Miracle-dz/UniFAR-FTUs huggingface dataset:
Peripheral Blood Gamma Interferon Release Assays Predict Lung Responses and Mycobacterium tuberculosis Disease Outcome in Mice

ABSTRACT Current diagnostic tests for tuberculosis (TB) are not able to distinguish active disease from latent Mycobacterium tuberculosis infection, nor are they able to quantify the risk of a latently infected person progressing to active TB. There is interest, however, in adapting antigen-specific gamma interferon (IFN-γ) release assays (IGRAs) to predict disease outcome. In this study, we used the differential susceptibilities of inbred mouse strains to M. tuberculosis infection to evaluate the prognostic capabilities of IGRAs. Using lung and blood cultures, we determined that CBA/J, DBA/2, and C3H/HeJ mice (models of heightened risk of progression to active TB) produced less antigen-specific IFN-γ in response to M. tuberculosis culture filtrate proteins and early secreted antigenic target-6 than the relatively resistant C57BL/6 mouse strain. Additionally, reduced IFN-γ secretion in supernatants reflected a reduced frequency of IFN-γ-responding cells in the lung and blood and not a specific defect in IFN-γ secretion at the single-cell level. Importantly, detection of antigen-specific IFN-γ from blood cultures accurately reflected lung responses, indicating that blood can be an appropriate test tissue in humans. Furthermore, reduced antigen-specific IFN-γ production and low frequencies of IFN-γ-responding cells from peripheral blood predicted increased risk of TB disease progression across genetically diverse TB disease-susceptible mouse strains, suggesting that similar results may occur in humans. The development of efficacious predictive diagnostic tests for humans would lead to targeted therapy prior to progression to active TB, reducing transmission, incidence, and prevalence rates while maximizing the use of public health resources.
Study of ECG quality using self learning techniques

The aim of this study was to develop a method that could automatically evaluate the quality of ECG recordings. In several situations, people performing the recording don't have the knowledge to evaluate the quality of the ECG and an immediate feedback about it would be useful. Since there is not a consensus on how to define and quantify ECG quality, we applied self learning techniques starting from a set (N= 1 OOO) of randomly selected ECGs from our internal repository. The full set of ECGs was blindly flagged by an expert cardiologist and subsequently analyzed by AMPS software which automatically computes a set of quality metrics. These quality parameters were used to train a neural network and build a decision tree. The performance of the proposed solutions were evaluated using the mean squared error (MSE) between expected results (from the ECGs set) and obtained results (from neural network and decision tree). The MSE resulting from the neural network and the decision tree were O.O1 and 0.004, respectively, indicating an error in range of 1%.
Assessment of Renewable Sources for the Energy Consumption in Malta in the Mediterranean Sea

The main purpose of this paper is to analyze the energy production in the Maltese islands, focusing on the employment of renewable energies in order to increase their energy independence. The main renewable source here proposed is wave energy: thanks to a strategic position, Malta will be able to produce electrical energy using an innovative type of Wave Energy Converter (WEC) based on the prototype of a linear generator realized by University of Palermo. The use of this new technology will be able to cut down the electrical energy production from traditional power plants and, consequently, the greenhouse gas emissions (GHG). Wave energy source and off-shore photovoltaic (PV) technology are here proposed. Particularly, the installation of 12 wave farms, for a total installed capacity of 86 MW, will generate about 9.5% of Malta’s energy requirement in 2025, while the installation of 9.6 MW of off-shore PV will generate about 0.73%.
Automatic Extraction of Bug Localization Benchmarks from History

Researchers have proposed a number of tools for automatic bug localization. Given a program and a description of the failure, such tools pinpoint a set of statements that are most likely to contain the bug. Evaluating bug localization tools is a difficult task because existing benchmarks are limited in size of subjects and number of bugs. In this paper we present iBugs, an approach that automatically extracts benchmarks for bug localization from the history of a project. For ASPECTJ, we extracted 369 bugs, 223 out of these had associated test cases (useful to test dynamic tools). We demonstrate the relevance of our dataset for both static and dynamic bug localization tools with case studies on FINDBUGS and AMPLE.
Tree-based fitted Q-iteration for multi-objective Markov decision processes in water resource management

Multi-objective Markov decision processes (MOMDPs) provide an effective modeling framework for decision-making problems involving water systems. The traditional approach is to define many single-objective problems (resulting from different combinations of the objectives), each solvable by standard optimization. This paper presents an approach based on reinforcement learning (RL) that can learn the operating policies for all combinations of objectives in a single training process. The key idea is to enlarge the approximation of the action-value function, which is performed by single-objective RL over the state-action space, to the space of the objectives9 weights. The batch-mode nature of the algorithm allows for enriching the training dataset without further interaction with the controlled system. The approach is demonstrated on a numerical test case study and evaluated on a real-world application, the Hoa Binh reservoir, Vietnam. Experimental results on the test case show that the proposed approach (multi-objective fitted Q-iteration; MOFQI) becomes computationally preferable over the repeated application of its single-objective version (fitted Q-iteration; FQI) when evaluating more than five weight combinations. In the Hoa Binh case study, the operating policies computed with MOFQI and FQI have comparable efficiency, while MOFQI provides a continuous approximation of the Pareto frontier with no additional computing costs.
Exploring Leadership: For College Students Who Want to Make a Difference

Getting the books Exploring Leadership For College Students Who Want To Make A Difference Ebook now is not type of challenging means. You could not single-handedly going subsequently books gathering or library or borrowing from your friends to edit them. This is an definitely easy means to specifically get lead by on-line. This online declaration Exploring Leadership For College Students Who Want To Make A Difference Ebook can be one of the options to accompany you in the same way as having new time.
How prevalent are anxiety disorders in schizophrenia? A meta-analysis and critical review on a significant association.

OBJECTIVE The presence of anxiety disorders (AD) in schizophrenia (SZ) is attracting increasing interest. However, published studies have yielded very broad variations in prevalence rates across studies. The current meta-analysis sought to (1) investigate the prevalence of co-occurring AD in SZ by reporting pooled prevalence rates and (2) identify potential sources of variations in reported rates that could guide our efforts to identify and treat these co-occurring disorders in patients with SZ. METHODS We performed a systematic search of studies reporting prevalence of AD in SZ and related psychotic disorders. Mean prevalence rates and 95% confidence intervals (CIs) were first computed for each disorder. We then examined the impact of potential moderators related to patient sampling or to AD assessment methods on these rates. RESULTS Fifty-two eligible studies were identified. Pooled prevalence rates and CIs were 12.1% (7.0%-17.1%) for obsessive-compulsive disorders, 14.9% (8.1%-21.8%) for social phobia, 10.9% (2.9%-18.8%) for generalized AD, 9.8% (4.3%-15.4%) for panic disorders, and 12.4% (4.0%-20.8%) for post-traumatic stress disorders. For all disorders, we found significant heterogeneity in rates across studies. This heterogeneity could at least partially be explained by the effect of moderator variables related to patient characteristics or assessment methods. CONCLUSIONS AD are highly prevalent in SZ, but important variations in rates are observed between studies. This meta-analysis highlights several factors that affect risk for, or detection of AD in SZ, and could, thus, have an important impact on treatment and outcome of SZ patients.
How optimal is the genetic code?

The genetic code is well-known to be fault tolerant, in the sense that transcription errors in the third codon position frequently do not influence the amino acid expressed, while errors in other codon positions often lead to amino acids having similar chemical properties. Several articles in the recent past ([? , ? , ? ] etc.) have studied the question of optimality of the genetic code. In [? ] Di Giulio estimated that the natural code has achieved 68% minimization of polarity distance, by comparing the natural code with random block respecting codes (those codes obtained by relabeling the 20 amino acids in the natural table by a permutation thereof). When considering single base changes in the codons, let Ni,j be the number of times the i-th amino acid changes into the j-th amino acid, and Xi be the polarity index [? ] of the i-th amino acid. The percent minimization is defined by
The Effect of Minimum Drinking Age Legislation on Youthful Auto Fatalities, 1970-1977

Composition particularly adapted to stabilize polymeric organic materials such as alpha -olefin polymers and copolymers against the deleterious effects of oxygen, heat and light comprising a mixture of 2,6-ditertiarybutyl-4-nonylphenol and hydrazine and the resultant stabilized materials.
Dissociation of human and computer voices in the brain: Evidence for a preattentive gestalt‐like perception

We investigated the early (“preattentive”) cortical processing of voice information, using the so‐called “mismatch response. ” This brain potential allows inferences to be made about the sensory short‐term store. Most importantly, the mismatch potential also provides information about the organization of long‐term memory traces in the auditory system. Such traces have reliably been reported for phonemes. However, it is unclear whether they also exist for human voice information. To explore this issue, 10 healthy subjects were presented with a single word stimulus uttered by voices of different prototypicality (natural, manipulated, synthetic) in a mismatch experiment (stimulus duration 380 msec, onset‐to‐onset interval 900 msec). The event‐related magnetic fields were recorded by a 148‐channel whole‐head magnetometer and a source current density modeling of the magnetic field data was performed using a minimum‐norm estimate. Each deviating voice signal in a series of standard‐voice stimuli evoked a mismatch response that was localized in temporal brain regions bilaterally. Increased mismatch related magnetic flux was observed in response to decreased prototypicality of a presented voice signal, but did not correspond to the acoustic similarity of standard voice and deviant voices. We, therefore, conclude that the mismatch activation predominantly reflects the ecological validity of the voice signals. We further demonstrate that the findings cannot be explained by mere acoustic feature processing, but rather point towards a holistic mapping of the incoming voice signal onto long‐term representations in the auditory memory. Hum. Brain Mapping 20:13–21, 2003. © 2003 Wiley‐Liss, Inc.
TOPDIS: Tensor-based Ranking for Data Search and Navigation

Web sources increasingly use the Resource Description Format (RDF) as a means for general-purpose knowledge representation. Many database-backed sites are now being complemented with a structured representation of their content; for example, the content of blogs, social networking sites, and Wikipedia is being made available in RDF and can be crawled and aggregated. Searching over large corpora of structured information collected from the Web brings about new challenges for ranking. One particular problem is that searches can result in graphs with thousands of edges, too large for a user to easily absorb. To this end, we introduce TOPDIS, a set of algorithmic tools to determine prominent elements in large semantic graphs. We provide a formalisation of the method using the concepts of multilinear algebra, evaluate scalability of the algorithm and quality of the results, and show how TOPDIS can improve search over structured data in general. Acknowledgements: This work has been supported by Science Foundation Ireland project Lion (SFI/02/CE1/I131) Copyright c © 2009 by the authors DERI TR 2009-06-21 I
Access to Post-secondary Education in the United States

This chapter discusses the past, present and future of enrolments in US postsecondary education by examining the institutional, economic, and public policy factors over the last 25 years that had a major impact on college enrolment in the United States. It uses the state of US higher education today and the current economic and political environment as the starting point for understanding the challenges and opportunities facing the future growth of higher education, especially among minorities and people from low income background.
Reheating after inflation.

The theory of reheating of the Universe after inflation is developed. We have found that typically at the first stage of reheating the classical inflation field $\ensuremath{\varphi}$ rapidly decays into $\ensuremath{\varphi}$ particles or into other bosons due to a broad parametric resonance. Then these bosons decay into other particles, which eventually become thermalized. Complete reheating is possible only in those theories where a single particle $\ensuremath{\varphi}$ can decay into other particles. This imposes strong constraints on the structure of inflationary models, and implies that the inflation field can be a dark matter candidate.
Pitch estimation of stereophonic mixtures of delay and amplitude panned signals

In this paper, a novel method for pitch estimation of stereophonic mixtures is presented, and it is investigated how the performance is affected by the pan parameters of the individual signals of the mixture. The method is based on a signal model that takes into account a stereophonic mixture created by mixing multiple individual channels with different pan parameters, and is hence suited for use in automatic music transcription, source separation and classification systems. Panning is done using both amplitude differences and delays. The performance of the estimator is compared to one single-channel, two multi-channel and one multi-pitch estimator using synthetic and real signals. Experiments show that the proposed method is able to correctly estimate the pitches of a mixture of three real signals when they are separated by more than 25 degrees.
Simultaneous color constancy.

Observers matched patches (simulated Munsell papers) in two simultaneously presented computer-controlled displays, a standard array presented under 6500-K illumination and a test array under 4000 or 10,000 K. Adaptation to the test illuminants was limited. The adjusted patch was surrounded by a single color (annulus display) or by many colors (Mondrian display). Observers either matched hue and saturation or made surface-color (paper) matches in which the subject was asked to make the test patch look as if it were cut from the same piece of paper as the standard patch. For two of the three subjects, the paper matches were approximately color constant. The hue-saturation matches showed little color constancy. Moreover, the illumination difference between the two displays was always visible. Our data show that simultaneous mechanisms alone (e.g., simultaneous color contrast) alter hues and saturations too little to produce hue constancy.
Why reinvent the wheel? Building new proteins based on ready‐made parts

We protein engineers are ambivalent about evolution: on the one hand, evolution inspires us with myriad examples of biomolecular binders, sensors, and catalysts; on the other hand, these examples are seldom well‐adapted to the engineering tasks we have in mind. Protein engineers have therefore modified natural proteins by point substitutions and fragment exchanges in an effort to generate new functions. A counterpoint to such design efforts, which is being pursued now with greater success, is to completely eschew the starting materials provided by nature and to design new protein functions from scratch by using de novo molecular modeling and design. While important progress has been made in both directions, some areas of protein design are still beyond reach. To this end, we advocate a synthesis of these two strategies: by using design calculations to both recombine and optimize fragments from natural proteins, we can build stable and as of yet un‐sampled structures, thereby granting access to an expanded repertoire of conformations and desired functions. We propose that future methods that combine phylogenetic analysis, structure and sequence bioinformatics, and atomistic modeling may well succeed where any one of these approaches has failed on its own.
Artificial Bandwidth Extension Method of telephony Speech in Mobile Terminal: A Review

The restricted audio quality of today's telephone networks is mainly due to the Narrow Band (NB) limitation to the frequency range from about 300 Hz to 3.4 KHz. Meanwhile, codecs for Wide Band (WB) telephony (50Hz to 7 kHz) exist with significantly improved speech intelligibility and naturalness. However, the broad introduction of wideband speech coding will require strong efforts of both network operator and customers because many elements of the networks have to be modified. The intermediate solution to overcome this narrowband limitation can be achieved by applying Artificial Bandwidth Extension (ABE) in the receiving terminal. At the receiver, wideband speech is produced by artificial bandwidth extension (BWE). The BWE algorithms can be realized with or without some low bit rate side information. In this paper we review the basic principles of bandwidth extension and discuss both methods of bandwidth extension.
Aboutness from a commonsense perspective

Information retrieval (IR) is driven by a process that decides whether a document is about a query. Recent attempts spawned from a logic-based information retrieval theory have formalized properties characterizing “aboutness,” but no consensus has yet been reached. The proposed properties are largely determined by the underlying framework within which aboutness is defined. In addition, some properties are only sound within the context of a given IR model, but are not sound from the perspective of the user. For example, a common form of aboutness, namely overlapping aboutness, implies precision degrading properties such as compositional monotonicity. Therefore, the motivating question for this article is: independent of any given IR model, and examined within an information-based, abstract framework, what are commonsense properties of aboutness (and its dual, nonaboutness)? We propose a set of properties characterizing aboutness and nonaboutness from a commonsense perspective. Special attention is paid to the rules prescribing conservative behavior of aboutness with respect to information composition. The interaction between aboutness and nonaboutness is modeled via normative rules. The completeness, soundness, and consistency of the aboutness proof systems are analyzed and discussed. A case study based on monotonicity shows that many current IR systems are either monotonic or nonmonotonic. An interesting class of IR models, namely those that are conservatively monotonic, is identified.
Identification and control for a single-axis PZT nanopositioner stage

In this paper, a second order transfer function of a single-axis PZT nanopositioner stage (P-752.21C) is identified around an operating point. The nonlinearity due to the hysteresis is modeled using look-up tables. The validation of the complete model is achieved experimentally. Two control approaches are developed. The former is a PI controller where the control parameters are tuned using Ziegler-Nichols method. The latter is a fuzzy controller like PI. The simulation results in MATLAB/Simulink are affirmed the potentials of the developed control methodologies.
Effects of green tea on weight maintenance after body-weight loss

The present study was conducted to investigate whether green tea may improve weight maintenance by preventing or limiting weight regain after weight loss of 5 to 10% in overweight and moderately obese subjects. The study had a randomised, parallel, placebo-controlled design. A total of 104 overweight and moderately obese male and female subjects (age 18–60 years; BMI 25–35kg/m2) participated. The study consisted of a very-low-energy diet intervention (VLED; 2·1MJ/d) of 4 weeks followed by a weight-maintenance period of 13 weeks in which the subjects received green tea or placebo. The green tea contained caffeine (104mg/d) and catechins (573mg/d, of which 323mg was epigallocatechin gallate). Subjects lost 6·4 (sd 1·9) kg or 7·5 (sd 2·2) % of their original body weight during the VLED (P<0·001). Body-weight regain was not significantly different between the green tea and the placebo group (30·5 (sd 61·8) % and 19·7 (sd 56·9)%, respectively). In the green tea treatment, habitual high caffeine consumption was associated with a higher weight regain compared with habitual low caffeine consumption (39 (sd 17) and 16 (sd 11)%, respectively; P<0·05). We conclude that weight maintenance after 7·5% body-weight loss was not affected by green tea treatment and that habitual caffeine consumption affected weight maintenance in the green tea treatment.
A control approach for PDE dynamics in Li-ion batteries using differential flatness theory

It is proven that the PDE dynamics in Li-ion batteries satisfies differential flatness properties and this enables to solve the associate state estimation problem and to design a stabilizing feedback controller. First, by applying semi-discretization and the finite differences method the particles' diffusion PDE model is decomposed into an equivalent set of nonlinear coupled ODEs and a state-space description is obtained. Next, by defining specific state variables as virtual control inputs it is shown that each row of the state-space model is a differentially flat subsystem for which a feedback control law can be found that eliminates the output's tracking error. Moreover, by exploiting differential flatness properties the state estimation problem for the diffusion PDE model can be solved which consequently means that feedback control can be implemented with the use of a small number of measurements. It is shown that, being differentially flat, the state-space model of the PDE can be transformed to the canonical form and that state-estimation can be performed with the use of the Derivative-free nonlinear Kalman Filter.