Miracle-dz/UniFAR-FTUs huggingface dataset:
Association between Human Papillomavirus and Non-cervical Genital Cancers in Brazil: A Systematic Review and Meta-Analysis

Background: Human papillomavirus (HPV) infection is associated with cervical cancer; however, it is controversial whether it is involved in non-cervical genital cancers. Objective: This study aimed to evaluate articles on the prevalence of HPV in penile cancer, vulvar cancer, colorectal cancer, prostate cancer and anal canal cancer in studies conducted in Brazil. Methods: The study was conducted in accordance with the Preferred Reporting of Systematic Reviews and Meta-Analysis Statement. Comprehensive searches for HPV and cancer for the years 2006 to 2016 were conducted in two databases (PubMed and Web of Knowledge) and Google Scholar system. We also tracked the references of all eligible articles to identify additional non-captured publications through online surveys. Results: Eighteen studies, with a combined sample size of 1,552 patients were analyzed. The overall prevalence of HPV was 43% (95% CI: 36–51%; p < 0.001). The pooled prevalence of HPV in penile cancer was 42% (95% CI: 32–55%; p < 0.001), in colorectal cancer it was 67% (95% CI: 64–70%; p < 0.001) and in vulvar cancer 43% (95% CI: 34–55%; p < 0.001). HPV 16 was the most prevalent in all sites evaluated, with prevalence estimated at 54% (95% CI: 44–66%; p < 0.001), followed by genotypes 33 (21%; 95% CI: 17–28; p < 0.001), 6 (15%; 95% CI: 8–26%; p < 0.001), 11 (13%; 95% CI: 5–32%; p < 0.001) and 18 (12%; 95% CI: 7–22%; p < 0.001), respectively. The pooled prevalence of single infection was 82% and infection by multiple genotypes of HPV was 22%. Conclusion: Our study demonstrated a high prevalence of HPV in non-cervical genital cancers in Brazil, with predominance of genotype 16, providing evidence for the need for preventive and control measures to avoid future harm to the population.
Machine Learning Based Classification of Colorectal Cancer Tumour Tissue in Whole-Slide Images

The recent introduction of whole-slide scanning systems enabled accumulation of highquality pathology images into large collections, thus opening new perspectives in cancer research, as well as new analysis challenges. Automated identification of tumour tissue in the whole-slide image enables further use of developed grading systems that classify tumour cell abnormalities and predict tumour developments. In this article, we describe several possibilities to achieve epithelium-stroma classification of tumour tissues in digital pathology images by employing annotated superpixels to train machine learning algorithms. We emphasize that annotating superpixels rather than manually outlining tissue classes in raw images is less time consuming, and more effective way of producing ground truth for computational pathology pipelines. In our approach feature space for supervised learning is created from tissue class assigned superpixels by extracting colour and texture parameters, and applying dimensionality reduction methods. Alternatively, to train convolutional neural network, labelled superpixels are used to generate square image patches by moving fixed size window around each superpixel centroid. The proposed method simplifies the process of ground truth data collection and should minimize the time spent by a skilled expert to perform manual annotation of whole-slide images. We evaluate our method on a private data set of colorectal cancer images. Obtained results confirm that a method produces accurate reference data suitable for the use of different machine learning based classification algorithms.
The mammalian mycobiome: A complex system in a dynamic relationship with the host

Mammalian barrier surfaces are densely populated by symbiont fungi in much the same way the former are colonized by symbiont bacteria. The fungal microbiota, otherwise known as the mycobiota, is increasingly recognized as a critical player in the maintenance of health and homeostasis of the host. Here we discuss the impact of the mycobiota on host physiology and disease, the factors influencing mycobiota composition, and the current technologies used for identifying symbiont fungal species. Understanding the tripartite interactions among the host, mycobiota, and other members of the microbiota, will help to guide the development of novel prevention and therapeutic strategies for a variety of human diseases.
Interpersonal Closeness Correlates With Social Influence on Color Perception Task Using Human and Artificial Agents

It is well known that artificial agents, such as robots, can potentially exert social influence and alter human behavior in certain situations. However, it is still unclear what specific psychological factors enhance the social influence of artificial agents on human decision-making. In this study, we performed an experiment to investigate what psychological factors predict the degree to which human partners versus artificial agents exert social influence on human beings. Participants were instructed to make a decision after a partner agent (human, computer, or android robot) answered the same question in a color perception task. Results indicated that the degree to which participants conformed to the partner agent positively correlated with their perceived interpersonal closeness toward the partner agent. Moreover, participants’ responses and accompanying error rates did not differ as a function of agent type. The current findings contribute to the design of artificial agents with high social influence.
Children With Cerebral Palsy Playing With Mainstream Robotic Toys: Playfulness and Environmental Supportiveness

Purpose: Play is a right for every child and has a key role in child development. Play can be analyzed according to the construct of playfulness, which is the child’s disposition to play. Children with cerebral palsy (CP) show difficulties in play and can also experience lower playfulness scores when compared to matched typically developing children. This paper analyses play and playfulness in children with CP using mainstream robotic toys with supporting adult play partners. Methodology: Five mainstream robotic toys were selected and used in play situations with six children with CP interacting with two adult partners. The play situations were coded through the Test of Playfulness (ToP) and the Test of Environmental Supportiveness (ToES), to analyze the role of robotic toys, adult partners and environment in supporting play and playfulness in children with CP. Results: The children obtained high ToP scores, showing that they were intrinsically motivated to be engaged in the play situations. The ToP scores weakly correlated with the ToES scores. To discuss this result, different features of each robot, the role of adults as scaffolder, and the space characteristics in supporting play are presented and discussed. Conclusion: This research field is new: to our knowledge, in the literature only one study focused on the use of one type of mainstream robotic toy to support the playfulness of children with CP. The parallel use of the ToP and the ToES was crucial to observe the complexity of the play situations and the role of playmates and toys during the play process. The role of the adult as play scaffolder has been important to mediate between the child with CP and the environment, toys included: the adult should be strongly aware of this role to better support the child in being in charge of the play situation. Further research is needed.
What Works in Facebook Content Versus Relational Communication: A Study of their Effectiveness in the Context of Museums

ABSTRACT This study aims to evaluate the effectiveness of museums’ communication strategy in Facebook. This research conducts two empirical studies: in the first, we analyze the communication strategies of 240 museum Facebook pages and their effect on engagement at a fan page level; in the second, we explore the communication strategy in each post in greater depth in order to gauge how the different content and relational elements contribute to increasing the number of likes, comments, and shares. The findings highlight that achieving user engagement entails developing a strategy based on content as well as the museum’s relationship and dialog with its audience, to the point where it becomes involved in conversations. This study proposes that if a museum is seeking an audience’s active participation in its communications, then the organization itself should also get involved in users’ conversations. Put differently, engagement should be reciprocal if more effective communication is to be achieved.
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Existing question answering (QA) datasets fail to train QA systems to perform complex reasoning and provide explanations for answers. We introduce HotpotQA, a new dataset with 113k Wikipedia-based question-answer pairs with four key features: (1) the questions require finding and reasoning over multiple supporting documents to answer; (2) the questions are diverse and not constrained to any pre-existing knowledge bases or knowledge schemas; (3) we provide sentence-level supporting facts required for reasoning, allowing QA systems to reason with strong supervision and explain the predictions; (4) we offer a new type of factoid comparison questions to test QA systems’ ability to extract relevant facts and perform necessary comparison. We show that HotpotQA is challenging for the latest QA systems, and the supporting facts enable models to improve performance and make explainable predictions.
THE EVALUATION OF PHYSICS STUDENTS' PROBLEM-SOLVING ABILITY THROUGH MAUVE STRATEGY (MAGNITUDE, ANSWER, UNITS, VARIABLES, AND EQUATION)

Problem-solving ability is very important to be developed in the process of learning physics especially in understanding the material of physics, both in concept, procedure analyses, and mathematical calculation. MAUVE strategy can help students as well as teachers in evaluating the extent to which students understand the concept of physics in accordance with the stages of problem-solving. The significance of this study are exploiting the way teachers to assess students' work in solving physics problems through MAUVE strategy and knowing physics students' problem-solving skills which were evaluated with the rubric developed by MAUVE. This paper applies descriptive quantitative research. The data collection uses test, observation, and interview. The result of this study is that MAUVE strategy facilitates teachers and students in evaluating problems on the physics material. Students can evaluate themselves about what deficiencies need to be improved in solving physics problems. For teachers, MAUVE is one of the easiest strategies to resolve problem-solving skills, so it needs to be evaluated for what needs to be improved. MAUVE strategy needs to be further developed on other topics of physics.
MRI-Based Mapping of Cerebral Propagation in Amyotrophic Lateral Sclerosis

Neuropathological studies revealed the propagation of amyotrophic lateral sclerosis (ALS) in a sequence of four separate disease-related regional patterns. Diffusion tensor imaging (DTI)-based analysis was established for the individual mapping of sequential disease spreading in ALS as the in vivo transfer to neuroimaging. The aim of this review is to summarize cross-sectional and longitudinal results of these technical approaches in ALS as an in vivo tool to image ALS propagation stages. This concept was also applied to restricted phenotypes of ALS, e.g., lower motor neuron disease (LMND) or primary lateral sclerosis (PLS). In summary, the regional disease patterns in the course of ALS have been successfully mapped by DTI in vivo both cross-sectionally and longitudinally so that this technique might have the potential as a read-out in clinical trials.
Aortic branch vessel flow during resuscitative endovascular balloon occlusion of the aorta

BACKGROUND Resuscitative endovascular balloon occlusion of the aorta (REBOA) is a torso hemorrhage control adjunct. Aortic branch vessel flow (BVF) during REBOA is poorly characterized and has implications for ischemia-reperfusion injury. The aim of this study is to quantify BVF in hypovolemic shock with and without REBOA. METHODS Female swine (79–90 kg) underwent anesthesia, 40% controlled hemorrhage and sonographic flow monitoring of the carotid, hepatic, superior mesenteric, renal, and femoral arteries. Animals were randomized to REBOA (n = 5) or no-REBOA (n = 5) for 4 hours, followed by full resuscitation and balloon deflation for 1 hour. RESULTS All animals were successfully induced into hemorrhagic shock with a mean decrease of flow in all vessels of 50% from baseline (p < 0.001). Deployment of REBOA resulted in a 200% to 400% increase in carotid flow, but near complete abolition of BVF distal to the balloon. The no-REBOA group saw recovery of BVF to 100% of baseline in all measured vessels, except the hepatic at 50% to 75%. two-way analysis of variance confirmed a significant difference between the groups throughout the protocol (p < 0.001). During resuscitation, the REBOA group saw BVF restore to between 25% and 50%, but never achieving baseline values. The lactate at 4 hours was significantly higher in the REBOA versus no-REBOA group (17.2 ± 0.1 vs. 4.9 ± 1.4; p < 0.001). CONCLUSION REBOA not only abolishing BVF during occlusion, but appears to have a post-REBOA effect, reducing visceral perfusion. This may be a source of REBOA associated ischemia-reperfusion injury and warrants further investigation in order to mitigate this effect.
SOURCE: Sheridan Scholarly Output, Research, and Creative SOURCE: Sheridan Scholarly Output, Research, and Creative Excellence Excellence

Current trends in society and technology make the concept of interruption a central human computer interaction problem. In this work, a novel soft computing implementation for an Interruption Classi ﬁ er was designed, developed and evaluated that draws from a user model and real-time observations of the user's actions as s/he works on computer-based tasks to determine ideal times to interact with the user. This research is timely as the number of interruptions people experience daily has grown considerably over the last decade. Thus, systems are needed to manage interruptions by reasoning about ideal timings of interactions. This research shows: (1) the classi ﬁ er incorporates a user model in its ’ reasoning process. Most of the research in this area has focused on task-based contextual information when designing systems that reason about interruptions; (2) the classi ﬁ er performed at 96% accuracy in experimental test scenarios and signi ﬁ cantly out-performed other comparable systems; (3) the classi ﬁ er is implemented using an advanced machine learning technology — an Adaptive Neural-Fuzzy Inference System — this is unique since all other systems use Bayesian Networks or other machine learning tools; (4) the classi ﬁ er does not require any direct user involvement — in other systems, users must provide interruption annotations while reviewing video sessions so the system can learn; and (5) a promising direction for reasoning about interruptions for free-form tasks – this is largely an unsolved problem.
Low Precision Policy Distillation with Application to Low-Power, Real-time Sensation-Cognition-Action Loop with Neuromorphic Computing

Low precision networks in the reinforcement learning (RL) setting are relatively unexplored because of the limitations of binary activations for function approximation. Here, in the discrete action ATARI domain, we demonstrate, for the first time, that low precision policy distillation from a high precision network provides a principled, practical way to train an RL agent. As an application, on 10 different ATARI games, we demonstrate real-time end-to-end game playing on low-power neuromorphic hardware by converting a sequence of game frames into discrete actions.
Metagenomic analysis of intestinal mucosa revealed a specific eukaryotic gut virome signature in early-diagnosed inflammatory bowel disease

ABSTRACT Intestinal dysbiosis is one of the causes underlying the pathogenesis of inflammatory bowel disease (IBD), encompassing ulcerative colitis (UC) and Crohn’s disease (CD). Besides bacteria, microbiota comprises both prokaryotic and eukaryotic viruses, that together compose the gut virome. Few works have defined the viral composition of stools, while the virome populating intestinal mucosae from early-diagnosed IBD patients has never been studied. Here we show that, by in-depth metagenomic analysis of RNA-Seq data obtained from gut mucosae of young treatment-naïve patients, early-diagnosed for CD and UC, and from healthy subjects (Ctrl), UC patients display significantly higher levels of eukaryotic Hepadnaviridae transcripts by comparison with both Ctrl and CD patients, whereas CD patients show increased abundance of Hepeviridae versus Ctrl. Moreover, we found that UC gut mucosa is characterized by lower levels of Polydnaviridae and Tymoviridae, whereas the mucosa of patients with CD showed a reduced abundance of Virgaviridae. Our findings support the idea that certain eukaryotic viruses might trigger intestinal inflammation and contribute to IBD pathogenesis and pave the way not only for the discovery of novel diagnostic biomarkers but also for the development of anti-viral drugs for the treatment of IBD.
Longitudinal structural brain development and externalizing behavior in adolescence

Background Cross‐sectional studies report relations between externalizing behavior and structural abnormalities in cortical thickness of prefrontal regions and volume reductions in subcortical regions. To understand how these associations emerge and develop, longitudinal designs are pivotal. Method In the current longitudinal study, a community sample of children, adolescents and young adults (N = 271) underwent magnetic resonance imaging (MRI) in three biennial waves (680 scans). At each wave, aspects of externalizing behavior were assessed with parent‐reported aggression and rule‐breaking scores (Child Behavior Checklist), and self‐reported aggression scores (Buss‐Perry Aggression Questionnaire). Regions of interest (ROIs) were selected based on prior research: dorsolateral prefrontal (dlPFC), orbitofrontal (OFC), anterior cingulate cortex (ACC), insula, and parahippocampal cortex, as well as subcortical regions. Linear mixed models were used to assess the longitudinal relation between externalizing behavior and structural brain development. Structural covariance analyses were employed to identify whether longitudinal relations between ROIs (maturational coupling) were associated with externalizing behavior. Results Linear mixed model analyses showed a negative relation between parent‐reported aggression and right hippocampal volume. Moreover, this longitudinal relation was driven by change in hippocampal volume and not initial volume of hippocampus at time point 1. Exploratory analyses showed that stronger maturational coupling between prefrontal regions, the limbic system, and striatum was associated with both low and high externalizing behavior. Conclusions Together, these findings reinforce the hypothesis that altered structural brain development coincides with development of more externalizing behavior. These findings may guide future research on normative and deviant development of externalizing behavior.
Clonal evolution through genetic bottlenecks and telomere attrition: Potential threats to in vitro data reproducibility

Tissue cultures of immortalized human cells, also known as established cell lines, are broadly accessible and cost‐efficient tools for biomedical research. We here review potential genetic sources of systematic error in cell line experiments due to clonal evolution in vitro. In particular, the authors highlight alterations in telomere function over prolonged culture and population bottlenecks, respectively, as two commonly overlooked phenomena that can result in significant alterations in cell line genotypes over just one or a few passages in vitro. These alterations may include changes in mutation status of oncogenes and large scale chromosomal imbalances. We introduce a simple list of factors to be avoided in order to reduce the risk of data misinterpretation due to clonal evolution, including unacknowledged in vitro selection pressures, prolonged culture per se, harsh population size reductions, experiments at early phases after establishment, and the employment of cell lines not sufficiently analyzed by high resolution genetic techniques.
Inter-institutional variability of small-field-dosimetry beams among HD120™ multileaf collimators: a multi-institutional analysis

Detector selection and technical problems can result in large variations in small-field-dosimetry data among institutions. In this study, we evaluated inter-institutional variability in the small-field-beam data of the Novalis Tx linear accelerator (Varian Medical Systems and BrainLAB) with an HD120™ multileaf collimator. Beam data for modeling an iPLAN treatment planning system (BrainLAB) were collected from 19 institutions and median values of percentage depth doses (PDD), diagonal profiles, transversal profiles, and ratios of detector readings (detector output factors; OFdet) were calculated. Inter-institutional variability was defined as the difference between the median value and the value for each machine. PDD measured with a 100 mm square field size and diagonal profiles showed only small variations; however, when measured with a 5 mm square field size, the PDD variation from the median exceeded ±2%, especially for ionization chambers. With a 10 mm square field, the variation was within approximately ±1%. The OFdet variation was within ±2% for ⩾20 mm square field sizes. The maximum variation exceeded 20% for 5 mm square fields. The ionization chambers’ OFdet values were smaller than the median, whereas those for the EDGE detector (Sun Nuclear Corp) were larger. When the OFdet values were corrected by output factor correction factors, the variation was greatly reduced, with only a few machines showing variations greater than ±5% from the median value. In conclusion, this multi-institutional investigation of small field dosimetry for HD120 multileaf collimators demonstrated some large variations in the dosimetric parameters, especially for a 5 mm square field size. Most differences were detector-dependent, and the variation was reduced when output correction factors were applied. However, variations probably due to measurement errors were also observed, indicating that careful management is needed for small-field dosimetry.