Miracle-dz/UniFAR-FTUs huggingface dataset:
Sonographic examination of the fetal central nervous system: guidelines for performing the ‘basic examination’ and the ‘fetal neurosonogram’

Central nervous system (CNS) malformations are some of the most common of all congenital abnormalities. Neural tube defects are the most frequent CNS malformations and amount to about 1–2 cases per 1000 births. The incidence of intracranial abnormalities with an intact neural tube is uncertain as probably most of these escape detection at birth and only become manifest in later life. Long-term follow-up studies suggest however that the incidence may be as high as one in 100 births1. Ultrasound has been used for nearly 30 years as the main modality to help diagnose fetal CNS anomalies. The scope of these guidelines is to review the technical aspects of an optimized approach to the evaluation of the fetal brain in surveys of fetal anatomy, that will be referred to in this document as a basic examination. Detailed evaluation of the fetal CNS (fetal neurosonogram) is also possible but requires specific expertise and sophisticated ultrasound machines. This type of examination, at times complemented by three-dimensional ultrasound, is indicated in pregnancies at increased risk of CNS anomalies. In recent years fetal magnetic resonance imaging (MRI) has emerged as a promising new technique that may add important information in selected cases and mainly after 20–22 weeks2,3, although its advantage over ultrasound remains debated4,5.
Learning Disability

The study of learning disability represents a special case of the study of mind (see Note 1). As such —and without wishing to invoke age-old arguments about materialism, reductionism, or dualism, but rather to consider the study of learning disability as a legitimate concern of modern biology—multiple approaches are preferred. The concept of multiple approaches is accepted over that of any single approach with the understanding that no approach is considered to be inherently superior to another, and that the decision about what approach to take depends on the purpose of the particular research as well as the intellectual bent the individual researcher finds most appealing. Some, for instance, prefer to describe behavior in terms of memory, syntax, and perception, while others are happier with concepts like synaptic facilitation, axonal depolarization, and genomic transcription. And, in the light of the present discussion, some would prefer to understand reading problems in terms of classroom size and composition, or graphemic-phonemic correspondences and phonological awareness, or even in terms of developmental plasticity and interhemispheric relationships. Most would require, however, that any approach be scientific and, moreover, compatible with the eventual goal of understanding the descriptive language of one in terms of the language of another. Science, after all, advances by consensus, and the agreement about a topic among workers in widely different disciplines represents the best type of consensus.
Ecologia e comportamento de Alouatta belzebul (Primates: cebidae) na mata atlantica

Ecological and behavioral observations of Aiouatta belzebul were made from February 1985 to April 1986 in a 271 ha patch of Atlantic forest at Pacatuba farm, 10 Km NE of Sape state of Paraiba, Brazil. The home range of the group covered an area of 9,5 ha. Its size was evidently associated with food availability. Sleeping trees, two defecation sites and a large number of food trees were restricted to a core area. Travel routes were fixed in this area but the rest of the range was used in rotation. Instantaneous Scan Sampling was used to study the daily activity patterns. Seasonal variation of environmental conditions influenced these patterns. In this particular forest, howling monkeys are mainly frugivorous, possibly because fruits are available all year round. There is a seasonal variation in the diet. During the study A. belzebul fed on 47 plant species, being a seed disperser for at least 12 and possibly 21 species of fruits and a seed predator for at least five others.
Estimation of recent changes in thickness and mass balance of the Patsio glacier in the Great Himalayan region using geodetic technique and ancillary data

Abstract An understanding of glacier mass budget in the Himalayas is important for regional water resource management. This study presents a detailed estimation of mass budget of the Patsio glacier (The Great Himalaya) using SRTM-X (2000), Cartosat-1 (2005) and TanDEM-X (2013) DEMs. Geodetic findings indicate an overall mass loss by −0.26±0.11 m.w. e/yr,−0.30±0.10 m.w. e/yr and −0.16±0.11 m.w. e/yr during 2000-2013, 2000-2005 and 2005–2013 respectively. Maximum downwasting was observed in the terminus area of the glacier during the period 2000–2013. The observed lower rate of mass loss between 2005 and 2013 was attributed to declining temperature during that period. However, long-term temperature trends depict warming, so was exhibited by mass loss during 2000–2013. Geodetic based findings were found to be concordant with GPR based estimation. This study confirms the suitability of geodetic mass balance technique for mountainous glaciers, which will be useful to evaluate future changes in the glacial extent and runoff study.
Compensation Incentives of Credit Rating Agencies and Predictability of Changes in Bond Ratings and Financial Strength Ratings

Over the past decade there has been mixed evidence on the lead–lag relation between issuer-paid and investor-paid credit rating agencies. We investigate the lead–lag relationship for changes in bond ratings (BRs) and financial strength ratings (FSRs), for the US insurance industry, where FSRs impose market discipline. First, we find that changes in issuer-paid BRs are led by changes in investor-paid BRs, even over a period that issuer-paid agencies have improved their timeliness. Second, information flows in both directions between changes in issuer-paid BRs and FSRs. Third, issuer-paid FSRs are predictable by investor-paid BRs. Fourth, the lead effect of investor-paid downgrades is economically significant as it is associated with an unconditional, post-event, 30-day cumulative abnormal return of −4%. This return is a result of investor-paid downgrades in BRs, which predict more downgrades in the following 90days (same period return of −11%).
Female Bicyclus anynana butterflies choose males on the basis of their dorsal UV-reflective eyespot pupils

Sexual and natural selection pressures are thought to shape the characteristic wing patterns of butterfly species. Here we test whether sexual selection by female choice plays a role in the maintenance of the male wing pattern in the butterfly Bicyclus anynana. We perform one of the most extensive series of wing pattern manipulations in butterflies, dissecting every component of the ‘bulls-eye’ eyespot patterns in both ventral and dorsal wing surfaces of males to test the trait's appeal to females. We conclude that females select males on the basis of the size and brightness of the dorsal eyespot's ultraviolet reflecting pupils. Pupil absence is strongly selected against, as are artificially enlarged pupils. Small to intermediate (normal sized) pupils seem to function equally well. This work contradicts earlier experiments that suggest that the size of dorsal eyespots plays a role in female choice and explains why male dorsal eyespots are very variable in size and often have indistinct rings of coloration, as the only feature under selection by females seems to be the central white pupil. We propose that sexual selection by female choice, rather than predator avoidance, may have been an important selective factor in the early stages of eyespot evolution in ancestral Lepidopteran lineages.
Linear dimensionality reduction via a heteroscedastic extension of LDA: the Chernoff criterion

We propose an eigenvector-based heteroscedastic linear dimension reduction (LDR) technique for multiclass data. The technique is based on a heteroscedastic two-class technique which utilizes the so-called Chernoff criterion, and successfully extends the well-known linear discriminant analysis (LDA). The latter, which is based on the Fisher criterion, is incapable of dealing with heteroscedastic data in a proper way. For the two-class case, the between-class scatter is generalized so to capture differences in (co)variances. It is shown that the classical notion of between-class scatter can be associated with Euclidean distances between class means. From this viewpoint, the between-class scatter is generalized by employing the Chernoff distance measure, leading to our proposed heteroscedastic measure. Finally, using the results from the two-class case, a multiclass extension of the Chernoff criterion is proposed. This criterion combines separation information present in the class mean as well as the class covariance matrices. Extensive experiments and a comparison with similar dimension reduction techniques are presented.
Toll like Receptor 3 & 4 Responses of Human Turbinate Derived Mesenchymal Stem Cells: Stimulation by Double Stranded RNA and Lipopolysaccharide

Background and objectives Multipotent mesenchymal stromal cells (MSCs) represent a promising cell-based therapy for a number of inflammatory or autoimmune diseases. Herein, Toll like receptor (TLR) expression by MSCs and their immune regulatory roles are investigated. In this study, we investigated the influence of TLR on the immune response, proliferation, and differentiation potential of human turbinated MSC (hTMSC) cultures in vitro. Subjects and Methods After isolating hTMSCs from discarded inferior turbinate tissue, FACS analysis was used to assess the expression of TLRs such as TLR2, TLR3, TLR4, and TLR5 in hTMSCs and cell proliferation was assessed using a cell counting kit (CCK)-8. Cytokine and chemokine secretions were analyzed with multiplex immunoassays for IL-1α, IL-1β, IL-4, IL-6, IL-8, IL-10, IL-12, IP-10 (CXCL10), RANTES (CCL5), TNF-a, GM-CSF, and IFN-γ. The differentiation potential of hTMSCs was evaluated in the osteogenic, chondogenic, and adipogeinc media and analyzed by histology and gene expression related to differentiation. Results FACS analysis revealed that TLR3 and TLR4 expression consisted of a relatively high percentage of the surface proteins expressed by hTMSCs. The proliferation of hTMSCs was influenced and significantly increased by the presence of TLR4 agonists. In particular, hTMSCs produced a set of cytokines and chemokines and the expression of IL-6, IL-8, IL-12, IP-10 (CXCL10), RANTES (CCL5), TNF-α, and GM-CSF were up-regulated in response to the TLR4 agonist LPS. The osteogenic and adipogeinc differentiation potential of hTMSCs was not affected by TLR agonists. Conclusions We conclude that TLR4 stimulation affects TLR expression, proliferation, and the immunomodulation potential of hTMSCs. Understanding the mechanism behind TLR's influence on hTMSCs and their immunomodulating properties would be useful for providing a novel target to exploit in the improvement of stem cell-based therapeutic strategies.
One-step and Two-step Classification for Abusive Language Detection on Twitter

Automatic abusive language detection is a difficult but important task for online social media. Our research explores a two-step approach of performing classification on abusive language and then classifying into specific types and compares it with one-step approach of doing one multi-class classification for detecting sexist and racist languages. With a public English Twitter corpus of 20 thousand tweets in the type of sexism and racism, our approach shows a promising performance of 0.827 F-measure by using HybridCNN in one-step and 0.824 F-measure by using logistic regression in two-steps.
Age at onset of bipolar disorder and risk for comorbid borderline personality disorder.

OBJECTIVES The relationship between bipolar disorder and cluster B personality disorders remains phenomenologically complex and controversial. We sought to examine the relationship between early age at onset of bipolar disorder and development of comorbid borderline personality disorder. METHODS A total of 100 adults in an academic specialty clinic for bipolar disorder underwent structured diagnostic interviews and clinical assessments to determine lifetime presence of comorbid borderline personality disorder, histories of childhood trauma, and clinical illness characteristics. RESULTS Logistic regression indicated that increasing age at onset of bipolar disorder was associated with a lower probability of developing comorbid borderline personality disorder (odds ratio = 0.91, 95% confidence interval: 0.83-0.99) while controlling for potential confounding factors, including a history of severe child trauma/abuse. CONCLUSION Early onset of bipolar disorder increases the probability of developing comorbid borderline personality disorder, independent of the effects of severe childhood trauma/abuse. In patients with borderline personality disorder, prospective studies of new-onset bipolar disorder may underestimate the prevalence of true comorbidity unless they capture the primary risk window for first-episode mania arising before the end of adolescence.
Object detection and mapping for service robot tasks

SUMMARY The problem studied in this paper is a mobile robot that autonomously navigates in a domestic environment, builds a map as it moves along and localizes its position in it. In addition, the robot detects predefined objects, estimates their position in the environment and integrates this with the localization module to automatically put the objects in the generated map. Thus, we demonstrate one of the possible strategies for the integration of spatial and semantic knowledge in a service robot scenario where a simultaneous localization and mapping (SLAM) and object detection recognition system work in synergy to provide a richer representation of the environment than it would be possible with either of the methods alone. Most SLAM systems build maps that are only used for localizing the robot. Such maps are typically based on grids or different types of features such as point and lines. The novelty is the augmentation of this process with an object-recognition system that detects objects in the environment and puts them in the map generated by the SLAM system. The metric map is also split into topological entities corresponding to rooms. In this way, the user can command the robot to retrieve a certain object from a certain room. We present the results of map building and an extensive evaluation of the object detection algorithm performed in an indoor setting.
Estimating Food Consumption by a Heavily Fished Stock of Zooplanktivorous Coregonus lavaretus

Abstract The food consumption of adult zooplanktivorous Coregonus lavaretus in Lake Constance, Germany, was estimated monthly from May to October 1989 with a bioenergetics model. To achieve fine temporal resolution of lakewide consumption, we scaled the monthly weight increments of fish during the 6-month growing season by the relative weights of the stomach contents of fish sampled around sunset. As a result, the proportion of maximum consumption varied from month to month. When this proportion was held constant, the total consumption estimates were similar but the allocation of consumption to each month differed by up to 30% between the two scenarios. Bythotrephes longimanus was the most important prey item from June to October. The average daily consumption of B. longimanus amounted to 15.4% of the standing stock, while that of daphnids Daphnia spp. and Leptodora kindtii was more than an order of magnitude lower. We conclude that adult C. lavaretus in Lake Constance may control the population dynamics .
Predicting Performance on MOOC Assessments using Multi-Regression Models

The past few years has seen the rapid growth of data min- ing approaches for the analysis of data obtained from Mas- sive Open Online Courses (MOOCs). The objectives of this study are to develop approaches to predict the scores a stu- dent may achieve on a given grade-related assessment based on information, considered as prior performance or prior ac- tivity in the course. We develop a personalized linear mul- tiple regression (PLMR) model to predict the grade for a student, prior to attempting the assessment activity. The developed model is real-time and tracks the participation of a student within a MOOC (via click-stream server logs) and predicts the performance of a student on the next as- sessment within the course offering. We perform a com- prehensive set of experiments on data obtained from three openEdX MOOCs via a Stanford University initiative. Our experimental results show the promise of the proposed ap- proach in comparison to baseline approaches and also helps in identification of key features that are associated with the study habits and learning behaviors of students.
Layout-independent fisheye views of nested graphs

Although a graph can be a useful device for visualizing complex relationships, drawings of large graphs can be difficult to comprehend. As one remedy, we formulated a novel generalized approach for generating fisheye views of nested graphs with multiple variable focal points, and devised an algorithm that creates fisheye views in the absence of application specific distance metrics. Previous solutions produced fisheye views by filtering or distorting drawings of graphs. Since these approaches relied on geometric notions of distance, they could only be applied effectively in limited cases. By contrast, our approach treats fisheye view generation as a phase that precedes graph layout, rather than as a technique that alters an existing drawing, and does not suffer these drawbacks. <<ETX>>
Current and emerging therapies for the treatment of myasthenia gravis

Myasthenia gravis (MG) is an autoimmmune disease in which autoantibodies to different antigens of the neuromuscular junction cause the typical weakness and fatigability. Treatment includes anticholinesterase drugs, immunosuppression, immunomodulation, and thymectomy. The autoimmune response is maintained under control by corticosteroids frequently associated with immunosuppressive drugs, with improvement in the majority of patients. In case of acute exacerbations with bulbar symptoms or repeated relapses, modulation of autoantibody activity by plasmapheresis or intravenous immunoglobulins provides rapid improvement. Recently, techniques removing only circulating immunoglobulins have been developed for the chronic management of treatment-resistant patients. The rationale for thymectomy relies on the central role of the thymus. Despite the lack of controlled studies, thymectomy is recommended as an option to improve the clinical outcome or promote complete remission. New videothoracoscopic techniques have been developed to offer the maximal surgical approach with the minimal invasiveness and hence patient tolerability. The use of biological drugs such as anti-CD20 antibodies is still limited but promising. Studies performed in the animal model of MG demonstrated that several more selective or antigen-specific approaches, ranging from mucosal tolerization to inhibition of complement activity or cellular therapy, might be feasible. Investigation of the transfer of these therapeutic approaches to the human disease will be the challenge for the future.
The effect of salt replacers and flavor enhancer on the processing characteristics and consumer acceptance of turkey sausages.

BACKGROUND Producing high-quality processed meats that contain reduced amounts of sodium chloride is a major challenge facing industry owing to the importance of sodium chloride toward the functional, microbial stability and sensory properties of these products. In order to create reduced sodium alternatives, a number of commercial salt replacers and flavor enhancers have entered the market; however, their ability to be applied in processed meats requires investigation. In this study, two salt replacers (Ocean's Flavor - OF45, OF60) and one flavor enhancer (Fonterra™ Savoury Powder - SP) were evaluated for their ability to effectively reduce sodium while maintaining the functional and sensory properties of turkey sausages. Functionality via instrumental measures (yield, purge loss, pH, expressible moisture, proximate composition, sodium content, color, texture), safety (microbiological assessment) and consumer acceptability were obtained on all samples. RESULTS All non-control treatments resulted in products with sodium chloride contents below Canada's Health Check™ Program target for processed meats. There was no detrimental effect on water binding and texture in treatments when NaCl was substituted with OF60 sea salt replacers. Sodium reduction had no negative effect on the shelf life of the turkey sausages with up to 60 days of refrigerated storage. Consumer acceptability for all attributes did not differ significantly, except for aftertaste, which scored lowest for OF45 compared with the control (regular NaCl content). CONCLUSION This work demonstrated that salt replacers could potentially substitute for NaCl in smoked turkey sausages; however, further flavor optimization may be required to suppress undesirable levels of bitterness elicited by some of these ingredients.
Combinational equivalence checking using satisfiability and recursive learning

The problem of checking the equivalence of combinational circuits is of key significance in the verification of digital circuits. Previously, several approaches have been proposed for solving this problem. Still, the hardness of the problem and the ever-growing complexity of logic circuits motivates studying and developing alternative solutions. In this paper we study the application of Boolean satisfiability (SAT) algorithms for solving the combinational equivalence checking (CEC) problem. Although existing SAT algorithms are in general ineffective for solving CEC, in this paper we show how to improve SAT algorithms by extending and applying recursive learning techniques to the analysis of instances of SAT. This in turn provides a new alternative and competitive approach for solving CEC. Preliminary experimental results indicate that the proposed improved SAT algorithm can be useful for a large variety of instances of CEC, in particular when compared with pure BDD-based approaches.
Peer influence: neural mechanisms underlying in-group conformity

People often conform to the behavior of others with whom they identify. However, it is unclear what fundamental mechanisms underlie this type of conformity. Here, we investigate the processes mediating in-group conformity by using functional magnetic resonance imaging (fMRI). Participants completed a perceptual decision-making task while undergoing fMRI, during which they were exposed to the judgments of both in-group and out-group members. Our data suggest that conformity to the in-group is mediated by both positive affect as well as the cognitive capacity of perspective taking. Examining the processes that drive in-group conformity by utilizing a basic decision-making paradigm combined with neuroimaging methods provides important insights into the potential mechanisms of conformity. These results may provide an integral step in developing more effective campaigns using group conformity as a tool for behavioral change.