Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-adapting numerical software (SANS) effort

The challenge for the development of next-generation software is the successful management of the complex computational environment while delivering to the scientist the full power of flexible compositions of the available algorithmic alternatives. Self-adapting numerical software (SANS) systems are intended to meet this significant challenge. The process of arriving at an efficient numerical solution of problems in computational science involves numerous decisions by a numerical expert. Attempts to automate such decisions distinguish three levels: algorithmic decision, management of the parallel environment, and processor-specific tuning of kernels. Additionally, at any of these levels we can decide to rearrange the user's data. In this paper we look at a number of efforts at the University of Tennessee to investigate these areas.
Graph data management systems for new application domains

Graph data management has long been a topic of interest for database researchers. The topic gained renewed interest recently, motivated by the rapid emergence of new application domains including social networks and the Web of data. This tutorial characterizes graph data management techniques and categorizes recent graph data management systems. In this context, we focus on the management of very large graphs such as social networks or the Web of data, rather than on the management of many smaller graphs (which frequently appear in bioinformatics and cheminformatics). The first part of this tutorial describes the requirements imposed by new application domains, and provides a classification of recent systems according to their data and computation models. Our classification also highlights the main representations used to store the graph (dense/sparse native graphs, triple storage or relational layouts), and the access patterns and typical queries considered (reachability or neighborhood queries, updates versus reads, transactional requirements and graph consistency models). In the second part of this tutorial, we map the data and computation models to concrete graph management systems, highlighting target application domains, implementation techniques, scalability and workload requirements. We pay special attentions to declarative models that allow query optimization (as performed in Horton [1] and Neo4j [2]), and contrast them to procedural models (such as Pregel [3]), which are more general but severely limit optimizations.
Using of FOTF toolbox and Z-transform for fractional control systems

The FOTF toolbox for MATLAB is proposed for research of fractional control systems in this article. For the technical realization of fractional controllers, it is proposed to approximate the transition functions by difference equations. For this purpose, the method of z-transform is used with the discrete integrator approximations. Telescope control system was use as the testing object of investigation for the digital fractional order controller.
Trusting your assistant

The assistant interface metaphor has the potential to shield the human user from low-level, task-specific details, while allowing the automation of the many idiosyncratic, mundane tasks falling between the capabilities of commercial software packages. However, a user will not willingly put resources (money, privacy, information) at risk unless the assistant can be trusted to carry out the task in accord with the user's goals and priorities. This risk is significant, because assistant behaviors, being idiosyncratic and highly customized, will not be as well supported or documented as is commercial software. This paper describes a solution to this problem, allowing the assistant to safely execute partially trusted behaviors and to interactively increase the user's trust in the behavior so that more of the steps can be carried out autonomously. The approach is independent of how the behavior was acquired and is based on using incremental formal validation to populate a trust library for the behavior.
The Effects of Ascorbate, N-Acetylcysteine, and Resveratrol on Fibroblasts from Patients with Mitochondrial Disorders

Reactive oxygen species (ROS) are assumed to be implicated in the pathogenesis of inborn mitochondrial diseases affecting oxidative phosphorylation (OXPHOS). In the current study, we characterized the effects of three small molecules with antioxidant properties (N-acetylcysteine, ascorbate, and resveratrol) on ROS production and several OXPHOS parameters (growth in glucose free medium, ATP production, mitochondrial content and membrane potential (MMP)), in primary fibroblasts derived from seven patients with different molecularly defined and undefined mitochondrial diseases. N-acetylcysteine appeared to be the most beneficial compound, reducing ROS while increasing growth and ATP production in some patients’ cells. Ascorbate showed a variable positive or negative effect on ROS, ATP production, and mitochondrial content, while incubation with resveratrol disclosed either no effect or detrimental effect on ATP production and MMP in some cells. The individual responses highlight the importance of investigating multiple parameters in addition to ROS to obtain a more balanced view of the overall effect on OXPHOS when evaluating antioxidant treatment options for mitochondrial diseases.
T cell receptors with allo-major histocompatibility complex specificity from rat and mouse. Similarity of size, plasmin susceptibility, and localization of antigen-binding region

Antisera specific for the constant part Ctau of T cell receptor molecules in mice and rats have been produced in rabbits by immunization with idiotype-positive rat T cell molecules. Such antisera could be shown to react with the majority of normal T lymphocytes from both rats and mice. Mixed leukocyte culture-activated T blasts displayed a higher percentage of positive cells than concanovalin A- or phytohemaglutinin-induced T blasts. Lipopolysaccharide-induced B blasts were not reactive with the antiserum. Lyt-1-,2+,3+ blasts displayed a significantly brighter straining than the corresponding Lyt-1+,2-,3- blasts. Isolation of the reactive molecules from T cells by immunosorption yielded a 70,000-dalton single chain polypeptide as the dominant group of molecules. Plasmin caused the chain to split into 45,000- and 25,000-dalton polypeptides, with the smaller fragment displaying antigen-binding capacity. Molecules identical in size and plasma degradation patterns were isolated from Lyt-1+,2-3- and 1-,2+,3+ blasts. Preliminary functional data supported the view that the antiserum is directed against the constant region Ctau relevant receptor structures on immunocompetent T lymphocytes.
Pipet: a design concept supporting photo sharing

To support reminiscing in the home, people collect an increasing amount of digital media on numerous devices. When sharing their media with other people, distribution of the media over different devices can be problematic. In this paper, we address this problem by designing an innovative interaction concept for cross-device interaction to support groups in sharing photos using multiple devices. We designed and implemented the Pipet concept. Results of a comparative study show that Pipet resulted in a pragmatic and hedonic user experience.
In Vivo and In Vitro Antıneoplastic Actions of Caffeic Acid Phenethyl Ester (CAPE): Therapeutic Perspectives

Cancer prevention and treatment strategies have attracted increasing interest. Caffeic acid phenethyl ester (CAPE), an active component of propolis extract, specifically inhibits NF-κB at μM concentrations and shows ability to stop 5-lipoxygenase-catalyzed oxygenation of linoleic acid and arachidonic acid. Previous studies have demonstrated that CAPE exhibits antioxidant, antiinflammatory, antiproliferative, cytostatic, antiviral, antibacterial, antifungal, and, most improtantly, antineoplastic properties. The primary goal of the present review is to summarize and critically evaluate the current knowledge regarding the anticancer effect of CAPE in different cancer types.
Projet IMPALA. Radar panoramique hyperfréquence pour la localisation et la cartographie simultanées en environnement extérieur

L'objectif du projet IMPALA est d'evaluer l'apport du radar comme solution alternative aux moyens de perception en robotique mobile d'exterieur. Cet article illustre a travers une application de localisation et de cartographie simultanees (SLAM). les potentialites d'un radar panoramique a modulation de frequence (FMCW) qui a ete developpe au cours du projet. Donnant acces a l'information de distance et de vitesse des entites mobiles presentes dans l'environnement, le radar permet d'envisager des applications de detection et de suivi d'objets mobiles (DATMO) dont un premier resultat est presente ici.
Tumor-Killing Capabilities of Innate and Adaptive Effector Cells with Polyfunctional and Long-Lasting Activation Alternative Maturation Mixtures Induce Fast Dendritic Cells Stimulated with

The clinical usage of dendritic cells (DC) for tumor immunotherapy still requires improvements. In this study, three alternative maturation mixtures were compared with the cytokine-based gold standard, and the overall interaction of the resulting DC with effector cells from the innate as well as the adaptive immunity was evaluated in healthy donors. Stimulation with the TLR-4 ligand monophosphoryl lipid A together with IFN- g (alt-2 DC) resulted in DC with the highest levels of costimulatory molecule expression and IL-12p70/IL-10 ratio. Whereas all alternative DC were able to induce NK and gd T cells to acquire cytotoxic properties and secrete type 1 and proinﬂammatory cytokines, after both short (20-h)- and long (5–8 d)-time coculture, secretion of IFN- g by the innate populations was induced in response to alt-2 and alt-1 DC (TNF- a , IFN- a , IFN- g , IL-1 b , poly IC), but not to alt-3 DC (TNF- a , IFN- g , IL-1 b , CL097). Regarding CD8 + T cell–mediated Ag-speciﬁc immune responses, a heterogeneous pattern of responses was obtained among the healthy donors, suggesting rather a competition than a synergy among the different effector cells. Our data promote further evaluation of alt-2 fast DC for translatability into clinical immunotherapy trials, while also fostering the need to identify biomarkers for immune cell responsiveness and tumor susceptibility to be able to select for each patient the best possible DC-based therapy. The Journal of Immunology , 2013, 190: 3328–3337.
IEEE 802.11 networks with dormant mode support: an IP paging approach and its performance analysis

IEEE802.11 networks are changing its primary role of extension of private LANs to become an access technology in competition or collaboration with current cellular networks. In addition, large-scale IEEE802.11 deployments are a reality that mesh networks can contribute to expand. But not only, networks are changing; their users are doing the same. More portable devices as WiFi enabled PDAs or phones will allow an increase of their number and mobility, but suffering from severe battery constraints. In addition, the interest in VoIP over WLAN will introduce the need of establishing sessions to WLAN users and not only from them. In order to support similar conditions, current cellular systems make use of a dormant mode with paging support which is inexistent in the IEEE802.11 networks. In this paper we propose the introduction of IP paging in IEEE802.11 networks in order to solve this problem. The aim of this paper is to demonstrate the usability of IP paging in order to reduce the mobility signaling cost. This is achieved through a new analytical approach that evaluates the following parameters: the call-to-mobility ratio (CMR), the size of the radio access network (RAN) and the size of the paging area. The solutions analyzed are the Hierarchical Mobile IPv6 (HMIPv6) protocol and a new extended version of this with IP paging support. The novelty of this latter version lies in its use of distance-based dynamic paging areas and its specific design for IEEE802.11 networks.
Exploiting Local Data Uncertainty to Boost Global Outlier Detection

This paper presents a novel hybrid approach to outlier detection by incorporating local data uncertainty into the construction of a global classifier. To deal with local data uncertainty, we introduce a confidence value to each data example in the training data, which measures the strength of the corresponding class label. Our proposed method works in two steps. Firstly, we generate a pseudo training dataset by computing a confidence value of each input example on its class label. We present two different mechanisms: kernel k-means clustering algorithm and kernel LOF-based algorithm, to compute the confidence values based on the local data behavior. Secondly, we construct a global classifier for outlier detection by generalizing the SVDD-based learning framework to incorporate both positive and negative examples as well as their associated confidence values. By integrating local and global outlier detection, our proposed method explicitly handles the uncertainty of the input data and enhances the ability of SVDD in reducing the sensitivity to noise. Extensive experiments on real life datasets demonstrate that our proposed method can achieve a better tradeoff between detection rate and false alarm rate as compared to four state-of-the-art outlier detection algorithms.
Baseline Prediction of Combination Therapy Outcome in Hepatitis C Virus 1b Infected Patients by Discriminant Analysis Using Viral and Host Factors

Background Current treatment of chronic hepatitis C virus (HCV) infection has limited efficacy −especially among genotype 1 infected patients−, is costly, and involves severe side effects. Thus, predicting non-response is of major interest for both patient wellbeing and health care expense. At present, treatment cannot be individualized on the basis of any baseline predictor of response. We aimed to identify pre-treatment clinical and virological parameters associated with treatment failure, as well as to assess whether therapy outcome could be predicted at baseline. Methodology Forty-three HCV subtype 1b (HCV-1b) chronically infected patients treated with pegylated-interferon alpha plus ribavirin were retrospectively studied (21 responders and 22 non-responders). Host (gender, age, weight, transaminase levels, fibrosis stage, and source of infection) and viral-related factors (viral load, and genetic variability in the E1–E2 and Core regions) were assessed. Logistic regression and discriminant analyses were used to develop predictive models. A “leave-one-out” cross-validation method was used to assess the reliability of the discriminant models. Principal Findings Lower alanine transaminase levels (ALT, p = 0.009), a higher number of quasispecies variants in the E1–E2 region (number of haplotypes, nHap_E1–E2) (p = 0.003), and the absence of both amino acid arginine at position 70 and leucine at position 91 in the Core region (p = 0.039) were significantly associated with treatment failure. Therapy outcome was most accurately predicted by discriminant analysis (90.5% sensitivity and 95.5% specificity, 85.7% sensitivity and 81.8% specificity after cross-validation); the most significant variables included in the predictive model were the Core amino acid pattern, the nHap_E1–E2, and gamma-glutamyl transferase and ALT levels. Conclusions and Significance Discriminant analysis has been shown as a useful tool to predict treatment outcome using baseline HCV genetic variability and host characteristics. The discriminant models obtained in this study led to accurate predictions in our population of Spanish HCV-1b treatment naïve patients.
Resources or Power? Implications of Social Networks on Compensation and Firm Performance

Using a sample of 4,278 listed UK firms, we construct a social network of directorship-interlocks that comprises 31,495 directors. We use social capital theory and techniques developed in social network analysis to measure a director's connectedness and investigate whether this connectedness is associated with their compensation level and their firms overall performance. We find connectedness is positively associated with compensation and with the firm's future performance. The results do not support the view that executive and outside directors use their connections to extract economic rents. Rather the company compensates these individuals for the resources these better connections provide to the firm.
White Blood Cells Count and Incidence of Type 2 Diabetes in Young Men

OBJECTIVE Association between white blood cell (WBC) count and diabetes risk has been recently suggested. We assessed whether WBC count is an independent risk factor for diabetes incidence among young healthy adults. RESEARCH DESIGN AND METHODS WBC count was measured in 24,897 young (mean age 30.8 ± 5.36 years), normoglycemic men with WBC range of 3,000 to 12,000 cells/mm3. Participants were periodically screened for diabetes during a mean follow-up of 7.5 years. RESULTS During 185,354 person-years of follow-up, diabetes was diagnosed in 447 subjects. A multivariate model adjusted for age, BMI, family history of diabetes, physical activity, and fasting glucose and triglyceride levels revealed a 7.6% increase in incident diabetes for every increment of 1,000 cells/mm3 (P = 0.046). When grouped in quintiles, a baseline WBC count above 6,900 cells/mm3 had an independent 52% increase in diabetes risk (hazard ratio 1.52 [95% CI 1.06–2.18]) compared with the lowest quintile (WBC <5,400 cells/mm3). Men at the lowest WBC quintile were protected from diabetes incidence even in the presence of overweight, family history of diabetes, or elevated triglyceride levels. After simultaneous control for risk factors, BMI was the primary contributor of the variation in multivariate models (P < 0.001), followed by age and WBC count (P < 0.001), and family history of diabetes and triglyceride levels (P = 0.12). CONCLUSIONS WBC count, a commonly used and widely available test, is an independent risk factor for diabetes in young men at values well within the normal range.
The effects of Mycobacterium vaccae on allergen-induced airway responses in atopic asthma

T-helper (Th)2 cytokines play a central role in asthma. Therefore, a double-blind randomised study was conducted to investigate whether heat-killed Mycobacterium vaccae (SRL172), a potent downregulator of Th2 cytokines, can reduce allergen-induced airway responses in patients with atopic asthma. A total 24 male asthmatics participated in this study. A bronchial allergen challenge was performed along with early (EAR) and late asthmatic responses (LAR) 2 weeks before and 3 weeks after a single intradermal injection of SRL172 or placebo. Before and after treatment, serum immunoglobulin (Ig)E levels and in vitro production of interleukin (IL)-5 by peripheral blood lymphocytes were studied. Neither treatment affected the EAR. SRL172 caused a mean 34% reduction of the area under the curve of the forced expiratory volume in one second (FEV1) changes during the LAR, which failed to reach conventional statistical significance when compared with placebo. SRL172 also caused a mean 25% decrease in the maximum fall in FEV1 during LAR, but this was not significantly different from placebo. SRL172 caused a reduction in serum IgE and IL-5 synthesis in vitro 3 weeks post-treatment (p=0.07). This study shows a trend toward significance for the effects of heat-killed Mycobacterium vaccae (SRL172) on allergen-induced airway responses. Further clinical trials, involving multiple dosing, are needed.
A Holistic Approach Towards a UML Profile for Business Modeling

Due to faster and faster changing business conditions, companies must be able to quickly adopt these changes to their IT infrastructure. Thus, business models must reflect these changes in order to design/align business processes supporting the value exchanges defined in the business model. Presently there are three major and well-accepted business modeling techniques e3-value, Resource-Event-Agent (REA) and the Business Modeling Ontology (BMO). All of them use their own proprietary notation, which is incompatible with UML the de-facto modeling standard in software engineering. In order to allow a straight-through modeling approach from business models over business process models to software artifacts, it is desirable to use a common modeling approach. Therefore we propose to specify a UML profile for business modeling integrating all benefits of these methodologies in one ontology. As a result this new ontology helps to cover our main research question the transition between a business model and a business process model. Furthermore the introduction of a framework for measuring the quality of business models as well as the definition of business modeling patterns is discussed.
ASSESSMENT OF THE PRODUCTION VARIABLES ON THE PELLETIZATION PROPERTIES OF MICROCRYSTALLINE CELLULOSE II (MCCII)

Objective: To study microcrystalline cellulose II (MCCII) as new pelletization aid using the extrusion/spheronization technology. Methods: The effect of the spheronization rate and spheronization time was assessed by a response surface design. The shape descriptors and physical properties of pellets were taken as response variables. Approximately, 30 g of MCCII were hydrated, passed through a # 20 mesh sieve and spheronizated at frequencies of 6, 9 and 12 Hz and residence times of 15, 240 and 480 s in 9 experimental runs. In a separate experimental set, moisture levels of 25, 50, 75, 100 and 125% were employed at the optimal operating conditions of 6 Hz and 480 s. A microscopy analysis was used to evaluate the shape descriptors. Pellets properties such as compressibility, friability, porosity, strength, flow rate and mass were also evaluated. Results: Pellets having a small size and a high value of shape descriptors related to morphology were obtained employing a spheronization rate and spheronization time of 6Hz and 480s and 100% wetting level. The spheronization time increased pellet densification but decreased the total porosity. Pellet mass was also favoured by using high spheronization rates. A high moisture level (>100%) rendered pellets having a large size, mass, low porosity and good yield. Conversely, pellet size decreased as sample load increased, whereas porosity and compressibility increased as sample load augmented. Conclusion: MCCII offers the potential for use as an alternative pelletization agent rendering pellets having a good flowability, high mechanical strength and low friability at the optimal operational conditions.
Porous chitosan scaffold and ngf promote neuronal differentiation of neural stem cells in vitro.

OBJECTIVE Successful neural stem cells (NSCs) therapies require the controlled differentiation of NSCs into neurons. Porous chitosan scaffold was explored if it promoted neuronal differentiation of NSCs in the presence of nerve growth factor (NGF) in 3-dimensional (3-D) culture. METHODS Chitosan scaffold was made by the freeze-drying technique. NSCs were cultured under four different conditions: on flat cover slips (2-D structure) in media with or without NGF, and on chitosan scaffold (3-D structure) in media with or without NGF. Immunohistochemical staining was used to observe multi-directional differentiation of cultured NSCs. Photomicrographs were taken and analyzed for cell number, soma size, and neuronal process length. RESULTS The porosity index of chitosan scaffold was around 90% and the diameter of pores was 50-350 μm. NSCs could differentiate into neurons, astrocytes, and oligodendrocytes under all culture conditions. The rank efficacy for neuronal differentiation was 3-D culture with NGF group > 3-D culture without NGF group > 2-D culture with NGF group > 2-D culture without NGF group. CONCLUSION The results suggest that the combination of chitosan scaffold and NGF exerts a synergistic effect on neuronal differentiation of NSCs, a requirement for successful integration into the damaged central nervous system.