Miracle-dz/UniFAR-FTUs huggingface dataset:
Using DNA Duplex Stability Information for Transcription Factor Binding Site Discovery

Transcription factor (TF) binding site discovery is an important step in understanding transcriptional regulation. Many computational tools have already been developed, but their success in detecting TF motifs is still limited. We believe one of the main reasons for the low accuracy of current methods is that they do not take into account the structural aspects of TF-DNA interaction. We have previously shown that knowledge about the structural class of the TF and information about nucleosome occupancy can be used to improve motif discovery. Here, we demonstrate the benefits of using information about the DNA double-helical stability for motif discovery. We notice that, in general, the energy needed to destabilize the DNA double helix is higher at TF binding sites than at random DNA sites. We use this information to derive informative positional priors that we incorporate into a motif finding algorithm. When applied to yeast ChIP-chip data, the new informative priors improve the performance of the motif finder significantly when compared to priors that do not use the energetic stability information.
Multimodal Sentiment Analysis of Telugu Songs

In this paper, an approach to detect the sentiment of a song based on its multi-modality natures (text and audio) is presented. The textual lyric features are extracted from the bag of words. By using these features, Doc2Vec will generate a single vector for each song. Support Vector Machine (SVM), Naive Bayes (NB) and a combination of both these classifiers are developed to classify the sentiment using the textual lyric features. Audio features are used as an add-on to the lyrical ones which include prosody features, temporal features, spectral features, tempo and chroma features. Gaussian Mixture Models (GMM), SVM and a combination of both these classifiers are developed to classify the sentiment using audio features. GMM are known for capturing the distribution in the features and SVM are known for discriminating the features. Hence these models are combined to improve the performance of sentiment analysis. Performance is further improved by combining the text and audio feature domains. These text and audio features are extracted at the beginning, ending and for the whole song. From our experimental results, it is observed that the first 30 seconds(s) of a song gives better performance for detecting the sentiment of the song rather than the last 30s or from the whole song.
Some pharmacological effects of cinnamon and ginger herbs in obese diabetic rats

Aims: The present study was designed to assess some pharmacological effects of cinnamon (CAE) and ginger (GAE) aqueous extracts in obese diabetic rats, and to elucidate the potential mechanisms. Materials and Methods: Forty-two Sprague-Dawley rats were randomized into 6 equal groups. Group 1 was a negative control and the other groups were rendered obese by feeding rats on high-fat diet for 4 weeks. The obese rats were subcutaneously injected with alloxan for 5*days to induce diabetes. Group 2 was a positive control, and Groups 3, 4, 5 and 6 were orally given CAE in doses 200 and 400 mg/kg and GAE in the same doses, respectively for 6 weeks. Blood samples were collected for serum biochemical analyses. Kidneys were dissected out to assay activity of tissue antioxidant enzymes: Superoxide dismutase, glutathione peroxidase and catalase. Results: CAE and GAE significantly reduced body weight and body fat mass; normalized serum levels of liver enzymes; improved lipid profile; decreased blood glucose and leptin and increased insulin serum levels in obese diabetic rats. Both extracts also increased activity of kidney antioxidant enzymes. Conclusion: CAE and GAE exhibit anti-obesity, hepatoprotective, hypolipidemic, antidiabetic and anti-oxidant effects in obese diabetic rats. These results confirm the previous reports on both extracts. The potential mechanisms underlying these effects are fully discussed and clarified. Our results affirm the traditional use of cinnamon and ginger for treating patients suffering from obesity and diabetes. The obese diabetic rat model used in this study is a novel animal model used in pharmacology researches.
A Quorum Sensing-Disrupting Brominated Thiophenone with a Promising Therapeutic Potential to Treat Luminescent Vibriosis

Vibrio harveyi is amongst the most important bacterial pathogens in aquaculture. Novel methods to control this pathogen are needed since many strains have acquired resistance to antibiotics. We previously showed that quorum sensing-disrupting furanones are able to protect brine shrimp larvae against vibriosis. However, a major problem of these compounds is that they are toxic toward higher organisms and therefore, they are not safe to be used in aquaculture. The synthesis of brominated thiophenones, sulphur analogues of the quorum sensing-disrupting furanones, has recently been reported. In the present study, we report that these compounds block quorum sensing in V. harveyi at concentrations in the low micromolar range. Bioluminescence experiments with V. harveyi quorum sensing mutants and a fluorescence anisotropy assay indicated that the compounds disrupt quorum sensing in this bacterium by decreasing the ability of the quorum sensing master regulator LuxR to bind to its target promoter DNA. In vivo challenge tests with gnotobiotic brine shrimp larvae showed that thiophenone compound TF310, (Z)-4-((5-(bromomethylene)-2-oxo-2,5-dihydrothiophen-3-yl)methoxy)-4-oxobutanoic acid, completely protected the larvae from V. harveyi BB120 when dosed to the culture water at 2.5 µM or more, whereas severe toxicity was only observed at 250 µM. This makes TF310 showing the highest therapeutic index of all quorum sensing-disrupting compounds tested thus far in our brine shrimp model system.
Rethinking Antivirus: Executable Analysis in the Network Cloud

Antivirus software installed on each end host in an organization has become the de-facto security mechanism used to defend against unwanted executables. We argue that the executable analysis currently provided by host-based antivirus software can be more efficiently and effectively provided as an in-cloud network service. Instead of running complex analysis software on every end host, we suggest that each end host run a lightweight process to acquire executables entering a system, send them into the network for analysis, and then run or quarantine them based on a threat report returned by the network service. An executable analysis service run inside an enterprise network or by a service provider could integrate antivirus software, behavioral simulation, and other analysis engines from multiple vendors providing better detection of malware and simplify client software enabling deployment on a broader range of devices. To explore this idea we construct a prototype composed of a Windows based host agent and an in-cloud analysis service and evaluate it using a diverse dataset of 5066 unique malicious executables. By correlating information between multiple detection engines, our system provides over 98% detection coverage of the malicious executables using eight antivirus engines and two behavioral engines compared to a 54% to 86% detection rate using the latest commercial antivirus products.
Bayesian analysis of finite Gaussian mixtures

The problem considered in this paper is parameter estimation of a multivariate Gaussian mixture distribution with a known number of components. The paper presents a new Bayesian method which sequentially processes the observed data points by forming candidate sequences of labels assigning data points to mixture components. Using conjugate priors, we derive analytically a recursive formula for the computation of the probability of each label sequence. The practical implementation of this algorithm keeps only a predefined number of the highest ranked label sequences with the ranking based on posterior probabilities. We show by numerical simulations that the proposed technique consistently outperforms both the k-means and the EM algorithm.
Arc welding technology for dissimilar joints

The most widely used metal underpinning modern industry is steel (carbon steel). Low-alloy steel designed to increase the strength and heat resistance of basic carbon steel and stainless steel to offer improved corrosion resistance and oxidation resistance are extensively used in the manufacture of thermal and nuclear power plants, chemical plants, etc. An extremely important and unavoidable practical requirement in modern steel construction technology is to be able to perform dissimilar welding of stainless steel to carbon and low-alloy steels (welding of dissimilar metals). This article profiles the basic principles and noteworthy features of dissimilar welding of stainless steel to carbon and low-alloy steels.
Combining AJAX and WSRF for Web-browser based Grid clients

This paper demonstrates the effectiveness of combining Asynchronous Javascript and XML (AJAX) and the Representational State Transfer (REST) architectural style with the Web Service Resource Framework (WSRF) standard. Accessing WS-Resources (according to WSRF) in a manner compatible with the REST principles, using a Web browser, makes it possible to provide a light-weight, portable client for interacting with scientific simulations in distributed computing environments, with similar functionality to pre-existing platform-specific clients that required a full installation procedure. This paper describes this client and emphasises which standards and principles of distributed computing have played a key role in putting this application together.
Characterization and Evaluation of Mobile CrowdSensing Performance and Energy Indicators

Mobile Crowdsensing (MCS) is a contribution-based paradigm involving mobiles in pervasive application deployment and operation, pushed by the evergrowing and widespread dissemination of personal devices. Nevertheless, MCS is still lacking of some key features to become a disruptive paradigm. Among others, control on performance and reliability, mainly due to the contribution churning. For mitigating the impact of churning, several policies such as redundancy, over-provisioning and checkpointing can be adopted but, to properly design and evaluate such policies, specific techniques and tools are required. This paper attempts to fill this gap by proposing a new technique for the evaluation of relevant performance and energy figures of merit for MCS systems. It allows to get insightson them from three different perspectives: end users, contributors and service providers. Based on queuing networks (QN), the proposed technique relaxes the assumptions of existing solutions allowing a stochastic characterization of underlying phenomena through general, non exponential distributions. To cope with the contribution churning it extends the QN semantics of a service station with variablenumber of servers, implementing proper mechanisms to manage the memory issues thus arising in the underlying process. This way, a preliminary validation of the proposed QN model against an analytic one and an in depth investigation also considering checkpointing have been performed through a case study.
Short-term wind power probabilistic forecasting considering spatial correlation

Wind power probabilistic forecasting is of great significance to the operation and dispatch of the power system. However, most researches have focused on how to predict wind power using local information rather than spatial correlation information of multiple wind farms in a region. In this paper a short-term wind power probabilistic forecasting approach considering spatial correlation is proposed. Originally, a set of explanatory variables highly correlated with the target variable is selected by calculating mutual information. Next, the principal component analysis can help to reconstruct the data and reduce the dimension of the explanatory variables. Finally, the conditional kernel density estimation is introduced to predict the short-term wind power of the target wind farm. Case studies on the dataset of Global Energy Forecasting Competition 2014 verify that the proposed approach can achieve better performance than traditional approach.
Audiovisual concatenative synthesis

Co-analysed audio and visual features can provide original concatenative synthesis effects in either or both modalities. This paper describes experiments in establishing audiovisual databases tagged by both audio and visual features, then creating new output streams by feature matching with a given input sequence; some intriguing effects are possible. Results are grounded in vectors of framewise data rather than higher level object recognition, but multi-modal processing extensions are discussed.
Fine-grained channel access in wireless LAN

Modern communication technologies are steadily advancing the physical layer (PHY) data rate in wireless LANs, from hundreds of Mbps in current 802.11n to over Gbps in the near future. As PHY data rates increase, however, the overhead of media access control (MAC) progressively degrades data throughput efficiency. This trend reflects a fundamental aspect of the current MAC protocol, which allocates the channel as a single resource at a time. This paper argues that, in a high data rate WLAN, the channel should be divided into separate subchannels whose width is commensurate with PHY data rate and typical frame size. Multiple stations can then contend for and use subchannels simultaneously according to their traffic demands, thereby increasing overall efficiency. We introduce FICA, a fine-grained channel access method that embodies this approach to media access using two novel techniques. First, it proposes a new PHY architecture based on OFDM that retains orthogonality among subchannels while relying solely on the coordination mechanisms in existing WLAN, carrier-sensing and broadcasting. Second, FICA employs a frequency-domain contention method that uses physical layer RTS/CTS signaling and frequency domain backoff to efficiently coordinate subchannel access. We have implemented FICA, both MAC and PHY layers, using a software radio platform, and our experiments demonstrate the feasibility of the FICA design. Further, our simulation results suggest FICA can improve the efficiency ratio of WLANs by up to 400% compared to existing 802.11.
Towards Constructive Text, Diagram, and Layout Generation for Information Presentation

Combining elements appropriately within a coherent page layout is a well-recognized and crucial aspect of sophisticated information presentation. The precise function and nature of layout has not, however, been sufficiently addressed within computational approaches; attention is often restricted to relatively local issues of typography and text-formatting, leaving broader issues of layout unaddressed. In this paper we focus on the selection and function of layout in pages that appropriately combine textual and graphical representation styles to yield coherent presentation designs. We demonstrate that layout offers a rich resource for achieving presentational coherence, alongside more traditional resources such as text-formatting and the text-internal marking of discourse connections. We also introduce an integrated approach to layout, text, and diagram generation. Our approach is developed on the basis of a preliminary empirical investigation of professionally produced layouts, followed by implementation within a prototype information system in the area of art history.
Biopesticides, Regulatory Innovation and the Regulatory State

This article analyses regulatory innovation. It considers, in particular, how a regulatory environmental agency has been encouraged to innovate in the area of biopesticides. The literature on regulatory innovation is reviewed, the discussion situated within Moran's theory of the regulatory state. It considers to what extent innovation has occurred within the agency, looking at its proactive stance, and how unusually for a regulatory body it has negotiated new policy spaces in which to operate. The article looks at the contextual drivers and also the exogenous and endogenous pressures behind the innovation. It shows how the executive has intervened in order to promote more use of biopesticides and how pressure is also being exerted within the regulatory authority. By using the existing literature and empirical evidence a framework is outlined for explaining the likelihood of regulatory innovation occurring in regulatory agencies.
Exploring the structure of mental representations by implementing computer algorithms with people

Computer metaphors have been a mainstay of cognitive psychology, treating minds like information processing systems that operate on memory and mix serial and parallel processes. Recent work has taken this idea beyond a metaphor, examining the consequences of treating people as components in an algorithm that is usually executed by digital computers. By implementing a popular class of randomized algorithms – Markov chain Monte Carlo algorithms – with people, we are able to generate samples from subjective probability distributions that reveal the mental representations that inform people’s judgments. In this chapter, we summarize the key idea behind this approach and review a number of ways in which it has recently been extended.
Interacting with Gestures: An Intelligent Virtual Environment

The paper addresses the opportunity of using gestures in virtual environments by taking into account current technologies for capturing human gestures, existing interaction techniques and various aspects dealing with gesture and gesticulation functionalities. Virtual environments have proven to be of an effective usefulness for a variety of applications such as medical training and exploration, military simulations, architecture, phobia therapy, etc. A great variety of devices have been developed for effectively interacting with such environments and many interaction techniques have been introduced. Many of them prove to be cumbersome and more or less obstructing the user and hence affecting his/her virtual experience. Natural gestures as a mean of human computer interaction have the great advantage of being the ideal interface as natural, efficient and intuitive means of communication (people use gestures everyday in a natural manner). Discussion is equally conducted on gestures being used for the three main tasks commonly encountered in virtual environments: selection, manipulation and travel. References to gesture definition and classification according to different criteria and their relevance for interacting in virtual environments are equally taken into account.
Writing Support for Controlled Natural Languages

In this paper we present interface techniques that support the writing process of machine-oriented controlled natural languages which are well-defined and tractable fragments of English that can be translated unambiguously into a formal target language. Since these languages have grammatical and lexical restrictions, it is important to provide a text editor that assists the writing process by using lookahead information derived from the grammar. We will discuss the requirements to such a lookahead text editor and introduce the semantic wiki AceWiki as an application where this technology plays an important role. We investigate two different approaches how lookahead information can be generated dynamically while a text is written and compare the runtimes and practicality of these approaches in detail.
Beyond the chalkboard: computer support for collaboration and problem solving in meetings

Although individual use of computers is fairly widespread, in meetings we tend to leave them behind. At Xerox PARC, an experimental meeting room called the Colab has been created to study computer support of collaborative problem solving in face-to-face meetings. The long-term goal is to understand how to build computer tools to make meetings more effective.
seL4: formal verification of an OS kernel

Complete formal verification is the only known way to guarantee that a system is free of programming errors. We present our experience in performing the formal, machine-checked verification of the seL4 microkernel from an abstract specification down to its C implementation. We assume correctness of compiler, assembly code, and hardware, and we used a unique design approach that fuses formal and operating systems techniques. To our knowledge, this is the first formal proof of functional correctness of a complete, general-purpose operating-system kernel. Functional correctness means here that the implementation always strictly follows our high-level abstract specification of kernel behaviour. This encompasses traditional design and implementation safety properties such as the kernel will never crash, and it will never perform an unsafe operation. It also proves much more: we can predict precisely how the kernel will behave in every possible situation. seL4, a third-generation microkernel of L4 provenance, comprises 8,700 lines of C code and 600 lines of assembler. Its performance is comparable to other high-performance L4 kernels.
Organization and Evolution of the cotG and cotH Genes of Bacillus subtilis

ABSTRACT The cotG and cotH genes of Bacillus subtilis encode two previously characterized spore coat proteins. The two genes are adjacent on the chromosome and divergently transcribed by σK, a sporulation-specific σ factor of the RNA polymerase. We report evidence that the cotH promoter maps 812 bp upstream of the beginning of its coding region and that the divergent cotG gene is entirely contained between the promoter and the coding part of cotH. A bioinformatic analysis of all entirely sequenced prokaryotic genomes showed that such chromosomal organization is not common in spore-forming bacilli. Indeed, CotG is present only in B. subtilis, B. amyloliquefaciens, and B. atrophaeus and in two Geobacillus strains. When present, cotG always encodes a modular protein composed of tandem repeats and is always close to but divergently transcribed with respect to cotH. Bioinformatic and phylogenic data suggest that such genomic organizations have a common evolutionary origin and that the modular structure of the extant cotG genes is the outcome of multiple rounds of gene elongation events of an ancestral minigene.