Miracle-dz/UniFAR-FTUs huggingface dataset:
Inhibition of RNA Helicases of ssRNA+ Virus Belonging to Flaviviridae, Coronaviridae and Picornaviridae Families

Many viral pathogens encode the motor proteins named RNA helicases which display various functions in genome replication. General strategies to design specific and selective drugs targeting helicase for the treatment of viral infections could act via one or more of the following mechanisms: inhibition of the NTPase activity, by interferences with ATP binding and therefore by limiting the energy required for the unwinding and translocation, or by allosteric mechanism and therefore by stabilizing the conformation of the enzyme in low helicase activity state; inhibition of nucleic acids binding to the helicase; inhibition of coupling of ATP hydrolysis to unwinding; inhibition of unwinding by sterically blocking helicase translocation. Recently, by in vitro screening studies, it has been reported that several benzotriazole, imidazole, imidazodiazepine, phenothiazine, quinoline, anthracycline, triphenylmethane, tropolone, pyrrole, acridone, small peptide, and Bananin derivatives are endowed with helicase inhibition of pathogen viruses belonging to Flaviviridae, Coronaviridae, and Picornaviridae families.
A New and Simple Method for Isolating Genomic Dna from Julandaceae for Genetic Diversity Analysis

Isolation of high-quality DNA from long stored Julandaceae leaves or dried Julandaceae leaves is particularly difficult because of their high levels of polyphenols, lipin, tannin, pigment, terpene and other compounds. The yields and quality of genomic DNA are considerably affected when the common protocol for DNA isolation is applied to the long stored or dried Julandaceae leaves. A simple, rapid and efficient protocol for the extraction of DNA from the Julandaceae leaves is described. The modified hexadecyltrimethylammonium bromide (CTAB) procedure, which uses high concentrations of polyvinylpyrrolidone (6% (w/v)) and 5% bentonite in the high-salt-concentration extraction buffer to remove polyphenols and polysaccharides. This protocol results in high yields of DNA. The average yield of DNA ranged from 986-1824 µg/g of fresh weight of leaves. Downstream results indicate that DNA quality is sufficient for random amplification of polymorphic DNA (RAPD) and amplified fragment length polymorphism (AFLP) analyses. Extractions are scaled down to suit 1.5-mL Eppendorf tubes, allowing easier handling and enhanced sterility.
Exploring the role of microglia in mood disorders associated with experimental multiple sclerosis

Microglia is increasingly recognized to play a crucial role in the pathogenesis of psychiatric diseases. In particular, microglia may be the cellular link between inflammation and behavioral alterations: by releasing a number of soluble factors, among which pro-inflammatory cytokines, that can regulate synaptic activity, thereby leading to perturbation of behavior. In multiple sclerosis (MS), the most common neuroinflammatory disorder affecting young adults, microglia activation and dysfunction may account for mood symptoms, like depression and anxiety, that are often diagnosed in patients even in the absence of motor disability. Behavioral studies in experimental autoimmune encephalomyelitis (EAE), the animal model of MS, have shown that emotional changes occur early in the disease and in correlation to inflammatory mediator and neurotransmitter level alterations. However, such studies lack a full and comprehensive analysis of the role played by microglia in EAE-behavioral syndrome. We review the experimental studies addressing behavioral symptoms in EAE, and propose the study of neuron-glia interaction as a powerful but still poorly explored tool to investigate the burden of microglia in mood alterations associated to MS.
Bimodal person-dependent emotion recognition comparison of feature level and decision level information fusion

Modern HCI systems tend to build a new channel of human-computer interaction in which the human emotion is understandable by computers. Since Humans depict emotional behavior in combination of various modalities (e.g. facial expression, speech articulations); The HCI should reliably perceive emotional information from multiple channels. The goal of the paper is to propose an approach for combining emotion related information from speech and facial expression. Two fusion approaches (feature level and decision level) are presented and compared with experimental results. Results show that the decision level fusion performs better than the other systems.
Phospholipases A2 Mediate Amyloid-β Peptide-Induced Mitochondrial Dysfunction

Mitochondrial dysfunction has been implicated in the pathophysiology of Alzheimer's disease (AD) brains. To unravel the mechanism(s) underlying this dysfunction, we demonstrate that phospholipases A2 (PLA2s), namely the cytosolic and the calcium-independent PLA2s (cPLA2 and iPLA2), are key enzymes mediating oligomeric amyloid-β peptide (Aβ1–42)-induced loss of mitochondrial membrane potential and increase in production of reactive oxygen species from mitochondria in astrocytes. Whereas the action of iPLA2 is immediate, the action of cPLA2 requires a lag time of ∼12–15 min, probably the time needed for initiating signaling pathways for the phosphorylation and translocation of cPLA2 to mitochondria. Western blot analysis indicated the ability of oligomeric Aβ1–42 to increase phosphorylation of cPLA2 in astrocytes through the NADPH oxidase and mitogen-activated protein kinase pathways. The involvement of PLA2 in Aβ1–42-mediated perturbations of mitochondrial function provides new insights to the decline in mitochondrial function, leading to impairment in ATP production and increase in oxidative stress in AD brains.
roactive product quality control : An integrated product and process control pproach to MIMO systems

Real-time control of product performance parameters is a key for proactive quality control (QC), as it can prevent the occurrence of potential quality problems in the earliest stage of manufacturing. It is recognized that dynamic product QC must be coordinated with the control of the process through which eywords: roduct quality control rocess control ntegrated product and process engineering ulti-input–multi-output system the product is manufactured. The integrated product and process control (IPPC) design methodology introduced recently is a proven approach to the simultaneous control of both the product quality and the process performance. In this paper, a general IPPC design methodology for multi-input–multi-output (MIMO) systems is introduced. A case study on polymeric coating curing shows that the resulting control system is capable of effectively tracking the set-points of both the product and the process, and demonstrating a satisfactory performance in rejecting disturbances, thereby ensuring achievement of desirable product quality and process performance.
Robust power plant control using clonal selection of immune algorithm based multiobjective

Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature, the change of the dynamic characteristics in the reheater. Up to the present time, PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper focuses on tuning of the controller with disturbance rejection using immune based multiobjective approach. In this paper, an ITSE (integral of time weighted squared error) is used to decide performance of tuning results.
FILTER STRUCTURES COMPOSED OF ALLPASS SUBFILTERS FOR HIGH-SPEED NARROW-BAND AND WIDEBAND FILTERING H

Abs t rac t Ð An approach to obtain high-speed recursive narrow-band and wideband filters is proposed. In the narrow-band case, a two-stage structure consisting of a periodic model filter and a masking filter in cascade is used. The model filter is a parallel connection of two allpass subfilters, while the masking filter is composed of N allpass subfilters in parallel. In the wideband case, a narrow-band filter and an allpass filter in parallel are used. All recursive parts correspond to functions of z N , which results in structures with high maximal sample frequencies. Further, the structures can be used for both lowpass and highpass filtering at the same time. It is also possible to realize filters with approximately linear-phase in the passband. Examples are included which compare this approach with other similar techniques.
Self-Grounded Vision: Hand Ownership Modulates Visual Location through Cortical β and γ Oscillations

Vision is known to be shaped by context, defined by environmental and bodily signals. In the Taylor illusion, the size of an afterimage projected on one's hand changes according to proprioceptive signals conveying hand position. Here, we assessed whether the Taylor illusion does not just depend on the physical hand position, but also on bodily self-consciousness as quantified through illusory hand ownership. Relying on the somatic rubber hand illusion, we manipulated hand ownership, such that participants embodied a rubber hand placed next to their own hand. We found that an afterimage projected on the participant's hand drifted depending on illusory ownership between the participants' two hands, showing an implication of self-representation during the Taylor illusion. Oscillatory power analysis of electroencephalographic signals showed that illusory hand ownership was stronger in participants with stronger α suppression over left sensorimotor cortex, whereas the Taylor illusion correlated with higher β/γ power over frontotemporal regions. Higher γ connectivity between left sensorimotor and inferior parietal cortex was also found during illusory hand ownership. These data show that afterimage drifts in the Taylor illusion do not only depend on the physical hand position but also on subjective ownership, which itself is based on the synchrony of somatosensory signals from the two hands. The effect of ownership on afterimage drifts is associated with β/γ power and γ connectivity between frontoparietal regions and the visual cortex. Together, our results suggest that visual percepts are not only influenced by bodily context but are self-grounded, mapped on a self-referential frame. SIGNIFICANCE STATEMENT Vision is influenced by the body: in the Taylor illusion, the size of an afterimage projected on one's hand changes according to tactile and proprioceptive signals conveying hand position. Here, we report a new phenomenon revealing that the perception of afterimages depends not only on bodily signals, but also on the sense of self. Relying on the rubber hand illusion, we manipulated hand ownership, so that participants embodied a rubber hand placed next to their own hand. We found that visual afterimages projected on the participant's hand drifted laterally, only when the rubber hand was embodied. Electroencephalography revealed spectral dissociations between somatic and visual effects, and higher γ connectivity along the dorsal visual pathways when the rubber hand was embodied.
Changes in hours worked, 1950?2000

This article describes changes in the number of average weekly hours of market work per person in the United States since World War II. Overall, this number has been roughly constant; for various groups, however, it has shifted dramatically - from males to females, from older people to younger people, and from single- to married-person households. The article provides a detailed look at how the lifetime pattern of work hours has changed since 1950 for different demographic groups. This article also documents several factors that lead to the reallocation of hours worked across groups: increases in relative wages of females to males; technological innovations that shift female labor from the home to the market; increases in Social Security benefits to retired workers; and changes in family structure. The data presented are based on those collected by the U.S. Bureau of the Census during the 1950? 2000 decennial censuses.
Maximum margin binary classifiers using intrinsic and penalty graphs

In this paper a variant of the binary Support Vector Machine classifier that exploits intrinsic and penalty graphs in its optimization problem is proposed. We show that the proposed approach is equivalent to a two-step process where the data is firstly mapped to an optimal discriminant space of the input space and, subsequently, the original SVM classifier is applied. Our approach exploits the underlying data distribution in a discriminant space in order to enhance SVMs generalization ability. We also extend this idea to the Least Squares SVM classifier, where the adoption of the intrinsic and penalty graphs acts as a regularizer incorporating discriminant information in the overall solution. Experiments on standard and recently introduced datasets verify our analysis since, in the cases where the classes forming the problem are not well discriminated in the original feature space, the exploitation of both intrinsic and penalty graphs enhances performance.
Interactive Ray Tracing on a Virtual Shared‐Memory Parallel Computer

This paper describes the results of experiments with accelerated ray tracing on a virtual shared‐memory parallel computer and attempts to determine whether this kind of architecture would be suitable for an interactive ray tracing system. The machine used, the Kendall Square Research KSR1, is described in sufficient detail for its novel features to be appreciated. The paper describes a new ray tracer written specifically to capitalise on the KSR1 's features. Models used in the experiments include well‐known test cases from the Haines database, permitting comparison with previously reported results. The results show that the program scales well up to 230 processors, and that with progressive rendering initial rendering times can be reduced to as little as 0.2 second on 32 processors.
A Look at Regional Differences in the Use of Online Incivility

The Internet has become a popular outlet for citizens to exercise their freedom of speech and engage in political discussion. However, the use of uncivil language online has become an increasingly common practice, in part due to specific characteristics of the Internet, such as increased anonymity. This study seeks to address if regional differences influence the incidence of online incivility in newspaper comment forums. Using a content analysis of a combined 2,604 newspaper comments, this study compares the incidence of incivility between the Arizona Daily Star and the Boston Globe to see if the commenters of one newspaper proved to be more “uncivil. ” The study results revealed that incivility occurred significantly more often in the Boston Globe than the Arizona Daily Star. By analyzing the specific regional factors characteristic of each newspaper, it may be possible to gain a better understanding of why such a difference occurred and ultimately why people use such language.
Machine Translation System for Patent Documents Combining Rule-based Translation and Statistical Postediting Applied to the NTCIR-10 PatentMT Task

In this article, we describe system architecture, preparation of training data and experimental results of the EIWA group in the NTCIR-9 Patent Translation Task. Our system is combining rulebased machine translation and statistical post-editing. Experimental results for Japanese to English (JE) subtask show 0.3169 BLEU score, 7.8161 NIST score, 0.7404 RIBES score, 3.43 adequacy score and 0.6381 pair wise comparison score for acceptability. Experimental results for Chinese to English (CE) subtask show 0.2597 BLEU score, 7.2282 NIST score, 0.7455 RIBES score, and 3.05 adequacy score.
A Service Robot Named Markovito

The idea of service robots to assist humans in everyday life has been around for many years. Although there is muc h work in developing different abilities for this kind of robo ts, little attention has been paid for the integration of these behavio rs into a complete functional system. In this paper we present our se rvice robot called Markovito. Markovito integrates different sk ills to interact with humans and its environment in order to: i) deliver messages and objects between people, ii) search for an objec t, iii) navigate to different destination points, and iv) follow a person under user requests. Experiments has shown that Markovito i s reliable in the execution of these tasks, while keeping a sim ple and intuitive robot software architecture able to incorporate new abilities in the near future.
Initial rotor position estimation of an interior permanent-magnet synchronous machine using carrier-frequency injection methods

This work presents a method using carrier-frequency injection to estimate the initial rotor position and magnetic polarity for an interior permanent-magnet synchronous machine. A nonsaturating inductance model of the machine provides no information about the polarity of the rotor magnet because the position observer based on this model is locally stable at both poles. To distinguish the polarity of the rotor magnet, the magnetic saturation effect can be used. The Taylor series can be used to describe the nonlinear magnetic saturation relationship between the current and the flux linkage in the d-axis rotor reference frame. The second-order term produces the second harmonic component of the carrier frequency, and the sign of its coefficient identifies the polarity of the rotor magnet being tracked. Both simulation and experimental results show good response of the position observer at several rotor electrical positions using either a rotating vector in the stationary reference frame or a oscillating vector in the estimated rotor reference frame.
Social profiles of virtual communities

The phenomenon "virtual community" reflects the social, political and economic impact of information and communications technology changing the architecture of interaction. We present an approach to describe and manage the social environments of transactions that are provided in virtual communities. We explore virtual communities, their novel social structures and the dynamics of the social momentum of communities. We present an empirical study of fifty virtual communities.
A Profound Survey of Sensor Networks & Related Routing Protocols

Advances in wireless sensor networks have led to many new protocols specifically designed for sensor networks where energy awareness is an essential consideration. Most of the attention, however, has been given to the routing protocols since they might differ depending on the application and network architecture. Tiny sensor nodes create sensor network. These nodes are severely constrained by energy, storage capacity and computing power. The prominent task of this network is to design proficient routing protocols for to make the node's life last longer. In this paper, we first analyze the requirements of sensor networks and its architecture. Then, we enlighten the existing routing protocols for sensor networks and present a critical analysis of these protocols. The paper concludes with open research issues. At the end of this paper, we compare and contrast these protocols.
Conditional Cramér–Rao Lower Bounds for DOA Estimation and Array Calibration

This letter aims at deriving the Cramér-Rao lower bounds (CRLB) of the direction-of-arrival (DOA) estimation and array calibration precisions in the case of determined and unknown signals based on the assumptions of small array perturbations. The analysis begins with a comprehensive perturbed array output formulation, and it is effective for various kinds of perturbations, such as mutual coupling, gain/phase uncertainty and sensor location error. The CRLB of the DOA and array perturbation parameters are well separated from each other in the letter, which facilitates their usage in performance evaluation of the self-calibration methods. However, the CRLB are finally given in the form of the inverse of the corresponding Fisher information matrices (FIM) as the inversion process can hardly be implemented mathematically. Simulation results are provided to compare the obtained conditional CRLB with the parameter estimation precision of the maximum likelihood estimators (MLE) and the unconditional CRLB.
Security Threats in Wireless Sensor Networks in Each Layer

Security Threats in Wireless Sensor Networks in Each Layer Anitha S Sastry Email : anithasastry@gmail.com Department of Electronics and Communication Engineering, Global Academy of Technology, Bangalore-98 Shazia Sulthana Email : shaziasulthana@yahoo.co.in Department of Electronics and Communication Engineering, Global Academy of Technology, Bangalore-98 Dr. S Vagdevi Department of Information Science and Engineering, Global Academy of Technology, Bangalore-98 Email: dr.vagdevi@gat.ac. in ------------------------------------------------------------------ABSTRACT-------------------------------------------------------------As the Wireless Sensor Networks (WSN) prove to be more beneficial in real-world applications. At the same time threatened by vulnerabilities. The threats faced by these WSN are similar but not limited to those observed in a simple network of computers or Internet. Attacks at all the layers of network protocol can be expected. Wireless sensor networks are characterized by severely constrained computational and energy resources and ad hoc operational environment. Resource limitations of WSN make these threats even more dangerous, even up to the extent of the consumption of a whole node or even a complete small network. This paper deals with the security aspects in the wireless sensor network giving the probable counter measures for the same.
Uncovering Population Trends with Actionable Clustering

Clustering is a widely-used data mining tool, which aims to discover groups of similar items in data. We introduce a new clustering paradigm, actionable clustering, that enables the discovery of population trends. Unlike previous clustering paradigms that aim to understand relationships amongst the individual members, the goal of actionable clustering is to uncover trends at the populations level (e.g. treatment groups) through the analysis of their members (e.g. subjects across different treatments). Insights gained from the trends of populations can often support a call to action that cannot be informed through previous clustering methods. We propose the first actionable clustering algorithm, and prove that it finds near-optimal solutions when data possesses inherent cluster structure. The insights revealed by actionable clusterings enabled experts in the field of medicine to isolate successful treatments for a neurodegenerative disease, and those in finance to discover patterns of unnecessary spending. We also perform experiments on six UCI datasets, which show that our algorithm outputs a superior quality actionable clustering when compared with its adapted competitors.