Miracle-dz/UniFAR-FTUs huggingface dataset:
Intranasal Administration of a Therapeutic HIV Vaccine (Vacc-4x) Induces Dose-Dependent Systemic and Mucosal Immune Responses in a Randomized Controlled Trial

Background Vacc-4x, a Gag p24-based therapeutic HIV vaccine, has been shown to reduce viral load set-points after intradermal administration. In this randomized controlled pilot study we investigate intranasal administration of Vacc-4x with Endocine as adjuvant. Methods Safety and immunogenicity were tested in patients on effective ART. They were randomized to low, medium or high dose Vacc-4x or adjuvant alone, administered four times at weekly intervals with no booster. Vacc-4x-specific T cell responses were measured in vitro by proliferation and in vivo by a single DTH skin test at the end of study. Nasal and rectal mucosal secretions were analyzed for Vacc-4x-specific antibodies by ELISA. Immune regulation induced by Vacc-4x was assessed by functional blockade of the regulatory cytokines IL-10 and TGF-β. Results Vacc-4x proliferative T cell responses increased only among the vaccinated (p≤0.031). The low dose group showed the greatest increase in Vacc-4x CD8+T cell responses (p = 0.037) and developed larger DTH (p = 0.005) than the adjuvant group. Rectal (distal) Vacc-4x IgA and IgG antibodies also increased (p = 0.043) in this group. In contrast, the high dose generated higher nasal (local) Vacc-4x IgA (p = 0.028) and serum IgG (p = 0.030) antibodies than the adjuvant. Irrespective of dose, increased Vacc-4x CD4+T cell responses were associated with low proliferation (r = −0.82, p<0.001) and high regulation (r = 0.61, p = 0.010) at baseline. Conclusion Intranasal administration of Vacc-4x with Endocine was safe and induced dose-dependent vaccine-specific T cell responses and both mucosal and systemic humoral responses. The clinical significance of dose, immune regulation and mucosal immunity warrants further investigation. Trial Registration ClinicalTrials.gov NCT01473810
Characterization of melanocortin-1 receptor gene variants in uveal melanoma patients.

PURPOSE Allelic variations of the melanocortin-1 receptor (MC1R) gene have been linked to red hair and sun-sensitive skin types and may play a role in the susceptibility to develop cutaneous malignant melanoma (CMM). To define the role of MC1R gene in uveal melanoma, a case control study was performed, in which the presence of MC1R gene variations in uveal melanoma patients was compared with that of healthy controls. METHODS MC1R gene variants were analyzed in 162 uveal melanoma patients and 255 healthy controls. After genomic DNA was isolated from venous blood, the MC1R gene was amplified by polymerase chain reaction (PCR) and examined for the presence of variants by single-strand conformation polymorphism (SSCP) analysis. Participants were asked to complete a questionnaire regarding skin type, eye color, and hair color. RESULTS No disparity was found between the distribution of the MC1R gene variants in both groups. Furthermore, no associations between MC1R genotype and pigment phenotype were found. In contrast to CMM, uveal melanoma patients did not show specific MC1R gene variants. Compared with controls, most uveal melanoma patients had blue eyes (65%, P = 0.060) and skin type III (56%); however, in the uveal melanoma group the presence of dark blond hair was significantly elevated (46%, P = 0.030). These findings are in contrast with studies on CMM, where most patients have skin type II and red/fair hair. CONCLUSIONS These data suggest that MC1R variants do not play a role in the susceptibility to develop uveal melanoma. Furthermore, most uveal melanoma patients share phenotypic characteristics that differ from findings in CMM patients.
Affective Computing and the Impact of Gender and Age

Affective computing aims at the detection of users’ mental states, in particular, emotions and dispositions during human-computer interactions. Detection can be achieved by measuring multimodal signals, namely, speech, facial expressions and/or psychobiology. Over the past years, one major approach was to identify the best features for each signal using different classification methods. Although this is of high priority, other subject-specific variables should not be neglected. In our study, we analyzed the effect of gender, age, personality and gender roles on the extracted psychobiological features (derived from skin conductance level, facial electromyography and heart rate variability) as well as the influence on the classification results. In an experimental human-computer interaction, five different affective states with picture material from the International Affective Picture System and ULM pictures were induced. A total of 127 subjects participated in the study. Among all potentially influencing variables (gender has been reported to be influential), age was the only variable that correlated significantly with psychobiological responses. In summary, the conducted classification processes resulted in 20% classification accuracy differences according to age and gender, especially when comparing the neutral condition with four other affective states. We suggest taking age and gender specifically into account for future studies in affective computing, as these may lead to an improvement of emotion recognition accuracy.
Dual Band-Notched UWB Antenna Based on Spiral Electromagnetic-Bandgap Structure

An ultra-wideband (UWB) printed monopole antenna with dual band-notched characteristics is proposed. Two spiral electromagnetic-bandgap (EBG) structures placed on the front and back side of the substrate are employed to create two notch bands at 5.2 and 5.8GHz for the lower and upper bands of the wireless local-area network (WLAN), respectively. The notch-frequency can be tuned, and the band width is narrow and adjustable. Furthermore, the spiral EBG structure used in this design are more compact than conventional mushroom-type EBG. Equivalent circuit model is extracted and discussed to explain the operating mechanism of this structure. The proposed antenna has been simulated and measured in both the frequency domain and time domain, good agreement between calculated and experimental results has been achieved.
An Architecture for Wearable, Wireless, Smart Biosensors: The MoteCare Prototype

Part of designing any system requires the development of an architecture on which the system and subsequent implementations are based. The architecture will vary depending on the requirements. For a healthcare monitoring application the researchers developed a four-tiered architecture that consists of the following layers: user interface, process management, database and sensor network. In this paper, the authors present their layered architecture for remote healthcare monitoring of aged and infirm persons and illustrate its advantages by describing their latest prototype which is called MoteCare. They also discuss the direction the researchers intend to take for the development of their fourth prototype, paying particular attention to the use of open source databases, the issue of security in the development of mote sensor networks (MSN) and the advantages of linking such systems with wireless broadband to enable potential users to achieve more mobility options.
Attribute and Case Selection for NN Classifier through Rough Sets and Naturally Inspired Algorithms

Supervised classification is one of the most active research fields in the Artificial Intelligence community. Nearest Neighbor (NN) is one of the simplest and most consistently accurate approaches to supervised classification. The training set preprocessing is essential for obtaining high quality classification results. This paper introduces an attribute and case selection algorithm using a hybrid Rough Set Theory and naturally inspired approach to improve the NN performance. The proposed algorithm deals with mixed and incomplete, as well as imbalanced datasets. Its performance was tested over repository databases, showing high classification accuracy while keeping few cases and attributes.
Harmonizing and Combining Large Datasets - an Application to Firm-Level Patent and Accounting Data

This paper discusses methods for the harmonization and combination of large-scale patent and trademark datasets with each other and other sources of data. Dictionary- and rule-based approaches to the consolidation of applicant names in patent data are presented and shown to have both benefits and drawbacks in isolation. We combine the two methods and develop a set of rules and dictionaries to consolidate European, Patent Cooperation Treaty (PCT) and US patent data with firm accounting data. The resulting data encompass about 131,000 patent applicant names from 46 countries, covering 58.8 percent of EPO applications and 50.6 percent of PCT applications by business organizations during the time period from 1979 to 2008. For US data, the resulting dataset includes around 54,000 assignee names and 51.3 percent of US granted patents during approximately the same time period.
Phase-Based Methods for Segmentation and Registration of Brightfield Microscope Images of Biological Cells

Performing segmentation and registration on images of transparent pha se objects, such as biological cells from brightfield microscope images, is a difficult problem due to the lack of obse rvable intensity contrast and noise. Previous image analysis solutions have used excessive defocusing or physical models to obtain the underlying phase properties. Here, an automatic multimodal registration algorithm and an impr oved cell boundary detection algorithm are proposed. These use local feature properties derived from the onogenic signal, which renders the algorithms invariant to intensity, making them ideal for these images. Validation is shown against manual expert segmentations and alignments.
Shape Based Object Classification for Automated Video Surveillance with Feature Selection

Object classification based on shape features for video surveillance has been a research problem for number of years. The object classification accuracy depends on the type of classifier and the extracted object features used for classification. Excellent classification accuracy can be obtained with an appropriate combination of the extracted features with a particular classifier. In this paper, we propose to use an online feature selection method which gives a good subset of features while the machine learns the classification task and use these selected features for object classification. This paper also explores the impact of different kinds of shape features on the object classification accuracy and the performance of different classifiers in a typical automated video surveillance application.
A Forward Scan based Plane Sweep Algorithm for Parallel Interval Joins

The interval join is a basic operation that finds application in temporal, spatial, and uncertain databases. Although a number of centralized and distributed algorithms have been proposed for the efficient evaluation of interval joins, classic plane sweep approaches have not been considered at their full potential. A recent piece of related work proposes an optimized approach based on plane sweep (PS) for modern hardware, showing that it greatly outperforms previous work. However, this approach depends on the development of a complex data structure and its parallelization has not been adequately studied. In this paper, we explore the applicability of a largely ignored forward scan (FS) based plane sweep algorithm, which is extremely simple to implement. We propose two optimizations of FS that greatly reduce its cost, making it competitive to the state-of-the-art single-threaded PS algorithm while achieving a lower memory footprint. In addition, we show the drawbacks of a previously proposed hash-based partitioning approach for parallel join processing and suggest a domain-based partitioning approach that does not produce duplicate results. Within our approach we propose a novel breakdown of the partition join jobs into a small number of independent mini-join jobs with varying cost and manage to avoid redundant comparisons. Finally, we show how these mini-joins can be scheduled in multiple CPU cores and propose an adaptive domain partitioning, aiming at load balancing. We include an experimental study that demonstrates the efficiency of our optimized FS and the scalability of our parallelization framework.
Philosophie de la précaution

Si l'attitude de prudence definit, en general, le comportement des hommes face a l'incertitude, on peut constater qu'il y a une histoire de la prudence. Ainsi, peut-on observer que, depuis 1804, nos societes ont vu a la fois se succeder et se concurrencer trois grands dispositifs de prudence : le dispositif de responsabilite, a base de faute, qui a domine le XIX e , siecle; le dispositif de solidarite, a base de risque, qui s'est developpe au cours du XX e siecle; un dispositif de surete dont nous assistons a la naissance autour de la reconnaissance du principe de precaution. Un ensemble de faits a la fois sociologiques, juridiques et reglementaires laissent penser que nous sommes les acteurs d'une transformation profonde qui annonce la reformulation de la problematique de la responsabilite
The effects of transformational leadership and personality on employee performance in Nissan Malang mediated by organizational commitment

This research aims to examine and analyze the effect of transformational leadership, personality, and organizational commitment on employee performance in Nissan Malang. This explanatory study uses SEM-PLS method to analyze and test the propose hypotheses and online sobel test to examine the mediation. The result indicate that transformational leadership has no significant effects on organizational commitment and employee performance, and personality and organizational commitment has signifikan effects on employee performance. In addition, personality shows a significant effect on organizational commitment. Further, the relationship between transformational leadership and employee performance are mediated by personality and not by organizational commitment. One of the proposed reasons for the insignificancy is two factors of transformational leadership, inspirational motivation and individualized consideration not implemented optimally in Nissan Malang. This affect to the low of organizational commitment in Nissan Malang.
Self-construal activation and focus of comparison as determinants of assimilation and contrast in social comparisons.

Les recherches sur la comparaison sociale ont montre que les effets de standard de comparaison eleves (versus faibles) sur les auto-evaluations subsequentes dependent de la centration de la comparaison. Alors qu'une comparaison centree sur autrui (i.e., une comparaison d'autrui a soi) entraine une assimilation du soi au standard, une comparaison centree sur soi (i.e., une comparaison de soi a autrui) entraine un contraste par rapport au standard. De plus, des etudes interculturelles ont montre que le point de centration d'une comparaison affecte les comparaisons sociales uniquement chez les membres de cultures individualistes, mais pas chez les membres de cultures collectivistes. Nous suggerons donc que la manipulation du point de centration de la comparaison aura plus d'impact si des connaissances de soi independantes (par opposition a interdependantes) sont accessibles. Apres avoir amorce des connaissances de soi independantes versus interdependantes chez les participants, ces derniers devaient se comparer avec une personne representant un standard de confiance en soi eleve (ou faible). Ils evaluaient ensuite leur propre confiance en soi. Les resultats des etudes anterieures sur la comparaison sociale ont ete repliques uniquement chez les participants amorces avec des connaissances de soi d'independance.
Distributed approximate KNN Graph construction for high dimensional Data

La construction des graphes de plus proches voisins est un probl eme crucial pour nombre d'applications, notamment celles impliquant des algorithmes d'apprentissage et de fouille de donn ees. Bien qu'il existe certain travaux visant a r esoudre le probl eme dans des environnements centralis es, ils en restent n eanmoins limit es en raison du volume croissant des donn ees ainsi que leur dimensionalit e. Dans cet article, nous proposons une m ethode bas ee sur des fonctions de hachage pour la construction des graphes de plus proches voisins. La m ethode propos ee est distribuable et scalable, aussi bien en volume qu'en dimensionalit e. Par ailleurs, l'utilisation d'une nouvelle famille de fonctions de hachage, RMMH, garantit l' equilibe des charges en environnements parall eles et distribu es.
The Minakshisundaram-Pleijel coefficients for the vector-valued heat kernel on compact locally symmetric spaces of negative curvature

We use harmonic analysis on semisimple Lie groups to determine the Minakshisundaram-Pleijel asymptotic expansion for the trace of the heat kernel on natural vector bundles over compact, locally symmetric spaces of strictly negative curvature. Introduction. Let G be a connected, real semisimple Lie group of rank one with finite center. Let G = K* A * N be an Iwasawa decomposition of G and let M be the centralizer of A in K. Denote by g = t ) a @ n the corresponding Iwasawa decomposition of g, the Lie algebra of G. We use the G-invariant Riemannian metric on G/K induced by a1* Bg (a1 is a convenient constant and Bg is the Killing form of g). If (T, VT) is an irreducible representation of K we form the homogeneous vector bundle ET = G X VT -> G/K. There is unique G-invariant connection on ET such that if s is a C cross-section, X E p, a: G -> G/K is the canonical projection and a. designates the differential of a at e (the identity of G), then V ,7 (x)(s) = dt=O s(exp(tX)K). We denote by V2 the connection Laplacian on (ET, V). We consider now a discrete, torsion free subgroup F of G such that F \ G is compact. We give to X = F \ G/K the push down Riemannian metric. Then X is the most general compact locally symmetric space of negative curvature. Also, D = _V2 pushes down to a nonnegative, elliptic differential operator on F \ G x VT--> X. Let {An} = spec(D) be the spectrum of D. As it is well known, e -SD exists and is trace-class for s > 0. Moreover 4T(s) = tr(e sD) e-S? has an asymptotic expansion OT(S) _ Sd/2( E2 ais') as sO i=O (C = 2 dim(G/K)) and the coefficients ai are local Riemannian invariants of X (see [ABP], [BGM], [MS] and [MP]). In this paper we will use harmonic analysis on G Received by the editors May 10, 1978 and, in revised form, March 22, 1979. AMS (MOS) subject classifications (1970). Primary 43A65, 58G99. 'The results of this article are part of the doctoral thesis of the author, written under the direction of Dr. N. R. Wallach at Rutgers University. The author wishes to thank Dr. Wallach for his help and encouragement. Thanks are also due to the referee for useful suggestions. 1980 American Mathematical Society 0002-9947/80/0000-0300/$09.25 1 This content downloaded from 157.55. 39.203 on Thu, 20 Oct 2016 04:09:04 UTC All use subject to http://about.jstor. org/terms
Managing & Analyzing Large Volumes of Dynamic & Diverse Data

This study reviews the topic of big data management in the 21st-century. There are various developments that have facilitated the extensive use of that form of data in different organizations. The most prominent beneficiaries are internet businesses and big companies that used vast volumes of data even before the computational era. The research looks at the definitions of big data and the factors that influence its access and use for different persons around the globe. Most people consider the internet as the most significant source of this data and more specifically on cloud computing and social networking platforms. It requires sufficient and adequate management procedures to achieve the efficient use of the big data. The study revisits some of the conventional methods that companies use to attain this. There are different challenges such as cost and security that limit the use of big data. Despite these problems, there are various benefits that everyone can exploit by implementing it, and they are the focus for most enterprises.
3D Torus ONoC: Topology design, router modeling and adaptive routing algorithm

With the rapid development of electronic products, the high-speed computing and the personal mobile terminal all make greater demands the on-chip performance. Due to the limited bandwidth, the low communication efficiency and the bad scalability, the Network on Chip (NoC) has been unable to satisfy the requirements of the applications above. More recently, the Optical NoC (ONoC) is introduced as an efficient solution. Compared with NoC, ONoC has the higher bandwidth, the lower power consumption and the shorter latency. With the increasing number of IP cores on a single chip, the study of 3-Dimensional (3D) ONoC has already entered the preliminary stage. Thus in this paper, we design a new 3D ONoC topology structure called 3D X-Torus. Next, we design a bidirectional optical router and a vertical optical router for our topology. Finally, we propose the corresponding routing algorithm. Our simulation results demonstrate the performances of our 3D ONoC topology, optical router and routing algorithm.
A greedy decoder for phrase-based statistical machine translation

Most phrase-based statistical machine translation decoders rely on a dynamic programming technique for maximizing a combination of models, including one or several language models and translation tables. One implication of this choice is the design of a scoring function that can be computed incrementally on partial translations, a restriction a search engine using a complete-state formulation does not have. In this paper, we present experiments we conducted with a simple, yet effective greedy search engine. In particular, we show that when seeded with the translations produced by a stateof-the-art beam search decoder, it produces an output of significantly higher quality than the latter taken alone, as measured by automatic metrics.
Biologically Inspired Turn Control for Autonomous Mobile Robots

An exportable and robust system for turn control using only camera images is proposed for path execution in robot navigation. Robot motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames in the image sequence. This information is used to compute the instantaneous rotation angle. Finally, control loop is closed correcting robot displacements when it is requested for a turn command. The proposed system has been successfully tested on the four-legged Sony Aibo robot.
Effect of Spermidine on Misfolding and Interactions of Alpha-Synuclein

Alpha-synuclein (α-Syn) is a 140 aa presynaptic protein which belongs to a group of natively unfolded proteins that are unstructured in aqueous solutions. The aggregation rate of α-Syn is accelerated in the presence of physiological levels of cellular polyamines. Here we applied single molecule AFM force spectroscopy to characterize the effect of spermidine on the very first stages of α-Syn aggregation – misfolding and assembly into dimers. Two α-Syn variants, the wild-type (WT) protein and A30P, were studied. The two protein molecules were covalently immobilized at the C-terminus, one at the AFM tip and the other on the substrate, and intermolecular interactions between the two molecules were measured by multiple approach-retraction cycles. At conditions close to physiological ones at which α-Syn misfolding is a rare event, the addition of spermidine leads to a dramatic increase in the propensity of the WT and mutant proteins to misfold. Importantly, misfolding is characterized by a set of conformations, and A30P changes the misfolding pattern as well as the strength of the intermolecular interactions. Together with the fact that spermidine facilitates late stages of α-Syn aggregation, our data demonstrate that spermidine promotes the very early stages of protein aggregation including α-Syn misfolding and dimerization. This finding suggests that increased levels of spermidine and potentially other polyamines can initiate the disease-related process of α-Syn.