Miracle-dz/UniFAR-FTUs huggingface dataset:
Osteoporosis: Current Concepts

Abstract Osteoporosis is a worldwide disease characterized by reduction of bone mass and alteration of bone architecture resulting in increased bone fragility and increased fracture risk. Causes of osteoporosis include increasing age, female sex, postmenopausal status, hypogonadism or premature ovarian failure, low body mass index, ethnic background, rheumatoid arthritis, low bone mineral density (BMD), vitamin D deficiency, low calcium intake, hyperkyphosis, current smoking, alcohol abuse, immobilization, and long-term use of certain medications. The diagnosis of osteoporosis is established by measurement of BMD of the hip and spine using dual energy X-ray absorptiometry. According to the World Health Organization criteria, osteoporosis is defined as a BMD that lies 2.5 standard deviation or more below the average value for young healthy women. Bone turnover biomarker detection may be useful in monitoring osteoporosis treatment and assessing fracture risk but not for diagnosis of osteoporosis. Management of osteoporosis consists of nonpharmacological interventions, which are recommended for all subjects, and pharmacological therapy in all postmenopausal women who have had an osteoporotic fracture or have BMD values consistent with osteoporosis.
Correlated Regression Feature Learning for Automated Right Ventricle Segmentation

Accurate segmentation of right ventricle (RV) from cardiac magnetic resonance (MR) images can help a doctor to robustly quantify the clinical indices including ejection fraction. In this paper, we develop one regression convolutional neural network (RegressionCNN) which combines a holistic regression model and a convolutional neural network (CNN) together to determine boundary points’ coordinates of RV directly and simultaneously. In our approach, we take the fully connected layers of CNN as the holistic regression model to perform RV segmentation, and the feature maps extracted by convolutional layers of CNN are converted into 1-D vector to connect holistic regression model. Such connection allows us to make full use of the optimization algorithm to constantly optimize the convolutional layers to directly learn the holistic regression model in the training process rather than separate feature extraction and regression model learning. Therefore, RegressionCNN can achieve optimally convolutional feature learning for accurately catching the regression features that are more correlated to RV regression segmentation task in training process, and this can reduce the latent mismatch influence between the feature extraction and the following regression model learning. We evaluate the performance of RegressionCNN on cardiac MR images acquired of 145 human subjects from two clinical centers. The results have shown that RegressionCNN’s results are highly correlated (average boundary correlation coefficient equals 0.9827) and consistent with the manual delineation (average dice metric equals 0.8351). Hence, RegressionCNN could be an effective way to segment RV from cardiac MR images accurately and automatically.
Immunological Modulation in Long-Term Karate Practitioners

Karate is a Japanese martial arts system with potential physical and psychological benefits. However, karate has been scarcely investigated from a psychobiological perspective, and its effects on the immune system remain virtually unknown. We designed the present study with the aim of analyzing the effects of karate practice on immunological parameters. 27 healthy male volunteer subjects participated in the study, 15 in the experimental group and 12 in the control. Experimental subjects were all karate players who had practiced this martial art for a minimum of three years attending regular lessons at a karate training center, in the evening, two to three days per week. Blood samples for the quantification of immunological parameters (total leukocytes, neutrophils, monocytes, eosinophils, basophils, lymphocytes, IgG, IgA, and IgM) were taken in both groups. A t-test for independent groups was performed in each dependent variable; a value of p<0.05 was considered to be significant. Karate practitioners exhibited a significantly higher number of total leukocytes (p<0.02), monocytes (p<0.01), and lymphocytes (p<0.01), a higher percentage of monocytes (p<0.01), and greater serum concentrations of IgG (p<0.02) and IgM (p<0.01). Our findings show that long-term karate practice is related to a broad modulation of immune parameters, including total and specific leukocyte counts, as well as immunoglobulin concentrations. This peculiar immunomodulatory profile, apart from its psychobiological relevance, may have noteworthy clinical implications.
Precoding Technique for Ill-Conditioned Massive MIMO-VLC System

Visible light communications (VLC) has lately emerged as a viable supplement to existing radio frequency (RF) based communication systems, and is an integral component of future communication systems. The possibility of deploying massive arrays of light emitting diodes (LED) and photo-detectors (PD), which translates to a massive array of multiple input multiple output (MIMO) system for VLC, have been recently proposed. However, massive-MIMO in VLC has the following drawbacks which limit its practical deployment: a) high condition number of the channel matrix, which negatively affects the robustness of traditional channel-inversion based detection, and b) high interference in a multi-user setting due to correlated columns of the overall MIMO channel matrix. In this paper, the multi-user (MU) massive-MIMO in VLC is considered, and a precoding technique is proposed that induces diverse effective channel matrices for different users, and hence facilitates MU detection using ordered successive interference cancellation. Further, it is shown that the proposed precoding technique maximizes an upper bound of the overall sum-rate of the MU massive-MIMO system. Lastly, simulations have been performed for MU massive LED and PD arrays demonstrating that the proposed precoding technique outperforms existing precoding techniques, and hence is a viable solution for massive-MIMO in VLC.
Assessment of northern bobwhite survival and fitness in the West Gulf Coastal Plain ecoregion

In the West Gulf Coastal Plains (WGCP) northern bobwhite (Colinus virginianus) are declining faster than range-wide averages and such declines have been linked to the consequences of land management. Management for the endangered red-cockaded woodpecker (Picoides borealis) has benefitted northern bobwhite by restoring mature pine-grassland ecosystems in some areas of the region. However, at Felsenthal National Wildlife Refuge, Crossett, Arkansas, USA, the bobwhite population was not increasing despite the availability of seemingly suitable habitat from management for the endangered species. To understand factors that may be affecting bobwhite survival on Felsenthal National Wildlife Refuge we conducted a telemetry study and assessed summer survival, brood survival, and nest success from 1 April– 11 August in 2013 and 1 April– 15 August in 2014. We also calculated home-range sizes and measured microhabitat characteristics around nests. Summer survival rates were 71% (SE = 0.17) and 47% (SE = 0.14); while nest success was 47% (SE = 0.02) and 100% for 2013 and 2014, respectively. Between years, both 95% and 50% kernel home-ranges were not different (pooled, 63.92±6.07 ha and 14.94±1.75 ha); however minimum convex polygon home-range sizes were (113.8 ± 20.1 ha in 2013; and 393.1 ± 49.0 ha in 2014, P < 0.001). Only numerical differences in microhabitat vegetation characteristics of nest sites and non- nest sites were observed. We suggest management for red-cockaded woodpeckers supports bobwhite populations but only as a buffer against more severe declines. Since bobwhites are declining range-wide, we believe areas federally managed for red-cockaded woodpeckers will become increasingly more important for sustaining regional bobwhite population levels.
A situation-aware collision avoidance strategy for car-following

In this paper, we discuss how to develop an appropriate collision avoidance strategy for car-following. This strategy aims to keep a good balance between traffic safety and efficiency while also taking into consideration the unavoidable uncertainty of position / speed perception / measurement of vehicles and other drivers. Both theoretical analysis and numerical testing results are provided to show the effectiveness of the proposed strategy.
Improved Device Performance in AlGaN/GaN HEMT by Forming Ohmic Contact With Laser Annealing

An AlGaN/GaN high-electron-mobility transistor with a novel ohmic contact formation process based on conventional pulsed laser annealing is proposed. Compared with the conventional rapid thermal annealing process, the laser annealing (LA) process not only improves the surface morphology of ohmic contact metal but also exhibits a higher OFF-state breakdown voltage. An excellent rms roughness of 16.5 nm is observed by atomic force microscope which is 16.3% of the reference one. In a device with a gate-to-drain distance of 5 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula>, a forward blocking voltage of 442 V is obtained at <inline-formula> <tex-math notation="LaTeX">${V}_{\textsf {GS}} = -\textsf {8}$ </tex-math></inline-formula> V which has a 37.3% improvement compared with the conventional device. The device with LA process has lower contact resistance at actual working temperature (above 125 °C). The current transport mechanism is dominated by thermionic field emission through the ohmic contact. Moreover, the degradation of dynamic ON-resistance is significantly suppressed due to lower surface states by protecting the bare AlGaN layer from directly exposing under high temperature ambient.
Design of Feedback Control Laws for Information Transfer in Spintronics Networks

Information encoded in networks of stationary, interacting spin-1/2 particles is central for many applications ranging from quantum spintronics to quantum information processing. Without control, however, information transfer through such networks is generally inefficient. Currently available control methods to maximize the transfer fidelities and speeds mainly rely on dynamic control using time-varying fields and often assume instantaneous readout. We present an alternative approach to achieving efficient, high-fidelity transfer of excitations by shaping the energy landscape via the design of time-invariant feedback control laws without recourse to dynamic control. Both instantaneous readout and the more realistic case of finite readout windows are considered. The technique can also be used to freeze information by designing energy landscapes that achieve Anderson localization. Perfect state or superoptimal transfer and localization are enabled by conditions on the eigenstructure of the system and signature properties for the eigenvectors. Given the eigenstructure enabled by superoptimality, it is shown that feedback controllers that achieve perfect state transfer are, surprisingly, also the most robust with regard to uncertainties in the system and control parameters.
Energy-Efficient Multicast/Unicast Edge Caching for Dense Small Cell Networks with Graph Theory

Local caching of popular content files at the wireless edge is a promising way to address several challenges for the next mobile radio generation. Apart from reducing latency, it also helps save energy and better control the available end-to-end power budget. In this paper, we take advantage of dense small cell networks' architecture to further reduce the power consumption of the system, using a graph-theoretic approach. The basic idea is to download the requested content file from a neighboring small cell rather than macro cell or backhaul, if it is not cached at the serving base station. More precisely, we build a graph to fetch the requested content file from the nearest less power consuming small cells. Special attention is paid to the adequate number of small base stations involved in the graph to ensure an energy efficient solution. In addition, we apply our graph theory based approach to multicast transmissions and show that our built graph outperforms the conventional unicast/multicast caching transmission in terms of energy efficiency. Simulation results also showed the effectiveness of our approach for different cache size and steepness parameter.
Clinical potential of ataluren in the treatment of Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is an autosomal dominant, X-linked neuromuscular disorder caused by mutations in dystrophin, one of the largest genes known to date. Dystrophin gene mutations are generally transmitted from the mother to male offspring and can occur throughout the coding length of the gene. The majority of the methodologies aimed at treating the disorder have focused on restoring a shorter, although partially functional, dystrophin protein. The approach has the potential of converting a severe DMD phenotype into a milder form of the disease known as Becker muscular dystrophy. Others have focused on ameliorating the disease by targeting secondary pathologies such as inflammation or loss of regeneration. Of great potential is the development of strategies that are capable of restoring full-length dystrophin expression due to their ability to produce a normal, fully functional protein. Among these strategies, the use of read-through compounds (RTCs) that could be administered orally represents an ideal option. Gentamicin has been previously tested in clinical trials for DMD with limited or no success, and its use in the clinic has been dismissed due to issues of toxicity and lack of clear benefits to patients. More recently, new RTCs have been identified and tested in animal models for DMD. This review will focus on one of those RTCs known as ataluren that has now completed Phase III clinical studies for DMD and at providing an overview of the different stages that have led to its clinical development for the disease. The impact that this new drug may have on DMD and its future perspectives will also be described, with an emphasis on the importance of further assessing the clinical benefits of this molecule in patients as it becomes available on the market in different countries.
Apparent resolution of parrot bornavirus infection in cockatiels (Nymphicus hollandicus)

Parrot bornavirus (PaBV), the etiologic agent of proventricular dilatation disease (PDD), is a major cause of concern in the avian health community. Within an infected flock, some birds will develop PDD and succumb to disease, while others remain healthy. Until now, there has been no study describing the results of long-term infection in apparently healthy carriers. For the last 5 years, the Schubot Exotic Bird Health Center at Texas A&M University has monitored individual PaBV shedding data in a flock of 66 naturally infected cockatiels. Of these birds, 53 were detected shedding PaBV4 in their droppings by reverse transcriptase polymerase chain reaction on at least one occasion. However, the prevalence of shedding declined over time, with the last positive cloacal swab being in October 2013. To determine whether the decline and eventual lack of shedding was an indication of virus elimination, seven previously shedding birds were euthanized and necropsied in 2016. Neither any gross lesion of PDD was observed nor was there any evidence of PDD or bornaviral encephalitis detected by histopathology. All tissues tested were negative for the presence of PaBV by reverse transcriptase polymerase chain reaction and immunohistochemistry. Thus, there was no evidence of an ongoing, productive infection in these birds. There are two possible explanations for these results. One possibility is that the birds were previously infected and have subsequently eliminated the virus. Alternatively, there may have been as few as three truly infected birds in the flock and the transient detection of PaBV in the droppings of other birds may simply be a “pass-through” phenomenon.
Deep unsupervised multi-view detection of video game stream highlights

We consider the problem of automatic highlight-detection in video game streams. Currently, the vast majority of highlight-detection systems for games are triggered by the occurrence of hard-coded game events (e.g., score change, end-game), while most advanced tools and techniques are based on detection of highlights via visual analysis of game footage. We argue that in the context of game streaming, events that may constitute highlights are not only dependent on game footage, but also on social signals that are conveyed by the streamer during the play session (e.g., when interacting with viewers, or when commenting and reacting to the game). In this light, we present a multi-view unsupervised deep learning methodology for novelty-based highlight detection. The method jointly analyses both game footage and social signals such as the players facial expressions and speech, and shows promising results for generating highlights on streams of popular games such as Player Unknown's Battlegrounds.
Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder

Human annotation for syntactic parsing is expensive, and large resources are available only for a fraction of languages. A question we ask is whether one can leverage abundant unlabeled texts to improve syntactic parsers, beyond just using the texts to obtain more generalisable lexical features (i.e. beyond word embeddings). To this end, we propose a novel latent-variable generative model for semi-supervised syntactic dependency parsing. As exact inference is intractable, we introduce a differentiable relaxation to obtain approximate samples and compute gradients with respect to the parser parameters. Our method (Differentiable Perturb-and-Parse) relies on differentiable dynamic programming over stochastically perturbed edge scores. We demonstrate effectiveness of our approach with experiments on English, French and Swedish.
The coagulation system in host defense

The blood coagulation system and immune system of higher organisms are thought to have a common ancestral origin. During infections, the blood coagulation system is activated and components of the hemostatic system are directly involved in the immune response and immune system modulations. The current view is that the activation of coagulation is beneficial for infections with bacteria and viruses. It limits pathogen dissemination and supports pathogen killing and tissue repair. On the other hand, over‐activation can lead to thrombosis with subsequent depletion of hemostatic factors and secondary bleeding. This review will summarize the current knowledge on blood coagulation and pathogen infection with focus on most recent studies of the role of the different parts of the blood coagulation system in selected bacterial and viral infections.
Gender Differences in Processing Fearful and Angry Body Expressions

Previous studies have demonstrated differential perception of body expressions between males and females. However, only two recent studies (Kret et al., 2011; Krüger et al., 2013) explored the interaction effect between observer gender and subject gender, and it remains unclear whether this interaction between the two gender factors is gender-congruent (i.e., better recognition of emotions expressed by subjects of the same gender) or gender-incongruent (i.e., better recognition of emotions expressed by subjects of the opposite gender). Here, we used event-related potentials (ERPs) to investigate the recognition of fearful and angry body expressions posed by males and females. Male and female observers also completed an affective rating task (including valence, intensity, and arousal ratings). Behavioral results showed that male observers reported higher arousal rating scores for angry body expressions posed by females than males. ERP data showed that when recognizing angry body expressions, female observers had larger P1 for male than female bodies, while male observers had larger P3 for female than male bodies. These results indicate gender-incongruent effects in early and later stages of body expression processing, which fits well with the evolutionary theory that females mainly play a role in care of offspring while males mainly play a role in family guarding and protection. Furthermore, it is found that in both angry and fearful conditions male observers exhibited a larger N170 for male than female bodies, and female observers showed a larger N170 for female than male bodies. This gender-incongruent effect in the structural encoding stage of processing may be due to the familiarity of the body configural features of the same gender. The current results provide insights into the significant role of gender in body expression processing, helping us understand the issue of gender vulnerability associated with psychiatric disorders characterized by deficits of body language reading.
Innate Immunity Induced by the Major Allergen Alt a 1 From the Fungus Alternaria Is Dependent Upon Toll-Like Receptors 2/4 in Human Lung Epithelial Cells

Allergens are molecules that elicit a hypersensitive inflammatory response in sensitized individuals and are derived from a variety of sources. Alt a 1 is the most clinically important secreted allergen of the ubiquitous fungus, Alternaria. It has been shown to be a major allergen causing IgE-mediated allergic response in the vast majority of Alternaria-sensitized individuals. However, no studies have been conducted in regards to the innate immune eliciting activities of this clinically relevant protein. In this study, recombinant Alt a 1 was produced, purified, labeled, and incubated with BEAS-2B, NHBE, and DHBE human lung epithelial cells. Alt a 1 elicited strong induction of IL-8, MCP-1, and Gro-a/b/g. Using gene-specific siRNAs, blocking antibodies, and chemical inhibitors such as LPS-RS, it was determined that Alt a 1-induced immune responses were dependent upon toll-like receptors (TLRs) 2 and 4, and the adaptor proteins MYD88 and TIRAP. Studies utilizing human embryonic kidney cells engineered to express single receptors on the cell surface such as TLRs, further confirmed that Alt a 1-induced innate immunity is dependent upon TLR4 and to a lesser extent TLR2.
Health Economic Evaluations of Cancer in Brazil: A Systematic Review

Background: A large number of health economic evaluation (HEE) studies have been published in developed countries. However, Brazilian HEE literature in oncology has not been studied. Objective: To investigate whether the scientific literature has provided a set of HEE in oncology capable of supporting decision making in the Brazilian context. Methods: A systematic review was conducted to identify and characterize studies in this field. We searched multiple databases selecting partial and full HEE studies in oncology (1998-2013). Results: Fifty-five articles were reviewed, of these, 33 (60%) were full health economic evaluations. Type of cancers most frequently studied were: breast (38.2%), cervical (14.6%), lung (10.9%) and colorectal (9.1%). Procedures (47.3%) were the technologies most frequently evaluated. In terms of the intended purposes of the technologies, most (63.6%) were treatments. The majority of the incremental cost-effectiveness ratios (ICERs) reported have been below the cost-effectiveness threshold suggested by the World Health Organization (WHO). Conclusions: There has been an increase in the number of HEEs related to cancer in Brazil. These studies may support decision-making processes regarding the coverage of and reimbursement of healthcare technologies for cancer treatment in Brazil.