Miracle-dz/UniFAR-FTUs huggingface dataset:
Bacterial vaginosis and the effect of intermittent prophylactic treatment with an acid lactate gel.

Intermittent treatment with an acid lactate gel (Lactal, ACO, Sweden) reduced symptoms of bacterial vaginosis (BV) and promoted the reestablishment of the normal vaginal flora of lactobacilli. Forty-two women seriously affected by recurrent BV were initially given acid gel (lactate gel, pH 3.8, 5 ml) to be inserted into the vagina daily for 7 consecutive days. Thereafter they entered into a double blind clinical trial and were treated prophylactically 3 days monthly for 6 months with either lactate gel or a placebo gel. Women treated with the lactate gel were clinically improved, i.e. no signs of BV in 88% compared to 10% in the placebo group (p less than 0.001). The vaginal lactobacilli flora was reestablished in 83% of the lactate group and in 16% of the placebo group. Local intermittent application of lactate gel was found to be free of side effects and is a preferable alternative to repeated treatments with antibiotics in patients with recurrent BV.
Resilient Robots: Concept, Review, and Future Directions

This paper reviews recent developments in the emerging field of resilient robots and the related robots that share common concerns with them, such as self-reconfigurable robots. This paper addresses the identity of the resilient robots by distinguishing the concept of resilience from other similar concepts and summarizes the strategies used by robots to recover their original function. By illustrating some issues of current resilient robots in the design of control systems, physical architecture modules, and physical connection systems, this paper shows several of the possible solutions to facilitate the development of the new and improved robots with higher resilience. The conclusion outlines several directions for the future of this field.
Thermal behavior and dielectric property analysis of boron nitride‐filled bismaleimide‐triazine resin composites

Bismaleimide-triazine (BT) resin/hexagonal boron nitride (h-BN) composites are prepared, and the effects of h-BN content on the thermal and dielectric properties are studied in the view of structure–property relationship. It is found that the introduction of the BN in the BT resin dramatically improve the thermal conductivity of BT resin. The thermal conductivity of the composites is up to 1.11 W/m.K, with an h-BN concentration of 50 wt %, which is increased by six times compared with the pure BT resin. The BT resin/h-BN composites also exhibit excellent thermal properties, with the glass transition temperatures above 200°C, and thermal decomposition temperatures over 390°C. Moreover, the composites possess good dielectric properties. Their dielectric constant and loss tangent (tan δ) are less than 4.5 and 0.015, respectively. The results indicate that the BT resin/h-BN composites are promising as efficient heat-releasing materials in the high-density electronic packaging technology. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013
Check Out This Place: Inferring Ambiance From Airbnb Photos

Airbnb is changing the landscape of the hospitality industry, and to this day, little is known about the inferences that guests make about Airbnb listings. Our work constitutes a first attempt at understanding how potential Airbnb guests form first impressions from images, one of the main modalities featured on the platform. We contribute to the multimedia community by proposing the novel task of automatically predicting human impressions of ambiance from pictures of listings on Airbnb. We collected Airbnb images, focusing on the countries Switzerland and Mexico as case studies, and used crowdsourcing mechanisms to gather annotations on physical and ambiance attributes, finding that agreement among raters was high for most of the attributes. Our cluster analysis showed that both physical and psychological attributes could be grouped into three clusters. We then extracted state-of-the-art features from the images to automatically infer the annotated variables in a regression task. Results show the feasibility of predicting ambiance impressions of homes on Airbnb, with up to 42% of the variance explained by our model, and best results were obtained using activation layers of deep convolutional neural networks trained on the Places dataset, a collection of scene-centric images.
Integrin-Mediated Survival Signals Regulate the Apoptotic Function of Bax through Its Conformation and Subcellular Localization

Most normal cells require adhesion to extracellular matrix for survival, but the molecular mechanisms that link cell surface adhesion events to the intracellular apoptotic machinery are not understood. Bcl-2 family proteins regulate apoptosis induced by a variety of cellular insults through acting on internal membranes. A pro-apoptotic Bcl-2 family protein, Bax, is largely present in the cytosol of many cells, but redistributes to mitochondria after treatment with apoptosis-inducing drugs. Using mammary epithelial cells as a model for adhesion-regulated survival, we show that detachment from extracellular matrix induced a rapid translocation of Bax to mitochondria concurrent with a conformational change resulting in the exposure of its BH3 domain. Bax translocation and BH3 epitope exposure were reversible and occurred before caspase activation and apoptosis. Pp125FAK regulated the conformation of the Bax BH3 epitope, and PI 3-kinase and pp60src prevented apoptosis induced by defective pp125FAK signaling. Our results provide a mechanistic connection between integrin-mediated adhesion and apoptosis, through the kinase-regulated subcellular distribution of Bax.
Modifying emotion recognition deficits in body dysmorphic disorder: an experimental investigation

Background: Individuals with body dysmorphic disorder (BDD) are characterized by excessive concerns about perceived defects or flaws in their appearance, most commonly, facial features. Previous research has shown that BDD sufferers, relative to mentally healthy controls, are characterized by emotion recognition deficits (particularly a bias to misinterpret neutral facial expressions in a negative way). It remains an open question though whether these deficits can be modified through specific training programs. Methods: To address this question, we evaluated emotion recognition among individuals with BDD (n = 34), individuals with a dermatological condition (n = 34), and mentally healthy control participants (n = 34) before and after a single‐session emotion recognition training program. Results: As expected, BDD participants were overall significantly worse in identifying neutral expressions, relative to the other groups, whereas no difference was obtained between the dermatology and control groups. Further, with respect to neutral and scared expressions, BDD participants improved significantly more in the training condition, relative to the nontraining condition. Conclusion: There is initial evidence that deficits in recognizing neutral and scared expressions can be normalized through a specific training program when evaluated immediately after the training session. It needs to be addressed in future research whether emotion recognition training programs can diminish these deficits on the long term, and how improved emotion recognition might be related to BDD's symptom reduction such as decreased avoidance behaviors in social situations. Depression and Anxiety, 2011. © 2011 Wiley Periodicals, Inc.
Stem Cell Dynamics in an Experimental Model of Stroke

We investigated the migration of endogenous neural stem cells (NSCs) toward an infarct lesion in a photo-thrombotic stroke model. The lesions produced by using rose bengal dye (20 mg/kg) with cold light in the motor cortex of Sprague-Dawley rats were also evaluated with sequential magnetic resonance imaging (MRI) from 30 minutes through 8 weeks. Migration of NSCs was identified by immunohistochemistry for nestin monoclonal antibody in the lesion cortex, subventricular zone (SVZ), and corpus callosum (CC). The contrast to noncontrast ratio (CNR) on MRI was greatest at 12 hours in DWI and decreased over time. By contrast, T1-weighted and T2-weighted images showed a constant CNR from the beginning through 8 weeks. MRI of the lesional cortex correlated with histopathologic findings, which could be divided into three stages: acute (edema and necrosis) within 24 hours, subacute (acute and chronic inflammatory cell infiltration) at 2 to 7 days, and chronic (gliofibrosis) at 2 to 4 weeks. The volume of the infarct was significantly reduced by reparative gliofibrosis. The number of nestin+ NSCs in the contralateral SVZ was similar to that of the ipsilateral SVZ in each group. However, the number of nestin+ NSCs in the ipsilateral cortex and CC increased at 12 hours to 3 days compared with the contralateral side (p<0.01) and was reduced significantly by 7 days (p<0.01). Active emigration of internal NSCs from the SVZ toward the infarct lesion may also contribute to decreased volume of the infarct lesion, but the self-repair mechanism by endogenous NSCs is insufficient to treat stroke causing extensive neuronal death. Further studies should be focused on amplification technologies of NSCs to enhance the collection of endogenous or transplanted NSCs for the treatment of stroke.
The feature of preventable adverse events in hospitals in the State of Rio de Janeiro , Brazil q

Objective: To analyze the features of preventable adverse events (AEs) in hospitals inpatient in the state of Rio de Janeiro, in Brazil, in order to identify elements to serve as a substrate for priority actions aimed at improving patient safety. Methods: Analysis of data from a baseline retrospective cohort study to assess the incidence of AEs in a sample of records in three teaching hospitals in the State of Rio de Janeiro to describe the features of preventable AEs. Results: In a sample of 1,103 patients, were identified 65 preventable AEs of 56 patients who suffered preventable AEs. The healthcare associated infections (HAI) accounted for 24.6% of preventable AEs; surgical complications and/or anesthetic, 20.0%; damages arising from delay or failure in diagnosis and/or treatment, 18.4%; pressure ulcers, 18.4%; damage from complications of venipuncture, 7.7%; damage due to falls, 6.2%; damage as a result of the use of drugs, 4.6%. The preventable AEs were responsible for additional 373 days of hospital stay. Conclusion: The HAI is the major preventable AE, as observed in other developing countries. Despite the limitations of the study, the characterization of preventable AEs indicates that known and effective actions available to reduce HAI, such as hand hygiene, to prevent pressure ulcers, to encourage adherence to protocol and clinical guidelines and to create continuing education programs for health professionals, should compose the list of priorities of hospital managers and health professionals involved in the care of hospitalized patients. © 2013 Elsevier Editora Ltda. All rights reserved. 422 REV ASSOC MED BRAS. 2013;59(5):421-428 Características de eventos adversos evitáveis em hospitais do Rio de Janeiro
Surgical Results After Preoperative Chemoradiation Therapy for Patients With Pancreatic Cancer

Objectives: The results of surgical therapy alone for pancreatic cancer are disappointing. We explored surgical results after neoadjuvant chemoradiation therapy (NACRT) for patients with pancreatic cancer that extended beyond the pancreas. Methods: Sixty-eight consecutive patients with pancreatic cancer who underwent pancreatic resection were included. Twenty-seven patients underwent surgical resection after NACRT (NACRT group). The other 41 patients were classified as surgery-alone group. Surgical results were compared in patients who underwent curative resection (R0/1) who were followed up for at least 25 months and underwent no adjuvant therapy. Results: A lower frequency of lymph node metastasis was observed in the NACRT group (P < 0.05). The frequency of residual tumor grading in the NACRT group was significantly different from that in surgery-alone (R0/1/2%, 52/15/33 vs 22/51/27; P = 0.0040). In R0/1 cases, overall survival and disease-free survival rates in the NACRT group (n = 18) were significantly longer than in surgery-alone (n = 30, P < 0.05). The rate of local recurrence in the NACRT group was significantly less than in surgery-alone (11% vs 47%, P = 0.0024). Conclusions: This single-institution experience indicates that NACRT is able to increase the resectability rate with clear margins and to decrease the rate of metastatic lymph nodes, resulting in improved prognosis of curative cases with pancreatic cancer that extended beyond the pancreas.
The RIG‐I‐like receptor LGP2 inhibits Dicer‐dependent processing of long double‐stranded RNA and blocks RNA interference in mammalian cells

In vertebrates, the presence of viral RNA in the cytosol is sensed by members of the RIG‐I‐like receptor (RLR) family, which signal to induce production of type I interferons (IFN). These key antiviral cytokines act in a paracrine and autocrine manner to induce hundreds of interferon‐stimulated genes (ISGs), whose protein products restrict viral entry, replication and budding. ISGs include the RLRs themselves: RIG‐I, MDA5 and, the least‐studied family member, LGP2. In contrast, the IFN system is absent in plants and invertebrates, which defend themselves from viral intruders using RNA interference (RNAi). In RNAi, the endoribonuclease Dicer cleaves virus‐derived double‐stranded RNA (dsRNA) into small interfering RNAs (siRNAs) that target complementary viral RNA for cleavage. Interestingly, the RNAi machinery is conserved in mammals, and we have recently demonstrated that it is able to participate in mammalian antiviral defence in conditions in which the IFN system is suppressed. In contrast, when the IFN system is active, one or more ISGs act to mask or suppress antiviral RNAi. Here, we demonstrate that LGP2 constitutes one of the ISGs that can inhibit antiviral RNAi in mammals. We show that LGP2 associates with Dicer and inhibits cleavage of dsRNA into siRNAs both in vitro and in cells. Further, we show that in differentiated cells lacking components of the IFN response, ectopic expression of LGP2 interferes with RNAi‐dependent suppression of gene expression. Conversely, genetic loss of LGP2 uncovers dsRNA‐mediated RNAi albeit less strongly than complete loss of the IFN system. Thus, the inefficiency of RNAi as a mechanism of antiviral defence in mammalian somatic cells can be in part attributed to Dicer inhibition by LGP2 induced by type I IFNs. LGP2‐mediated antagonism of dsRNA‐mediated RNAi may help ensure that viral dsRNA substrates are preserved in order to serve as targets of antiviral ISG proteins.
Can Network Embedding of Distributional Thesaurus Be Combined with Word Vectors for Better Representation?

Distributed representations of words learned from text have proved to be successful in various natural language processing tasks in recent times. While some methods represent words as vectors computed from text using predictive model (Word2vec) or dense count based model (GloVe), others attempt to represent these in a distributional thesaurus network structure where the neighborhood of a word is a set of words having adequate context overlap. Being motivated by recent surge of research in network embedding techniques (DeepWalk, LINE, node2vec etc.), we turn a distributional thesaurus network into dense word vectors and investigate the usefulness of distributional thesaurus embedding in improving overall word representation. This is the first attempt where we show that combining the proposed word representation obtained by distributional thesaurus embedding with the state-of-the-art word representations helps in improving the performance by a significant margin when evaluated against NLP tasks like word similarity and relatedness, synonym detection, analogy detection. Additionally, we show that even without using any handcrafted lexical resources we can come up with representations having comparable performance in the word similarity and relatedness tasks compared to the representations where a lexical resource has been used.
Dapagliflozin is associated with lower risk of cardiovascular events and all‐cause mortality in people with type 2 diabetes (CVD‐REAL Nordic) when compared with dipeptidyl peptidase‐4 inhibitor therapy: A multinational observational study

To compare the sodium‐glucose‐cotransporter‐2 (SGLT‐2) inhibitor dapagliflozin with dipeptidyl peptidase‐4 (DPP‐4) inhibitors with regard to risk associations with major adverse cardiovascular (CV) events (MACE; non‐fatal myocardial infarction, non‐fatal stroke or cardiovascular mortality), hospitalization for heart failure (HHF), atrial fibrillation and severe hypoglycaemia in patients with type 2 diabetes (T2D) in a real‐world setting.
Open Access Research an Exploratory Study of Engagement in a Technology-supported Substance Abuse Intervention

article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: The continuing gap between the number of people requiring treatment for substance use disorders and those receiving treatment suggests the need to develop new approaches to service delivery. Meanwhile, the use of technology to provide counseling and support in the substance abuse field is exploding. Despite the increase in the use of technology in treatment, little is known about the impact of technology-supported interventions on access to services for substance use disorders. The E-TREAT intervention brings together the evidence-based practice of Motivational Interviewing and theories of Persuasive Technology to sustain clients' motivation to change substance use behaviors, provide support for change, and facilitate continuity across treatment settings. Methods: This study used descriptive statistics, tests of statistical significance, and logistic regression to explore the characteristics and perceptions of the first 157 people who agreed to participate in E-TREAT and the predictors of their active engagement in E-TREAT services. In addition, responses to open-ended questions about the participants' experiences with the intervention were analyzed. Results: The data reveal that clients who engaged in E-TREAT were more likely than those who did not engage to be female, have children and report a positive relationship with their recovery coach, and were less likely to have completed treatment for a substance use disorder in the past. A majority of people engaging in E-TREAT reported that it was helpful to talk with others with similar problems and that the program assisted them in developing a sense of community. Conclusions: The authors conclude that technology-assisted interventions hold promise in expanding access to treatment for substance use disorders especially for women and parents. Further, the characteristics of the relationship with a coach or helper may be critical to engagement in technology-supported interventions. Additional investigation into ways technology may be useful to enhance treatment access for certain subgroups is needed. Background Nationally, the demand for substance use disorder treatment in publicly funded systems far exceeds the available capacity. In 2008, over 20 million people who needed treatment for alcohol or illicit drug abuse or dependence were unable to access this needed service [1]. As a result of this gap between treatment demand and capacity, providers often establish waiting lists. Moreover, the motiva
Extracting relevant named entities for automated expense reimbursement

Expense reimbursement is a time-consuming and labor-intensive process across organizations. In this paper, we present a prototype expense reimbursement system that dramatically reduces the elapsed time and costs involved, by eliminating paper from the process life cycle. Our complete solution involves (1) an electronic submission infrastructure that provides multi- channel image capture, secure transport and centralized storage of paper documents; (2) an unconstrained data mining approach to extracting relevant named entities from un-structured document images; (3) automation of auditing procedures that enables automatic expense validation with minimum human interaction. Extracting relevant named entities robustly from document images with unconstrained layouts and diverse formatting is a fundamental technical challenge to image-based data mining, question answering, and other information retrieval tasks. In many applications that require such capability, applying traditional language modeling techniques to the stream of OCR text does not give satisfactory result due to the absence of linguistic context. We present an approach for extracting relevant named entities from document images by combining rich page layout features in the image space with language content in the OCR text using a discriminative conditional random field (CRF) framework. We integrate this named entity extraction engine into our expense reimbursement solution and evaluate the system performance on large collections of real-world receipt images provided by IBM World Wide Reimbursement Center.
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data

Several important applications, such as streaming PCA and semidefinite programming, involve a large-scale positive-semidefinite (psd) matrix that is presented as a sequence of linear updates. Because of storage limitations, it may only be possible to retain a sketch of the psd matrix. This paper develops a new algorithm for fixed-rank psd approximation from a sketch. The approach combines the Nystrom approximation with a novel mechanism for rank truncation. Theoretical analysis establishes that the proposed method can achieve any prescribed relative error in the Schatten 1-norm and that it exploits the spectral decay of the input matrix. Computer experiments show that the proposed method dominates alternative techniques for fixed-rank psd matrix approximation across a wide range of examples.
Recommendations : Modeling Music Ratings with Temporal Dynamics and Item Taxonomy

In the past decade large scale recommendation datasets were published and extensively studied. In this work we describe a detailed analysis of a sparse, large scale dataset, specifically designed to push the envelope of recommender system models. The Yahoo! Music dataset consists of more than a million users, 600 thousand musical items and more than 250 million ratings, collected over a decade. It is characterized by three unique features: First, rated items are multi-typed, including tracks, albums, artists and genres; Second, items are arranged within a four level taxonomy, proving itself effective in coping with a severe sparsity problem that originates from the unusually large number of items (compared to, e.g., movie ratings datasets). Finally, fine resolution timestamps associated with the ratings enable a comprehensive temporal and session analysis. We further present a matrix factorization model exploiting the special characteristics of this dataset. In particular, the model incorporates a rich bias model with terms that capture information from the taxonomy of items and different temporal dynamics of music ratings. To gain additional insights of its properties, we organized the KddCup-2011 competition about this dataset. As the competition drew thousands of participants, we expect the dataset to attract considerable research activity in the future.