Miracle-dz/UniFAR-FTUs huggingface dataset:
Institutional Repository The e ect of 14 weeks of vitamin D 3 supplementation on antimicrobial peptides and proteins in athletes

Heavy training is associated with increased respiratory infection risk and antimicrobial proteins are important in defence against oral and respiratory tract infections. We examined the effect of 14 weeks of vitamin D3 supplementation (5000 IU/day) on the resting plasma cathelicidin concentration and the salivary secretion rates of secretory immunoglobulin A (SIgA), cathelicidin, lactoferrin and lysozyme in athletes during a winter training period. Blood and saliva were obtained at the start of the study from 39 healthy men who were randomly allocated to vitamin D3 supplement or placebo. Blood samples were also collected at the end of the study; saliva samples were collected after 7 and 14 weeks. Plasma total 25(OH)D concentration increased by 130% in the vitamin D3 group and decreased by 43% in the placebo group (both P=0.001). The percentage change of plasma cathelicidin concentration in the vitamin D3 group was higher than in the placebo group (P=0.025). Only in the vitamin D3 group, the saliva SIgA and cathelicidin secretion rates increased over time (both P=0.03). A daily 5000 IU vitamin D3 supplement has a beneficial effect in upregulating the expression of SIgA and cathelicidin in athletes during a winter training period which could improve resistance to respiratory infections.
Hybrid blind deconvolution of images using variable splitting and proximal point methods

The problem of blind deconvolution of digital images has long been recognized as one of the central problems in imaging science. In this paper, the problem is solved using a hybrid deconvolution approach. Here, the “hybridization” suggests a two-stage reconstruction procedure. In the first stage, some partial information about the point spread function of the imaging system (namely, its magnitude spectrum) is recovered. Subsequently, the obtained information is exploited to explicitly constrain the procedure of inverse filtering. The latter is realized in the form of an optimization problem which is solved using alternating direction method of multipliers (ADMM). We show that this method leads to a particularly efficient numerical scheme, which can be implemented as a succession of analytically computable proximity operations. The effectiveness of the proposed deconvolution procedure is exemplified by a number of computer experiments.
TINA: A Natural Language System for Spoken Language Applications

A new natural language system, TINA, has been developed for applications involving spoken language tasks. TINA integrates key ideas from context free grammars, Augmented Transition Networks (ATN's), and the unification concept. TINA provides a seamless interface between syntactic and semantic analysis, and also produces a highly constraining probabilistic language model to improve recognition performance. An initial set of context-free rewrite rules provided by hand is first converted to a network structure. Probability assignments on all arcs in the network are obtained automatically from a set of example sentences. The parser uses a stack decoding search strategy, with a top-down control flow, and includes a feature-passing mechanism to deal with long-distance movement, agreement, and semantic constraints. TINA provides an automatic sentence generation capability that has been effective for identifying overgeneralization problems as well as in producing a word-pair language model for a recognizer. The parser is currently integrated with MIT's SUMMIT recognizer for use in two application domains, with the parser screening recognizer outputs either at the sentential level or to filter partial theories during the active search process.
An assessment of the validity of SOFA score based triage in H1N1 critically ill patients during an influenza pandemic

Sequential Organ Failure Assessment (SOFA) score based triage of influenza A H1N1 critically ill patients has been proposed for surge capacity management as a guide for clinical decision making. We conducted a retrospective records review and SOFA scoring of critically ill patients with influenza A H1N1 in a mixed medical‐surgical intensive care unit in an urban hospital. Eight critically ill patients with influenza A H1N1 were admitted to the intensive care unit. Their mean (range) age was 39 (26–52) years with a length of stay of 11 (3–17) days. All patients met SOFA score based triage admission criteria with a modal SOFA score of five. Five patients required invasive ventilation for a mean (range) of 5 (4–11) days. Five patients would have been considered for withdrawal of treatment using SOFA scoring guidelines at 48 h. All patients survived. We conclude that SOFA score based triage could lead to withdrawal of life support in critically ill patients who could survive with an acceptably low length of stay in the intensive care unit.
Cooperative Evolutionary Learning of Linguistic Fuzzy Rules and Parametric Aggregation Connectors for Mamdani Fuzzy Systems

There are two tasks in the design of linguistic fuzzy models for a concrete application: The derivation of the linguistic rule base and the setup of the inference system and the defuzzification method. Traditionally, the derivation of the linguistic rule base has been considered the most important task, but the use of the appropriate aggregation connectors in the inference system and the defuzzification interface can improve the fuzzy system behavior. In this paper, we take in consideration this idea, we propose an evolutionary learning method to learn a linguistic rule base and the parametric aggregation connectors of the inference and defuzzification in a single step. The aim of this methodology is to make possible a high level of positive synergy between the linguistic rule base and the aggregation connectors, improving the accuracy of the linguistic Mamdani fuzzy systems. Our proposal has shown good results solving three different applications. We introduce a statistical analysis of results for validating the model behavior on the applications used in the experimental study. We must remark that we present an experimental study with a double intention: (a) to compare the behavior of the new approach in comparison with those ones that first learn the rule base and then adapt the connectors, and (b) to analyze the rule bases obtained with fixed aggregation connectors and with the adaptive ones for showing the changes on the consequent rules, changes on labels that produce a better behavior of the linguistic model than the classic ones.
Stability of sampled-data control systems with uncertain delays

Standard analysis and synthesis techniques for digital control systems assume that the total time-delay in the feedback loop is negligible or precisely known. This might not be the case in some applications. Such systems are quite common in industry, especially due to strong trends towards networking. Under certain circumstances the network-induced delays can be considered constant, and yet it might be very difficult to get an exact value of the time-delay. The delay then enters the description of the system as an uncertain parameter which is only known to be bounded by some extreme values. It is then possible to apply some convenient results of parametric robust control theory to test the stability of such systems. Polynomial description of SISO systems is considered. Possible extension to the more realistic case of varying delays is only outlined.
Decentralized optimal frequency control of interconnected power systems with transient constraints

We design decentralized frequency control of multi-area power systems that will re-balance power and drive frequencies to their nominal values after a disturbance. Both generators and controllable loads are utilized to achieve frequency stability while minimizing regulation cost. In contrast to recent results, the design is completely decentralized and does not require communication between areas. Our control enforces operational constraints not only in equilibrium but also during transient. Moreover, our control is capable of adapting to unknown load disturbance. We show that the closed-loop system is asymptotically stable and converges to an equilibrium that minimizes the regulation cost. We present simulation results to demonstrate the effectiveness of our design.
Expression of an idiotype (Id-460) during in vivo anti-dinitrophenyl antibody responses. II. Transient idiotypic dominance

After immunization of mice with 2,4-dinitrophenyl-ovalbumin (DNP-OVA), it was shown previously that strains having Igh-Va genes and able to express light chains of the Vk1 group produce high levels of anti-DNP antibody bearing an idiotype (Id-460) associated with the combining site of the BALB/c DNP-binding myeloma protein MOPC 460. Expression of Id-460 in serum is transient; Id-460 levels peak early in the response and are regulated independently of total anti-DNP antibody. In this paper, the transient dominance of Id-460 expression has been confirmed at the cellular level by inhibition of splenic anti-DNP plaque-forming cells (PFC) with rabbit anti-Id-460 antiserum. Id-460+ PFC can account for 52-91% of anti-DNP PFC early after secondary challenge with DNP- OVA. Furthermore, Id-460 is represented at these high levels in IgM, IgG, and IgG1, and IgG2a, the three isotypes tested in the PFC assay, as well as in IgE, as tested by passive cutaneous anaphylaxis. Thus, there is no preferential association of Id-460 with a given isotype. We conclude from these studies that Id-460 is a dominant idiotype in the anti-DNP antibody response of BALB/c mice to DNP-OVA. This dominance is expressed transiently and is independent of isotype. A further conclusion from these studies is that regulation of isotype expression is independent of the regulation of idiotype expression in this system. We would suggest that regulation of Id-460 expression involves Ig- dependent helper T cells specific for Id-460 that induce Id-460+ B cells and also activate suppressor T cells, both events occurring via idiotype-anti-idiotype interactions.
Effects of anticipatory action on human-robot teamwork: Efficiency, fluency, and perception of team

A crucial skill for fluent action meshing in human team activity is a learned and calculated selection of anticipatory actions. We believe that the same holds for robotic team-mates, if they are to perform in a similarly fluent manner with their human counterparts. In this work, we propose an adaptive action selection mechanism for a robotic teammate, making anticipatory decisions based on the confidence of their validity and their relative risk. We predict an improvement in task efficiency and fluency compared to a purely reactive process. We then present results from a study involving untrained human subjects working with a simulated version of a robot using our system. We show a significant improvement in best-case task efficiency when compared to a group of users working with a reactive agent, as well as a significant difference in the perceived commitment of the robot to the team and its contribution to the team's fluency and success. By way of explanation, we propose a number of fluency metrics that differ significantly between the two study groups.
Towards the logic defect diagnosis for partial-scan designs

Local defect diagnosis is a critical yet challenging process in VLSI manufacturing. It involves the identification of the defect spots in a logic IC that fail testing. In the last decade, algorithms for diagnosis have progressed significantly and the results are showing promise for full-scan designs. In this paper, we first review several classical algorithms such as fault dictionary based analysis and effect cause analysis. Then, we discuss several diagnosis algorithms borrowed from the design debugging techniques. These algorithms do not require a pre-determined fault model, and thus, are more flexible and applicable to ICs in which the defects do not behave like common stuck-at or bridging faults. Finally, we will probe the possibility of extending these algorithms to designs with only partial-scan support.
Achieve the Degrees of Freedom of K-User MIMO Interference Channel with a MIMO Relay

This paper investigates the problem of achieving the degrees of freedom (DoF) of a K-user multiple-input-multipleoutput (MIMO) interference channel with a MIMO relay, where each transmitter and receiver is equipped with M antennas. We propose a two-hop relay aided transmission scheme based on the idea of interference alignment to achieve the full DoF KM/2. The scheme requires global channel state information (CSI) at the MIMO relay only while other nodes only need to have their local CSI. We also study the number of antennas needed at the MIMO relay to achieve interference alignment. In particular, we find that using just linear processing at the relay, the minimum number of antennas needed at the relay for each transmitter-receiver pair to achieve the maximum M/2 DoF per channel use is (K-1)M, less than what is needed for decode-and-forward approach and all other reported approaches in existing literatures.
Antibody-Mediated Neutralization of Human Rhinovirus 14 Explored by Means of Cryoelectron Microscopy and X-Ray Crystallography of Virus-Fab Complexes

ABSTRACT The structures of three different human rhinovirus 14 (HRV14)-Fab complexes have been explored with X-ray crystallography and cryoelectron microscopy procedures. All three antibodies bind to the NIm-IA site of HRV14, which is the β-B–β-C loop of the viral capsid protein VP1. Two antibodies, Fab17-IA (Fab17) and Fab12-IA (Fab12), bind bivalently to the virion surface and strongly neutralize viral infectivity whereas Fab1-IA (Fab1) strongly aggregates and weakly neutralizes virions. The structures of the two classes of virion-Fab complexes clearly differ and correlate with observed binding neutralization differences. Fab17 and Fab12 bind in essentially identical, tangential orientations to the viral surface, which favors bidentate binding over icosahedral twofold axes. Fab1 binds in a more radial orientation that makes bidentate binding unlikely. Although the binding orientations of these two antibody groups differ, nearly identical charge interactions occur at all paratope-epitope interfaces. Nucleotide sequence comparisons suggest that Fab17 and Fab12 are from the same progenitor cell and that some of the differing residues contact the south wall of the receptor binding canyon that encircles each of the icosahedral fivefold vertices. All of the antibodies contact a significant proportion of the canyon region and directly overlap much of the receptor (intercellular adhesion molecule 1 [ICAM-1]) binding site. Fab1, however, does not contact the same residues on the upper south wall (the side facing away from fivefold axes) at the receptor binding region as do Fab12 and Fab17. All three antibodies cause some stabilization of HRV14 against pH-induced inactivation; thus, stabilization may be mediated by invariant contacts with the canyon.
Differential Healing Activities of CD34+ and CD14+ Endothelial Cell Progenitors

Objective—Peripheral blood contains primitive (stem cell-like) and monocytic-like endothelial cell progenitors. Diabetes apparently converts these primitive progenitors, from a pro-angiogenic to anti-angiogenic phenotype. Monocytic progenitors seem to be less affected by diabetes, but potential pro-angiogenic activities of freshly isolated monocytic progenitors remain unexplored. We compared the ability of primitive and monocytic endothelial cell progenitors to stimulate vascular growth and healing in diabetes and investigated potential molecular mechanisms through which the cells mediate their in vivo effects. Methods and Results—Human CD34+ primitive progenitors and CD14+ monocytic progenitors were injected locally into the ischemic limbs of diabetic mice. CD14+ cell therapy improved healing and vessel growth, although not as rapidly or effectively as CD34+ cell treatment. Western blot analysis revealed that cell therapy modulated expression of molecules in the VEGF, MCP-1, and angiopoietin pathways. Conclusions—Injection of freshly isolated circulating CD14+ cells improves healing and vascular growth indicating their potential for use in acute clinical settings. Importantly, CD14+ cells could provide a therapeutic option for people with diabetes, the function of whose CD34+ cells may be compromised. At least some progenitor-induced healing probably is mediated through increased sensitivity to VEGF and increases in MCP-1, and possibly modulation of angiopoietins.
Rational Transductions for Phonetic Conversion and Phonology

Phonetic conversion, and other conversion problems related to phonetics, can be performed by finite-state tools. This chapter presents a finite-state conversion system, BiPho, based on tranducers and bimachines. The linguistic data used by this system are described in a readable format and actual computation is efficient. The system constitutes a spelling-to-phonetics conversion system for French.
A Community-based Expert Finding System

This paper proposes a system to facilitate exchange of information by automatically ﬁnding experts, competent in answering a given question. Our objective is to provide an online tool, which enables individuals within a potentially large organization to search for experts in a certain area, which may not be represented in company organization or reporting lines. The advantage of the proposed system over standard forums or other group-ware systems is that full-formatted questions can automatically be compared with stored qualiﬁcation proﬁles, which were automatically derived from documents and possibly reﬁned manually. This allows to ﬁnd competent colleagues (or helpful literature such as how-tos) for a given problem in a single step, and without intermediate iterations. The system is symmetric in that it does not distinguish between “questioners” (asking questions) and “experts” (answering them), therefore forming a “community” of users, which are distributed over an ontology covering the total knowledge. This ontology can either be given (i.e. in the form of an organizational chart), or it can be derived from the experts’ knowledge.
The Influence of Phase Change Materials on the Properties of Self-Compacting Concrete

The aim of this paper is to research new thermally-efficient concrete walls, analyzing the mechanical behavior of a self-compacting concrete to manufacture an uncoated solid structural panel, with the incorporation of a micro-encapsulated phase change material as additive. Different dosages are tested and mechanical properties of the product obtained from the molding of concrete specimens are evaluated, testing mechanical compressive strength, slump flow, and density. The results reveal the optimum percentage of additive in the mixture that enables compliance with the technical specifications required by the product to be manufactured. A test is also performed for measuring the thermal conductivity for the optimal sample obtained and it evidences the reduction thereof.
3-D Lookup: Fast Protein Structure Database Searches at 90% Reliability

There are far fewer classes of three-dimensional protein folds than sequence families but the problem of detecting three-dimensional similarities is NP-complete. We present a novel heuristic for identifying 3-D similarities between a query structure and the database of known protein structures. Many methods for structure alignment use a bottom-up approach, identifying first local matches and then solving a combinatorial problem in building up larger clusters of matching substructures. Here, the top-down approach is to start with the global comparison and select a rough superimposition using a fast 3-D lookup of secondary structure motifs. The superimposition is then extended to an alignment of C alpha atoms by an iterative dynamic programming step. An all-against-all comparison of 385 representative proteins (150,000 pair comparisons) took 1 day of computer time on a single R8000 processor. In other words, one query structure is scanned against the database in a matter of minutes. The method is rated at 90% reliability at capturing statistically significant similarities. It is useful as a rapid preprocessor to a comprehensive protein structure database search system.
Some principles and practices of genetic biobanking studies

Genetic biobanking studies are becoming increasingly common as researchers recognise the need for large samples to identify the genetic basis of susceptibility to complex disease. In the present review, the authors give a brief overview of some of the issues that should be considered when implementing such a large-scale project, from study design to sample management, data coding and storage to the statistical analysis and engagement with the public. Specific solutions to these issues are presented, as implemented in the Generation Scotland projects, but the general principles outlined are relevant to any biobanking study.
Introduction to mediation analysis with structural equation modeling

In mediation, we consider an intermediate variable, called the mediator, that helps explain how or why an independent variable influences an outcome. In the context of a treatment study, it is often of great interest to identify and study the mechanisms by which an intervention achieves its effect. By investigating mediational processes that clarify how the treatment achieves the study outcome, not only can we further our understanding of the pathology of the disease and the mechanisms of treatment, but we may also be able to identify alternative, more efficient, intervention strategies. For example, a tobacco prevention program may teach participants how to stop taking smoking breaks at work (the intervention) which changes their social norms about tobacco use (the intermediate mediator) and subsequently leads to a reduction in smoking behavior (study outcome).
Score guided musical source separation using Generalized Coupled Tensor Factorization

Providing prior knowledge about sources to guide source separation is known to be useful in many audio applications. In this paper we present two tensor factorization models for musical source separation where musical information is incorporated by using the Generalized Coupled Tensor Factorization (GCTF) framework. The approach is an extension of Nonnegative Matrix Factorization where more than one matrix or tensor object is simultaneously factorized. The first model uses a temporally aligned transcription of the mixture and incorporates spectral knowledge via coupling. In contrast of using a temporally aligned transcription, the second model incorporates harmonic information by taking an approximate, incomplete, and not necessarily aligned transcription of the musical piece as input. We evaluate our models on piano and cello duets where the experiments show that instead of using a temporally aligned transcription, we can achieve competitive results by using only a partial and incomplete transcription.