Miracle-dz/UniFAR-FTUs huggingface dataset:
Promoter Motifs in NCLDVs: An Evolutionary Perspective

For many years, gene expression in the three cellular domains has been studied in an attempt to discover sequences associated with the regulation of the transcription process. Some specific transcriptional features were described in viruses, although few studies have been devoted to understanding the evolutionary aspects related to the spread of promoter motifs through related viral families. The discovery of giant viruses and the proposition of the new viral order Megavirales that comprise a monophyletic group, named nucleo-cytoplasmic large DNA viruses (NCLDV), raised new questions in the field. Some putative promoter sequences have already been described for some NCLDV members, bringing new insights into the evolutionary history of these complex microorganisms. In this review, we summarize the main aspects of the transcription regulation process in the three domains of life, followed by a systematic description of what is currently known about promoter regions in several NCLDVs. We also discuss how the analysis of the promoter sequences could bring new ideas about the giant viruses’ evolution. Finally, considering a possible common ancestor for the NCLDV group, we discussed possible promoters’ evolutionary scenarios and propose the term “MEGA-box” to designate an ancestor promoter motif (‘TATATAAAATTGA’) that could be evolved gradually by nucleotides’ gain and loss and point mutations.
1 PRION PROTEIN-MEDIATED TOXICITY OF AMYLOID-β OLIGOMERS REQUIRES LIPID RAFTS AND THE TRANSMEMBRANE LRP 1

Jo V. Rushworth, Heledd H. Griffiths, Nicole T. Watt and Nigel M. Hooper* School of Molecular and Cellular Biology, Astbury Centre for Structural Molecular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK. Running head: Prion-mediated toxicity of Aβ oligomers *Address correspondence to Nigel M. Hooper E-mail: N.M. Hooper@leeds.ac. uk, Tel: +44 (0)113 343 3163, Fax: +44 (0)113 343 5638
Variables predictorias del ajuste psicológico en mujeres maltratadas desde un modelo de estrés

Recent findings in research on battered women provide evidence for association between domestic violence and psychological symptomatology for traumatic responses. This study presents a stress model for analyzing and examining the relationship between battering, personal factors, contextual factors, coping and psychosocial adjustment, as measured by the SCL-90-R (Derogatis, 1977) and by a Self-esteem Questionnaire. The SCL-90-R has 9 subscales and can offer a General Severity Index and a Post-Traumatic Stress Disorder
Automated Ontology Evolution : Utilising Bridging Rules

The thesis extends McNeill's Ontology Repair System (ORS). ORS is an automated system for ontology repair which demonstrate the problem of ontological mismatches between agents in a multiagent system. In the current ORS, the agent in ORS keeps only one copy of the ontology is kept. When mismatches are identified and repaired, the changes are made to this ontology, with no information about the previous repair being kept. This approach risks the agents losing the useful information, making it unable to interact with agents that it previously had successful interactions with. In this project, we extended ORS to enable it to keep and reuse the repair information. We introduce the term 'bridge rule', which is the rule extracted from the repair information. We hypothesize that keeping bridge rules leads to fewer failures and fewer repairs compared to the original ORS. We present the design structure of our bridge rules and our implementation of bridge rules as one of component in ORS. The evaluation of the system confirms our hypothesis and demonstrates the effectively and efficiency performance.
Behavioral Response of Aedes aegypti Mosquito towards Essential Oils Using Olfactometer

Background: Aedes aegypti mosquito is responsible for transmitting human diseases like dengue and chikungunya. Personal or space protection with insect repellents is a practical approach to reducing human mosquito contact, thereby minimizing disease transmission. Essential oils are natural volatile substances from plants used as protective measure against blood-sucking mosquitoes. Methods: Twenty-three essential oils were evaluated for their repellent effect against Ae. aegypti female mosquito in laboratory conditions using Y-tube olfactometer. Results: The essential oils exhibited varying degree of repellency. Litsea oil showed 50.31%, 60.2 %, and 77.26% effective mean repellency at 1 ppm, 10 ppm and 100 ppm respectively, while DEET exhibited 59.63%, 68.63%, 85.48% and DEPA showed 57.97%, 65.43%, and 80.62% repellency at respective above concentrations. Statistical analysis revealed that among the tested essential oils, litsea oil had effective repellency in comparison with DEET and DEPA against Ae. aegypti mosquito at all concentration. Essential oils, DEET and DEPA showed significant repellence against Ae. aegypti (P< 0.05) at all 3 concentration tested. Conclusion: Litsea oil exhibited effective percentage repellency similar to DEET and DEPA. The essential oils are natural plant products that may be useful for developing safer and newer herbal based effective mosquito repellents.
Local Oxidative Stress Expansion through Endothelial Cells – A Key Role for Gap Junction Intercellular Communication

Background Major circulation pathologies are initiated by oxidative insult expansion from a few injured endothelial cells to distal sites; this possibly involves mechanisms that are important to understanding circulation physiology and designing therapeutic management of myocardial pathologies. We tested the hypothesis that a localized oxidative insult of endothelial cells (ECs) propagates through gap junction inter-cellular communication (GJIC). Methodology/Principal Findings Cultures comprising the bEnd.3 cell line, that have been established and recognized as suitable for examining communication among ECs, were used to study the propagation of a localized oxidative insult to remote cells. Spatially confined near infrared illumination of parental or genetically modified bEnd.3 cultures, pretreated with the photosensitizer WST11, generated O2•− and •OH radicals in the illuminated cells. Time-lapse fluorescence microscopy, utilizing various markers, and other methods, were used to monitor the response of non-illuminated bystander and remote cells. Functional GJIC among ECs was shown to be mandatory for oxidative insult propagation, comprising de-novo generation of reactive oxygen and nitrogen species (ROS and RNS, respectively), activation and nuclear translocation of c-Jun N-terminal kinase, followed by massive apoptosis in all bystander cells adjacent to the primarily injured ECs. The oxidative insult propagated through GJIC for many hours, over hundreds of microns from the primary photogeneration site. This wave is shown to be limited by intracellular ROS scavenging, chemical GJIC inhibition or genetic manipulation of connexin 43 (a key component of GJIC). Conclusion/Significance Localized oxidative insults propagate through GJIC between ECs, while stimulating de-novo generation of ROS and RNS in bystander cells, thereby driving the insult's expansion.
A novel partitioning and tracing approach for distributed systems based on vector clocks

Tracking, partitioning and tracing in modern dynamic high performance computing systems are three of the most innovative and important development aspects for performance optimization purposes and state-of-the-art advanced quality. This paper discusses these three aspects with respect to distributed systems and proposes new mechanisms for an advanced utilization of software in this domain. We present a specific tracking mechanism via vector clocks for model and code partitioning purposes and the determination of causality relations. Further, a tracing approach for an effective analysis and thereby utilization of code and the corresponding architecture is introduced. The combination of both approaches leads to a high degree of parallelism and a fine-grained structure of execution units, that further traced, supports a precise analysis of synchronous and asynchronous system's behavior as well as an optimal load balancing. The mechanisms are introduced with respect to a model based control engineering tool and event diagrams.
Monte Carlo Analysis of Security Protocols: Needham-Schroeder Revisited∗

We apply Monte Carlo model checking to the Needham-Schroeder public key authentication protocol. The Monte Carlo approach uses random sampling of “lassos” (reachable cycles) to compute an estimate of the weighted expectation that a system S satisfies an LTL formula φ within a factor of 1 ± with probability at least 1− δ. It does so using a number of samples N that is optimal to within a constant factor, and in expected time O(N · D) and expected space O(D), where D is the recurrence diameter of the directed graph representing the product of S’s state transition graph and the Buchi automaton for ¬φ. Our results indicate that Monte Carlo model checking can find attacks in security protocols like Needham-Schroeder when traditional model checkers fail due to state explosion; and that the weighted expectation that Needham-Schroder is attack-free increases linearly with the nonce range (number of rounds).
A Preliminary Study of Lateralized Processing in Attention-Deficit/Hyperactivity Disorder

Attention-deficit/hyperactivity disorder (ADHD) is associated with deficits in spatial and sustained attention processes normally linked to the right parietal and frontal lobes. However, data on lateralization changes in attention processes are sparse. Little research has addressed whether the problems may reflect a more widespread lateralization disorder or whether there are lateralization changes over time. To address these issues, the authors examined several tasks, each using a lateralized process largely localized to a particular lobe and 2 age ranges (11-14 and 18-26 years) of unmedicated ADHD participants and control participants. ADHD children bisected lines significantly more rightward compared with control children, indicating an altered spatial attention process normally localized to the right parietal lobe. This problem was absent in young adults, suggesting a developmental resolution. The authors observed sustained attention decrements at both ages appearing earlier in the left hemisphere during a vigil. Finally, in these preliminary data, ADHD-related problems appeared specific to attention processes.
Contrast analysis in behavioral research

Les contrastes sont, de maniere substantielle et statistique, un outil puissant pour le developpement ou le perfectionnement d'une theorie. Ils sont un moyen de quantification du degre de congruence entre les resultats (predits et actuels), ainsi que de test des hypotheses adversaires ou post hoc
A Distributed Algorithm to Evaluate Quantified Boolean Formulae

In this paper, we present PQSOLVE, a distributed theorem-prover for Quantified Boolean Formulae. First, we introduce our sequential algorithm QSOLVE, which uses new heuristics and improves the use of known heuristics to prune the search tree. As a result, QSOLVE is more efficient than the QSAT-solvers previously known. We have parallelized QSOLVE. The resulting distributed QSAT-solver PQSOLVE uses parallel search techniques, which we have developed for distributed game tree search. PQSOLVE runs efficiently on distributed systems, i. e. parallel systems without any shared memory. We briefly present experiments that show a speedup of about 114 on 128 processors. To the best of our knowledge we are the first to introduce an efficient parallel QSAT-solver.
Real time cantilever signal frequency determination using digital signal processing

We describe a digital signal processing method for high precision frequency evaluation of approximately sinusoidal signals based on a computationally efficient method. We demonstrate frequency measurement enabling sensitive measurement of the oscillatory force exerted on a micromechanical cantilever. We apply this technique to detection of the force signal arising in a micromechanically detected magnetic resonance force microscopy electron spin resonance signal. Our frequency detection measurements agree well with the theoretical noise analysis presented here, and we find that due to the excellent sensitivity of optical displacement detection, our sensitivity is limited only by the thermal displacement noise of the cantilever.
Structured adaptive and random spinners for fast machine learning computations

We consider an efficient computational framework for speeding up several machine learning algorithms with almost no loss of accuracy. The proposed framework relies on projections via structured matrices that we call Structured Spinners, which are formed as products of three structured matrix-blocks that incorporate rotations. The approach is highly generic, i.e. i) structured matrices under consideration can either be fully-randomized or learned, ii) our structured family contains as special cases all previously considered structured schemes, iii) the setting extends to the non-linear case where the projections are followed by non-linear functions, and iv) the method finds numerous applications including kernel approximations via random feature maps, dimensionality reduction algorithms, new fast cross-polytope LSH techniques, deep learning, convex optimization algorithms via Newton sketches, quantization with random projection trees, and more. The proposed framework comes with theoretical guarantees characterizing the capacity of the structured model in reference to its unstructured counterpart and is based on a general theoretical principle that we describe in the paper. As a consequence of our theoretical analysis, we provide the first theoretical guarantees for one of the most efficient existing LSH algorithms based on the HD3HD2HD1 structured matrix [Andoni et al., 2015]. The exhaustive experimental evaluation confirms the accuracy and efficiency of structured spinners for a variety of different applications.
Parallel information fusion method for microarray data analysis

Classification of microarray data has always been a challenging task due to the enormous number of genes. Finding a small, closely related gene set to accurately classify disease cells is an important research problem. Integrating biological knowledge into genomic analysis to help to improve the interpretation of the results is an effective approach. In this paper, affinity propagation (AP) clustering algorithm is chosen to analyze the impact of the biological similarity on the results. We integrate GO semantic similarity into AP clustering for granule construction. Using MapReduce programming model, a parallel information fusion method is proposed. The process of similarity matrix construction and message passing in AP algorithm is parallelized using MapReduce. Parallel randomly directed hill climb ensemble pruning (RandomDHCEP) method based on MapReduce is introduced for ensemble pruning. An instance analysis represents the process of affinity propagation and ensemble pruning by using iterative MapReduce program. The proposed method can offer good scalability on large data with increasing number of nodes and it can also provide higher classification accuracy rather than using whole gene set for classification.
Adjusted indirect comparison of new oral anticoagulants for stroke prevention in atrial fibrillation.

BACKGROUND Vit-K antagonists are the therapy of choice to prevent thromboembolic events due to atrial fibrillation since many years. New oral anticoagulants (NOA) showed encouraging results vs. warfarin but there are no data directly comparing different NOA. We performed an adjusted indirect meta-analysis. METHODS Randomized controlled trials (RCTs) were searched. Efficacy end points were the cumulative rate of thomboembolic stroke (TES) and systemic embolism (SE). Main safety end point was the rate of hemorrhagic stroke (HS). RESULTS Three RCTs (50578 patients) were included. Overall, NOA were comparable to warfarin according to the cumulative risk of TES and SE, as well as for TES alone. NOA were associated with a reduced rate of SE [OR 0.64 (0.44, 0.94], P=0.02]. Compared to warfarin, NOA were associated with a significantly reduced risk of HS [OR 0.43 (0.34, 0.55), P<0.001, NNT to avoid a HS 153] and all cause death [OR 0.90 [0.84, 0.96], P=0.03, NNT to save one fatality 43]. Head to head comparison showed that in terms of cumulative rate of TES/SE, as well as of TES, none of the NOA was significantly superior to the others (all Ps>0.05). Rivaroxaban showed superiority in the prevention of SE. Dabigatran 150 mg/twice daily was associated with the largest reduction in the risk of HS vs. warfarin and vs. other NOA. Overall mortality was quite comparable across NOA. CONCLUSION Overall superiority of NOA over warfarin is largely influenced by the reduction of HS. Dabigatran 150 mg/twice daily seems to have the best risk/benefit profile.
Planar Trademark and Logo Retrieval

Sport advertising has become an important business increasingly raising the interest of an efficient analysis. To reduce the manual workload, in this work we present an automatic specific trademark and logo recognition system overcoming typical problems of existing (mostly SIFT-based) approaches. In particular, we need to cope with relatively small or correlated trademarks, severe background clutter, and huge perspective variations. This is realized by introducing a concept to increase the perspective invariance, a sophisticated verification, a guided matching phase that is able to deal with a vast number of outliers, and the use of an additional complementary interest region detector with multi-resolution shape description. To show the benefits of the approach, we demonstrate it for a representative real-world test set consisting of images of the EURO 2008 final game. The results clearly show that using the proposed method existing approaches can be outperformed in terms of accuracy and recall.
Iterative Channel Estimation Algorithm in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing Systems

Problem statement: The objective of this study is improving channel estimation accuracy in MIMO-OFDM system because channel state information is required for signal detection at receiver and its accuracy affects the overall performance of system and it is essential to improve the channel estimation for more reliable communications. MIMO-OFDM system was chosen in this study because it has been widely used today due to its high data rate, channel capacity and its adequate performance in frequency selective fading channels. For this purpose a 2
Internet Resear h Needs Better

Networking researchers work from mental models of the Internet’s important properties. The scenarios used in simulations and experiments (including our own) reveal aspects of these mental models, often including one or more of the following implicit assumptions: Flows live for a long time and transfer a lot of data. Simple topologies, like a “dumbbell” topology with one congested link, are sufficient to study many traffic properties. Flows on the congested link share a small range of round-trip times. Most traffic across the link is one-way; reverse-path traffic is rarely congested. All of these modeling assumptions can deeply affect simulation and experimental results, and therefore our evaluations of research. But none of them are confirmed by measurement studies, and some are actively wrong. Some divergences from reality are unimportant, in that they don’t affect the validity of simulation results, and simple models help us understand the underlying dynamics of our systems. However, as a community we do not yet understand which aspects of models affect fundamental system behavior, and which aspects can safely be ignored. It is our belief that lack of good measurements, lack of tools for evaluating measurement results and applying their results to models, and lack of diverse and wellunderstood simulation scenarios based on these models, are holding back the field. We need a much richer understanding of the range of realistic models, and of the likely relevance of different model parameters to network performance.
The Pharmacology and Function of Receptors for Short-Chain Fatty Acids

Despite some blockbuster G protein–coupled receptor (GPCR) drugs, only a small fraction (∼15%) of the more than 390 nonodorant GPCRs have been successfully targeted by the pharmaceutical industry. One way that this issue might be addressed is via translation of recent deorphanization programs that have opened the prospect of extending the reach of new medicine design to novel receptor types with potential therapeutic value. Prominent among these receptors are those that respond to short-chain free fatty acids of carbon chain length 2–6. These receptors, FFA2 (GPR43) and FFA3 (GPR41), are each predominantly activated by the short-chain fatty acids acetate, propionate, and butyrate, ligands that originate largely as fermentation by-products of anaerobic bacteria in the gut. However, the presence of FFA2 and FFA3 on pancreatic β-cells, FFA3 on neurons, and FFA2 on leukocytes and adipocytes means that the biologic role of these receptors likely extends beyond the widely accepted role of regulating peptide hormone release from enteroendocrine cells in the gut. Here, we review the physiologic roles of FFA2 and FFA3, the recent development and use of receptor-selective pharmacological tool compounds and genetic models available to study these receptors, and present evidence of the potential therapeutic value of targeting this emerging receptor pair.
A Low Cost Alternative to Monitor Human Gait Temporal Parameters–Wearable Wireless Gyroscope

Gait events and temporal parameters are presently identified by requiring both patient and healthcare professional to be present at a gait laboratory. This requirement is not feasible for the general population in developing countries, where access to such laboratories is limited and costly. Therefore, an inexpensive gait monitoring device has great potential to address this limitation. This paper presents the development of a low cost wearable wireless device that relies on gyroscopic data to: 1) identify gait events, that is, heel-strike (HS) and toe-off (TO), and 2) determine gait temporal parameters. This wearable device is to be worn around the human foot and ankle. It relies on heuristics and zero-crossing method to detect HS and TO accurately. In the experimental study, the identified gait events were benchmarked against force plate. The average errors were found to be between -20.45 and -17.33 ms for HS and -25.21 and -8.97 ms for TO. The R2 and Bland Altman plot showed positive and consistent results. These findings demonstrated the viability of the proposed system in identifying gait events and determining gait temporal parameters.
Artificial Immune System Based Intrusion Detection: Innate Immunity using an Unsupervised Learning Approach

This paper presents an intrusion detection system architecture based on the artificial immune system concept. In this architecture, an innate immune mechanism through unsupervised machine learning methods is proposed to primarily categorize network traffic to “self” and “non-self” as normal and suspicious profiles respectively. Unsupervised machine learning techniques formulate the invisible structure of unlabeled data without any prior knowledge. The novelty of this work is utilization of these methods in order to provide online and real-time training for the adaptive immune system within the artificial immune system. Different methods for unsupervised machine learning are investigated and DBSCAN (density-based spatial clustering of applications with noise) is selected to be utilized in this architecture. The adaptive immune system in our proposed architecture also takes advantage of the distributed structure, which has shown better self-improvement rate compare to centralized mode and provides primary and secondary immune response for unknown anomalies and zero-day attacks. The experimental results of proposed architecture is presented and discussed.