Miracle-dz/UniFAR-FTUs huggingface dataset:
Utilization of a mouse model of infection to investigate Kaposi ’ s sarcoma-associated herpesvirus LANA function in vivo

1 Kaposi’s sarcoma-associated herpesvirus (or human herpesvirus 8) is a gamma-2-herpesvirus that was first identified in 1994 by Yuan Chang and his colleagues (Chang et al., 1994). It is the etiological agent of Kaposi’s sarcoma (KS), primary effusion lymphoma (PEL) and multicentric Castleman’s disease (MCD) (Coscoy, 2007; Wu et al., 2010). The genome of KSHV consists in a long unique region (LUR) with approximately 145 kb which is flanked by 20-35 kb of non-coding terminal repeats region with a high G+C content (Juillard et al., 2016; Moore and Chang, 2003). KSHV life cycle has two distinct phases of infection: a lytic infection and a persistent latent infection, both with different patterns of gene expression and both contribute to the pathogenicity of the virus (Uppal et al., 2014; Wu et al., 2010). In latently infected cells, viral genome is maintained as a multi-copy, non-integrated episome (Wen and Damania, 2010; Wu et al., 2010). KSHV latency-associated nuclear antigen (kLANA) is the responsible protein for the establishment of latency and it is constituted by a proline-rich N-terminal domain, an internal repeat region and the C-terminal DNA binding domain (DBD) (Figure 1A) (Ponnusamy et al., 2015). There are two key components to episome persistence in proliferating cells and kLANA is responsible for both: the episomal DNA need to replicate with each cell division and the episomes have to segregate to daughter cells nuclei following mitosis to avoid their destruction in the cytoplasm (Juillard et al., 2016). Only in vitro studies were performed to try to understand a possible function for internal repeat region, which is the more uncharacterized part of kLANA. This internal region is constituted by three segments: an aspartate and glutamate (DE) region, from amino acid 330 to 430, a glutamine (Q) region, from amino acid 440 to 756 and a leucine (L), valine (V), glutamate and glutamine Utilization of a mouse model of infection to investigate Kaposi’s sarcomaassociated herpesvirus LANA function in vivo
ROLE OF MORPHO-PHYSIOLOGICAL ATTRIBUTES ON YIELD IN LENTIL

Samad MA, Yasmin A, Mondal MMA (2010) Role of morpho-physiological attributes on yield in lentil. Int. J. Sustain. Crop Prod. 5(4), 4245. The experiment was carried out in Rabi season (November-March) of 2008-09 at the experimental farm of Bangladesh Institute of Nuclear Agriculture, Mymensingh (2475 ́ N latitude and 9050 ́ E longitude) to investigate variability and correlation for morpho-physiological, yield attributes and yield in 16 lentil mutants/cultivar. Results revealed that high yielding genotypes, in general, showed taller plant, higher number branches plant, greater leaf area index (LAI), total dry mass (TDM) plant and absolute growth rate (AGR) than in the low yielding ones. In terms of seed yield, two mutants, LM-31 and LM-44 produced higher seed yield attributed for higher number of pods plant and bolder seed sizes. In contrast, LM-135 and LM-201 produced lower seed yield due to production of fewer pods and smaller seed sizes. Seed yield and pod number had highly positive and significant correlation with branch number and TDM, and TDM depends on branch number, LAI and AGR indicating yield could be increased by increasing dry matter production through increased LAI and AGR. Hence, these traits could be used for the improvement of seed yield resulting in the evolution of high yielding varieties of lentil.
Identification and compensation of parasitic effects in coreless linear motors

• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
A doubly nonlocal Laplace operator and its connection to the classical Laplacian

In this paper, motivated by the state-based peridynamic framework, we introduce a new nonlocal Laplacian that exhibits double nonlocality through the use of iterated integral operators. The operator introduces additional degrees of flexibility that can allow for better representation of physical phenomena at different scales and in materials with different properties. We study mathematical properties of this state-based Laplacian, including connections with other nonlocal and local counterparts. Finally, we obtain explicit rates of convergence for this doubly nonlocal operator to the classical Laplacian as the radii for the horizons of interaction kernels shrink to zero.
Salient region detection in the task of visual question answering

Salient region detection in Visual Question Answering (VQA) is an attempt to simulate a human ability to quickly perceive a scene by selectively looking on image fragments instead of processing a whole scene. The conventional approach deals with a neural network application. However, the Convolutional Neural Networks (CNNs) have many disadvantages compared with traditional methods for salient region detection. We modified the basic algorithm of salient region detection for VQA task by selecting such image fragments, which have a high probability to be included in a questionnaire. The experiments have been conducted on images from MS-COCO dataset and provided good segmentation results.
ON FACTORS AFFECTING MANAGEMENT STYLES

Management style can be stated as a way to manage an organization and its people. Various models have been proposed by research scholars to identify the management styles adopted by the supervisors and managers in a company. The concept of Management styles dates back to ancient era and is evident in Sanskrit Literature. However, the articulation of Management styles happened in the nineteenth century when this topic started gaining attention of the researchers. With growing industries, both in number and their sizes, twentieth century experienced a very comprehensive research on this topic so as to enable sustainable growth of these companies. The study accounts for the work on Management styles in India and abroad.This paper is an attempt to review the studies on Management styles and bridge the gap for budding researchers to pursue this topic with new and innovative concepts. So also, it will enable them to conduct studies in the upcoming sectors like Insurance, telecom etc.
Analysis and optimisation of coupled winding in magnetic resonant wireless power transfer systems with orthogonal experiment results

1 Abstract —The coupled magnetic resonant unit (CMRU) has great effect on the transmitting power capability and efficiency of magnetic resonant wireless power transfer system. The key objective i.e. the efficiency coefficient k Q is introduced in the design of CMRU or the coupled windings based on the mutual inductance model. Then the design method with orthogonal experiments and finite element method simulation is proposed to maximize the k Q due to low precise analytical model of AC resistance and inductance for PCB windings at high- frequency. The method can reduce the design iterations and thereby can get more optimal design results. The experiments verified the design objective of k Q as well as the design method effectively. In the optimal PCB windings prototype at operating frequency of 4 MHz, the k Q and the maximum efficiency are increased by about 12% and 4% respectively. ,
PARAMETER-FREE INCREMENTAL CO-CLUSTERING ON OPTIMIZED FEATURES

To improve effectiveness and efficiency for clustering dynamic multi-modal data in cyberphysical-social systems, several co-clustering approaches have been proposed with the rapid growth of CyberPhysical-Social Systems. Large amounts of dynamic multi-modal data are being generated and collected, so clustering Multi modal dynamic data is challenging. In highdimensional dynamic data, classic metrics fail in identifying real similarities between objects. Moreover, the huge number of features makes the cluster interpretation hard. In the proposed method, the single-modality similarity measure is extended to multiple modalities and three operations, those are cluster creating, cluster merging, and instance partitioning, are defined to incrementally integrate new arriving objects to current clustering patterns without introducing additive parameters. Moreover, an adaptive weight scheme is designed to measure the importance of feature modalities based on the intra-cluster scatters and also add feature selection method for reducing time. Extensive experiments on various multimodal dynamic datasets demonstrate the effectiveness of the proposed approach.
Numerical Focusing of a Wide Field-of-View Instrument for Monitoring the Planetary Energy Budget

Wide field-of-view optical instruments based on Ritchey-Crétien telescopes have been proposed to replace narrow field-of-view scanning instruments for Earth radiation budget monitoring applications. A disadvantage of such instruments is that they are subject to significant focal plane distortion. A novel numerical focusing scheme is proposed and demonstrated using a Monte Carlo ray-trace-based simulation of the performance of a candidate instrument. Results are presented which indicate that image recovery error can be significantly reduced using the proposed algorithm.
Recent Trends in Computing ( ICRTC ’ 2015 ) Validating the E ff ectiveness of Object-Oriented Metrics for Predicting Maintainability

In this study, empirically investigates the relationship of existing class level object-oriented metrics with a quality parameter i.e., maintainability. Here, different subset of Object-Oriented software metrics have been considered to provide requisite input data to design the models for predicting maintainability using Neuro-Genetic algorithm (hybrid approach of neural network and genetic algorithm). This technique is applied to estimate maintainability on two different case studies such as Quality Evaluation System (QUES) and User Interface System (UIMS). The performance parameters of this technique are evaluated based on the basis of Mean absolute error (MAE), Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), and Standard Error of the Mean (SEM). The results reported that the identified subset metrics demonstrated an improved maintainability prediction with higher accuracy. c © 2014 The Authors. Published by Elsevier B.V. Peer-review under responsibility of organizing committee of Fourth International Conference on Selected Topics in Mobile & Wireless Networking (MoWNet’2014).
Lyrics Summarization Inspired by Audio

Given the peculiar structure of songs, applying generic text summarization methods to lyrics can lead to the generation of highly redundant and incoherent text. In this paper, we propose to enhance state-of-the-art text summarization approaches with a method inspired by audio thumbnailing. Instead of searching for the thumbnail clues in the audio of the song, we identify equivalent clues in the lyrics. We then show how these summaries that take into account the audio nature of the lyrics outperform the generic methods according to both an automatic evaluation and human judgments.
Detection and Mitigation of DDOS Attacks in Software Defined Networks : A Survey

DDOS Attacks have been a serious threat to the Network Security for the last few years. With the introduction of SDN, Although the problem of DDOS Attacks can easily be resolved in traditional networks as it provides a central control plane paradigm for such attacks in the network but due to the separate control plane it also increases the SDN-self DDOS threats. In this paper, we first look at the algorithms supported by SDN for the detection of DDOS in traditional network. Then we describe the different types of algorithms for the detection and mitigation of SDN-self DDOS threats. Also, we classify the different algorithms based on selected approaches and compare
Elephants in Sri Lanka : past present and future Policy

Introduction The Asian elephant (Elephas maximus) is considered an ‘endangered species’. Historically, the range of the Asian elephant extended from the Euphrates and Tigris Rivers in west Asia to the Yangtze-Kiang River in China (Olivier, 1978). Exponential growth of human populations and attendant land use changes over the past few decades have extirpated Asian elephants from approximately 85% of their former range. As a ‘free ranging’ or ‘wild’ species, the Asian elephant (hereafter, ‘the elephant’) is now limited to a number of isolated and fragmented populations in thirteen south and southeast Asian states with a total estimated population of 35,000–50,000 (Sukumar, 1989; Santiapillai and Jackson, 1990). In Sri Lanka, as in the rest of Asia, the elephant has been closely associated with man and has played a central role in the country’s economy, conflicts, religion, and culture for many millennia (Jayewardene, 1994). It continues to hold an important position in the religious and cultural traditions of the country and plays a significant and high profile role in the country’s conservation efforts.
Putting gravity in control C

The aim of the present manuscript is to present a novel proposal in Geometric Control Theory inspired in the principles of General Relativity and energy-shaping control. It has been a pleasure to prepare this contribution to celebrate the two parallel lives of effort and inspiration in Theoretical Physics of Rodolfo Gambini and Luis Herrera. Albeit different in scope, their research shares the common thread of gravity and its geometric principles, together with their ultimate consequences ranging from the very nature of space and time to the astrophysical implications of thermodynamics and gravity. It is thus our wish to take this opportunity to present a different perspective on the use of the same guiding principles that led to General Relativity and explore, even if very briefly, its implications within the area of control theory. General relativity brought a new paradigm in the understanding of physical reality, establishing a deep connection between geometry and physics through the falsification of the motion of a test body due to a universal force [1] by free motion in a curved manifold. In such case, curvature becomes morally tantamount to a universal force field strength. This insight gave rise to a successful geometrization programme for field theories. However, due to the nonuniversal nature of the other known interactions, the geometrization is slightly different from that of gravity. In geometric field theories, problems are of two kinds: given the sources determine the curvature, or, given the curvature determine the trajectories of test particles. In this two type of problems, it is the source which determines the background geometry for the motion. Thus, in general, changing the source distribution changes the curvature of the spacetime manifold, and thus the motion of the test particles. Therefore, in principle, one could be able to reproduce any observed motion in space by means of a suitable distribution of energy. By placing appropriate sources here and there, one can control the motion of test particles. Of course, one cannot simply engineer and energy-momentum tensor so that test particles follow our desired trajectories. Most of such energy distributions are indeed unphysical from the spacetime point of view. However, this very principle might be applied to a different physical setting, one for which the background geometry is not the spacetime manifold. Such is the case of the geometrization of classical mechanics and the control theory that can be built from it. We begin by briefly revisiting the geometrization programme of classical mechanics. Let us consider a mechanical systems characterized by n degrees of freedom (DoF) and defined by a Lagrangian function L : TQ −→ R. Here, the configuration space is an n dimensional manifold Q whose tangent bundle is denoted by TQ. The generic problem in geometric mechanics can be stated as follows. Given a pair of points p1, p2 ∈ Q, find the curve γ ⊂ Q γ : [0, 1] −→ Q, γ(0) = p1, γ(1) = p2, (1) for which the functional S [γ] = ∫ 1
Sentiment Analysis with Word Embedding

The basic task of sentiment analysis is to determine the sentiment polarity (positivity, neutrality or negativity) of a piece text. The traditional bag-of-words models deficiencies affect the accuracy of sentiment classifications. The purpose of this study is to improve the accuracy of the sentiment classification by employing the concept of word embedding. This study uses Word2Vec to produce high-dimensional word vectors that learn contextual information of words. The resulting word vectors are used to train machine learning algorithms in the form of classifiers for sentiment classification. Our experiments on real world datasets shows that the use of word embedding improves the accuracy of sentiments classification.
Improving Vision-based Topological Localization by Combing Local and Global Image Features

Vision-based mobile robot localization method has become popular in recent years. Most of the current approaches use either global or local image feature for appearance representation. However, pure global image feature based method suffers from its low invariance to occlusions and view point changes. Meanwhile, pure local image feature based method ignores the global context of the image, which is very important in place representation. In this paper, we present a vision-based robot localization system that uses both local and global image features to represent locations, and the estimated location of the robot is determined by a Bayesian tracking filter which uses the proposed hybrid image representation. Experiments were conducted using a 1200 m campus route and the results show that the proposed method works reliably even with large appearance changes.
HPTLC PHENOLIC COMPOUNDS FINGERPRINT AND ANTIOXIDANT ACTIVITY OF SAMBUCUS EBULUS LEAVES AND FRUIT

Phenolic compounds fingerprint of the 50% (v/v) ethanol extracts obtained from leaves (LE) and fruits (FE) of Sambucus ebulus (dwarf elder), fam Adoxaceae, was obtained by high performance thin layer chromatography (HPTLC), in order to evaluated its qualitative chemical composition and antioxidant activity (by DPPH and TAC assays). Quantitative evaluation of total polyphenolic compounds was made by Folin Ciocalteu assay. The obtained fingerprints showed that both extracts are characterized by the presence of flavonoid glycosides and phenol carboxylic acids. The presence of anthocyanins was revealed only in fruit extract Total phenol content was 19.5 mg GAE/g dry material for LE and 52,5 mg GAE/g dry material for FE. Both extracts have important antioxidant activity in a concentration-dependent manner, fruits extract exhibiting a higher one.
FuzzFactory: domain-specific fuzzing with waypoints

Coverage-guided fuzz testing has gained prominence as a highly effective method of finding security vulnerabilities such as buffer overflows in programs that parse binary data. Recently, researchers have introduced various specializations to the coverage-guided fuzzing algorithm for different domain-specific testing goals, such as finding performance bottlenecks, generating valid inputs, handling magic-byte comparisons, etc. Each such solution can require non-trivial implementation effort and produces a distinct variant of a fuzzing tool. We observe that many of these domain-specific solutions follow a common solution pattern. In this paper, we present FuzzFactory, a framework for developing domain-specific fuzzing applications without requiring changes to mutation and search heuristics. FuzzFactory allows users to specify the collection of dynamic domain-specific feedback during test execution, as well as how such feedback should be aggregated. FuzzFactory uses this information to selectively save intermediate inputs, called waypoints, to augment coverage-guided fuzzing. Such waypoints always make progress towards domain-specific multi-dimensional objectives. We instantiate six domain-specific fuzzing applications using FuzzFactory: three re-implementations of prior work and three novel solutions, and evaluate their effectiveness on benchmarks from Google's fuzzer test suite. We also show how multiple domains can be composed to perform better than the sum of their parts. For example, we combine domain-specific feedback about strict equality comparisons and dynamic memory allocations, to enable the automatic generation of LZ4 bombs and PNG bombs.
Controlling the Head Position during individual HRTF Measurements and its Effect on Accuracy

The head-related transfer function (HRTF) describes the incident direction and frequency dependent representation of sound at the eardrum of a listener, caused by transmission effects of the specific outer ear, head and torso. It is an individual ”fingerprint” that we are used to hear the world through, and when the HRTF of a subject is known, persuading simulation of free-field listening can be achieved by processing a signal with the HRTF prior to presentation over headphones [1]. When measuring HRTFs, one source of error is movement of the subject, particularly the head, causing the effective sound incident direction to dynamically deviate from the desired one. Such movement is inevitable and occurs even if the subjects are instructed to remain still, and do in their subjective impression. Commonly, this source of inaccuracy is addressed by providing a headrest or similar mechanic support, which however cannot avoid such movement completely [2–6]. In this work, a novel method for both recording and interactively controlling the head position based on visual feedback is presented. The approach was successfully implemented and applied in individual HRTF measurements, where repeated rounds of measurements were conducted and a stable subject position was particularly crucial. The results show that excellent control over the head position and orientation is achieved, and the connected residual influence on the obtained HRTFs is in a negligible size.
Quantifier-free least fixed point functions for phonology

In this paper we deﬁne quantiﬁer-free least ﬁxed point functions (QFLFP) and argue that they are an appropriate and valuable approach to modeling phonological processes (construed as input-output maps ). These functions, characterized in terms of ﬁrst order logic interpretations over graphs, provide a close ﬁt to the observed typology, capturing both local and long-distance phenomena, but are also restrictive in desirable ways. Namely, QFLFP logical functions approximate the computation of deterministic ﬁnite-state transducers, which have been argued to form a restrictive hypothesis for phonological processes.
AnonyMate: A Toolkit for Anonymizing Unstructured Chat Data

Most existing research on the automatic anonymization of text data has been limited to the de-identiﬁcation of medical records. This is beginning to change following the passage of GDPR privacy laws, which have made the task of automatic text anonymization more relevant than ever. We present our privacy protection toolkit, AnonyMate, which is built to anonymize both personal identifying information (PII) as well as corporate identifying information (CII) in human-computer dialogue text data.