Miracle-dz/UniFAR-FTUs huggingface dataset:
A Two-Step Approach for an Enhanced Quadrotor Attitude Estimation via IMU Data

In this brief, an approach is presented to design a robust quadrotor attitude estimator when only inertial measurement units (IMUs) sensor data can be available. A two-step procedure is proposed to improve attitude estimation in the presence of IMU biases and measurement noise. In the first step, a smooth sliding mode observer is designed to estimate the roll and pitch angles using accelerometer measurements. The second step enhances the attitude estimation performance in the presence of noise and bias in IMU data by using a complementary nonlinear filter. Experimental results on a quadrotor test bed together with simulation results obtained using a representative nonlinear model are used to highlight the potential and performance of the proposed solution.
Computational accelerators for analog-to-digital and digital processing of sensor signals in information measuring systems

The analysis of hardware, temporal and structural complexity of the special processor components, analog-to-digital and digital processing of sensor signals has been carried out. New circuit solutions of analog-to-digital parallel-type converters, single-digit half and full adders, multi-digit combinational and pyramid adders with accelerated transfers, and devices for binary digits sorting and the Hamming distance calculating between signals were proposed. Calculations, diagrams and graphs of estimation of time, hardware and structural complexity of the proposed circuit solutions of computational accelerators were presented. Examples of increasing of the efficiency of the special processor components in comparison with the available ones were shown. A wide scope of application of the developed accelerators in information measuring and image recognition systems was defined.
Seasonal Changes in Serum Thyrotropin Concentrations Observed from Big Data Obtained During Six Consecutive Years from 2010 to 2015 at a Single Hospital in Japan.

BACKGROUND This study analyzed big data for serum thyrotropin (TSH), free triiodothyronine (fT3), and free thyroxine (fT4) concentrations in patients who had attended the outpatient clinic of Ito Hospital (Tokyo, Japan) during a recent six-year period (between January 1, 2010, and December 31, 2015) in order to investigate for seasonal changes. METHODS The serum TSH concentrations were reviewed for all 135,417 patients aged >20 years. Patients with any thyroid diseases were included, irrespective of whether they were receiving drug therapy. In total 1,637,721 serum samples were analyzed for TSH, 1,626,269 for fT3, and 1,669,381 for fT4. RESULTS It was observed that the TSH concentrations showed annual changes during the six-year period. They decreased during the summer, while they increased during the winter. The TSH concentrations were negatively correlated with the daily temperatures (Spearman rank correlation coefficient -0.4486; p < 0.0001). The same applied for the correlation between fT3 concentrations and daily temperatures. CONCLUSIONS The fact that the TSH concentrations show annual changes in areas where the temperature ranges during the year are rather wide should be borne in mind for interpretation of results.
How many individuals achieve symptom abstinence following psychological treatments for bulimia nervosa? A meta‐analytic review

OBJECTIVES It is unclear how many patients with bulimia nervosa (BN) completely abstain from the core behavioral symptoms after receiving psychological treatment. The present meta-analysis of randomized controlled trials (RCTs) aimed to (a) estimate the prevalence of patients who abstain from binge eating and/or purging following all psychological treatments for BN, and (b) test whether these abstinence estimates are moderated by the type of treatment modality delivered, the definition of abstinence applied, and trial quality. METHOD Forty-five RCTs were included, with 78 psychotherapy conditions. Pooled event rates were calculated using random effects models. RESULTS At post-treatment, the total weighted percentage of treatment-completers who achieved abstinence was 35.4% (95% CI = 29.6, 41.7), while the total weighted percentage of abstinence for all randomized patients (intention-to-treat) was 29.9% (95% CI = 25.7, 33.2). Abstinence estimates were highest in trials that used behavioral-based treatments (e.g., cognitive-behavioral therapy, behavior therapy). There was also evidence that guided self-help interventions produced the lowest post-treatment abstinence rates, but with no difference at follow-up from clinician-led treatments, and studies that used a shorter timeframe for defining abstinence (i.e., 14 days symptom-free compared to 28-days symptom-free) produced the highest abstinence rates. Abstinence estimates at follow-up for both the completer (34.6%; 95% CI = 29.3, 40.2) and intention-to-treat (28.6%; 95% CI = 25.1, 32.3) analyses were essentially the same as the post-treatment estimates. DISCUSSION Over 60% of patients fail to fully abstain from core BN symptoms even after receiving our most empirically-supported treatments. The present findings highlight the urgency toward improving the effectiveness of psychological treatments for BN.
Development and Validation of a Predictive Score for Preoperative Diagnosis of Early Stage Epithelial Ovarian Cancer

Objective: To develop and validate a simplified multi-parameter risk-based scoring system for preoperative diagnosis of early stage epithelial ovarian cancer. Methods: All women presented with adnexal mass and were scheduled for operation at Phrapokklao hospital during September 2013 – December 2017 were included and categorized according to their histopathologic reports into early stage ovarian cancer groups and benign ovarian tumor groups. Multivariable logistic regression was used to explore for potential predictors. The selected logistic coefficients were transformed into risk-based scoring system. Internal validation was done with bootstrapping procedure. Results: A total of 270 participants were included in analysis and predictive model development, 54 in early stage ovarian cancer group and 216 in benign ovarian tumor group. Menopausal status, two abnormal ultrasound findings (presence of solid component or ascites), tumor size and serum CA-125 level were used for derivation of the scoring system. The score-based model showed area under ROC of 0.88 (95%CI 0.82-0.93). The developed scoring system ranged from 0 to 51 was classified into 3 subcategories for clinical practicability. The positive predictive values for the presence of early stage ovarian cancer were 2.07 (95%CI 0.43-6.05) for low risk patient, 29.13(95%CI 19.65-41.58) for moderate risk patient, and 95.45(95%CI 77.16-99.88) for high risk patient. Conclusion: This simplified risk-based scoring system for preoperative diagnosis of early stage ovarian cancer could aid general physicians or general gynecologists in evaluation of patients presenting with ovarian tumors and help gynecologic oncologists in management planning and prioritization of patients for operation.
Imaging, Tracking and Computational Analyses of Virus Entry and Egress with the Cytoskeleton

Viruses have a dual nature: particles are “passive substances” lacking chemical energy transformation, whereas infected cells are “active substances” turning-over energy. How passive viral substances convert to active substances, comprising viral replication and assembly compartments has been of intense interest to virologists, cell and molecular biologists and immunologists. Infection starts with virus entry into a susceptible cell and delivers the viral genome to the replication site. This is a multi-step process, and involves the cytoskeleton and associated motor proteins. Likewise, the egress of progeny virus particles from the replication site to the extracellular space is enhanced by the cytoskeleton and associated motor proteins. This overcomes the limitation of thermal diffusion, and transports virions and virion components, often in association with cellular organelles. This review explores how the analysis of viral trajectories informs about mechanisms of infection. We discuss the methodology enabling researchers to visualize single virions in cells by fluorescence imaging and tracking. Virus visualization and tracking are increasingly enhanced by computational analyses of virus trajectories as well as in silico modeling. Combined approaches reveal previously unrecognized features of virus-infected cells. Using select examples of complementary methodology, we highlight the role of actin filaments and microtubules, and their associated motors in virus infections. In-depth studies of single virion dynamics at high temporal and spatial resolutions thereby provide deep insight into virus infection processes, and are a basis for uncovering underlying mechanisms of how cells function.
The hierarchical map forming model

In the present paper we propose a motor control model inspired by organizational priciples of the cerebral cortex. Specifically the model is based on cortical maps and functional hierarchy in sensory and motor areas of the brain. Self-Organizing Maps (SOM) have proven to be useful in modeling cortical topological maps (Palakal et al., 1995). A hierarchical SOM provides a natural way to extract hierarchical information from the environment, which we propose may in turn be used to select actions hierarchically. We use a neighborhood update version of the Q-learning algorithm, so the final model maps a continuous input space to a continuous action space in a hierarchical, topology preserving manner. The model is called the Hierarchical Map Forming model (HMF) due to the way in which it forms maps in both the input and output spaces in a hierarchical manner.
Cardiac rehabilitation and physical activity: systematic review and meta-analysis

Objective To undertake a systematic review and meta-analysis to assess the impact of cardiac rehabilitation (CR) on physical activity (PA) levels of patients with heart disease and the methodological quality of these studies. Methods Databases (MEDLINE, EMBASE, CENTRAL, CINAHL, PsychINFO and SportDiscus) were searched without language restriction from inception to January 2017 for randomised controlled trials (RCTs) comparing CR to usual care control in adults with heart failure (HF) or coronary heart disease (CHD) and measuring PA subjectively or objectively. The direction of PA difference between CR and control was summarised using vote counting (ie, counting the positive, negative and non-significant results) and meta-analysis. Results Forty RCTs, (6480 patients: 5825 CHD, 655 HF) were included with 26% (38/145) PA results showing a statistically significant improvement in PA levels with CR compared with control. This pattern of results appeared consistent regardless of type of CR intervention (comprehensive vs exercise-only) or PA measurement (objective vs subjective). Meta-analysis showed PA increases in the metrics of steps/day (1423, 95% CI 757.07 to 2089.43, p<0.0001) and proportion of patients categorised as physically active (relative risk 1.55, 95% CI 1.19 to 2.02, p=0.001). The included trials were at high risk of bias, and the quality of the PA assessment and reporting was relatively poor. Conclusion Overall, there is moderate evidence of an increase in PA with CR participation compared with control. High-quality trials are required, with robust PA measurement and data analysis methods, to assess if CR definitely leads to important improvements in PA.
MicroRNA‐130b targets PTEN to induce resistance to cisplatin in lung cancer cells by activating Wnt/β‐catenin pathway

More and more studies indicate the relevance of miRNAs in inducing certain drug resistance. Our study aimed to investigate whether microRNA‐130b‐3p (miR‐130b) mediates the chemoresistance as well as proliferation of lung cancer (LC) cells. MTS assay and apoptosis analysis were conducted to determine cell proliferation and apoptosis, respectively. Binding sites were identified using a luciferase reporter system, whereas mRNA and protein expression of target genes was determined by RT‐PCR and immunoblot, respectively. Mouse xenograft model was used to evaluate the role of miR‐130b in cisplatin resistance in vivo. The rising level of miR‐130b in cisplatin resistance LC cell lines (A549/CR and H446/CR) versus its parental cell lines, indicated its crucial relevance for LC biology. We identified PTEN as miR‐130b's major target and inversely correlated with miR‐130b expression in LC. Moreover, excessive miR‐130b expression promoted drug resistance and proliferation, decreased apoptosis of A549 cells. Suppression of miR‐130b enhanced drug cytotoxicity and reduced proliferation of A549/CR cells both internally and externally. Particularly, miR‐130b mediated Wnt/β‐catenin signalling pathway activities, chemoresistance and proliferation in LC cell, which was partially blocked following knockdown of PTEN. These findings suggest that miR‐130b targets PTEN to mediate chemoresistance, proliferation, and apoptosis via Wnt/β‐catenin pathway. The rising level of miR‐130b in cisplatin resistance LC cell lines (A549/CR and H446/CR) versus its parental cell lines, indicated its crucial relevance for LC biology. Moreover, excessive miR‐130b expression promoted drug resistance and proliferation, decreased apoptosis of A549 cells. These findings suggest that miR‐130b targets PTEN to mediate chemoresistance, proliferation, and apoptosis via Wnt/β‐catenin pathway.
Biological–Machine Systems Integration: Engineering the Neural Interface

The state of the art of biological-machine systems integration (BMSI) with an emphasis on neural interfacing is reported. The goal of BMSI from a medical viewpoint is to effectively replace or facilitate activation of, or recording from, neural elements in a part of the nervous system. BMSI will be firstly examined from a generic level whereby the current technologies for noninvasive and invasive neural recording and neural stimulation will be detailed. A case study in the area of visual neuroprosthesis will be presented to elucidate the current and future issues facing BMSI. This will include a discussion on biocompatibility, design of stimulating electrodes, the implanted microelectronic neurostimulator, and parallelization of stimulus encoding and delivery.
OmicsMapNet: Transforming omics data to take advantage of Deep Convolutional Neural Network for discovery

We developed OmicsMapNet approach to take advantage of existing deep leaning frameworks to analyze high-dimensional omics data as 2-dimensional images. The omics data of individual samples were first rearranged into 2D images in which molecular features related in functions, ontologies, or other relationships were organized in spatially adjacent and patterned locations. Deep learning neural networks were trained to classify the images. Molecular features informative of classes of different phenotypes were subsequently identified. As an example, we used the KEGG BRITE database to rearrange RNA-Seq expression data of TCGA diffuse glioma samples as treemaps to capture the functional hierarchical structure of genes in 2D images. Deep Convolutional Neural Networks (CNN) were derived using tools from TensorFlow to learn the grade of TCGA LGG and GBM samples with relatively high accuracy. The most contributory features in the trained CNN were confirmed in pathway analysis for their plausible functional involvement.
A Formal Model of Partitioning for Integrated Modular Avionics

The aviation industry is gradually moving toward the use of integrated modular avionics (IMA) for civilian transport aircraft. An important concern for IMA is ensuring that applications are safely partitioned so they cannot interfere with one another. We have investigated the problem of ensuring safe partitioning and logical noninterference among separate applications running on a shared Avionics Computer Resource (ACR). This research was performed in the context of ongoing standardization efforts, in particular, the work of RTCA committee SC-182, and the recently completed ARINC 653 application executive (APEX) interface standard. We have developed a formal model of partitioning suitable for evaluating the design of an ACR. The model draws from the mathematical modeling techniques developed by the computer security community. This report presents a formulation of partitioning requirements expressed first using conventional mathematical notation, then formalized using the language of SRI''s Prototype Verification System (PVS). The approach is demonstrated on three candidate designs, each an abstraction of features found in real systems.
Sarcocystis neurona–Induced Myeloencephalitis Relapse Following Anticoccidial Treatment

ABSTRACT Sarcocystis neurona is a ubiquitous parasite in the eastern United States, which is the principal causative agent in the neurologic disorder equine protozoal myeloencephalitis (EPM). While much is known about this protozoa's life cycle in its natural host, the opossum (Didelphis virginiana), little is known of how it acts in the aberrant equine host, which displays a high incidence of exposure with a relatively low rate of morbidity. For this study, we employed the popular interferon gamma knockout mouse model to determine the potential for recrudescence of S. neurona infection after treatment with the anticoccidial drug diclazuril. Mice were infected with S. neurona merozoites, and 7-days post-infection (DPI) they were treated with diclazuril for 30 or 60 days or not treated at all. All infected non-treated mice developed neurologic signs consistent with S. neurona infection within 30 DPI. All diclazuril-treated infected mice remained clinically normal while on treatment but developed neurologic signs within 60 days of treatment cessation. Histological examination of cerebella from all infected mice demonstrated characteristic lesions of S. neurona infection, regardless of treatment status. Cerebellar samples collected from infected treated mice, displaying neurologic signs, produced viable S. neurona in culture. However, cerebellar samples collected from infected and neurologically normal mice at the end of a 30-day treatment period did not produce viable S. neurona in culture. Analysis of the humoral immune response in infected mice showed that during treatment IgM antibody production decreased, suggesting the organism was sequestered from immune surveillance. The cessation of treatment and subsequent development of neurologic disease resulted in increased IgM antibody production, suggesting recognition by the immune system at that time. Based on the study results the authors propose that diclazuril was able to inhibit the replication and migration of S. neurona but not fully eliminate the parasite, suggesting recrudescence of infection after treatment is possible.
Delay Minimization for Data Dissemination in Large-Scale VANETs with Buses and Taxis

Minimizing the end-to-end delay for data dissemination in a large-scale VANET with both buses of fixed schedules and taxis of random schedules is a challenging issue, due to the scalability, high-mobility, and network heterogeneity concerns. Particularly, the mix of random taxis and fixed-scheduled buses makes the delay components along a path dependent and hard to estimate. In this paper, to address the scalability and high-mobility issues, we introduce a store-and-forward framework for VANETs with extra storage using “drop boxes”, which function similar to network routers. Next, we propose an optimal link strategy which is independent of the message arrival time and can be executed in a distributed manner. Then, we derive the expected path delay, considering the dependence of the delay components along the path, and propose the optimal routing strategy to minimize the expected path delay. Trace-driven simulations have been used to validate the rigorous analysis, and demonstrate the superior performance of the proposed strategies, which result in a substantial delay reduction and a much higher delivery ratio when compared with the state-of-the-art solutions without drop boxes. The strategies can further improve the delay performance when compared with the over-simplified routing solutions which ignore the dependence of the delay components.
2 Mental wellbeing in elite male under 23 soccer players: a team case study

Recent research suggests a high prevalence of mental health disorders in professional soccer players, including symptoms of anxiety, depression, distress and adverse eating behaviours. Whilst a limited number of studies address this issue, the existing evidence is alarming and highlights a need for further investigations to develop a better understanding of the causes and consequences of mental health problems in professional soccer players. Thus, the aim of this study was to examine the influence of physical and emotional stressors on mental wellbeing (MW) in professional male soccer players. Using a longitudinal design, twenty-five male soccer players from the under 23 squad playing in the Premier League 2 division in the UK completed the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) each week of the 2017/2018 season (37 weeks in total). Independent predictor variables of MW were injury, match selection (in the match squad), weekly training load (sum of total duration, total distance and total sprint distance) and win rate. Mean MW scores were calculated across the season for each player with a squad mean of 48±3.94, which is below the England population norm of 51.6. Mean MW was significantly lower when injured vs. not-injured (43.6±5.0 vs 49.9±3.5; p=0.01), but was not affected by selection, training load or match result. Multivariate regression models showed time out with injury to have the strongest influence on MW (r2=0.40, p<0.01), with longer periods of injury linked to lower MW scores. Matchday selection was the only other statistically significant variable, with a positive correlation between MW and selection (r2=0.23, p=0.02). Whilst elucidating the mechanisms by which time out with injury may affect MW was beyond the scope of this study, the association between injury and reduced MW highlights a need for mental health and wellbeing monitoring in injured soccer players. This could facilitate interventions and support to ensure health and performance are not negatively affected.