Miracle-dz/UniFAR-FTUs huggingface dataset:
The Type of Responder T-Cell Has a Significant Impact in a Human In Vitro Suppression Assay

Background In type 1 diabetes (T1D), a prototypic autoimmune disease, effector T cells destroy beta cells. Normally, CD4+CD25+high, or natural regulatory T cells (Tregs), counter this assault. In autoimmunity, the failure to suppress CD4+CD25low T cells is important for disease development. However, both Treg dysfunction and hyperactive responder T-cell proliferation contribute to disease. Methods/Principal Findings We investigated human CD4+CD25low T cells and compared them to CD4+CD25- T cells in otherwise equivalent in vitro proliferative conditions. We then asked whether these differences in suppression are exacerbated in T1D. In both single and co-culture with Tregs, the CD4+CD25low T cells divided more rapidly than CD4+CD25- T cells, which manifests as increased proliferation/reduced suppression. Time-course experiments showed that this difference could be explained by higher IL-2 production from CD4+CD25low compared to CD4+CD25- T cells. There was also a significant increase in CD4+CD25low T-cell proliferation compared to CD4+CD25- T cells during suppression assays from RO T1D and at-risk subjects (n = 28, p = 0.015 and p = 0.024 respectively). Conclusions/Significance The in vitro dual suppression assays proposed here could highlight the impaired sensitivity of certain responder T cells to the suppressive effect of Tregs in human autoimmune diseases.
E-Learning Process Characterization using data driven approaches

This paper summarizes the outcomes of different data driven analyses. The data used are authentic data coming from an European E- Learning Project. The paper is aimed at presenting the approaches used for learners' profiles characterization. Learners' profiles characterization is here intended with respect to the learning strategies used by learners from one side; from the other, with respect to different ways of non linear navigation. In both cases the focus is on the effectiveness of data driven approaches in detecting individual differences. It is shown that, in both cases, data driven approaches are able to detect such individual differences. Therefore, it can be concluded that data driven approaches are effective for learners' profiling, and that their employment can be beneficial for improving personalization of learning environments.
Massive Binary Black Holes in the Cosmic Landscape

Binary black holes occupy a special place in our quest for understanding the evolution of galaxies along cosmic history. If massive black holes grow at the center of (pre-)galactic structures that experience a sequence of merger episodes, then dual black holes form as inescapable outcome of galaxy assembly. But, if the black holes reach coalescence, then they become the loudest sources of gravitational waves ever in the universe. Nature seems to provide a pathway for the formation of these exotic binaries, and a number of key questions need to be addressed: How do massive black holes pair in a merger? Depending on the properties of the underlying galaxies, do black holes always form a close Keplerian binary? If a binary forms, does hardening proceed down to the domain controlled by gravitational wave back reaction? What is the role played by gas and/or stars in braking the black holes, and on which timescale does coalescence occur? Can the black holes accrete on flight and shine during their pathway to coalescence? N-Body/hydrodynamical codes have proven to be vital tools for studying their evolution, and progress in this field is expected to grow rapidly in the effort to describe, in full realism, the physics of stars and gas around the black holes, starting from the cosmological large scale of a merger. If detected in the new window provided by the upcoming gravitational wave experiments, binary black holes will provide a deep view into the process of hierarchical clustering which is at the heart of the current paradigm of galaxy formation. They will also be exquisite probes for testing General Relativity, as the theory of gravity. The waveforms emitted during the inspiral, coalescence and ring-down phase carry in their shape the sign of a dynamically evolving space-time and the proof of the existence of an horizon.
AdTorrent: Digital Billboards for Vehicular Networks

Advertisements, are the most important source of revenue for some of the biggest Internet-based companies. With vehicular networks poised to become part of the Internet in the near future, this new “edge” of the Internet represents a new frontier that companies will be striving to reach. In this paper we investigate the feasibility of targeted dissemination of ad content in a car network. We present Digital Billboards, a scalable “push” model architecture for ad content delivery. We then propose, AdTorrent, an integrated system for search, ranking and content delivery in this architecture. We evaluate our design using a realistic vehicular mobility model which captures mobility characteristics such as temporal and spatial dependencies and geographic restrictions.
Pathways of Renal Fibrosis and Modulation of Matrix Turnover in Experimental Hypercholesterolemia

Dyslipidemia often accompanies and accelerates renal disease, partly by promoting fibrosis. However, the mechanisms mediating this effect are unclear. We hypothesized that hypercholesterolemia modulates several interlinked pathways that promote deposition and blunt degradation of extracellular matrix, and that these could be manipulated by reversal of hypercholesterolemia. Fourteen pigs were fed a 16-week 2% high-cholesterol diet (HC-HC; n=7) or normal diet (n=7), whereas in 7 others, a 10-week HC was followed by a 6-week normal diet (HC-N). Renal endothelial function was assessed in vivo with electron-beam computed tomography, and renal tissue was then studied ex vivo using Western blot, real-time quantitative polymerase chain reaction, gelatin zymography, and immunostaining. HC-HC kidneys showed endothelial dysfunction, accompanied by increased intrarenal oxidative stress, inflammation, activation of the endothelin and transforming-growth factor-&bgr; systems, and decreased matrix metalloproteinase expression and activity. Accordingly, HC-HC kidneys showed increased collagen IV expression and fibrosis. A lipid-lowering dietary intervention reversed most of these changes. In conclusion, this study indicates that renal fibrosis in early atherosclerosis is a result of a simultaneous increase in extracellular matrix deposition and blunted matrix metalloproteinase–mediated degradation, overall promoting perivascular and tubulointerstitial fibrosis. Notably, many of these pathways may be reversible in hypercholesterolemia, and crucial targets could potentially be identified for early interventions to preserve the kidney.
Micromechanical analysis of fully coupled electro-magneto-thermo-elastic multiphase composites

A homogenization micromechanical method is employed for the prediction of the effective moduli of electro-magneto-thermo-elastic composites. These include the effective elastic, piezoelectric, piezomagnetic, dielectric, magnetic permeability and electromagnetic coupling moduli, as well as the effective thermal expansion coefficients and the associated pyroelectric and pyromagnetic constants. Comparisons between the present homogenization theory, the generalized method of cells and the Mori-Tanaka predictions are given. Results are presented for fibrous and periodically bilaminated composites.
The undue influence of significant p-values on the perceived importance of study results

Background Statistically significant differences between treatments (i.e., results typically associated with p < 0.05) may not always correspond to important differences upon which to base orthopedic practice. If the hypothesis that p < 0.05 unduly influences the perception of importance of study results were true, we would expect that presenting such a p-value would lead to 1) greater agreement among clinicians about the importance of a study result, and 2) greater perceived importance of a study result, when compared with presenting the same results omitting the p-value. Methods The participants were 3 orthopedics residents, 5 fellows, and 4 attending orthopedic surgeons at a university hospital. We constructed a 40-item questionnaire with the comparison groups, primary outcome of interest, and the results from each of 40 studies. These studies represent a variety of interventions across orthopedic surgery assessed in 2-group comparative intervention studies (randomized trials, observational studies) and were published between 2000 and 2002 in the Journal of Bone and Joint Surgery-American Volume. For each question, respondents were asked to rate the importance of the study results. Participants answered the questionnaire first without p-values and then, 8 weeks later, with p-values (and a random sample of items without p-values). An intra-class correlation quantified agreement between clinicians when answering items with and without p-values. The difference in mean importance scores between the two presentations was also estimated. Results Of 40 eligible clinical comparative studies, 30 reported p < 0.05 for their primary comparison. Without presenting p-values, overall agreement regarding clinical significance among reviewers was fair (ICC = 0.35, 95% CI: 0.25–0.49). In the 30 studies with p < 0.05, mean importance scores (1 = low; 3 = high) were greater when p-values were presented (difference 0.6, CI 0.1–1.1). 10 of 12 reviewers perceived results to be more important when presented with significant p-values. Interpretation When significant, p-values unduly influence the perception of clinicians regarding the importance of study results.
Identification of Downstream Components of Ubiquitin-Conjugating Enzyme PHOSPHATE2 by Quantitative Membrane Proteomics in Arabidopsis Roots[W][OPEN]

This work reports quantitative membrane proteomic analysis and provides insights into the mechanism of PHO2-mediated Pi acquisition via posttranslational regulation of PHT1s. The results highlight the fundamental role of PHO2 in orchestrating Pi acquisition at the root surface and Pi loading at the xylem of root stele to maintain Pi homeostasis. MicroRNA399-mediated regulation of the ubiquitin-conjugating enzyme UBC24/PHOSPHATE2 (PHO2) is crucial for Pi acquisition and translocation in plants. Because of a potential role for PHO2 in protein degradation and its association with membranes, an iTRAQ (for isobaric tags for relative and absolute quantitation)- based quantitative membrane proteomic method was employed to search for components downstream of PHO2. A total of 7491 proteins were identified from Arabidopsis thaliana roots by mass spectrometry, 35.2% of which were predicted to contain at least one transmembrane helix. Among the quantifiable proteins, five were significantly differentially expressed between the wild type and pho2 mutant under two growth conditions. Using immunoblot analysis, we validated the upregulation of several members in PHOSPHATE TRANSPORTER1 (PHT1) family and PHOSPHATE TRANSPORTER TRAFFIC FACILITATOR1 (PHF1) in pho2 and demonstrated that PHO2 mediates the degradation of PHT1 proteins. Genetic evidence that loss of PHF1 or PHT1;1 alleviated Pi toxicity in pho2 further suggests that they play roles as downstream components of PHO2. Moreover, we showed that PHO2 interacts with PHT1s in the postendoplasmic reticulum compartments and mediates the ubiquitination of endomembrane-localized PHT1;1. This study not only uncovers a mechanism by which PHO2 modulates Pi acquisition by regulating the abundance of PHT1s in the secretory pathway destined for plasma membranes, but also provides a database of the membrane proteome that will be widely applicable in root biology research.
Extraction of commonsense knowledge for “Bring something” robotic service at home

Sharing commonsense knowledge is one key to realize symbiosis between human and robot. However, as human knowledge is so complicated, it is difficult to extract appropriate information for robot. This paper presents our approach to extract the core part from Basic-level Knowledge Network (BKN) to be used for intuitive “Bring something” robotic service. A two-step filtering method was implemented based on the weighting mechanism of BKN. The first step used one weighting parameter to filter the most irrelevant data. The second step combined all weighting parameters from BKN with user response data from a questionnaire to estimate commoness of object-activity connections. Result showed that the proposed approach is efficient to extract the most common activities related to each object in BKN, therefore to help robot understands human intention and provide intuitive service.
Differential Response of Period 1 Expression within the Suprachiasmatic Nucleus

The suprachiasmatic nuclei (SCNs) of the hypothalamus contain a circadian clock that exerts profound control over rhythmic physiology and behavior. The clock consists of multiple autonomous cellular pacemakers distributed throughout the rat SCN. In response to a shift in the light schedule, the SCN rapidly changes phase to achieve the appropriate phase relationship with the shifted light schedule. Through use of a transgenic rat in which rhythmicity in transcription of the Period 1 gene was measured with a luciferase reporter (Per1-luc), we have been successful in tracking the time course of molecular rhythm phase readjustments in different regions of the SCN that occur in response to a shift in the light schedule. We find that different regions of the SCN phase adjust at different rates, leading to transient internal desynchrony in Per1-luc expression among SCN regions. This desynchrony among regions is most pronounced and prolonged when the light schedule is advanced compared with light schedule delays. A similar asymmetry in the speed of phase resetting is observed with locomotor behavior, suggesting that phase shifting kinetics within the SCN may underlay the differences observed in behavioral resetting to advances or delays in the light schedule.
Revealing skype traffic: when randomness plays with you

Skype is a very popular VoIP software which has recently attracted the attention of the research community and network operators. Following a closed source and proprietary design, Skype protocols and algorithms are unknown. Moreover, strong encryption mechanisms are adopted by Skype, making it very difficult to even glimpse its presence from a traffic aggregate. In this paper, we propose a framework based on two complementary techniques to reveal Skypetraffic in real time. The first approach, based on Pearson'sChi-Square test and agnostic to VoIP-related trafficcharacteristics, is used to detect Skype's fingerprint from the packet framing structure, exploiting the randomness introduced at the bit level by the encryption process. Conversely, the second approach is based on a stochastic characterization of Skype traffic in terms of packet arrival rate and packet length, which are used as features of a decision process based on Naive Bayesian Classifiers.In order to assess the effectiveness of the above techniques, we develop an off-line cross-checking heuristic based on deep-packet inspection and flow correlation, which is interesting per se. This heuristic allows us to quantify the amount of false negatives and false positives gathered by means of the two proposed approaches: results obtained from measurements in different networks show that the technique is very effective in identifying Skype traffic. While both Bayesian classifier and packet inspection techniques are commonly used, the idea of leveraging on randomness to reveal traffic is novel. We adopt this to identify Skype traffic, but the same methodology can be applied to other classification problems as well.
Nanostructured surfaces for dramatic reduction of flow resistance in droplet-based microfluidics

This paper reports a dramatic reduction of liquid droplet flow resistance by engineering the surfaces into nanomechanical hydrophobic structures that show a contact angle over 175/spl deg/. Flow resistances of droplets on open surfaces as well as in confined microchannels (between surfaces) have been measured with significant reduction of flow resistance (over 99% and over 95%, respectively) compared with a surface of the same material.
Residual stress analysis for oxide thin film deposition on flexible substrate using finite element method

Residual or internal stresses directly affect a variety of phenomena including adhesion, generation of crystalline defects, perfection of epitaxial layers and formation of film surface growths such as hillocks and whiskers. Sputtering oxide films with high density promote high compressive stress, and it offers researchers a reference if the value of residual stress could be analyzed directly. Since, the study of residual stress of SiO2 and Nb2O5 thin film deposited by DC magnetron sputtered on hard substrate (BK7) and flexible substrate (PET and PC). A finite element method (FEM) with an equivalent-reference-temperature (ERT) technique had been proposed and used to model and evaluate the intrinsic strains of layered structures. The research has improved the equivalent reference temperature (ERT) technique of the simulation of intrinsic strain for oxygen film. The results have also generalized two models connecting to the lattice volume to predict the residual stress of hard substrate and flexible substrate with error of 3% and 6%, respectively.
Visual summary of egocentric photostreams by representative keyframes

Building a visual summary from an egocentric photostream captured by a lifelogging wearable camera is of high interest for different applications (e.g. memory reinforcement). In this paper, we propose a new summarization method based on keyframes selection that uses visual features extracted by means of a convolutional neural network. Our method applies an unsupervised clustering for dividing the photostreams into events, and finally extracts the most relevant keyframe for each event. We assess the results by applying a blind-taste test on a group of 20 people who assessed the quality of the summaries.
Quantum Transport Simulations of InGaAs HEMTs: Influence of Mass Variations on the Device Performance

This paper presents a simulation work of In0.7Ga0. 3As HEMT devices for logic applications using a quantum ballistic 2D simulator based on the non-equilibrium Green's function (NEGF) approach coupled to a 2D Poisson for the electrostatics. In a previous study, we showed that In0.7Ga0. 3As short channel HEMT devices operates close to the ballistic limit and can be modeled as a ballistic channel attached to two series resistances. Since the electronic structure of the quantized channel is not known precisely, or can be altered by strain fields, in this work, we quantify our results, by investigating the variation in device performance due to variations in the effective mass values. We conclude that for these devices, variations in the electronic structure do not impact the device performance significantly. The results also provide insight into the expected effect of strain on the performance due to mass variations.
On using human movement invariants to generate target-driven anthropomorphic locomotion

We present a method for generating anthropomorphic motion by studying ‘invariants’ in human movements and applying them as kinematic tasks. We recorded whole-body motion of 14 participants during a walking and grasping task and performed a detailed analysis in order to synthesize the stereotypy in human motion as rules. We propose an algorithm that produces the key parameters of motion taking into account the knowledge from human movement, and the limitations of the anthropomorph. We generalize our results such that we can create motion parameters for objects which were not in the original protocol. The algorithmic output is applied in a task based prioritized inverse kinematics solver to generate dynamically stable and realistic anthropomorphic motion. We illustrate our results on the humanoid HRP-2 by making it walk to and grasp objects at various positions.
The performance of some meta-heuristics in continuous problems studied according to the location of the optima in the search space

Many hard optimization problems can only be effectively handled by meta-heuristic methods. Some continuous optimization problems have specifi c characteristics that demand a particular interest. These features include the location of the optima in a specifi c region of search space. Hence the main goal of this paper is assessing the performance of some outstanding population-based meta-heuristics on functions with optima on bounds and problems with optima off bounds. It is studied by taking a set of benchmark functions from the fi eld of optimization as a point of departure.
Digital holographic microscopy

A traditional microscope is not capable of imaging phase object or three dimensional object. Computational Microscopy is proposed to address these two limitations. In Computational Microscopy, the sample is under coherent illumination and the intensities of the diffracted light are recorded by a detector system (CCD camera in most cases). The recorded information is then numerically processed by computer to retrieve the complex field scattered by the object from which the quantitative properties of the object are reconstructed. Three dimensional imaging via Computational Microscopy is performed by illuminating the semi-transparent object from multiple directions and solving the inverse scattering problem via techniques of Optical Diffraction Tomography(ODT). Digital holographic microscopy(DHM) discussed in this thesis is a synthetic implementation of the Computational Microscopy and employs phase-shifting digital holography for phase retrieval. Different experimental schemes were tested and three numerical back-propagation methods were implemented for back-propagating the complex wave from measurement plane to near field. The most emphasized part of the thesis is the research in the algorithms for ODT. An inverse scattering algorithm based on distorted wave approximation for the geometry of ODT is introduced. We implement the algorithm to two Optical Diffraction Tomography configurations: free space and cylindrical symmetric background. For free space case both near field and far field inverse scattering problems are studied. For cylindrical symmetric background inverse scattering based on Distorted Wave Born Approximation and Distorted Wave Rytov Approximation are discussed and compared via computer simulation. In addition, an inverse scattering algorithm based on ray tracing is derived based on the similar idea. Experimental results are presented in which we have successfully reconstructed transmission functions of 2D semi-transparent objects and refractive index profile of a step index optical fiber.
The role of agriculture growth in reducing poverty and hunger: The case of Tanzania

Although Sub-Saharan Africa experienced unprecedented economic growth in recent decades, this did not always translate into less poverty or improved nutrition. The Tanzanian economy is one example of a country that failed to reap the benefits of sustained rapid growth. National gross domestic product (GDP) grew at 6.6 percent per year during 1998â€“2007, while agricultural growth, often regarded as instrumental in lowering poverty rates in agrarian-based developing countries, averaged a respectable 4.4 percent during the period. Yet, between 2001 and 2007, Tanzaniaâ€™s poverty rate only fell from 35.7 to 33.6 percent, while the share of the population consuming insufficient calories declined marginally from 25.0 to 23.6 percent.