Miracle-dz/UniFAR-FTUs huggingface dataset:
Surface Molecules Released by Trypanosoma cruzi Metacyclic Forms Downregulate Host Cell Invasion

Background The question whether metacylic trypomastigote (MT) forms of different T. cruzi strains differentially release surface molecules, and how they affect host cell invasion, remains to be fully clarified. We addressed that question using T. cruzi strains that differ widely in the ability to invade cells. Methodology/Principal Findings Metacyclic forms were incubated at 37°C for 1 h in complete D10 medium or in nutrient-deprived PBS containing Ca2+ and Mg2+ (PBS++). The conditioned medium (CM), collected after parasite centrifugation, was used for cell invasion assays and Western blot analysis, using monoclonal antibodies directed to gp82 and gp90, the MT surface molecules that promote and negatively regulate invasion, respectively. CM of poorly invasive G strain (G-CM) contained high amounts of gp90 and gp82, either in vesicles or as soluble molecules. CM of highly invasive CL strain (CL-CM) contained gp90 and gp82 at very low levels. HeLa cells were incubated for 1 h with CL strain MT in D10, in absence or in the presence of G-CM or CL-CM. Parasite invasion was significantly inhibited by G-CM, but not by CL-CM. As G strain MT invasion rate in D10 is very low, assays with this strain were performed in PBS++, which induces invasion-promoting lysosome-spreading. G-CM, but not CL-CM, significantly inhibited G strain internalization, effect that was counteracted by preincubating G-CM with an anti-gp90 monoclonal antibody or anti-gp82 polyclonal antibody that do not recognize live MT. G strain CM generated in PBS++ contained much lower amounts of gp90 and gp82 as compared to CM produced in D10, and exhibited lower inhibitory effect on host cell invasion. Conclusion/Significance Our data suggest that the surface molecules spontaneously released by MT impair parasite-host cell interaction, gp82 presumably competing with the molecule expressed on MT surface for the host cell receptor, and gp90 further contributing to down modulate invasion.
Hybrid harmony search algorithm for global optimization

This paper proposes two hybrid optimization methods based on Harmony Search algorithm (HS) and two different nature-inspired metaheuristic algorithms. In the first contribution, the combination was between the Improved Harmony Search (IHS) and the Particle Swarm Optimization (PSO). The second contribution merged the IHS with the Differential Evolution (DE) operators. The basic idea of hybridization was to ameliorate all the harmony memory vectors by adapting the PSO velocity or the DE operators in order to increase the convergence speed. The new algorithms (IHSPSO and IHSDE) have been compared to the IHS, DE, PSO and some other algorithms like DHS and HSDM. The DHS and HSDM are two existing algorithms, which use different hybridization concepts between HS and DE. All of these algorithms have been evaluated by different test Benchmark functions. The results demonstrated that the hybrid algorithm IHSDE have the better convergence speed into the global optimum than the IHSPSO and the standard IHS, DE and PSO.
Foundations of Total Functional Data-Flow Programming

The field of declarative stream programming (discrete time, clocked synchronous, modular, data-centric) is divided between the data-flow graph paradigm favored by domain experts, and the functional reactive paradigm favored by academics. In this paper, we describe the foundations of a framework for unifying functional and data-flow styles that differs from FRP proper in significant ways: It is based on set theory to match the expectations of domain experts, and the two paradigms are reduced symmetrically to a low-level middle ground, with strongly compositional semantics. The design of the framework is derived from mathematical first principles, in particular coalgebraic coinduction and a standard relational model of stateful computation. The abstract syntax and semantics introduced here constitute the full core of a novel stream programming language.
Creation of 3D Human Avatar using Kinect

 Abstract— While the number of web and desktop 3D applications continue to increase, users would like to create their own 3D avatars which will look exactly like them. The Kinect(1) can help to users to reach this goal; after scanning human by Kinect's depth and RGB cameras it is possible to create almost the same 3D model including human faces and hairstyles that can be used for several algorithm in education, medicine, conferences, game industry, 3D social networks, etc.
University of Waterloo at TREC 2008 Blog Track

The paper reports the University of Waterloo participation in the opinion and polarity tasks of the Blog track. The proposed method uses a lexicon built from several linguistic resources. The opinion discriminating ability of each subjective lexical unit was estimated using the Kullback-Leibler divergence. The KLD scores of subjective words occurring within fixed-size windows around instances of query terms were used in calculating document scores. The described system also used a method of identifying phrases in topic titles by matching them to Wikipedia titles. The results show that both KLD-based scores of subjective lexical units and Wikipedia-matched phrases are useful techniques that help improve opinion retrieval performance.
Bumblebee workers from different sire groups vary in susceptibility to parasite infection

Female multiple mating with different males (polyandry) can be advantageous because the resulting genetic heterogeneity among offspring reduces the effects of parasitism. However, the underlying assumption that offspring fathered by different males vary in their susceptibility to parasites is so far only supported indirectly. Here we tested this crucial assumption using data from a study on the bumblebee Bombus terrestris L. with queens inseminated with sperm of either one or several males that originated from different sire groups (i.e. groups of brothers). We found that, under field conditions, workers from different sire groups, forming a patriline within a given colony, indeed differ in their susceptibility to the common intestinal parasite, Crithidia bombi, and do so independently of queen mating frequency.
De-noising Of Image and Its Performance Evaluation

The most important task in image processing is denoising the image. Lots of research is conducted in this era but the compelling challenge in this field is to get the efficient denoised image.In this paper three noises are added to the image one by one and then denoised with the bayes shrink and vishu shrink . Different authors had proposed the simple formulas for these methods. Comparison of both filters wih effect of noise is done using the various image matrics such as BER,MSE,PSNR . The filters are impleted on the matlab (R2013a)
Homburger ADHS-Skalen für Erwachsene (HASE)

HASE enthalt ein Manual (54 Seiten, DIN-A4-Format), jeweils funf Testbogen/Testhefte der Einzelverfahren Wender Utah Rating Scale in der Kurzform (WURS-K), Wender-Reimherr-Interview (WRI), Wender-ReimherrInterview Verlaufsdokumentation (WRI–V), ADHSSelbstbeurteilungsskala (ADHS-SB), ADHS-Diagnostische Checkliste (ADHS-DC), ADHS-Diagnostische Checkliste-Quantitativ (ADHS-DC-Q), Checkliste komorbider Storungen sowie eine Gesamtauswertung.
Antibodies against Food Antigens in Patients with Autistic Spectrum Disorders

Purpose. Immune system of some autistic patients could be abnormally triggered by gluten/casein assumption. The prevalence of antibodies to gliadin and milk proteins in autistic children with paired/impaired intestinal permeability and under dietary regimen either regular or restricted is reported. Methods. 162 ASDs and 44 healthy children were investigated for intestinal permeability, tissue-transglutaminase (tTG), anti-endomysium antibodies (EMA)-IgA, and total mucosal IgA to exclude celiac disease; HLA-DQ2/-DQ8 haplotypes; total systemic antibodies (IgA, IgG, and IgE); specific systemic antibodies: α-gliadin (AGA-IgA and IgG), deamidated–gliadin-peptide (DGP-IgA and IgG), total specific gliadin IgG (all fractions: α, β, γ, and ω), β-lactoglobulin IgG, α-lactalbumin IgG, casein IgG; and milk IgE, casein IgE, gluten IgE, -lactoglobulin IgE, and α-lactalbumin IgE. Results. AGA-IgG and DPG-IgG titers resulted to be higher in ASDs compared to controls and are only partially influenced by diet regimen. Casein IgG titers resulted to be more frequently and significantly higher in ASDs than in controls. Intestinal permeability was increased in 25.6% of ASDs compared to 2.3% of healthy children. Systemic antibodies production was not influenced by paired/impaired intestinal permeability. Conclusions. Immune system of a subgroup of ASDs is triggered by gluten and casein; this could be related either to AGA, DPG, and Casein IgG elevated production or to impaired intestinal barrier function.
Changing epidemiology of invasive pneumococcal disease among older adults in the era of pediatric pneumococcal conjugate vaccine.

CONTEXT A conjugate vaccine targeting 7 pneumococcal serotypes was licensed for young children in 2000. In contrast to the 23-valent polysaccharide vaccine used in adults, the 7-valent conjugate vaccine affects pneumococcal carriage and transmission. Early after its introduction, incidence of invasive pneumococcal disease declined among older adults, a group at high risk for pneumococcal disease. OBJECTIVE To determine among adults aged 50 years or older whether incidence of invasive pneumococcal disease, disease characteristics, or the spectrum of patients acquiring these illnesses have changed over the 4 years since pneumococcal conjugate vaccine licensure. DESIGN, SETTING, AND POPULATION Population-based surveillance of invasive pneumococcal disease in 8 US geographic areas (total population, 18,813,000), 1998-2003. MAIN OUTCOME MEASURES Incidence of invasive pneumococcal disease by pneumococcal serotype and other characteristics; frequency among case patients of comorbid conditions and other factors influencing mortality. RESULTS Incidence of invasive pneumococcal disease among adults aged 50 years or older declined 28% (95% confidence interval [CI], -31% to -24%), from 40.8 cases/100,000 in 1998-1999 to 29.4 in 2002-2003. Among those aged 65 years or older, the 2002-2003 rate (41.7 cases/100,000) was lower than the Healthy People 2010 goal (42 cases/100,000). Among adults aged 50 years or older, incidence of disease caused by the 7 conjugate vaccine serotypes declined 55% (95% CI, -58% to -51%) from 22.4 to 10.2 cases/100,000. In contrast, disease caused by any of the 16 serotypes only in polysaccharide vaccine did not change, and disease caused by serotypes not in either vaccine increased somewhat, from 6.0 to 6.8 cases/100,000 (13%; 95% CI, 1% to 27%). Between 1998-1999 and 2002-2003, the proportion of case-patients with human immunodeficiency virus infection increased from 1.7% (47/2737) to 5.6% (124/2231) (P<.001), and those with any comorbid condition that is an indication for pneumococcal polysaccharide vaccination increased from 62.3% (1842/2955) to 72.0% (1721/2390) (P<.001). CONCLUSIONS Our findings indicate that use of conjugate vaccine in children has substantially benefited older adults. However, persons with certain comorbid conditions may benefit less than healthier persons from the indirect effects of the new vaccine.
A Hybrid Method for Solving Traveling Salesman Problem

One of the important problems in graphs theory is TSP. Both learning automata and genetic algorithms are search tools which are used for solving many NP-complete problems. In this paper a hybrid algorithm is proposed to solve TSP. This algorithm uses both GA and LA simultaneously to search in state space. It has been shown that the speed of reaching to answer increases remarkably using LA and GA simultaneously in search process, and it also prevents algorithm from being trapped in local minimums. Experimental results show the superiority of hybrid algorithm over LA and GA.
Smoluchowski's coagulation equation: uniqueness, non-uniqueness and a hydrodynamic limit for the stochastic coalescent

Sufficient conditions are given for existence and uniqueness in Smoluchowski's coagulation equation, for a wide class of coagulation kernels and initial mass distributions. An example of non-uniqueness is constructed. The stochastic coalescent is shown to converge weakly to the solution of Smoluchowski's equation.
College students' suicidal ideation: Testing the predictions of the existential - constructivist theory of suicide

Lockman, Jennifer D. Ph.D., Purdue University, December 2016. College Students’ Suicidal Ideation: Testing the Predictions of the Existential Constructivist Theory of Suicide. Committee Chair: Heather Servaty-Seib, Ph.D. Suicide is the second leading cause of death in the college student population (Schwartz, 2006), and empirically supported theories for understanding suicide among college students are lacking (Lester, 1989; Prinstein, 2008; Rogers & Benson, 2013). Although not yet examined empirically, Rogers (2001) proposed an Existential Constructivist Theory of Suicide (ECTS), in which existential distress and the inability to reconstruct meaning from adverse life events contribute to suicidal ideation. ECTS includes both interpersonal and intrapersonal drivers of suicidal ideation, and for this reason, may better explain suicidal ideation in college students than existing theoretical models. Existing research focuses on Joiner’s (2005) Interpersonal Theory of Suicide (ITS) which proposes that two interpersonal cognitive affective states (i.e., perceived burdensomeness, thwarted belongingness) contribute to suicidal ideation (i.e., thoughts about death by suicide). Thus, in the present study I (a) tested the central hypotheses of the ECTS in a college student sample and (b) compared the model fit of the ECTS to the ITS to assess which statistical model best explained suicidal ideation in college students. Survey data were collected electronically from 195 college students (i.e., aged 18 – 25) attending Purdue University. Data were analyzed using SEM. The results supported the
SATISFACTION WITH PEER EDUCATORS AMONG HIV INFECTED PERSONS

Background An insuffi cient number of health personnel and excessive workload have been common barriers for the provision of adequate HIV care in Thailand. HIV patients are often discouraged when they experience medication side effects as they commence highly active antiretroviral therapy (HAART). Peer educators present a potential solution to this problem. This report focuses on patient satisfaction with the activities of peer educators. Method Two hundred and twenty three people living with HIV/AIDS (PLHA) were enrolled into this study following initiation of HAART. A structured interview was used. Complete data of 219 participants at month 4, and 211 at month 12 after initiation of HAART were collected. Focus group discussions were held in 4 selected hospitals. Descriptive statistical analyses were performed. Paired t-tests were carried out to compare satisfaction difference between month 4 and month 12. Content analyses of qualitative data were done. Result The mean age of participants was 35 (range: 18-73 years) and 53% of them were male. Their need for home visits by peer educators was higher at month 4 than at month 12. Participants expressed a high satisfaction rate with peer educators (time provided; willingness to listen; ability to explain; convenience in making contact when necessary; client comfort in talking to them; attentive to the condition; and provision of help, advice and encouragement in taking anteretroviral (ARV) medications at month 4 as well as month
Cloud computing for big data from biomedical sensors monitoring, storage and analyze

The paper present aspects regarding importance of using cloud computing technology for big data processing from biosensors. The wireless sensors for personal area network have applications have been used in healthcare monitoring application. There are some limitations of wireless sensors in terms of memory, energy, computation, communication, scalability and efficient management of the big data collected from biosensors. In healthcare area is need for powerful and scalable high-performance computing and massive storage infrastructure for real-time processing, storing and analyzing (online or offline) of the biosensors data by using complex algorithms for extract required values from database. The patients can interact with hospitals or doctor in offline or online, but the data must be storage by using cloud computing technology because this allow computing, storage and software services (SaaS) with customization possibilities and virtualization at low cost. The Cloud Computing can provide an open, flexible, and reconfigurable platform (PaaS) for monitoring and controlling applications.
Coding errors lead to unsupported conclusions: a critique of Hofmann et al. (2015)

We have detected coding errors in the meta-analysis of Hofmann et al. (2015) who investigated the effect of intranasal oxytocin on psychiatric symptoms. We demonstrate that, after correcting these errors and reanalysing the data, the main conclusions of Hofmann et al. (2015) are no longer supported.
Theoretical Computer Science Special Issue on Complex Networks

Complex networks are large networks encountered in practice that seem to lack any apparent structure. Typical complex networks include internet topologies, web graphs, peer-to-peer networks, social networks (cooperation between people , economical exchanges, friendships, and others), biological networks (pro-tein/gene interactions, brain, food webs), linguistic networks (co-occurrence graphs, synonyms), and many more. Precisely defining a complex network is a tricky proposition since it is hard to set up a definition that is broad enough to capture the above examples, yet restrictive enough to make mathematical sense. Notice that the above networks are very different in nature. Some are submitted to physical constraints (e.g., the internet or the brain) while others are purely virtual (e.g., social friendship networks); some come from natural sciences (e.g., biological networks) and others arise from technology (e.g., the internet); some are explicitly optimized with a notion of efficiency (e.g., economic networks or the internet) while others are not (e.g., the web). All these networks, however, have several properties in common [56]. In particular, they have • low global density—the number of links grows roughly linearly with the number of nodes, leading to a constant average degree; • low average distance, typically logarithmic or sub-logarithmic in the number of nodes; • heavy-tailed degree distributions, often modeled by power laws, Zipf, or log-normal distributions; • high local density—the probability that two neighbors of any nodes are themselves connected (i.e., the clustering coefficient) is large compared to the global density.
A Task-Pool Parallel I/O Paradigm for an I/O Intensive Application

In regards to applications like 3D seismic migration, it is quite important to improve the I/O performance within an cluster computing system. Such seismic data processing applications are the I/O intensive applications. For example, large 3D data volume cannot be hold totally in computer memories. Therefore the input data files have to be divided into many fine-grained chunks. Intermediate results are written out at various stages during the execution, and final results are written out by the master process. This paper describes a novel manner for optimizing the parallel I/O data access strategy and load balancing for the above-mentioned particular program model. The optimization, based on the application defined API, reduces the number of I/O operations and communication (as compared to the original model). This is done by forming groups of threads with "group roots", so to speak, that read input data (determined by an index retrieved from the master process) and then send it to their group members. In the original model, each process/thread reads the whole input data and outputs its own results. Moreover the loads are balanced, for the on-line dynamic scheduling of access request to process the migration data. Finally, in the actual performance test, the improvement of performance is often more than 60% by comparison with the original model.
UNDERSTANDING COMMUNICATIVE INTENTIONS USING SIMULATED ROLE-REVERSAL

Understanding the communicative intention of a speaker is the ultimate goal of language comprehension. Yet, there is very little computational work on this topic. In this chapter a general cognitive plausible model of how an addressee can understand communicative intentions is presented in mathematical detail. The key mechanism of the model is simulated role-reversal of the addressee with the speaker, i.e., the addressee puts himself in the state of the speaker and — using his own experience about plausible intentions — computes the most likely intention in the given context. To show the model’s computational effectiveness, it was implemented in a multi-agent system. In this system agents learn about which states of the world are desirable using a neural network trained with reinforcement learning. The power of simulated role-reversal in understanding communicative intention was demonstrated by depriving the utterances of speakers of all content. Employing the outlined model, the agents nevertheless accomplished a remarkable understanding of intentions using context information alone.
Higher-order glass-transition singularities in systems with short-ranged attractive potentials

Within the mode-coupling theory for the evolution of structural relaxation, the A4-glass-transition singularities are identified for systems of particles interacting with a hard-sphere repulsion complemented by different short-ranged potentials: Baxter's singular potential regularized by a large-wavevector cut-off, a model for the Asakura–Oosawa depletion attraction, a triangular potential, a Yukawa attraction, and a square-well potential. The regular potentials yield critical packing fractions, critical Debye–Waller factors, and critical amplitudes very close to each other. The elastic moduli and the particle localization lengths for corresponding states of the Yukawa system and the square-well system may differ by up to 20 and 10%, respectively.
New Frontier for Soft Computing Zero-Point Probability for Linear Source Separation

Blind” signal processing techniques have attracted a great deal of interest from the signal processing community in recent years. The term “blind” refers to the fact that very little information is known about the signals or processing in question. This paper deals with blind signal separation, the separation of unknown signals that have been mixed in an unknown way. In this paper the linear mixture model has been adopted; the signals in question are assumed to be linear mixtures of stationary sources. Techniques that address this problem using higher-order statistics rely on the accurate estimation of higher-order moments, either implicitly or explicitly. This can cause difficulties in real-time adaptive systems as anomalous outliers in the data can have disproportionate effects on the system. We introduce a novel on-line method for separating super-Gaussian signal mixtures that does not rely on higher-order moments, called “zero-point probability” (ZPP).