Miracle-dz/UniFAR-FTUs huggingface dataset:
ECIL-6 guidelines for the treatment of invasive candidiasis, aspergillosis and mucormycosis in leukemia and hematopoietic stem cell transplant patients

The European Conference on Infections in Leukemia (ECIL) provides recommendations for diagnostic strategies and prophylactic, pre-emptive or targeted therapy strategies for various types of infection in patients with hematologic malignancies or hematopoietic stem cell transplantation recipients. Meetings are held every two years since 2005 and evidence-based recommendations are elaborated after evaluation of the literature and discussion among specialists of nearly all European countries. In this manuscript, the ECIL group presents the 2015-update of the recommendations for the targeted treatment of invasive candidiasis, aspergillosis and mucormycosis. Current data now allow a very strong recommendation in favor of echinocandins for first-line therapy of candidemia irrespective of the underlying predisposing factors. Anidulafungin has been given the same grading as the other echinocandins for hemato-oncological patients. The beneficial role of catheter removal in candidemia is strengthened. Aspergillus guidelines now recommend the use of either voriconazole or isavuconazole for first-line treatment of invasive aspergillosis, while first-line combination antifungal therapy is not routinely recommended. As only few new data were published since the last ECIL guidelines, no major changes were made to mucormycosis recommendations.
Fifty Years of Diazeniumdiolate Research. From Laboratory Curiosity to Broad-Spectrum Biomedical Advances

Here I show that a “pure” research project, seemingly totally lacking in practical application when it was first published, can years later spark a whole new scientific field with the potential to revolutionize clinical practice. A 1961 publication describing adducts of nitric oxide (NO) with certain nucleophiles attracted little notice at the time, but later work showing that the adducts could be hydrolyzed to regenerate the NO in bioactive form has provided the foundation for a host of biomedical applications. Crucial to the discovery of widely used tools for studying NO’s chemical biology as well as for the design of a variety of promising therapeutic advances has been the increasingly detailed understanding of the physicochemical properties of these “diazeniumdiolates” (also known as NONOates).
Cardiac-Specific IGF-1 Receptor Transgenic Expression Protects Against Cardiac Fibrosis and Diastolic Dysfunction in a Mouse Model of Diabetic Cardiomyopathy

OBJECTIVE Compelling epidemiological and clinical evidence has identified a specific cardiomyopathy in diabetes, characterized by early diastolic dysfunction and adverse structural remodeling. Activation of the insulin-like growth factor 1 (IGF-1) receptor (IGF-1R) promotes physiological cardiac growth and enhances contractile function. The aim of the present study was to examine whether cardiac-specific overexpression of IGF-1R prevents diabetes-induced myocardial remodeling and dysfunction associated with a murine model of diabetes. RESEARCH DESIGN AND METHODS Type 1 diabetes was induced in 7-week-old male IGF-1R transgenic mice using streptozotocin and followed for 8 weeks. Diastolic and systolic function was assessed using Doppler and M-mode echocardiography, respectively, in addition to cardiac catheterization. Cardiac fibrosis and cardiomyocyte width, heart weight index, gene expression, Akt activity, and IGF-1R protein content were also assessed. RESULTS Nontransgenic (Ntg) diabetic mice had reduced initial (E)-to-second (A) blood flow velocity ratio (E:A ratio) and prolonged deceleration times on Doppler echocardiography compared with nondiabetic counterparts, indicative markers of diastolic dysfunction. Diabetes also increased cardiomyocyte width, collagen deposition, and prohypertrophic and profibrotic gene expression compared with Ntg nondiabetic littermates. Overexpression of the IGF-1R transgene markedly reduced collagen deposition, accompanied by a reduction in the incidence of diastolic dysfunction. Akt phosphorylation was elevated ∼15-fold in IGF-1R nondiabetic mice compared with Ntg, and this was maintained in a setting of diabetes. CONCLUSIONS The current study suggests that cardiac overexpression of IGF-1R prevented diabetes-induced cardiac fibrosis and diastolic dysfunction. Targeting IGF-1R–Akt signaling may represent a therapeutic target for the treatment of diabetic cardiac disease.
Privacy-Preserving Clustering by Object Similarity-Based Representation and Dimensionality Reduction Transformation

Preserving privacy of individuals when data are shared for clustering is a challenging problem. Data owners must not only meet privacy requirements but also guarantee valid clustering results. In this paper, we show that this dual goal can be achieved by transforming a database using two simple and effective data transformations: Object Similarity-Based Representation (OSBR) and Dimensionality Reduction-Based Transformation (DRBT). The former relies on the idea behind the similarity between objects, and the latter relies on the intuition behind random projection. The major features of our data transformations are: a) they are independent of distance-based clustering algorithms; b) they have a sound mathematical foundation; and c) they do not require CPU-intensive operations.
Use of Digital Droplet PCR to Detect Mycobacterium tuberculosis DNA in Whole Blood-Derived DNA Samples from Patients with Pulmonary and Extrapulmonary Tuberculosis

Tuberculosis (TB) is a chronic infectious disease that has been threatening public health for many centuries. The clinical diagnostic procedure for TB is time-consuming and laborious. In the last 20 years, real-time fluorescence-based quantitative PCR (real-time PCR) has become a better alternative for TB diagnosis in clinics due to its sensitivity and specificity. Recently, digital droplet PCR (ddPCR) has been developed, and it might be an ideal alternative to conventional real-time PCR for microorganism detection. In this study, we aimed to assess the capacity of ddPCR and real-time PCR for detecting low levels of circulating Mycobacterium tuberculosis (MTB) DNA. The study involved testing whole blood samples for an MTB DNA target (known as IS6110). Blood samples were obtained from 28 patients with pulmonary TB, 28 patients with extrapulmonary TB, and 28 healthy individuals. The results show that ddPCR could be used to measure low levels of MTB DNA, and it has the potential to be used to diagnose pulmonary and extrapulmonary TB based on clinical samples.
Simple and efficient parallelization for probabilistic temporal tensor factorization

Probabilistic Temporal Tensor Factorization (PTTF) is an effective algorithm to model the temporal tensor data. It leverages a time constraint to capture the evolving properties of tensor data. Nowadays the exploding dataset demands a large scale PTTF analysis, and a parallel solution is critical to accommodate the trend. Whereas, the parallelization of PTTF still remains unexplored. In this paper, we propose a simple yet efficient Parallel Probabilistic Temporal Tensor Factorization, referred to as P2T2F, to provide a scalable PTTF solution. P2T2F is fundamentally disparate from existing parallel tensor factorizations by considering the probabilistic decomposition and the temporal effects of tensor data. It adopts a new tensor data split strategy to subdivide a large tensor into independent sub-tensors, the computation of which is inherently parallel. We train P2T2F with an efficient algorithm of stochastic Alternating Direction Method of Multipliers, and show that the convergence is guaranteed. Experiments on several real-word tensor datasets demonstrate that P2T2F is a highly effective and efficiently scalable algorithm dedicated for large scale probabilistic temporal tensor analysis.
American college students' requesting competence in Chinese as a foreign language

Using written Discourse Completion Task, this study examined requesting competence of American college students learning Chinese as a foreign language. In analyzing requesting behaviors, we focused particularly on the use of request strategy and external modification strategy. Comparing the practices of Chinese native speakers and the learners, we found that the learners’ competence in making requests in Chinese is generally low in that their use of request did not approximate much to the practice of native speakers. On the one hand, the learners overused conventional indirect strategies, which affected the appropriateness of their requesting behaviors; on the other hand, in mitigating the face-threatening effects of head act, the learners used far fewer external modification strategies than native Chinese speakers did. In addition, we found that learners’ competence in adjusting their strategy use in response to situational variations also lagged behind that of the native speaker.
Hopf oscillator based adaptive locomotion control for a bionic quadruped robot

This contribution aims to construct an adaptive locomotion controller for legged robots based on learning animals' rhythmic behaviors. The design of locomotion control method, different from traditional ones, is inspired from biological term of Central Pattern Generators (CPG), used to produce rhythmic motions. A symmetrically netted CPG structure consisting of coupled oscillators is presented to simply generate stable and natural gait patterns for legged robots. Moreover, gait transition among different gaits with locked phase relation is realized by introducing rotation matrix as coupling term that arbitrary phase difference can be obtained. Thus, smooth and prompt gait switching is achieved so as to perform dynamic walking. Also, in order to enhance adaptability to uneven terrains like slope, we adopt body attitude as sensory feedback to CPG network and the control signals for locomotion are modulated to accomplish dynamic walking on slope. The results from simulations and physical prototype experiment validate the feasibility of proposed control strategy.
Discriminatively Modeling Commonality of Term Types for Extracting Relation from Small Corpora

In this paper, we present a novel strategy to partly solve the data sparseness problem caused by small corpora in relation extraction by discriminatively modeling commonality among terms in each term type associated with the relation. The key idea is to use the information of terms rather than that of term pairs to extract relations. Based on this idea, terms in each term type were separately extracted from the corpora and a special function, called relation function, is used to determine whether the two terms selected from each term type have the target relation. As we can get more information of terms than that of term pairs in limited corpora, instances of the target relation we get using commonality among terms will be larger in amount and more reliable in quality. This is also proved by the experiments.
Observing and interpreting complex human activities in everyday environments

In this thesis we developed a system for observing and interpreting complex human activities to enable novel interactive application scenarios e.g. in robotics. We describe the design, implementation and empirical evaluation of unintrusive methods for human fullbody motion capture. Our system is accurate and reliable even in the case of occlusions, object manipulations or interactions with the environment or another person. This is achieved by combining an anthropometric human model with novel hierarchical sampling strategies for probabilistic state estimation and implicit environment models. In addition, observed activities can be recognized using learned and self-adaptive motion models.
Secret Forwarding of Events over Distributed Publish/Subscribe Overlay Network

Publish/subscribe is a communication paradigm where loosely-coupled clients communicate in an asynchronous fashion. Publish/subscribe supports the flexible development of large-scale, event-driven and ubiquitous systems. Publish/subscribe is prevalent in a number of application domains such as social networking, distributed business processes and real-time mission-critical systems. Many publish/subscribe applications are sensitive to message loss and violation of privacy. To overcome such issues, we propose a novel method of using secret sharing and replication techniques. This is to reliably and confidentially deliver decryption keys along with encrypted publications even under the presence of several Byzantine brokers across publish/subscribe overlay networks. We also propose a framework for dynamically and strategically allocating broker replicas based on flexibly definable criteria for reliability and performance. Moreover, a thorough evaluation is done through a case study on social networks using the real trace of interactions among Facebook users.
Community participation and emerging surfing tourism destinations: a case study of the Mentawai Islands

ABSTRACT The Mentawai Islands, Indonesia, are an emerging surfing tourism destination. Surfing tourism has the potential to provide significant economic income and employment opportunities for remote communities in less-developed destinations. However, much of the current surfing tourism development is controlled by foreign investors and the actual reported benefits to local community are marginal. Therefore, the aim of this paper was to explore the local community participation in the Mentawai Islands surfing tourism industry. The paper also investigated possible future directions for increasing the local community involvement in the surfing tourism industry. Field research was conducted in the period between July and September of 2010, through in-depth interviews with local stakeholder representatives. In conclusion, the local community perceived foreign ownership and lack of government support as the major barriers to participation. A key finding of this paper was that the local community recognised education and training as the most effective way to increase their participation in the surfing tourism industry; therefore, it is recommended that future studies examine the viability of implementing tourism-specific education and training.
Asymptotics for linear predictors of strongly dependent time series

This paper assesses the performance of finite-sample predictors as compared to forecasts based on the infinite past, in the context of long-memory processes. We establish the rate at which the autoregressive expansion based on a finite number of past observations for a large class of long-memory processes, including the popular fractional autoregressive moving average model, converges in mean square to the best linear predictor given the entire infinite past, as the number of observations increases to infinity
Experimental research activity on additive manufacturing of microwave passive waveguide components

All metal passive waveguide components are key building-blocks of several RF systems used for telecommunications, navigation, imaging, radio-astronomy, and cosmology. The accurate manufacture of these devices in Additive Manufacturing (AM) technologies can open the way to a high integration level of microwave functionalities with a significant cost and mass reduction. In the paper, after an introduction on the most common AM technologies with particular detail on selective laser melting (SLM) and stereo-lithography apparatus (SLA) processes, the results on the on-going research activity are discussed. Measured performances are reported for AM prototypes of Ku/K/Ka-band rectangular and circular waveguide lines, microwave filters and a smooth wall horn.
Human interleukin 1. Purification to homogeneity

We have purified human interleukin 1 (IL-1) to homogeneity by a simplified procedure that results in excellent yields of pure material that retains a high level of biological activity. IL-1, secreted by human peripheral blood macrophages that have been stimulated with Staphylococcus aureus, was purified by ion exchange chromatography and affinity chromatography on Procion Red agarose. The pure protein has a specific activity of 3.2 X 10(8) U/mg in the thymocyte mitogenesis assay, and is pyrogenic. No molecular weight heterogeneity was observed, in contrast to findings for mouse IL-1 and earlier reports of human IL-1. Purified IL-1, as analyzed by two-dimensional electrophoresis/electrofocusing gels, exhibited a series of charged species with isoelectric points ranging from 6.0 to 4.9, all with a molecular weight of approximately 17,500. Amino acid analysis indicated an abundance of acidic residues, in agreement with the low isoelectric points. There is little or no cysteine in the molecule. No evidence was found for the presence of carbohydrate moieties. The overall yield for this procedure was approximately 31% of the activity contained in the initial culture supernatant.
Computerized tomography with total variation and with shearlets

To reduce the x-ray dose in computerized tomography (CT), many constrained optimization approaches have been proposed aiming at minimizing a regularizing function that measures a lack of consistency with some prior knowledge about the object that is being imaged, subject to a (predetermined) level of consistency with the detected attenuation of x-rays. One commonly investigated regularizing function is total variation (TV), while other publications advocate the use of some type of multiscale geometric transform in the definition of the regularizing function, a particular recent choice for this is the shearlet transform. Proponents of the shearlet transform in the regularizing function claim that the reconstructions so obtained are better than those produced using TV for texture preservation (but may be worse for noise reduction). In this paper we report results related to this claim. In our reported experiments using simulated CT data collection of the head, reconstructions whose shearlet transform has a small ℓ1-norm are not more efficacious than reconstructions that have a small TV value. Our experiments for making such comparisons use the recently-developed superiorization methodology for both regularizing functions. Superiorization is an automated procedure for turning an iterative algorithm for producing images that satisfy a primary criterion (such as consistency with the observed measurements) into its superiorized version that will produce results that, according to the primary criterion are as good as those produced by the original algorithm, but in addition are superior to them according to a secondary (regularizing) criterion. The method presented for superiorization involving the ℓ1-norm of the shearlet transform is novel and is quite general: It can be used for any regularizing function that is defined as the ℓ1-norm of a transform specified by the application of a matrix. Because in the previous literature the split Bregman algorithm is used for similar purposes, a section is included comparing the results of the superiorization algorithm with the split Bregman algorithm.
Effectiveness of the Practice Style and Reciprocal Style of Teaching: A Meta-Analysis

The purpose of this meta-analysis was to examine the effectiveness of Mosston and Ashworth’s (2008) practice and reciprocal styles of teaching on motor skill acquisition of school-age and university students. A systematic search in bibliographical databases led to the identification of 23 relevant studies published in peer-reviewed journals. Using certain methodological and statistical criteria, we retained six studies for further analysis. We estimated proper effect size statistics for each study and teaching style. Heterogeneity of the effect sizes was almost zero for the reciprocal style and moderate to large for the practice style (I 2 > 50%). Both teaching styles appear to produce large effects, with the practice style (mean d = 1.16) having larger effects than the reciprocal style (mean d = 0.94). This meta-analysis provides an overview and synthesis of relevant studies and highlights both teaching styles for increasing K–12 and university students’ motor skill learning. The results are discussed in light of the Spectrum theory. Subscribe to TPE
Kimochis™. Plushy Feely Corp., 11 San Rafael Avenue, San Anselmo, CA 94960

Many studies have shown that children diagnosed with specific language impairment (SLI) have deficits in a variety of social skills (e.g., Fujiki, Brinton, Hart, & Fitzgerald, 1999; Fujiki, Brinton, Isaacson, & Summers, 2001; Fujiki, Brinton, & Todd, 1996). Most of this research has been based on younger children. We are just beginning to learn about the long-term outcomes of persons diagnosed with SLI in childhood (Johnson, Beitchman, & Brownlie, 2010). How might the social deficits observed in children with SLI affect their social interactions, particularly friendships, in adolescence and adulthood? Close friendships require good communication. Through talking, friends share thoughts, emotions, and experiences with each other. As they get older, teenagers spend increasingly more time talking to peers. Communication skills such as initiating interactions, self-disclosure, listening, and responding support the development of intimacy in friendships (Paul & White, 1990). The ability to use language effectively may be important for engaging emotionally in close friendships and romantic relationships. How an individual behaves toward others is also important for close friendships. Prosocial behaviors, such as helping and sharing, are characteristics of high-quality friendships among young people (Berndt, 1982). In contrast, negative behavior, such as aggression, is associated with lowquality friendships (Cillessen, Jiang, West, & Laszkowski, 2005). A tendency toward prosocial behavior should support engagement in close friendships, whereas a tendency toward problem behavior is likely to be a hindrance or barrier. Shyness and sociability also affect social interactions and friendships and are likely to affect close relationships. Shyness inhibits interpersonal communication and the development of A newsletter dedicated to speech & language in school-age children
Behavioral Ethics in Organizations: A Review

The importance of ethical behavior to an organization has never been more apparent, and in recent years researchers have generated a great deal of knowledge about the management of individual ethical behavior in organizations. We review this literature and attempt to provide a coherent portrait of the current state of the field. We discuss individual, group, and organizational influences and consider gaps in current knowledge and obstacles that limit our understanding. We conclude by offering directions for future research on behavioral ethics in organizations.
Effective Feature Selection on Data with Uncertain Labels

Nowadays, various learning technologies are required on uncertain data. As an important pre-processing step in data mining, feature selection needs to consider this vagueness or uncertainty. In this paper, we propose a novel algorithm to evaluate the correlation between features and uncertain class labels on the basis of Hilbert-Schmidt Independence Criterion. Consequently, the features can be ranked according to this criterion. Experimental results on extensive datasets demonstrate the benefits of our method.