Miracle-dz/UniFAR-FTUs huggingface dataset:
A Sequential Method for Discovering Probabilistic Motifs in Proteins

Summary Objectives: This paper proposes a greedy algorithm for learning a mixture of motifs model through likelihood maximization, in order to discover common substrings, known as motifs, from a given collection of related biosequences. Methods: The approach sequentially adds a new motif component to a mixture model by performing a combined scheme of global and local search for appropriately initializing the component parameters. A hierarchical clustering scheme is also applied initially which leads to the identification of candidate motif models and speeds up the global searching procedure. Results: The performance of the proposed algorithm has been studied in both artificial and real biological datasets. In comparison with the well-known MEME approach, the algorithm is advantageous since it identifies motifs with significant conservation and produces larger protein fingerprints. Conclusion: The proposed greedy algorithm constitutes a promising approach for discovering multiple probabilistic motifs in biological sequences. By using an effective incremental mixture modeling strategy, our technique manages to successfully overcome the limitation of the MEME scheme which erases motif occurrences each time a new motif is discovered.
Suppressing Syndecan-1 Shedding Ameliorates Intestinal Epithelial Inflammation through Inhibiting NF-κB Pathway and TNF-α

Syndecan-1 (SDC1), with a long variable ectodomain carrying heparan sulfate chains, participates in many steps of inflammatory responses. But reports about the efforts of SDC1's unshedding ectodomain on intestinal epithelial inflammation and the precise underlying mechanism are limited. In our study, unshedding SDC1 from intestinal epithelial cell models was established by transfecting with unshedding SDC1 plasmid into the cell, respectively. And the role of unshedding SDC1 in intestinal inflammation was further investigated. We found that components of NF-κB pathway, including P65 and IκBα, and secretion of TNF-α were upregulated upon LPS stimulation in intestinal epithelial cells. SDC1, especially through its unshed ectodomain, significantly lessened the upregulation extent. It also functioned in inhibiting migration of neutrophils by downregulating secretion of CXCL-1. Taken together, we conclude that suppressing SDC1 shedding from intestinal epithelial cells relieves severity of intestinal inflammation by inactivating NF-κB pathway and downregulating TNF-α expression. These results indicate that the ectodomain of SDC1 might be the optional therapy for intestinal inflammation.
Zeaxanthin dipalmitate alleviates hepatic injury induced by superimposed chronic hepatitis B and non-alcoholic steatohepatitis in non-obese mice

Abstract A hepatitis B virus (HBV) transgenic mice model was used to establish the fatty liver superimposed model by feeding the methionine choline-deficient (MCD) diet for 8 weeks, with or without the gavage of 2 mg/kg zeaxanthin dipalmitate (ZD) three times per week. Both wild-type and HBV transgenic mice, with MCD diet, gained typical non-obese non-alcoholic steatohepatitis (NASH) and HBV symptoms. Coadministration with ZD exhibited evident therapeutic effects through alleviating those pathological events. Moreover, long-term vehicle-ZD treatment was found to be safe. Thus, ZD is a promising and safe hepato-protective agent against hepatic injury induced by superimposed HBV and NASH in non-obese mice.
A study on the near-field interactions of ultrasonic surface waves with surface-breaking defects

This thesis is concerned with the detection of surface-breaking defects, such as stress corrosion cracking, using an ultrasonic scanning approach in which a laser source and detector are scanned over the near-field of a defect. Large increases in the amplitude and frequency content of an incident ultrasonic wave are present when either the source or the detector is very close to the defect, leading to a phenomenon known as ultrasonic near-field enhancement. The extent of the ultrasonic enhancement varies with defect characteristics such as defect depth and angle to the surface. Ultrasonic enhancement is observed in both experiment and finite element simulations using Rayleigh waves for both scanning laser detection and scanning laser source methods. The near-field enhancement is shown to vary as a function of the angle of the defect to the horizontal for Rayleigh wave enhancements, allowing the positioning and characterisation of artificial angled defects that are similar to rolling contact fatigue defects in railtrack. The mechanisms behind the near-field enhancement of Rayleigh waves at angled defects are identified, and this aids in the understanding of the behaviour of ultrasound as it interacts with surface-breaking defects. Ultrasonic enhancements are also reported to be present in individual Lamb wave modes for interactions with artificial open-mouthed defects in thin plates, which are similar to the open end of stress corrosion defects. The mechanisms behind both the scanning laser detection and scanning laser source enhancements are identified and used to explain the variation in the enhancement as a function of increasing defect severity. Positioning of these defects is also achieved by identification of the enhancement location. Finally, the scanning laser technique is applied to real stress-driven defects, and both scanning approaches are shown to be capable of detecting partially-closed defects in a variety of sample geometries. The position, geometric alignment and an estimate of the defect depth are obtained for real defects in thin plates, pipework sections and in irregularly shaped engine components.
Use of ground EPDM wastes in EPDM-based rubber compounds

Ethylene-propylene-diene monomer rubber (EPDM)-based ground wastes (W-EPDM) are reutilized as rubber matrix in plug material compounds for automotive applications. Production scraps of target product are ground to 35, 40 and 60 mesh in ambient conditions. Effect of particle size and the amount of W-EPDM is studied. A new trial product of maleated ethylene-propylene rubber (EPM) and bitumen are used to improve interphase adhesion of the waste and the virgin EPDM. Cure characteristics, physico-mechanical and aging properties of all compounds are determined. Micro structure of the vulcanizates is studied for explaining dispersion and interaction between different phases. Reutilization of W-EPDM causes some reasonable deterioration in cure characteristics and mechanical properties of the product. However, some systematic and alternative recipes for plug materials are suggested considering cost and environmental benefits.
Investigating Perceived Emotional Correlates of Rhythmic Density in Algorithmic Music Composition

Affective algorithmic composition is a growing field that combines perceptually motivated affective computing strategies with novel music generation. This article presents work toward the development of one application. The long-term goal is to develop a responsive and adaptive system for inducing affect that is both controlled and validated by biophysical measures. Literature documenting perceptual responses to music identifies a variety of musical features and possible affective correlations, but perceptual evaluations of these musical features for the purposes of inclusion in a music generation system are not readily available. A discrete feature, rhythmic density (a function of note duration in each musical bar, regardless of tempo), was selected because it was shown to be well-correlated with affective responses in existing literature. A prototype system was then designed to produce controlled degrees of variation in rhythmic density via a transformative algorithm. A two-stage perceptual evaluation of a stimulus set created by this prototype was then undertaken. First, listener responses from a pairwise scaling experiment were analyzed via Multidimensional Scaling Analysis (MDS). The statistical best-fit solution was rotated such that stimuli with the largest range of variation were placed across the horizontal plane in two dimensions. In this orientation, stimuli with deliberate variation in rhythmic density appeared farther from the source material used to generate them than from stimuli generated by random permutation. Second, the same stimulus set was then evaluated according to the order suggested in the rotated two-dimensional solution in a verbal elicitation experiment. A Verbal Protocol Analysis (VPA) found that listener perception of the stimulus set varied in at least two commonly understood emotional descriptors, which might be considered affective correlates of rhythmic density. Thus, these results further corroborate previous studies wherein musical parameters are monitored for changes in emotional expression and that some similarly parameterized control of perceived emotional content in an affective algorithmic composition system can be achieved and provide a methodology for evaluating and including further possible musical features in such a system. Some suggestions regarding the test procedure and analysis techniques are also documented here.
Sunnhemp and millet as green manure for tropical maize production

A liberacao de nutrientes dos residuos de leguminosas e rapida nos tropicos. A consorciacao com gramineas pode resultar em liberacao de nutrientes desses residuos mais lenta e adequada aos requerimentos de N da cultura subsequente. Os objetivos do trabalho foram avaliar os efeitos dos adubos verdes crotalaria (Crotalaria juncea) e milheto (Pennisetum glaucum), solteiros ou consorciados, sobre o desempenho do milho com ou sem a aplicacao de N-fertilizante. O experimento foi instalado em quatro blocos casualizados em parcelas subdivididas. Os tratamentos da parcela consistiram do cultivo previo de crotalaria, milheto, crotalaria+milheto e ervas. Os tratamentos da subparcela foram 90 kg N ha-1 e ausencia de N-fertilizante. A parte aerea da crotalaria solteira ou consorciada apresentou, respectivamente, 173 kg ha-1 e 89 kg ha-1 de FBN-N. Metade do N foi liberado em 15 e 22 dias, dos residuos de crotalaria solteira e crotalaria+milheto respectivamente. Esta diferenca foi provavelmente causada pela imobilizacao temporaria devido a maior C/N da crotalaria+milheto. Na ausencia de N-fertilizante o cultivo previo de crotalaria+milheto resultou em maior produtividade do milho que a crotalaria solteira. Esse resultado nao se repetiu com a aplicacao de N-fertilizante. Esse efeito e atribuido a liberacao de N mais sincronizada com o requerimento do milho do que com crotalaria e milheto solteiros. O balanco de nitrogenio mostra que a recuperacao de N-FBN foi de 15% e 10% do N nos grao de milho apos crotalaria solteira e crotalaria+milheto respectivamente. A utilizacao de N-FBN pelo milho foi 65% maior apos crotalaria+milheto do que apos crotalaria solteira.
The role of the field redefinition in noncommutative Maxwell theory

We discuss $\theta$-deformed Maxwell theory at first order in $\theta$ with the help of the Seiberg-Witten (SW) map. With an appropriate field redefinition consistent with the SW-map we analyse the one-loop corrections of the vacuum polarization of photons. We show that the radiative corrections obtained in a previous work may be described by the Ward-identity of the BRST-shift symmetry corresponding to a field redefinition.
Some Patterns for Insurance Systems

Building flexible insurance systems that allow short product release cycles is a challenge for many insurance firms. Despite the huge market and the many projects that do near identical things these projects are still a little bit like black magic. There’s virtually no literature around on the topic. This paper provides a collection of patterns that help explain the basic forces and solutions for the design of product driven insurance systems.
Enhanced Photosynthesis and Growth in atquac1 Knockout Mutants Are Due to Altered Organic Acid Accumulation and an Increase in Both Stomatal and Mesophyll Conductance1

Impaired stomatal closure in a anion channel mutant is accompanied by increased mesophyll conductance, photosynthesis, and leaf area, ultimately enhancing biomass accumulation under controlled conditions. Stomata control the exchange of CO2 and water vapor in land plants. Thus, whereas a constant supply of CO2 is required to maintain adequate rates of photosynthesis, the accompanying water losses must be tightly regulated to prevent dehydration and undesired metabolic changes. Accordingly, the uptake or release of ions and metabolites from guard cells is necessary to achieve normal stomatal function. The AtQUAC1, an R-type anion channel responsible for the release of malate from guard cells, is essential for efficient stomatal closure. Here, we demonstrate that mutant plants lacking AtQUAC1 accumulated higher levels of malate and fumarate. These mutant plants not only display slower stomatal closure in response to increased CO2 concentration and dark but are also characterized by improved mesophyll conductance. These responses were accompanied by increases in both photosynthesis and respiration rates, without affecting the activity of photosynthetic and respiratory enzymes and the expression of other transporter genes in guard cells, which ultimately led to improved growth. Collectively, our results highlight that the transport of organic acids plays a key role in plant cell metabolism and demonstrate that AtQUAC1 reduce diffusive limitations to photosynthesis, which, at least partially, explain the observed increments in growth under well-watered conditions.
Facial Expression Recognition using Local Binary Patterns and Kullback Leibler Divergence

divergence. Firstly Viola Jones algorithm is used to detect pair of eyes using which effective part of face is obtained which is further processed to eliminate illumination effect. LBP operator is then applied on the preprocessed image to extract local features represented by histogram. Template histograms for seven basic expressions using training images are formed which are compared with the test histogram distribution using an efficient KL divergence for dissimilarity measure. This algorithm is implemented on JAFFE database resulting in a high classification accuracy of 95.24%.
Tales from the crypt and coral reef: the successes and challenges of identifying new herpesviruses using metagenomics

Herpesviruses are ubiquitous double-stranded DNA viruses infecting many animals, with the capacity to cause disease in both immunocompetent and immunocompromised hosts. Different herpesviruses have different cell tropisms, and have been detected in a diverse range of tissues and sample types. Metagenomics—encompassing viromics—analyses the nucleic acid of a tissue or other sample in an unbiased manner, making few or no prior assumptions about which viruses may be present in a sample. This approach has successfully discovered a number of novel herpesviruses. Furthermore, metagenomic analysis can identify herpesviruses with high degrees of sequence divergence from known herpesviruses and does not rely upon culturing large quantities of viral material. Metagenomics has had success in two areas of herpesvirus sequencing: firstly, the discovery of novel exogenous and endogenous herpesviruses in primates, bats and cnidarians; and secondly, in characterizing large areas of the genomes of herpesviruses previously only known from small fragments, revealing unexpected diversity. This review will discuss the successes and challenges of using metagenomics to identify novel herpesviruses, and future directions within the field.
Simulating the activation, contraction and movement of skeletal muscles using the bidomain model

A simulation of the muscle activation, contraction and movement is here presented. This system was developed based on the Bidomain mathematical model of the electrical propagation in muscles. This study shows an electrical stimuli input to a muscle and how this behave. The comparison between healthy subject and patient with muscle activation impairment is depicted, depending on whether the signal reaches a threshold. A 3D model of a bicep muscle and a forearm bone connected was constructed using OpenGL. This platform could be used for development of controllers for biomechatronic systems in future works. This kind of bioinspired model could be used for a better understanding of the neuromotor system.
Alagebrium Reduces Glomerular Fibrogenesis and Inflammation Beyond Preventing RAGE Activation in Diabetic Apolipoprotein E Knockout Mice

Advanced glycation end products (AGEs) are important mediators of diabetic nephropathy that act through the receptor for AGEs (RAGE), as well as other mechanisms, to promote renal inflammation and glomerulosclerosis. The relative contribution of RAGE-dependent and RAGE-independent signaling pathways has not been previously studied in vivo. In this study, diabetic RAGE apoE double-knockout (KO) mice with streptozotocin-induced diabetes were treated with the AGE inhibitor, alagebrium (1 mg/kg/day), or the ACE inhibitor, quinapril (30 mg/kg/day), for 20 weeks, and renal parameters were assessed. RAGE deletion attenuated mesangial expansion, glomerular matrix accumulation, and renal oxidative stress associated with 20 weeks of diabetes. By contrast, inflammation and AGE accumulation associated with diabetes was not prevented. However, treatment with alagebrium in diabetic RAGE apoE KO mice reduced renal AGE levels and further reduced glomerular matrix accumulation. In addition, even in the absence of RAGE expression, alagebrium attenuated cortical inflammation, as denoted by the reduced expression of monocyte chemoattractant protein-1, intracellular adhesion molecule-1, and the macrophage marker cluster of differentiation molecule 11b. These novel findings confirm the presence of important RAGE-independent as well as RAGE-dependent signaling pathways that may be activated in the kidney by AGEs. This has important implications for the design of optimal therapeutic strategies for the prevention of diabetic nephropathy.
Cross community news event summary generation based on collaborative ranking

In order to make the users to access their interested news content conveniently, news analysis has been a hot research topic for a long time. However, most of the previous works only focus on news event detection, tracking, etc. Little attention has been paid to news report difference analysis and comparison. News is full of people's cognition of the world. Because of the different background, ideologies, the cognition of the people is different from one to another. Then, the angle of the news report is different accordingly. In this paper we propose a novel scheme to summarize and compare news report from different communities by using news pictures. Two challenges are addressed: similar news reports summary generation and different news reports summary generation. Firstly, news pictures from different sources are downloaded. Then, the bag-of-visual word features are extracted from these pictures to represent their content. After that, based on the similarity and dissimilarity of the pictures from different sources, collaborative ranking is adopted to rank the images to obtain the news similar and difference summaries. Experimental results on the selected news topics are promising and demonstrate that the proposed approach is effective.
CORE: Augmenting regenerating-coding-based recovery for single and concurrent failures in distributed storage systems

Data availability is critical in distributed storage systems, especially when node failures are prevalent in real life. A key requirement is to minimize the amount of data transferred among nodes when recovering the lost or unavailable data of failed nodes. This paper explores recovery solutions based on regenerating codes, which are shown to provide fault-tolerant storage and minimum recovery bandwidth. Existing optimal regenerating codes are designed for single node failures. We build a system called CORE, which augments existing optimal regenerating codes to support a general number of failures including single and concurrent failures. We theoretically show that CORE achieves the minimum possible recovery bandwidth for most cases. We implement CORE and evaluate our prototype atop a Hadoop HDFS cluster testbed with up to 20 storage nodes. We demonstrate that our CORE prototype conforms to our theoretical findings and achieves recovery bandwidth saving when compared to the conventional recovery approach based on erasure codes.
Sampling Techniques and Distance Metrics in High Dimensional Continuous Landscape Analysis: Limitations and Improvements

In metaheuristic optimization, understanding the relationship between problems and algorithms is important but nontrivial. There has been a growing interest in the literature on techniques for analyzing problems and algorithm performance; however, the validity of the assumptions and implementation choices behind many techniques is often not closely examined. In this paper, we review some interesting theoretical properties regarding sampling techniques and distance metrics in continuous spaces. In particular, we examine the effect of using Euclidean distance in conjunction with uniform random sampling on the behavior of the Dispersion metric. We show that the current methodology employed for the estimation of dispersion has important flaws, and we propose and evaluate modifications to improve the methodology. The modifications are simple and do not add significant complexity or computational effort to the methodology.
ImageNet Classification with Multiple Classifiers

In this project we proposed an ensemble classifier to classify over 20 thousand images sampled from ImageNet, which originally has over 10 million images. One of the challenge of this classification problem is that the images cannot be precisely represented by one type of features, such as SIFT and GIST. Hence, in this project, we use different kinds of features. Another challenge is that different classification models perform differently on different feature set. Here, we use different classifiers (Kernel Regression and SVM) on different features and ensemble the classification results in a weighting manner. The accuracy of the ensemble classifier outperforms almost all of the baselines.