Miracle-dz/UniFAR-FTUs huggingface dataset:
Seroprevalence of chronic Chlamydia pneumoniae infection in patients affected by chronic stable asthma.

OBJECTIVE To evaluate the seroprevalence of Chlamydia pneumoniae and age, gender and smoking habits in stable asthmatic patients. METHODS Over a period of 3 months, 197 adult patients affected by intermittent-to-severe chronic asthma were enrolled from 16 respiratory disease units in the south of Italy. As a control group, we tested 185 healthy, non-asthmatic subjects matched for age and gender, recruited among hospital staff. All patients were submitted to clinical examination, spirometry and blood collection for C. pneumoniae serology. The presence of infection was investigated by microimmunofluorescence (Micro-IF Test) for C. pneumoniae-specific IgG, IgM and IgA antibodies. RESULTS C. pneumoniae IgG titers > or =1 : 64 were detected in 30.4% of asthmatics and in 30.8% of controls. Correlation of age, gender and smoking habit with C. pneumoniae seropositivity was evaluated by linear regression analysis. Age was significantly associated with C. pneumoniae IgG titer > or =1 : 64 when seropositive asthmatics were tested. Moreover, C. pneumoniae seroprevalence was higher among smokers with a diagnosis of chronic asthma. CONCLUSIONS The seroprevalence of C. pneumoniae in stable asthmatics was comparable with the controls; therefore, the study does not support the association between C. pneumoniae antibody titers and stable asthma. However, the analysis for likely confounders such as age, gender and smoking status suggests a possible association of enhanced susceptibility to C. pneumoniae infection with age and smoking habitus.
Midwife-led continuity models versus other models of care for childbearing women.

The aim of this bi-monthly column is to highlight Cochrane Systematic Reviews of relevance to pregnancy and childbirth and to stimulate discussion on the relevance and implications of the review for practice. The Cochrane Collaboration is an international organisation that prepares and maintains high quality systematic reviews to help people make well-informed decisions about healthcare and health policy. A systematic review tries to search for, appraise and bring together existing research to answer a specific research quesiton. The Cochrane Database of Systematic Reviews (CDSR) is published monthly online. Residents in countries with a national licence to the Cochrane Libray, including the U.K. and Ireland, can access the Cochrane Library online, free of charge through www.thecochranelibrary. com.
Semantic structure for robotic teaching and learning

Instructing human novices on complex tasks in non-standardized environments are an underexplored potential use for social co-robots, since instruction and skill transfer involving human experts can require an enormous commitment of time and resources. In this paper, we enable a humanoid Baxter robot to build a semantically accessible framework for task learning, teaching and representation via active learning with human experts using hierarchical semantic labels. This process not only helps the robot to learn tasks from expert demonstrations, but later improves the ability of the robot to teach novice human operators. Our results show that the better-understood learning from demonstration (LfD) task is greatly enhanced by the active learning and mutual semantic structure building in a expert-robot partnership, while the robot's ability to teach novices is improved, though the results are suggestive rather than conclusive at this point. We discuss the important aspects and power of learning and teaching from demonstration and how both benefit from communication and joint human-robot creation of semantic hierarchies.
Consumer Participation in Mental Health Research: Articulating a Model to Guide Practice

Objective: Consumer involvement in mental health research is considered both a right and a benefit, despite the identified barriers to forming effective collaborative relationships. The purpose of this paper is to examine the literature relating to consumer involvement in mental health research with a view to articulating a model to guide this process. Method: A qualitative review of the relevant literature was undertaken. Literature referring to consumer roles in research was accessed and reviewed with the aim of articulating the benefits of, and barriers to, consumer participation in research. Results: The literature has identified a number of important benefits and some significant barriers to consumer involvement in mental health research. However, a clear model to articulate definitions of involvement is lacking. Four distinct levels of involvement were articulated. Conclusions: The identification of clearly defined models for consumer involvement in mental health research is important in order to facilitate collaboration and avoid tokenism. Research is required in order to determine the applicability of these models within actual research projects.
Meetings about meetings: research at ICSI on speech in multiparty conversations

In early 2001, we reported (at the Human Language Technology meeting) the early stages of an ICSI (International Computer Science Institute) project on processing speech from meetings (in collaboration with other sites, principally SRI, Columbia, and UW). We report our progress from the first few years of this effort, including: the collection and subsequent release of a 75-meeting corpus (over 70 meeting-hours and up to 16 channels for each meeting); the development of a prosodic database for a large subset of these meetings, and its subsequent use for punctuation and disfluency detection; the development of a dialog annotation scheme and its implementation for a large subset of the meetings; and the improvement of both near-mic and far-mic speech recognition results for meeting speech test sets.
A Bayesian Approach for LPV Model Identification and Its Application to Complex Processes

Obtaining mathematical models that can accurately describe nonlinear dynamics of complex processes and be further used for model-based control design is a challenging task. In this brief, a Bayesian approach is introduced for data-driven identification of linear parameter-varying regression models in an input–output dynamic representation form with an autoregressive with exogenous variable (ARX) noise structure. The applicability of the proposed approach is then investigated for the modeling of complex nonlinear process systems. In this approach, the dependence structure of the model on the scheduling variables is identified based on a Gaussian process (GP) formulation. The GP is used as a prior distribution to describe the possible realization of the scheduling-dependent coefficient functions of the estimated model. Then, a posterior distribution of these functions is obtained given the measured data and the mean value of this distribution is used to determine the estimated model. The properties and performance of the proposed method are evaluated using an illustrative example of a chemical process, namely, a distillation column, as well as an experimental case study with a three tank system.
The Effect of Religiosity on Therapy Outcome for Substance Abusing Adolescents.

Adolescent substance abuse has been on the rise for the past few decades, constituting a major personal and social problem. According to researchers, the causes are many, including biological, temperamental, psychological, behavioral, and environmental factors. Yet, only a few intervention methods have proven effective. Numerous studies demonstrated that religious beliefs and practices exert a deterrent effect on substance abuse among teens. However, there is little information available that applies specifically to Jewish adolescents from an orthodox background. This pilot study was conducted with a group of substance abusing Jewish adolescent boys attending an alternative religious high school, to examine the influence of religiosity of substance abuse therapy outcome. The assumption was that the religious environment would influence the boys to better respond to therapy, adding another weapon in the war against teens' substance abuse. Three appendixes contain a religiosity questionnaire, diagnostic schedule, and data table. (Contains 72 references.) (Author) Reproductions supplied by EDRS are the best that can be made from the original document. U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) This document has been reproduced as received from the person or organization originating it. Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. The Effect of Religiosity on Therapy Outcome for Substance Abusing Adolescents
What Every Teacher Should Know About Multicultural and Global Education

An introduction to the essential concepts of multicultural and global education. Describes practical application of multicultural and global concepts and how they can be combined into a cohesive and effective philosophy of education using six major principles: diversity, human rights, multiple perspectives, interconnectedness and interdependence, co-responsibility, and global society. For pre-service and practicing teachers in graddes K-12. "
The Influence of Age on T Cell Generation and TCR Diversity1

The ability to mount protective immune responses depends on the diversity of T cells. T cell diversity may be compromised by the declining thymic output of new T cells. The aging process imposes a threat to diversity, because thymic function deteriorates. In this study we have examined the relationship between thymic production, homeostatic T cell proliferation and TCR β-chain diversity in young (∼25 years), middle-aged (∼60 years), and elderly adults (∼75 years). TCR excision circles (TREC) as a marker of thymic output exponentially decreased by >95% between 25 and 60 years of age. The frequency of Ki67+ cycling CD4 T cells remained steady, and surprisingly, the diversity of the naive CD4 T cell repertoire was maintained at ∼2 × 107 different TCR β-chains. After the age of 70 years, TRECs only slightly declined, but homeostatic proliferation doubled. The diversity of the T cell pool drastically contracted to 200,000 TCR β-chains. Also, the phenotypic distinction between naive and memory CD4 T cells became fuzzy. The collapse in CD4 T cell diversity during the seventh and eighth decades indicates substantial T cell loss and implies that therapeutic measures to improve vaccine responses will have to include strategies for T cell replenishment.
Extracting Thee-Structured Representations of Thained Networks

A significant limitation of neural networks is that the representations they learn are usually incomprehensible to humans. We present a novel algorithm, TREPAN, for extracting comprehensible , symbolic representations from trained neural networks. Our algorithm uses queries to induce a decision tree that approximates the concept represented by a given network. Our experiments demonstrate that TREPAN is able to produce decision trees that maintain a high level of fidelity to their respective networks while being comprehensible and accurate. Unlike previous work in this area, our algorithm is general in its applicability and scales well to large networks and problems with high-dimensional input spaces.
Intravenous Thrombolysis for Acute Ischemic Stroke in Patients Receiving Antiplatelet Therapy: A Systematic Review and Meta‐analysis of 19 Studies

Background The safety and long‐term outcome of systemic thrombolysis in patients receiving antiplatelet medications remain subjects of great clinical significance. The objective of this meta‐analysis was to determine how prestroke antiplatelet therapy affects the risks and benefits of intravenous thrombolysis in patients with acute ischemic stroke. Methods and Results A dual‐reviewer search was conducted in PubMed and EMBASE databases through November 2015, from which 19 studies involving a total of 108 588 patients with acute ischemic stroke were identified based on preset inclusion criteria. Information on study designs, patient characteristics, exposures, outcomes, and adjusting confounders was extracted, and estimates were combined by using random‐effects models. The pooled crude estimates suggested that taking long‐term antiplatelet medications was associated with higher odds of symptomatic intracranial hemorrhage (odds ratio [OR] 1.70, 95% CI 1.47–1.97) and death (OR 1.46, 95% CI 1.22–1.75) and lower odds of favorable functional outcomes (OR 0.86, 95% CI 0.80–0.93). However, the combined confounder‐adjusted results only confirmed a relatively weak positive association between prior antiplatelet therapy and symptomatic intracranial hemorrhage (OR 1.21, 95% CI 1.02–1.44) and demonstrated no significant relationship between antiplatelet therapy and the other 2 outcomes (favorable outcome OR 1.09, 95% CI 0.96–1.24; death OR 1.02, 95% CI 0.98–1.07). Subgroup analyses revealed that the associations between prestroke antiplatelet therapy and outcomes were dependent on time and antiplatelet agents. Conclusions Patients with acute ischemic stroke receiving long‐term antiplatelet medications were associated with greater risks of developing symptomatic intracranial hemorrhage after systemic thrombolysis. However, the overall independent association between prestroke antiplatelet therapy and unfavorable outcomes or mortality was insignificant.
Machine Reading through Textual and Knowledge Entailment

While information extraction and textual entailment systems have greatly enhanced the amount of knowledge available from a text corpus, the next generation of natural language understanding systems – such as Machine Reading systems – will need to employ dedicated mechanisms to ensure that acquired knowledge is consistent with the previous commitments encoded in the system’s knowledge base. This paper introduces a new technique for knowledge acquisition for Machine Reading systems, known as Reading by Entailment (RbE), which uses two complementary systems for recognizing entailment relationships in order to identify the set of hypotheses that can be inferred from a text corpus. Entailment hypotheses are generated by a random walk model that operates on texts and informs a plausible model of knowledge entailment. Knowledge entailment is cast as a maximal knowledge relevance problem which operates on knowledge mappings.
On Dynamic Selection of the Most Informative Samples in Classification Problems

In this paper, we propose a dynamic technique for selecting the most informative samples in classification problems as coming in two stages: the first stage conducts sample selection in batch off-line mode based on unsupervised criteria extracted from cluster partitions, the second phase proposes an active learning scheme during on-line adaptation of classifiers in non-stationary environments. This is based on the reliability of the classifiers in their output responses (confidences in their predictions). Both approaches contribute to a reduction of the annotation effort for operators, as operators only have to label/give feedback on a subset of the off-line/online. At the same time they are able to keep the accuracy on almost the same level as when the classifiers would have been trained on all samples. This will be verified based on real-world data sets from two image classification problems used in on-line surface inspection scenarios.
Animal models for plaque rupture: a biomechanical assessment

Summary Rupture of atherosclerotic plaques is the main cause of acute cardiovascular events. Animal models of plaque rupture are rare but essential for testing new imaging modalities to enable diagnosis of the patient at risk. Moreover, they enable the design of new treatment strategies to prevent plaque rupture. Several animal models for the study of atherosclerosis are available. Plaque rupture in these models only occurs following severe surgical or pharmaceutical intervention. In the process of plaque rupture, composition, biology and mechanics each play a role, but the latter has been disregarded in many animal studies. The biomechanical environment for atherosclerotic plaques is comprised of two parts, the pressure-induced stress distribution, mainly - but not exclusively – influenced by plaque composition, and the strength distribution throughout the plaque, largely determined by the inflammatory state. This environment differs considerably between humans and most animals, resulting in suboptimal conditions for plaque rupture. In this review we describe the role of the biomechanical environment in plaque rupture and assess this environment in animal models that present with plaque rupture.
A hidden wholeness : the journey toward an undivided life : welcoming the soul and weaving community in a wounded world

In "A Hidden Wholeness", Parker Palmer reveals the same compassionate intelligence and informed heart that shaped his best-selling books "Let Your Life Speak" and "The Courage to Teach". Here he speaks to our yearning to live undivided lives - lives that are congruent with our inner truth - in a world filled with the forces of fragmentation. Mapping an inner journey that we take in solitude and in the company of others, Palmer describes a form of community that fits the limits of our active lives. Defining a 'circle of trust' as 'a space between us that honors the soul," he shows how people in settings ranging from friendship to organizational life can support each other on the journey toward living "divided no more'. This paperback edition includes two new and useful features. "Circles of Trust" is a DVD containing interviews with Parker J. Palmer and footage from retreats he facilitated for the Center for Courage & Renewal. "Bringing the Book to Life", by Caryl Hurtig Casbon and Sally Z. Hare, is a reader's and leader's guide to exploring the themes in "A Hidden Wholeness". The DVD illuminates and illustrates the principles and practices behind circles of trust. The guide includes questions that connect the DVD to the book, offering 'a conversation with the author' as well as an engagement with the text. Together, these features give readers new ways to internalize the themes of "A Hidden Wholeness" and share with others this approach to sustaining identity and integrity in all the venues of our lives. Inspired by Palmer's writing and speaking - and challenged by the conditions of twenty-first century life - people across the country, from many walks of life, have been coming together in circles of trust to reclaim their integrity and help foster wholeness in their workplaces and their world. For over a decade, the principles and practices in this book have been proven on the ground-by parents and educators, clergy and politicians, community organizers and corporate executives, physicians and attorneys, and many others who seek to rejoin soul and role in their private and public lives. "A Hidden Wholeness" weaves together four themes that its author has pursued for forty years: the shape of an integral life, the meaning of community, teaching and learning for transformation, and nonviolent social change. The hundreds of thousands of people who know Parker Palmer's books will be glad to find the journey continued.
Pancreaticopleural fistula: a rare complication of ERCP – induced pancreatitis

Pancreaticopleural fistula is a rare complication of acute and chronic pancreatitis caused by an inflammatory or traumatic injury to the pancreatic duct. The ensuing thoracic collections may be in the form of pleural effusions, pleural pseudocysts or mediastinal pseudocysts. Treatment options may be conservative or surgical. We present a case of post endoscopic retrograde cholangio-pancreatography (ERCP) acute pancreatitis with a pancreaticopleural fistula where conservative management failed.
Importance of Organosulfur Utilization for Survival of Pseudomonas putida in Soil and Rhizosphere

ABSTRACT The sulfur present in both agricultural and uncultivated soils is largely in the form of sulfonates and sulfate esters and not as free, bioavailable inorganic sulfate. Desulfurization of the former compounds in vitro has previously been studied in Pseudomonas putida, a common rhizosphere inhabitant. Survival of P. putida strains was now investigated in three sulfur-deficient Danish soils which were found to contain 60 to 70% of their sulfur in sulfonate or sulfate ester form, as determined by X-ray near-edge spectroscopy. The soil fitness of P. putida S-313 was compared with that of isogenic strains with mutations in the sftR and asfA genes (required for in vitro desulfurization of sulfate esters and arylsulfonates, respectively) and in the ssu locus (required in vitro for the desulfurization of both sulfonates and sulfate esters). asfA or sftR mutants showed significantly reduced survival compared to the parent strain in bulk soil that had been enriched with carbon and nitrogen to mimic rhizosphere conditions, but this reduced survival was not observed in the absence of these additives. In a tomato rhizosphere grown in compost, survival of sftR and ssu mutants was reduced relative to the parent strain. The results demonstrate that the ability to desulfurize sulfonates and sulfate esters is critical for survival of bacteria in the rhizosphere but less so in bulk soils outside the influence of plant roots, where carbon is the limiting nutrient for growth.
Data-driven inverse learning of passenger preferences in urban public transits

Urban public transit planning is crucial in reducing traffic congestion and enabling green transportation. However, there is no systematic way to integrate passengers' personal preferences in planning public transit routes and schedules so as to achieve high occupancy rates and efficiency gain of ride-sharing. In this paper, we take the first step tp exact passengers' preferences in planning from history public transit data. We propose a data-driven method to construct a Markov decision process model that characterizes the process of passengers making sequential public transit choices, in bus routes, subway lines, and transfer stops/stations. Using the model, we integrate softmax policy iteration into maximum entropy inverse reinforcement learning to infer the passenger's reward function from observed trajectory data. The inferred reward function will enable an urban planner to predict passengers' route planning decisions given some proposed transit plans, for example, opening a new bus route or subway line. Finally, we demonstrate the correctness and accuracy of our modeling and inference methods in a large-scale (three months) passenger-level public transit trajectory data from Shenzhen, China. Our method contributes to smart transportation design and human-centric urban planning.