patterns to be discovered without compromising privacy. This paper presents an brief overview on preserving data mining methodologies.
Trust and innovation

In innovation, trust is especially needed as well as especially problematic. One needs trust under uncertainty and in innovation uncertainty is high. If one were certain about conditions, conduct and outcomes one would no longer talk about trust. This is related to a paradox of information concerning trust (Pagden, 1988). On the one hand, trust entails lack of information, since that entails risk of vulnerability to actions of others, and if one were certain about such actions, there would no longer be risk. On the other hand, trust is seldom completely uninformed, and is to some extent based on information, in attributions of trustworthiness or lack of it based on observed or reported behaviour. Trust entails uncertainty of conditions, conduct or outcomes that maybe calculable (usually referred to as ‘risk’ in this technical sense) or incalculable (radical uncertainty). The uncertainty of trust entails a possibility of loss due to mishap or misconduct.
Graph-Based Object Hypothesis

Reasoning about three-dimensional scenes involves the analysis of large amounts of complex, time-varying information. This paper presents a novel representation for storing such information that provides a unified, intuitive framework for reasoning about rigid objects. The core structure is a graph that represents features of the scene as vertices, and stores distances between these features at the edges. These relationships evolve over time, as more information is presented to the system, and an approach to dealing with uncertain information using interval arithmetic is proposed. An algorithm for rigid object extraction is presented, based on this graph. The graph structure can also be used in support of some low-level tasks, and the problem of tracking three-dimensional features is considered. Results are presented for both artificial and real scenes.
Decoding and file transfer delay balancing in network coding broadcast

Network Coding is a packet encoding technique which has recently been shown to improve network performance (by reducing delays and increasing throughput) in broadcast and multicast communications. The cost for such an improvement comes in the form of increased decoding complexity (and thus delay) at the receivers end. Before delivering the file to higher layers, the receiver should first decode those packets. In our work we consider the broadcast transmission of a large file to N wireless users. The file is segmented into a number of blocks (each containing K packets - the Coding Window Size). The packets of each block are encoded using Random Linear Network Coding (RLNC). We obtain the minimum coding window size so that the completion time of the file transmission is upper bounded by a used defined delay constraint.