Miracle-dz/UniFAR-FTUs huggingface dataset:
Multilayer analysis of the influence of mobility models on TCP flows in AODV ad-hoc networks

Mobile ad-hoc network (MANET) technology is an essential piece in the path towards ubiquitous networking. In the past, most MANET research has been performed assuming the random waypoint mobility model for determining nodes movements. In the last years, some researchers have focused on alternative mobility models. In this paper, we perform a simulation based joint analysis of ad-hoc network performance at three layers (physical layer, network layer and transport layer) using four different mobility models, AODV as the routing protocol and TCP as the transport protocol. In some cases, we obtain counterintuitive results, which can be explained by correlating the behavior measured at the three considered layers
Towards automated user-centric cloud provisioning: Job provisioning and scheduling on heterogeneous virtual machines

The cloud Infrastructure-as-a-Service (IaaS) model, which provides users with remote virtual machines in a pay-peruse method, is attracting more people to start using IaaS services. This work advances the state-of-the-art one step further towards the realization of an automatic user-centric cloud provisioning and job scheduling tool. First, we extend some of the existing provisioning and scheduling strategies to be applicable to a real infrastructure of heterogeneous virtual machines. Second, we evaluate the extended strategies using the MetaCentrum data set. Our results show that handling different types of machines and applying backfilling scheduling successfully increased the average machine utilization and decreased the average job waiting time.
Evidence from intrinsic activity that asymmetry of the human brain is controlled by multiple factors

Cerebral lateralization is a fundamental property of the human brain and a marker of successful development. Here we provide evidence that multiple mechanisms control asymmetry for distinct brain systems. Using intrinsic activity to measure asymmetry in 300 adults, we mapped the most strongly lateralized brain regions. Both men and women showed strong asymmetries with a significant, but small, group difference. Factor analysis on the asymmetric regions revealed 4 separate factors that each accounted for significant variation across subjects. The factors were associated with brain systems involved in vision, internal thought (the default network), attention, and language. An independent sample of right- and left-handed individuals showed that hand dominance affects brain asymmetry but differentially across the 4 factors supporting their independence. These findings show the feasibility of measuring brain asymmetry using intrinsic activity fluctuations and suggest that multiple genetic or environmental mechanisms control cerebral lateralization.
Short-term foreign exchange rate trading based on the support/resistance level of Ichimoku Kinkohyo

In this study, we conducted foreign exchange rate simulated trading based on a traditional Japanese technical indicator called Ichimoku Kinkohyo, which is well-known and widely used in Japan for technical analysis on various kinds of market prices. We designed two trading strategies based on the support/resistance level of the five elements of Ichimoku and conducted simulated trading on short-term foreign exchange rate. The trading strategies are applied to five currency pairs: USD/JPY, EUR/USD, GBP/USD, USD/CHF and AUD/USD. Experimental results show that the average return of one trading strategy that based on Ichimoku Kinkohyo is extremely better than that of other baseline strategies.
Modeling Carbon-Climate Interactions

How fast greenhouse warming will proceed depends on a large part on how fast carbon dioxide is increasing in the atmosphere. The abundance and growth rate of atmospheric CO2 is determined not only by the rate of anthropogenic emissions but also by the rates of biogeochemical processes that sequester carbon in the land and ocean. The biogeochemical processes in turn responds to and alters climate and circulation changes. A goal of carbon cycle modeling is to understand the interactions among the physical and biogeochemical processes that exchange carbon among the mobile reservoirs on seasonal to millennial time scales, and to project the future co-evolution of CO2 and climate. The task requires the synthesis of atmospheric, oceanic and terrestrial observations of carbon inventories and carbon fluxes, and the coupling of the physical and biogeochemical systems. CO2 is radiatively active but chemically inert in the atmosphere. The geographic and intraseasonal variations are observed to be small (<10%) and are radiatively insignificant compared to the global annual mean concentrations (~350 ppmv). In this way CO2 departures from the global mean (referred to as “tracer CO2”) are unimportant for the radiative and biogeochemical processes, and can be treated as an inert tracer in the atmosphere. This has permitted the traditional separation of climate models and carbon cycle models. In climate models, the global annual mean CO2 concentration is specified. In carbon cycle models, the only crucial atmospheric and oceanic processes to model are those related to large-scale advection and turbulent mixing; the challenge lies in the prescription of source/sink functions for the tracer. In this paper, we review the status of carbon cycle modeling, and discuss the outlooks for global environment modeling, both in the future and of the future.
Wordrank: A Method for Ranking Web Pages Based on Content Similarity

This paper presents WordRank, a new page ranking system, which exploits similarity between interconnected pages. WordRank introduces the model of the 'biased surfer' which is based on the following assumption: "the visitor of a Web page tends to visit Web pages with similar content rather than content irrelevant pages". The algorithm modifies the random surfer model by biasing the probability of a user to follow a link in favor of links to pages with similar content. It is our intuition that WordRank is most appropriate in topic based searches, since it prioritizes strongly interconnected pages, and in the same time is more robust to the multitude of topics and to the noise produced by navigation links. This paper presents preliminary experimental evidence from a search engine we developed for the Greek fragment of the World Wide Web. For evaluation purposes, we introduce a new metric (SI score) which is based on implicit user's feedback, but we also employ explicit evaluation, where available.
Web service discovery based on behavioral aspects

The rapid growth of published Web services (WS) makes their discovery more difficult. There are many WS that have similar functional characteristics. So, it is obligatory to facilitate to consumers the selection of the most relevant WS according to their needs. Different approaches have been proposed to WS discovery including syntactic, semantic and context aware approaches. In this paper, we highlight the importance of behavioral aspect in WS discovery. We argue that the execution manner of WS operations become a quality criterion which has not been treated in the previously proposed approaches. The purpose of this paper is to realize a literature review of existing research on WS discovery and highlight their failure to deal with the behavioral aspect.
Image-based haptic texture rendering

In this paper, we present a new image-based method to display haptic texture information extracted from a static two dimensional image. The three dimensional forces allow the user to feel the contours and textures of the image with sufficient realism using haptic devices. The texture force is decomposed into a normal force component and a tangential force component at the haptic interaction point. The magnitude of the normal force is determined either by the color temperature (i.e. the emotions of warmth/coolness evoked by colors) or the luminance values in images. Warmer/brighter colors determine stronger normal forces to generate bumps, and cooler/darker colors determine weaker normal forces to produce depressions. The tangential force describes the relative color variation between haptic interaction point and its neighbors, thus, can be considered as a descriptor of the local texture feature. Because it is oriented to the pixels with cooler color in the neighborhood, when the user is exploring the bump by a haptic device, tangential resistive forces are sent to the user until the top of the bump is reached and, after the top, the virtual probe is pulled in the other direction. Our force model is by means of simple image processing techniques. The calculation is totally done by local, independent and direct operation. In other words, global operation such as recovering height maps is not necessary.
A 0.4–6-GHz 17-dBm B1dB 36-dBm IIP3 Channel-Selecting Low-Noise Amplifier for SAW-Less 3G/4G FDD Diversity Receivers

A channel-selecting low-noise amplifier (CS-LNA) with blocker filtering is presented for a SAW-less diversity path receiver (RX) in frequency-division duplexing cellular systems. A hybrid N-path bandpass filter/band-reject filter (BPF/BRF) feedback network is applied to the LNA to create close-in reject bands around the passband to suppress transmit leakage and improve the out-of-band (OOB) input-referred third-order intercept point (IIP3). Control of the frequency and depth of the reject bands is demonstrated with analysis and simulation. A gm2-gm3 cancellation linearization is applied to improve the in-band (IB) linearity. Adaptive LO swing and silicon-on-insulator (SOI) thick-oxide devices are demonstrated to improve the power-handling capability. The proposed CS-LNA is implemented in 32-nm CMOS SOI and operates from 0.4 to 6 GHz with the maximum rejection larger than 60 dB and power-handling capability up to 17 dBm. The prototype demonstrates an OOB IIP3 of 36 dBm and IB IIP3 of 10 dBm at 1 GHz. To the authors' knowledge, this is the highest blocker rejection, power-handling capability, linearity, and the widest tuning range for an LNA with tunable filtering.
Elucidation of a novel Vibrio cholerae lipid A secondary hydroxy-acyltransferase and its role in innate immune recognition

Similar to most Gram‐negative bacteria, the outer leaflet of the outer membrane of Vibrio cholerae is comprised of lipopolysaccharide. Previous reports have proposed that V. cholerae serogroups O1 and O139 synthesize structurally different lipid A domains, which anchor lipopolysaccharide within the outer membrane. In the current study, intact lipid A species of V. cholerae O1 and O139 were analysed by mass spectrometry. We demonstrate that V. cholerae serogroups associated with human disease synthesize a similar asymmetrical hexa‐acylated lipid A species, bearing a myristate (C14:0) and 3‐hydroxylaurate (3‐OH C12:0) at the 2′‐ and 3′‐positions respectively. A previous report from our laboratory characterized the V. cholerae LpxL homologue Vc0213, which transfers a C14:0 to the 2′‐position of the glucosamine disaccharide. Our current findings identify V. cholerae Vc0212 as a novel lipid A secondary hydroxy‐acyltransferase, termed LpxN, responsible for transferring the 3‐hydroxylaurate (3‐OH C12:0) to the V. cholerae lipid A domain. Importantly, the presence of a 3‐hydroxyl group on the 3′‐linked secondary acyl chain was found to promote antimicrobial peptide resistance in V. cholerae; however, this functional group was not required for activation of the innate immune response.
Aebp2 as an Epigenetic Regulator for Neural Crest Cells

Aebp2 is a potential targeting protein for the mammalian Polycomb Repression Complex 2 (PRC2). We generated a mutant mouse line disrupting the transcription of Aebp2 to investigate its in vivo roles. Aebp2-mutant homozygotes were embryonic lethal while heterozygotes survived to adulthood with fertility. In developing mouse embryos, Aebp2 is expressed mainly within cells of neural crest origin. In addition, many heterozygotes display a set of phenotypes, enlarged colon and hypopigmentation, similar to those observed in human patients with Hirschsprung's disease and Waardenburg syndrome. These phenotypes are usually caused by the absence of the neural crest-derived ganglia in hindguts and melanocytes. ChIP analyses demonstrated that the majority of the genes involved in the migration and development process of neural crest cells are downstream target genes of AEBP2 and PRC2. Furthermore, expression analyses confirmed that some of these genes are indeed affected in the Aebp2 heterozygotes. Taken together, these results suggest that Aebp2 may regulate the migration and development of the neural crest cells through the PRC2-mediated epigenetic mechanism.
Optimal policies for inventory systems with concave ordering costs

In this paper we study the structure of optimal policies for periodic review inventory systems with concave ordering costs and general demand distributions. By extending the Scarf ( ) model to systems with piecewise linear concave ordering costs, we show that, except for a bounded region, the generalized (s, S) policy is optimal. We do so by (a) introducing the notion of c‐convexity and (b) proving a conditional monotonicity property for the optimal order‐up‐to levels. We also provide conditions under which the generalized (s, S) policy is optimal for all regions of the state space.
Two Methods for Improving Performance of a HMM and their Application for Gene Finding

A hidden Markov model for gene finding consists of submodels for coding regions, splice sites, introns, intergenic regions and possibly more. It is described how to estimate the model as a whole from labeled sequences instead of estimating the individual parts independently from subsequences. It is argued that the standard maximum likelihood estimation criterion is not optimal for training such a model. Instead of maximizing the probability of the DNA sequence, one should maximize the probability of the correct prediction. Such a criterion, called conditional maximum likelihood, is used for the gene finder 'HMM-gene'. A new (approximative) algorithm is described, which finds the most probable prediction summed over all paths yielding the same prediction. We show that these methods contribute significantly to the high performance of HMMgene.
Kiwifruit Information Resource (KIR): a comparative platform for kiwifruit genomics

The Kiwifruit Information Resource (KIR) is dedicated to maintain and integrate comprehensive datasets on genomics, functional genomics and transcriptomics of kiwifruit (Actinidiaceae). KIR serves as a central access point for existing/new genomic and genetic data. KIR also provides researchers with a variety of visualization and analysis tools. Current developments include the updated genome structure of Actinidia chinensis cv. Hongyang and its newest genome annotation, putative transcripts, gene expression, physical markers of genetic traits as well as relevant publications based on the latest genome assembly. Nine thousand five hundred and forty-seven new transcripts are detected and 21 132 old transcripts are changed. At the present release, the next-generation transcriptome sequencing data has been incorporated into gene models and splice variants. Protein–protein interactions are also identified based on experimentally determined orthologous interactions. Furthermore, the experimental results reported in peer-reviewed literature are manually extracted and integrated within a well-developed query page. In total, 122 identifications are currently associated, including commonly used gene names and symbols. All KIR datasets are helpful to facilitate a broad range of kiwifruit research topics and freely available to the research community. Database URL: http://bdg.hfut. edu.cn/kir/index.html.
Explicit solutions to the semi-discrete modified KdV equation and motion of discrete plane curves

We construct explicit solutions to continuous motion of discrete plane curves described by a semi-discrete potential modified KdV equation. Explicit formulas in terms of the τ function are presented. Bäcklund transformations of the discrete curves are also discussed. We finally consider the continuous limit of discrete motion of discrete plane curves described by the discrete potential modified KdV equation to motion of smooth plane curves characterized by the potential modified KdV equation.
From Policies to Principals: Tiered Influences on School-Level Coupling

Abstract:For decades, educational scholars have claimed that public schools are loosely coupled organizations, but research does not fully address how schools create the coupling structure. Recent federal policies have centralized the public education system, but state laws, districts, and principals still play a prominent role in shaping the organization of schools. In this paper, I investigate how the multiple tiers of the public education system influence the coupling structures of schools. Utilizing all seven waves of the Schools and Staffing Survey (SASS), I rely on OLS regression to analyze how couplings emerge within schools. Findings suggest three major influences on coupling within schools. First, federal policies have had a non-linear effect on school-level coupling. Second, the relationship between the district and the school affects school-level coupling. Finally, principals play a key role in shaping the coupling within the school, and coupling is a gendered process.
Application of Subspace Gaussian Mixture Models in Contrastive Acoustic Scenarios

This paper describes experimental results of applying Subspace Gaussian Mixture Models (SGMMs) in two completely diverse acoustic scenarios: (a) for Large Vocabulary Continuous Speech Recognition (LVCSR) task over (well-resourced) English meeting data and, (b) for acoustic modeling of underresourced Afrikaans telephone data. In both cases, the performance of SGMM models is compared with a conventional context-dependent HMM/GMM approach exploiting the same kind of information available during the training. LVCSR systems are evaluated on standard NIST Rich Transcription dataset. For under-resourced Afrikaans, SGMM and HMM/GMM acoustic systems are additionally compared to KL-HMM and multilingual Tandem techniques boosted using supplemental out-of-domain data. Experimental results clearly show that the SGMMapproach (having considerably less model parameters) outperforms conventional HMM/GMM system in both scenarios and for all examined training conditions. In case of under-resourced scenario, the SGMM trained only using indomain data is superior to other tested approaches boosted by data from other domain.
FORMAÇÃO DO DOCENTE PARA A GESTÃO UNIVERSITÁRIA: uma análise indutiva dos professores gestores da pós-graduação stricto sensu da UFRRJ

Os professores gestores dos Programas de Pos-Graduacao da Universidade Federal Rural do Rio de Janeiro sao oriundos de areas diversas a Administracao. A ausencia de formacao especifica orientada para o desempenho das funcoes da gestao levou ao objetivo desta pesquisa: descrever como o professor gestor de Programa de Pos-Graduacao em Instituicao Federal de Ensino Superior – IFES aprende e desenvolve suas competencias gerenciais, mesmo sem capacitacao especifica para a gestao. Para alcanca-lo na pesquisa, adotou-se metodologia qualitativa indutiva de analise de dados, nos termos de Thomas, pela qual os resultados emergem dos dados pesquisados. Da analise resultaram formas, fontes e conteudo da aprendizagem gerencial destes docentes, e o que desejam aprender, que permitiram identificar assuntos para capacitacao na gestao. Neste artigo especificamente, que tem por objetivo evidenciar a ausencia de formacao do docente para a funcao de gestor, considerou-se a capacitacao para o desenvolvimento de competencias e consequente desempenho das funcoes no servico publico federal, assim como a transicao do docente para funcao de gestor. As recomendacoes finais envolvem processos de aprendizagem na pratica da gestao, necessidade de reflexao para desenvolver competencias considerando a relacao entre contexto social, individuo e suas experiencias vividas. The management professors of the Post-Graduation Programs of the Federal Rural University of Rio de Janeiro come from different areas to the Administration. The lack of specific training oriented to the performance of the management functions led to the objective of this research: To describe how the professor of postgraduate program in Federal Institution of Higher Education – IFES Learns and develops their managerial skills, even without specific training for management. To reach it in the research, it was adopted a qualitative inductive methodology of data analysis, according to Thomas, by which the results emerge from the data surveyed. From the analysis resulted the forms, sources and content of managerial learning of these teachers, and what they want to learn, which made it possible to identify subjects for training in management. In this article specifically, which aims to evidence the absence of teacher training for the role of manager, it was considered the qualification for the development of competences and consequent performance of the functions in the federal public service, as well as the transition from teacher to manager. The final recommendations involve learning processes in the management practice, need for reflection to develop competencies considering the relationship between social context, individual and their lived experiences.
Agent based dynamic resource allocation on federated clouds

Current large distributed system allows users to share and trade resources. In cloud computing, users purchase different resources like network bandwidth, computing power and storage system from one or more cloud providers for a limited period of time with a variable or fixed price. Federated cloud is a mechanism for sharing resources thereby increasing scalability. Allocating resources in cloud is a complex procedure. In order to improve resource allocation agent based resource allocation method is used. In this method, the user needs not know who is the cloud service provider and where the resources reside. The consumer gets the resources with the minimum price. The proposed system has three types of agents namely Consumer agent, Resource Brokering agent and Resource Provider agent.
Optimization of Vehicle Routing Problem with Load Balancing and Time Windows in Distribution

Vehicle route scheduling is an important activity in supply chain management. It is virtually a kind of vehicle routing problem with time windows (VRPTW). An improved model of VRPTW with load balancing was built up. It aims to achieve minimum vehicles, the shortest distribution distance, load balancing and customer's time demand. The algorithm was designed to two-stage. The first Stage was used to find the vehicle route schedule through particle swarm optimization. An improved inertial coefficient was considered to enhance the search speed. The second Stage was implemented for load balancing. The optimal or sub-optimal solution can be found efficiently through the proposed model for medium size vehicle routing problem.
IMPLEMENTATION OF A LEARNING SYNAPSE AND A NEURON FOR PULSE – COUPLED NEURAL NETWORKS Pavol

A new architecture of a learning synapse with on-chip learning and a neuron for pulse-coupled neural networks is presented. The main advantages of the proposed synapse are: continuous learning, easily adjustable parameters, compact design, low power and area consumption. This paper also contains results obtained from simulations performed with our model of a leaky integrate-and-fire neuron. The proposed neuron works with both constant or slowly changing input voltage level (input layer of a neural network) and pulse input (hidden layers and the output layer). Our circuits were designed in HSPICE and implemented in CAMELEON.