Miracle-dz/UniFAR-FTUs huggingface dataset:
Environmental Influence on Precision and Accuracy Estimating Gene Effect by Molecular Marker Regression Model

In the past, the gene effect causing the variation of quantitative trait was researched as a whole body. For avoiding the QTL mapping, the molecular marker regression was used to research the quantitative trait controlled by polygene. A general analysis model using molecular marker material was established for estimating the gene effect controlling quantitative trait, and the mathematical relation between gene’s relative effect and molecular marker genotype was found. However, the environmental influence on precision and accuracy estimating gene effect by molecular marker regression model was not discussed. In this research, quantitative trait genetic model and molecular marker regression model were established to simulate the environmental influence on precision and accuracy estimating gene effect, the result showed that precision and accuracy were reduced with the increasing of environmental effect, ignoring of main gene loci and augment of the number of gene loci controlling quantitative trait. Therefore, for increasing the precision and accuracy estimating gene effect, enough number of gene loci and main QTL (quantitative trait locus) should be considered in estimating the polygenic effects, and the levels in orthogonal rows should also be considered as different allele combinations of animal samples, other than individuals.
Perfil de citocinas en mucosa nasal de pacientes pediátricos con infecciones respiratorias virales agudas.

Proposlto del Estudio: Las infecciones respiratorias agudas son principalmente causadas por virus respiratorios como hRV, RSV, hMPV. coronavinus, IV, PIV, bocavirus, adenovirus, entre otros, asl como, bacterias como S. pneumoniae. Estas infecciones causan gran marbi-mortalidad en ninos pequenos a 5 anos de edad. El perfi de citoainas generado a nivel local en el mcto respirador superior de estos sujetos pediatricos por una interaccion respiratoria aguda como la correlacion de los agentes causales de la infeccion con la gravedad de los pacientes aun no esta bien definida. En este estudio se incluyeron clento veintiun pacientes pediatricos con infeccion respiratoria aguda reclutados en el departamento de pediatria de la Universidad Autonoma de Nuevo Led. Se obtuvieron dos tipos de muestras, un exudado faringeo y una reaccion de los agentes causales de la infeccion respiratoria aguda a traves del kit de lavado. nasal para la determinacion del impacto de las celuas de Luminex XTAG RVP y QRT-PCR, y para los dichos pacientes mediante ELISA tpo sandwich (TOF 9) y el kit Bio Plex Pro-Human (Premaed) Th17 Cytokine (OL-1p, 1L -8, IL-21, 1-23. TNFo, IL 10, IFNy, IL-4, IL3 IL-33, IL-17A L-17F, L-zz IL-25, sCD40L) Contribuciones y conclusiones: ET 47% de los pacientes al menos un virus respiratorio, mientras que el 95% fueron pospuestos para el neumonia El 150% de los pacientes recurrio a la infeccion por VIH y la neumonia respoctivamente con la gravedad de la gripe enfermedad de los pacientos (Pe0.05) Los pacientes infectados con S pneumoniae tenen un riesgo relativo 3 de cursur con la muerte y tumba (Pr0 05) La cargh viral en los pacientos det saxo femenino fue mayor que en los de sexo masculino (Peo CS) Los agentes etulbgicos indujeron ta produccion de aiversas citocinas y estas vanaron segun los agentes y clinicas de los clinicos, estos ha lazges nos permten sugen que la carga bacteriana y viral corretaciona con el estodo grave de los pacentes, asi como la concontracion de certas ctoonas pueden ser biomarcadores de gravedad o posioles biancos terapeuticos
Container orchestration environments for M&S

Deployment and execution of HLA federates in Docker containers offers many benefits. However, managing the execution of multiple HLA federate containers to run a complete HLA federation across a set of compute nodes in a local area network or in a cloud environment can be time consuming and error prone. A small HLA federation can easily consist of ten or more containers and it quickly becomes impossible to oversee these containers without proper tools to orchestrate them. Tools to support the orchestration of containers exist and reduce the effort required to configure, coordinate, and manage containers. Many of these tools are open source, are freely available and evolve quickly. The most popular ones include Docker Native tools from Docker Inc. and Kubernetes from Google. In an earlier SISO paper (16F-SIW-031), guidelines and best practices for containerizing HLA applications were presented. This paper discusses the topic of container orchestration environments for M&S, in particular for containerized HLA applications. Topics covered in this paper include the following: what is required to effectively deploy a HLA federation via an orchestration tool? What orchestration solutions are available and what benefits/challenges do each provide? By the end of this paper the reader should have a good idea of what is available, what is needed, and how to use orchestration tools to field a HLA federation. This paper provides orchestration solutions that can be equally well used for simulation technology other than the HLA. Â© Winter Simulation Innovation Workshop, SIW 2018. All rights reserved.
A Blind Source Separation Algorithm Based on Whitening and Non-linear Decorrelation

Blind source separation (BSS) methods become more attractive targets in neural network and signal processing literature recently. And independent component analysis (ICA) methods are one kind of widely used and important solutions to blind source separation problems. Whitening is a very useful preparation step for blind separation of source and meanwhile non-linear decorrelation acts as a basic estimation theory upon ICA methods. Then an on-line real-time blind source separation algorithm based on the whitening and non-linear decorrelation is proposed in this paper. Performance of the proposed method is simulated and analyzed and then the results show that our proposed algorithm has better convergence speed and steady-state error than the normalized EASI, nature gradient and whitening-only methods.
Visual Hierarchical Dimension Reduction

Traditional visualization techniques for multidimensional data sets, such as parallel coordinates, star glyphs, and scatterplot matrices, do not scale well to high dimensional data sets. A common approach to solve this problem is dimensionality reduction. Existing dimensionality reduction techniques, such as Principal Component Analysis, Multidimensional Scaling, and Self Organizing Maps, have serious drawbacks in that the generated low dimensional subspace has no intuitive meaning to users. In addition, little user interaction is allowed in those highly automatic processes. In this thesis, we propose a new methodology to dimensionality reduction that combines automation and user interaction for the generation of meaningful subspaces, called the visual hierarchical dimension reduction (VHDR) framework. Firstly, VHDR groups all dimensions of a data set into a dimension hierarchy. This hierarchy is then visualized using a radial space-filling hierarchy visualization tool called Sunburst. Thus users are allowed to interactively explore and modify the dimension hierarchy, and select clusters at different levels of detail for the data display. VHDR then assigns a representative dimension to each dimension cluster selected by the users. Finally, VHDR maps the high-dimensional data set into the subspace composed of these representative dimensions and displays the projected subspace. To accomplish the latter, we have designed several extensions to existing popular multidimensional display techniques, such as parallel coordinates, star glyphs, and scatterplot matrices. These displays have been enhanced to express semantics of the selected subspace, such as the context of the dimensions and dissimilarity among the individual dimensions in a cluster. We have implemented all these features and incorporated them into the XmdvTool software package, which will be released as XmdvTool Version 6.0. Lastly, we developed two case studies to show how we apply VHDR to visualize and interactively explore a high dimensional data set.
Assessment of Non-native Prosody for Spanish as L2 using quantitative scores and perceptual evaluation

In this work we present SAMPLE, a new pronunciation database of Spanish as L2, and first results on the automatic assessment of Non-native prosody. Listen and repeat and read tasks are carried out by native and foreign speakers of Spanish. The corpus has been designed to support comparative studies and evaluation of automatic pronunciation error assessment both at phonetic and prosodic level. Four expert evaluators have annotated utterances with perceptual scores related to prosodic aspects of speech, intelligibility, phonetic quality and global proficiency level in Spanish. From each utterance, we computed several prosodic features and ASR scores. A correlation study over subjective and quantitative measures is carried out. An estimation of the prediction of perceptual scores from speech features is shown.
Ping-pong Document Clustering using NMF and Linkage-Based Refinement

This paper proposes a ping-pong document clustering method using NMF and the linkage based refinement alternately, in order to improve the clustering result of NMF. The use of NMF in the ping-pong strategy can be expected effective for document clustering. However, NMF in the ping-pong strategy often worsens performance because NMF often fails to improve the clustering result given as the initial values. Our method handles this problem with the stop condition of the ping-pong process. In the experiment, we compared our method with the k-means and NMF by using 16 document data sets. Our method improved the clustering result of NMF significantly.
Scalable Graph-Based Learning Applied to Human Language Technology

Scalable Graph-Based Learning Applied to Human Language Technology Andrei Alexandrescu Chair of the Supervisory Committee: Associate Research Professor Katrin Kirchhoff Electrical Engineering Graph-based semi-supervised learning techniques have recently attracted increasing attention as a means to utilize unlabeled data in machine learning by placing data points in a similarity graph. However, applying graph-based semi-supervised learning to natural language processing tasks presents unique challenges. First, natural language features are often discrete and do not readily reveal an underlying manifold structure, which complicates the already empirical graph construction process. Second, natural language processing problems often use structured inputs and outputs that do not naturally fit the graph-based framework. Finally, scalability issues limit applicability to large data sets, which are common even in modestly-sized natural language processing applications. This research investigates novel approaches to using graph-based semi-supervised learning techniques for natural language processing, and addresses issues of distance measure learning, scalability, and structured inputs and outputs.
Particle Swarm Optimization for multivariable PID controller tuning

In this paper, the tuning of multivariable PID (MPID) controller using particle swarm optimisation (PSO) is presented. To provide better performance in the industry, MPID implementation often uses heuristic approach, which is based on experience. However, this method of tuning is time consuming and inadequate for complex systems. To obtain a better performance in decoupling capabilities and closed loop performance, in this study, the MPID parameters are fine-tuned using Multi-objective PSO. Simulation results show tuning parameters of MPID controllers obtained via PSO yield better performance when applied to nonlinear system for different control strategies.
Using Particle Swarm Optimization to Improve the Precision and Recall of Taxonomy Extraction

The web offers a huge amount of information from which ontologies can be developed. The available information on the web can also be harnessed to help create correct ontologies from other documents. Taxonomy or hierarchy of concepts is part of ontology layers. In this work, we present the use of particle swarm optimization (PSO) for automatic acquisition of concept hierarchy from text documents. First, all pairs of noun phrases or terms in a text document was extracted and three different features were calculated for each pair. The first feature count the number of times the pair occurs in is-a relationship patterns in a redefined corpus over all is-a relations involving the first term in the corpus. The second feature counts the number of times the pairs occurs in is-a relationship patterns on a subset of web documents containing the pairs is-a relationship patterns over all is-a relations containing the first term in the subset. The third feature uses the number of paths between all senses of the terms in Word Net over all senses of the first term. Next, PSO was used to optimize the weights of each feature. Finally, the weights were multiplied with the feature values and then summed up to score all the pairs. The best scoring pairs were selected as taxonomy candidates derived from the documents and compared with a taxonomy gold standard developed previously with subject matter experts. Findings showed that the one obtained from Web get the best results when each feature was used individually. However, when the features were combined using weight optimized with PSO, the best result was achieved by the pre-defined corpus and Web. Overall, results for optimized weight using PSO is better than those using balanced weights for all features.
The emergence of intercultural sensitivity through experiential learning in the attitudes of Emirati women

The expatriate population of Dubai, in the United Arab Emirates stands at close to 90% of the population. The challenges this presents the leaders of the UAE are complex and reflect the social and cultural fabric of the region. Ensuring Emiratis remain the stake-holders in their country is key and only achievable through an Emiratization policy and buy-in from the tertiary sector. This study looks at the Higher Colleges of Technology (HCT) which has responded to the government Emiratization initiative by mandating that all Bachelor Degree students undertake an Intercultural Studies course as part of their studies. The research explores the role of experiential learning in fostering intercultural openness understanding and development is perceived by this particular group. This is a mixed methods study that includes ethnographic data collection, uncovering the complexities of a lived classroom learning experience from the perspective of the students. As an inductive exploratory study the movement is from observation to generalisation to theory. The data collected was sourced from interviews with students, written reflections and a Likert scale survey. Themes were not pre-determined and were be generated through a coding system based on frequency and constant comparison until core categories were clearly defined. Both sets of data were then compared to generate more conclusive theory. Participation was entirely voluntary and taken from the students from a current Intercultural Studies class. This study has contributed significantly to a field that has not yet explored experiential learning as a vehicle for intercultural studies in an Emirati context. The results provided a much needed road map for the teaching and learning of intercultural studies globally. Finally, this study was unique in that it was of their learning, and of the pedagogy, rather than adopting a more traditional type of external measure.
Nitric oxide as a regulator of B. anthracis pathogenicity

Nitric oxide (NO) is a key physiological regulator in eukaryotic and prokaryotic organisms. It can cause a variety of biological effects by reacting with its targets or/and indirectly inducing oxidative stress. NO can also be produced by bacteria including the pathogenic Bacillus anthracis; however, its role in the infectious process only begins to emerge. NO incapacitates macrophages by S-nitrosylating the intracellular proteins and protects B. anthracis from oxidative stress. It is also implicated in the formation of toxic peroxynitrite. In this study we further assessed the effects of B. anthracis NO produced by the NO synthase (bNOS) on bacterial metabolism and host cells in experiments with the bNOS knockout Sterne strain. The mutation abrogated accumulation of nitrite and nitrate as tracer products of NO in the culture medium and markedly attenuated growth in both aerobic and microaerobic conditions. The regulatory role of NO was also suggested by the abnormally high rate of nitrate denitrification by the mutant in the presence of oxygen. Anaerobic regulation mediated by NO was reflected in reduced fermentation of glucose by the mutant correlating with the reduced toxicity of bacteria toward host cells in culture. The toxic effect of NO required permeabilization of the target cells as well as the activity of fermentation-derived metabolite in the conditions of reduced pH. The host cells demonstrated increased phosphorylation of major survivor protein kinase AKT correlating with reduced toxicity of the mutant in comparison with Sterne. Our global proteomic analysis of lymph from the lymph nodes of infected mice harboring bacteria revealed numerous changes in the pattern and levels of proteins associated with the activity of bNOS influencing key cell physiological processes relevant to energy metabolism, growth, signal transduction, stress response, septic shock, and homeostasis. This is the first in vivo observation of the bacterial NO effect on the lymphatic system.
MIMO relay design for multiple link pairs based on SINR constraints

We address the problem of multiple-input multiple-output (MIMO) relay design for multiple distributed source and destination pairs with signal-to-interference-plus-noise-ratio (SINR) constraints. Multiple link pairs communicating through a relay can be beneficial in the wireless digital home network (DHN) scenario where various equipments exchange or share digital media contents. In the first hop from the source nodes to the relay, cooperative transmit-receive beamforming design is performed to maximize SINR at the relay. Then joint power allocation and transmit-receive beamforming is conducted in the second hop from the relay to the destination nodes based on the SINR constraints for each link pair. The beamforming filter is a group maximum SINR filter which exploits intra-group cooperation. The group-based uplink-downlink duality property in downlink channel is adopted and modified for amplify-and-forward (AF) relaying. An iterative algorithm is then proposed to solve the problem. Simulation results show the superiority of the proposed algorithm over other methods.
Monotone and near-monotone network structure

This paper provides an expository introduction to monotone and near-monotone biochemical network structures. Monotone systems respond in a predictable fashion to perturbations, and have very robust dynamical characteristics. This makes them reliable components of more complex networks, and suggests that natural biological systems may have evolved to be, if not monotone, at least close to monotone. In addition, interconnections of monotone systems may be fruitfully analyzed using tools from control theory.
Off equilibrium dynamics and aging in unfrustrated systems

We analyse the Langevin dynamics of the random walk, the scalar field, the X-Y model and the spinoidal decomposition. We study the deviations from the equilibrium dynamics theorems (FDT and homogeneity), the asymptotic behaviour of the systems and the aging phenomena. We compare the results with the dynamcal behaviour of (random) spin-glass mean-field models.
Rendement et qualité du blé panifiable soumis à divers types de fertilisation azotée dans deux sols contrastants

BACKGROUND: Spring wheat (Triticum aestivum L.) was sown on a silty clay and a sandy loam under two newly-established tillage systems (mouldboard plough or minimum till). Wheat received either phosphorus (P) and potassium (K) only [PK], or 90 kg ha -1 available nitrogen (N) either as complete mineral fertilization [NPK], liquid swine [LSM], liquid cattle [LCM], or solid poultry manure [SPM]) during two years under cool and wet climate. RESULTS: Grain yields were greater in the silty clay (3070 kg ha -1 ) than in the sandy loam (2247 kg ha -1 ), and were attributed to a higher N availability in the fine-textured silty clay. Globally, wheat was unaffected by tillage, but grain yield and grain protein and gluten contents were higher with the N treatments than PK. The use of LSM and SPM resulted in grain yields similar to those obtained with NPK (2808 to 2862 kg ha -1 ), but to lower grain protein content (respectively 14.3 and 14.4 vs. 15.0% for NPK). Grain yield and protein content obtained with LCM (2666 kg ha -1 and 14.2%) were intermediate between PK (2047 kg ha -1 and 13.7%) and the other manure types. These disparities in grain yield and quality among treatments did not reflect in baking tests.
Towards Sustainability Framework Development: Identifying Organisational Capability for Sustainability Practices

The growing awareness of the importance of sustainability motivates companies to engage in sustainability practices. However, practising sustainability is challenging since most initiatives are interorganisational in nature. The implementation depends heavily on the capability of multiple organisations within the supply chain, which are not easily assessed. Although a few scholars have proposed a number of frameworks to help organisations identify the required organisational capabilities, none of them is comprehensive enough due to the limited scope. In order to develop a more comprehensive sustainability framework, a complete understanding of organisational capabilities needed for sustainability practices is necessary. This research-in-progress paper therefore aims to synthesize the required key capabilities based on widely implemented sustainability guidelines/standards. The identification of key capabilities is important to understand and explore how ICT can be used by organisations to develop the required sustainability capabilities. This study will potentially contribute to the development of a holistic sustainability framework.
High-level ribosomal frameshifting directs the synthesis of IS150 gene products.

IS150 contains two tandem, out-of-phase, overlapping genes, ins150A and ins150B, which are controlled by the same promoter. These genes encode proteins of 19 and 31 kD, respectively. A third protein of 49 kD is a transframe gene product consisting of domains encoded by both genes. Specific -1 ribosomal frameshifting is responsible for the synthesis of the large protein. Expression of ins150B also involves frameshifting. The IS150 frameshifting signals operate with a remarkably high efficiency, causing about one third of the ribosomes to switch frame. All of the signals required for this process are encoded in a 83-bp segment of the element. The heptanucleotide A AAA AAG and a potential stem-loop-forming sequence mark the frameshifting site. Similar sequence elements are found in -1 frameshifting regions of bacterial and retroviral genes. A mutation within the stem-loop sequence reduces the rate of frameshifting by about 80%. Artificial transposons carrying this mutation transpose at a normal frequency, but form cointegrates at a approximately 100-fold reduced rate. Images