Miracle-dz/UniFAR-FTUs huggingface dataset:
Linking community and disease ecology: the impact of biodiversity on pathogen transmission

The increasing number of zoonotic diseases spilling over from a range of wild animal species represents a particular concern for public health, especially in light of the current dramatic trend of biodiversity loss. To understand the ecology of these multi-host pathogens and their response to environmental degradation and species extinctions, it is necessary to develop a theoretical framework that takes into account realistic community assemblages. Here, we present a multi-host species epidemiological model that includes empirically determined patterns of diversity and composition derived from community ecology studies. We use this framework to study the interaction between wildlife diversity and directly transmitted pathogen dynamics. First, we demonstrate that variability in community composition does not affect significantly the intensity of pathogen transmission. We also show that the consequences of community diversity can differentially impact the prevalence of pathogens and the number of infectious individuals. Finally, we show that ecological interactions among host species have a weaker influence on pathogen circulation than inter-species transmission rates. We conclude that integration of a community perspective to study wildlife pathogens is crucial, especially in the context of understanding and predicting infectious disease emergence events.
A store-and-forward architecture for video-on-demand service

The authors present store-and-forward architecture that can provide video-on-demand (VOD), as well as other data-based services. They assume a B-ISDN network to be in place. The four major elements in this architecture are the information provider warehouse (IPw) where video material is archived; the central office (CO) server which contains a processor responsible for the service management and a video buffer that interacts directly with network customers; and, finally, the customer premise equipment. A requested video program is provided in a real-time fashion from the CO server to the customer. However, at the information provider, the video program is retrieved from the archival storage in blocks, and with transfer rates much faster than real time. Subsequently, it is sent in a bursty mode to the CO servers via high-speed trunks.
Nitrogen Limitation Alters Biomass Production but Enhances Steviol Glycoside Concentration in Stevia rebaudiana Bertoni

The need for medicinal and aromatic plants for industrial uses creates an opportunity for farmers to produce alternative crops. Stevia rebaudiana Bertoni, a perennial shrub originating from Paraguay, is of increasing interest as a source of zero-calorie natural sweeteners: the steviol glycosides (SVglys). The aim of this study was to investigate the relevance of nitrogen (N) supply for leaf yield and for SVgly concentrations in leaves, which are the two major components of S. rebaudiana productivity. In this regard, the relationship between leaf N concentration, CO2 assimilation, leaf production and SVgly accumulation was investigated. The experiments were conducted consecutively in growth-chamber (CC: controlled conditions), in greenhouse (SCC: semi-controlled conditions) and in field conditions (FC) on two genotypes. In CC and SCC, three levels of N fertilization were applied. Plants were grown on four locations in the FC experiment. Both N supply (CC and SCC) and location (FC) had a significant effect on N content in leaves. When light was not limiting (SCC and FC) N content in leaves was positively correlated with CO2 assimilation rate and biomass accumulation. Irrespective of the growth conditions, N content in leaves was negatively correlated with SVgly content. However, increased SVgly content was correlated with a decreased ratio of rebaudioside A over stevioside. The evidence that the increased SVgly accumulation compensates for the negative effect on biomass production suggests that adequate SVgly productivity per plant may be achieved with relatively low fertilization.
Approximate particle number projection for finite range density dependent forces.

The Lipkin-Nogami method is generalized to deal with finite range density dependent forces. New expressions are derived and realistic calculations with the Gogny force are performed for the nuclei {sup 164}Er and {sup 168}Er. The sharp phase transition predicted by the mean field approximation is washed out by the Lipkin-Nogami approach. A much better agreement with the experimental data is reached with the new approach than with the Hartree-Fock-Bogoliubov one, especially at high spins. {copyright} {ital 1996 The American Physical Society. }
TLR9 regulates Th1 responses and cooperates with TLR2 in mediating optimal resistance to Mycobacterium tuberculosis

To investigate the role of Toll-like receptor (TLR)9 in the immune response to mycobacteria as well as its cooperation with TLR2, a receptor known to be triggered by several major mycobacterial ligands, we analyzed the resistance of TLR9−/− as well as TLR2/9 double knockout mice to aerosol infection with Mycobacterium tuberculosis. Infected TLR9−/− but not TLR2−/− mice displayed defective mycobacteria-induced interleukin (IL)-12p40 and interferon (IFN)-γ responses in vivo, but in common with TLR2−/− animals, the TLR9−/− mice exhibited only minor reductions in acute resistance to low dose pathogen challenge. When compared with either of the single TLR-deficient animals, TLR2/9−/− mice displayed markedly enhanced susceptibility to infection in association with combined defects in proinflammatory cytokine production in vitro, IFN-γ recall responses ex vivo, and altered pulmonary pathology. Cooperation between TLR9 and TLR2 was also evident at the level of the in vitro response to live M. tuberculosis, where dendritic cells and macrophages from TLR2/9−/− mice exhibited a greater defect in IL-12 response than the equivalent cell populations from single TLR9-deficient animals. These findings reveal a previously unappreciated role for TLR9 in the host response to M. tuberculosis and illustrate TLR collaboration in host resistance to a major human pathogen.
A Survey of Visual Sensor Networks

Visual sensor networks have emerged as an important class of sensor-based distributed intelligent systems, with unique performance, complexity, and quality of service challenges. Consisting of a large number of low-power camera nodes, visual sensor networks support a great number of novel vision-based applications. The camera nodes provide information from a monitored site, performing distributed and collaborative processing of their collected data. Using multiple cameras in the network provides different views of the scene, which enhances the reliability of the captured events. However, the large amount of image data produced by the cameras combined with the network's resource constraints require exploring new means for data processing, communication, and sensor management. Meeting these challenges of visual sensor networks requires interdisciplinary approaches, utilizing vision processing, communications and networking, and embedded processing. In this paper, we provide an overview of the current state-of-the-art in the field of visual sensor networks, by exploring several relevant research directions. Our goal is to provide a better understanding of current research problems in the different research fields of visual sensor networks, and to show how these different research fields should interact to solve the many challenges of visual sensor networks.
Color Brightness Transfer Function evaluation for non overlapping multi camera tracking

People Tracking in multiple cameras is of great interest for wide area video surveillance systems. Multi-camera tracking with non-overlapping fields of view (FOV) involves the tracking of people in the blind region and their correspondence matching across cameras. We consider these problems in this paper. We propose a multi camera architecture for wide area surveillance and a real time people tracking algorithm across non overlapping cameras. We compared different methods to evaluate the color Brightness Transfer Function (BTF) between non overlapping cameras. These approaches are based on a testing phase during which the color histogram mapping, between pairs of images of the same object observed in the different field of views, is carried out. The experimental results compare two different transfer functions and demonstrate their limits in people association when a new person enters in one camera FOV.
CHALLENGES FACED BY PROFESSIONALS WORKING IN CHILD SEXUAL ABUSE MULTI-SECTORIAL FORUMS: A CASE OF THE VICTIM-FRIENDLY SYSTEM IN ZIMBABWE

This article discusses the challenges faced by role players who work with survivors of child sexual abuse within the Victim-Friendly System. The Victim Friendly System represents a confluence of multi-sectorial professional interventions targeting child sexual abuse survivors in Zimbabwe. Professionals involved in the Victim-Friendly System include social workers, medical doctors, nurses, police, as well as role players within the justice system such as magistrates and prosecutors, counsellors, educationists and psychologists. The findings of this qualitative study show that professionals work within the context of a shrinking economy that has given rise to a plethora of challenges that include, among other things, staff and skills shortages, lack of financial and material resources, poor access to proper infrastructure and other logistical constrains. The authors end the paper by discussing recommendations that have policy, administrative and professional implications
Estimating infectious disease parameters from data on social contacts and serological status

Summary. In dynamic models of infectious disease transmission, typically various mixing patterns are imposed on the so‐called ‘who acquires infection from whom’ matrix. These imposed mixing patterns are based on prior knowledge of age‐related social mixing behaviour rather than observations. Alternatively, we can assume that transmission rates for infections transmitted predominantly through non‐sexual social contacts are proportional to rates of conversational contact which can be estimated from a contact survey. In general, however, contacts reported in social contact surveys are proxies of those events by which transmission may occur and there may be age‐specific characteristics that are related to susceptibility and infectiousness which are not captured by the contact rates. Therefore, we model transmission as the product of two age‐specific variables: the age‐specific contact rate and an age‐specific proportionality factor, which entails an improvement of fit for the seroprevalence of the varicella zoster virus in Belgium. Furthermore, we address the effect on the estimation of the basic reproduction number, using non‐parametric bootstrapping to account for different sources of variability and using multimodel inference to deal with model selection uncertainty. The method proposed makes it possible to obtain important information on transmission dynamics that cannot be inferred from approaches that have been traditionally applied hitherto.
Modeling and Performances Evaluation of HARQ Technique for MIMO Transmission in Downlink LTE Cellular Networks

Long Term Evolution (LTE) is designed for deployment in a variety of spectrum allocation ranging from 1.4 MHz to 20 MHz. The peak data rate envisaged for LTE is 100 Mbps in downlink and 50 Mbps in the uplink. Unfortunately, different constraints have a strong influence on system performance such as the velocity of user equipment and effect of multipath channel. To achieve data rate compliance with LTE standard, Different transmissions techniques are deployed such as MIMO transmission, Adaptive Modulation and Coding (AMC) and Hybrid Automatic Repeat request (HARQ) Technique. In this paper we simulate and discuss the performances of HARQ process for downlink LTE system using MIMO transmit diversity and spatial multiplexing. In first time, we study the effect of HARQ technique over AWGN channel then we perform different MIMO transmission schemes for downlink LTE system in multipath channel. Extended Vehicular-A tapped delay channel model are used to model high speed user equipment. Keywords—Hybrid Automatic Repeat reQuest; transmit diversity; Open loop spatial multiplexing; Mutiple input mutiple output
One research of clustering algorithm based on rough set and genetic algorithm

This paper integrates rough set theory and adaptive genetic algorithm to propose a new clustering method based on symbols attributes (RAGACA). For each different value, the algorithm adopts the top-down divisive hierarchical clustering strategy and uses RAGA algorithm to dichotomize the data sets step by step until it reaches pre-specified number of cluster, and then output the clustering result. The experimental results show that RACACA has higher accuracy and convergence for the data with symbols attributes.
The Heisenberg Representation of Quantum Computers

Since Shor`s discovery of an algorithm to factor numbers on a quantum computer in polynomial time, quantum computation has become a subject of immense interest. Unfortunately, one of the key features of quantum computers--the difficulty of describing them on classical computers--also makes it difficult to describe and understand precisely what can be done with them. A formalism describing the evolution of operators rather than states has proven extremely fruitful in understanding an important class of quantum operations. States used in error correction and certain communication protocols can be described by their stabilizer, a group of tensor products of Pauli matrices. Even this simple group structure is sufficient to allow a rich range of quantum effects, although it falls short of the full power of quantum computation.
Identification and Applications of Three-dimensional Non-local Structural Motifs in Protein Folding Data

How does a protein fold into its biologically functional three-dimensional (3D) structure? This problem remains one of the greatest challenges in structural biology [Dill & Chan 1997, Dobson 2003,]. However, recent advances in experimental technologies and computational theories have led researchers closer to solving this problem [Dinner et al. 2000, Pande, 2003, Onuchic & Wolynes, 2004]. Specifically, computer simulations based on theories in molecular dynamics have allowed scientists to gain insights into the folding process at an unprecedented temporal and spatial resolution, for instance, at the atomistic level with femtosecond (10 s) scale [Dauber-Osguthorpe et al. 1996, Raman et al. 2008, Snow et al., 2002, van der Spoel & Seibert 2006, Wallin & Shakhnovich 2008]. The product of such simulations is a collection of folding trajectories of the protein under study, where each trajectory consists of an ordered sequence of 3D structures sampled during the folding simulation. In this article, we refer to each 3D structure on a trajectory as a frame. A trajectory essentially depicts the evolving path that a protein acquires its final 3D structure from an initially random structure. Figure 1 illustrates four frames along a folding trajectory of a designed protein Beta3S. By analyzing these folding trajectories, researchers have gained invaluable insights in understanding the nature of the folding process such as key residues [Vendruscol et al., 2001] and different folding mechanisms (e.g., the nucleation-condensation model [White et al., 2005]). These findings have also been subsequently verified by experimental methods. A wide range of studies has been conducted to analyze protein folding trajectories. Almost all of these studies consider the 3D structures along a trajectory as indivisible entities, as evidenced by the three commonly adopted structure representations: (1) reaction coordinates, (2) distance matrix, and (3) secondary structure-based schema. In the first schema, a 3D structure is projected as a set of scalar
Tasks to Tease Apart Scatterplot Design Decisions

Scatterplots are among the most common methods for exploring and presenting data, covering a wide range of tasks and designs. The variety of scatterplot designs has created a proliferation of potential design decisions to consider when constructing a scatterplot. However, there remain many unexamined assumptions in respect to the trade-offs between these decisions. In this short summary, we begin the process of synthesizing recent work to build descriptive knowledge of how design decisions affect the analysis tasks viewers perform with scatterplots. Through deriving twelve abstracted scatterplot tasks, we can start to tease apart the different affordances of design decisions, and begin to formulate a basis for prescriptive scatterplot design.
The importance of shadows in augmented reality

In AugmentedReality (AR) virtual objectsare visually addedto real scenary, i.e., the real sceneis augmented with virtual objects.In someAR applicationsit is a goal in itself thatthevirtual objectsareindistinguishablefrom realobjects.A majordifficulty in achieving thisrealismis to ensurethatthevirtual objectsarerenderedusinglighting conditionswhichareconsistentwith thelighting conditionsin therealscene.If thisdifficulty canbeovercome the virtual objectscanbe shaded,andcancastshadows, just as if they had actually beenpart of the real scene. Ourwork focusesondevelopingmethodsfor determining suchlighting conditionsandresultsshow thataddingthe correctshadingandshadowing to virtual objectssubstantially enhancesthevisualqualityof theaugmentedscene, andmakesit mucheasierfor peopleto percei vethespatial relationsbetweenrealandvirtual objects.
Deposited in DRO : 04 January 2010 Version of attached le : Accepted Version Peer-review status of attached

As an extension to Floyd-Hoare logic, separation logic has been used to facilitate reasoning about imperative programs manipulating shared mutable data structures. Recently, it has also been extended to support modular reasoning in Java-like object-oriented languages where only single inheritance is allowed. In this paper we propose an extension of separation logic to support also the reasoning for multiple inheritance in C++ -like languages. To cater for multiple inheritance, we modified the standard storage model for separation logic in a way that the correct reference to a field or a method can be easily determined. On top of this storage model, a set of proof rules are proposed. Our verification system also provides basic support for behavioral subtyping.
Graph-based Analysis for E-Commerce Recommendation

Recommender systems automate the process of recommending products and services to customers based on various types of data including customer demographics, product features, and, most importantly, previous interactions between customers and products (e.g., purchasing, rating, and catalog browsing). Despite significant research progress and growing acceptance in real-world applications, two major challenges remain to be addressed to implement effective e-commerce recommendation applications. The first challenge is concerned with making recommendations based on sparse transaction data. The second challenge is the lack of a unified framework to integrate multiple types of input data and recommendation approaches. This dissertation investigates graph-based algorithms to address these two problems. The proposed approach is centered on consumer-product graphs that represent sales transactions as links connecting consumer and product nodes. In order to address the sparsity problem, I investigate the network spreading activation algorithms and a newly proposed link analysis algorithm motivated by ideas from Web graph analysis techniques. Experimental results with several e-commerce datasets indicated that both classes of algorithms outperform a wide range of existing collaborative filtering algorithms, especially under sparse data. Two graph-based models that enhance the simple consumer-product graph were proposed to provide unified recommendation frameworks. The first model, a two-layer graph model, enhances the consumer-product graph by incorporating the consumer/product attribute information as consumer and product similarity links. The second model is based on probabilistic relational models (PRMs) developed in the relational learning literature. It is demonstrated with e-commerce datasets that the proposed frameworks not only conceptually unify many of the existing recommendation approaches but also allow the exploitation of a wider range of data patterns in an integrated manner, leading to improved recommendation performance. In addition to the recommendation algorithm design research, this dissertation also employs the random graph theory to study the topological characteristics of consumer-product graphs and the fundamental mechanisms that generate the sales transaction data. This research represents the early step towards a meta-level analysis framework for validating the fundamental assumptions made by different recommendation algorithms regarding the consumer-product interaction generation process and thus supporting systematic recommendation model/algorithm selection and evaluation.
Risk-Aware Virtual Resource Management for Access Control-Based Cloud Datacenters

Multitenancy and virtualization features of cloud computing enhance resource utilization and lower the cloud provider total cost of hosting customers data for big data applications. However, the cloud computing has many security challenges that are exacerbated by virtual resource sharing. In particular, sharing of resources among potentially untrusted tenants can result in an increased risk of information leakage due to vulnerability of virtual resources causing side channel attacks or VM escape. For the big data applications, an access control policy such as RBAC can be used to control the data sharing among cloud customers. However, an unintelligent cloud resources management mechanism can significantly increase the risk of data leakage among roles. The goal of this paper is to develop efficient risk-aware virtual resource assignment mechanisms for Cloud’s multitenant environment. The objective is to minimize of risk of information leakage due to Cloud virtual resources vulnerability. Such an assignment problem is shown to be NP-Complete. We present several scheduling heuristics including a scalable solution and compare their relative performance.
Couture: Tailoring STT-MRAM for Persistent Main Memory

Modern computer systems rely extensively on dynamic random-access memory (DRAM) to bridge the performance gap between on-chip cache and secondary storage. However, continuous process scaling has exposed DRAM to high off-state leakage and excessive power consumption from frequent refresh operations. Spintransfer torque magnetoresistive RAM (STT-MRAM) is a plausible replacement for DRAM, given its high endurance and near-zero leakage. However, conventional STT-MRAM cannot directly substitute DRAM due to its large cell space area and the high latency and energy costs for writes. In this work, we present Couture – a main memory design using tailored STT-MRAM that can offer a storage density comparable to DRAM and high performance with low-power consumption. In addition, we propose an intelligent data scrubbing method (iScrub) to ensure data integrity with minimum overhead. Our evaluation results show that, equipped with the iScrub policy, our proposed Couture can achieve up to 23% performance improvement, while consuming 18% less energy, on average, compared to a contemporary DRAM.