Miracle-dz/UniFAR-FTUs huggingface dataset:
Medicine use and recurrent complaints among 15-years-old adolescents in Tuscany.

BACKGROUND The use of medicines to treat common complaints, such as headache, stomachache, difficulty in getting to sleep and nervousness, is widespread among adolescents, and is increasing. The aim of this survey was to estimate the prevalence of recurrent specific complaints among 15-year-old adolescents in Tuscany over three years (2006, 2010 and 2014) and that of medicine use to treat these complaints among boys and girls. METHODS The present study is based on data from the Tuscan HBSC studies at three time points (2006, 2010 and 2014), which involved 2830 adolescents, aged 15 years old (1395 boys and 1435 girls). RESULTS Overall, the data confirm that adolescents who suffer from recurrent complaints are more likely to use medicines. The prevalence rates of all complaints were higher in girls than in boys in the three years considered. Over the whole period, headache, stomachache and difficulty in getting to sleep increased in girls, while boys displayed significant decrease in nervousness and stomachache. CONCLUSION Our findings underline the fact that the use of medicines in adolescence is a public health concern and constitutes an emerging issue that needs greater attention and investigation on the part of scientific research.
Outcomes and hospital admission patterns in patients with diabetes during Ramadan versus a non-fasting period

BACKGROUND Fasting during Ramadan is a challenge for Muslim patients with diabetes and for their healthcare providers. However, data on the effects of Ramadan fasting on hospital admissions and outcomes in patients with diabetes are scarce. OBJECTIVES Evaluate the characteristics of patients with diabetes admitted during the fasting month of Ramadan compared with the non-fasting month of Dhu al-Qidah. DESIGN A retrospective cohort study medical record review. SETTING A university teaching hospital. PATIENTS AND METHODS We reviewed the records of all patients with diabetes admitted to the medical department at Benghazi Medical Center, including medical ward, intensive care unit and coronary care unit, during the months of Ramadan and Dhu al-Qidah, 2016. We compared differences in reasons for admission, length of stay and in-hospital mortality between patients admitted during Ramadan and Dhu al-Qidah and between patients who were fasting at time of admission during Ramadan and those who were not. MAIN OUTCOME MEASURES Main reason for admission, length of stay and in-hospital mortality rate. SAMPLE SIZE 402 patients with diabetes. RESULTS During Ramadan, 186 patients were admitted compared with 216 during Dhul al-Qidah. There was no statistically significant difference in reasons for admission, length of hospital stay, or in-hospital mortality (borderline for mortality, P=.078), between patients with diabetes admitted during Ramadan and Dhu al-Qidah. Of those admitted in Ramadan, 59.1% were fasting on admission. Fasting patients admitted during Ramadan had a significantly higher proportion of the diseases of the circulatory system when compared with non-fasting patients (39.4% vs. 23.6%, P=.028) while in-hospital mortality was higher in non-fasting patients (29.2% vs. 8.7%, P<.001). There was no significant difference in length of stay between fasting and non-fasting patients. CONCLUSIONS The frequency of admissions for most medical conditions were not changed during Ramadan but the frequency of acute coronary syndrome was higher in those who were fasting on admission. Patients with diabetes who were not fasting on admission had more high-risk features that prevented them from fasting and therefore are at increased risk of in-hospital mortality. LIMITATIONS Single center and retrospective.
A Robot Localization Framework Using CNNs for Object Detection and Pose Estimation

External localization is an essential part for the indoor operation of small or cost-efficient robots, as they are used, for example, in swarm robotics. We introduce a two-stage localization and instance identification framework for arbitrary robots based on convolutional neural networks. Object detection is performed on an external camera image of the operation zone providing robot bounding boxes for an identification and orientation estimation convolutional neural network. Additionally, we propose a process to generate the necessary training data. The framework was evaluated with 3 different robot types and various identification patterns. We have analyzed the main framework hyperparameters providing recommendations for the framework operation settings. We achieved up to 98% mAP@IOU0.5 and only 1.6° orientation error, running with a frame rate of 50 Hz on a GPU.
Strength endurance training but not intensive strength training reduces senescence-prone T-cells in peripheral blood in community-dwelling elderly women.

Ageing is characterized by a progressive decline in immune function known as immunosenescence (IS). While the causes of IS are likely to be multi-factorial, an age-associated accumulation of senescent T-cells and decreased naïve T-cell repertoire are key contributors to the phenomenon. On the other hand, there is a growing consensus that physical exercise may improve immune response in ageing. However, the optimum training modality required to obtain beneficial adaptations in older subjects is lacking. Therefore, we aimed to investigate the effects of exercise modality on T-cell phenotypes in older women. 100 women (aged ≥65 years) were randomized to either intensive strength training (80% of one-repetition maximum (1RM)), strength endurance training (SET, 40% 1RM), or control (stretching exercise) for 2-3 times/week during 6 weeks. The T-cell percentages and absolute counts were determined using flow cytometry and hematology analyzer. C-reactive protein was measured using immunonephelometry. We report for the first time that 6 weeks of SET significantly decreased the basal percentage and absolute counts of senescence-prone T-cells, which was positively related to the number of training sessions performed. Conceivably, training protocols with many repetitions - at a sufficiently high external resistance - might assist the reduction of senescence-prone T-cells in older women.
PhoneMD: Learning to Diagnose Parkinson's Disease from Smartphone Data

Parkinson’s disease is a neurodegenerative disease that can affect a person’s movement, speech, dexterity, and cognition. Clinicians primarily diagnose Parkinson’s disease by performing a clinical assessment of symptoms. However, misdiagnoses are common. One factor that contributes to misdiagnoses is that the symptoms of Parkinson’s disease may not be prominent at the time the clinical assessment is performed. Here, we present a machine-learning approach towards distinguishing between people with and without Parkinson’s disease using long-term data from smartphone-based walking, voice, tapping and memory tests. We demonstrate that our attentive deep-learning models achieve significant improvements in predictive performance over strong baselines (area under the receiver operating characteristic curve = 0.85) in data from a cohort of 1853 participants. We also show that our models identify meaningful features in the input data. Our results confirm that smartphone data collected over extended periods of time could in the future potentially be used as a digital biomarker for the diagnosis of Parkinson’s disease.
Regional Absorption of Fimasartan in the Gastrointestinal Tract by an Improved In Situ Absorption Method in Rats

The aim of the present study was to assess the regional absorption of fimasartan by an improved in situ absorption method in comparison with the conventional in situ single-pass perfusion method in rats. After each gastrointestinal segment of interest was identified, fimasartan was injected into the starting point of each segment and the unabsorbed fimasartan was discharged from the end point of the segment. Blood samples were collected from the jugular vein to evaluate the systemic absorption of the drug. The relative fraction absorbed (Fabs,relative) values in the specific gastrointestinal region calculated based on the area under the curve (AUC) values obtained after the injection of fimasartan into the gastrointestinal segment were 8.2% ± 3.2%, 23.0% ± 12.1%, 49.7% ± 11.5%, and 19.1% ± 11.9% for the stomach, duodenum, small intestine, and large intestine, respectively, which were comparable with those determined by the conventional in situ single-pass perfusion. By applying the fraction of the dose available at each gastrointestinal segment following the oral administration, the actual fraction absorbed (F′abs) values at each gastrointestinal segment were estimated at 10.9% for the stomach, 27.1% for the duodenum, 40.7% for the small intestine, and 5.4% for the large intestine, which added up to the gastrointestinal bioavailability (FX·FG) of 84.1%. The present method holds great promise to assess the regional absorption of a drug and aid to design new drug formulations.
Thrust Ripple Reduction in Permanent Magnet Synchronous Linear Motor Based on Tuned Viscoelastic Damper

This paper focuses on the thrust ripple reduction in permanent magnet synchronous linear motors (PMSLMs), which are applied to laser cutting machines. To meet the high-precision performance requirements of laser cutting machines, a novel auxiliary suppression device, tuned viscoelastic damper (TVD), is designed to reduce the thrust ripple of PMSLM. First, TVD is designed with the structure and motion characteristics of PMSLM. The PMSLM with TVD is an integrated structure. Then, the equivalent magnetization method is used to analyze the PMSLM thrust, which is the excitation of TVD. Under the excitation of the PMSLM thrust, the damping force of TVD is expressed by the Kelvin model and validated by finite-element analysis (FEA). Subsequently, the thrust of PMSLM with TVD is obtained by adding the PMSLM thrust and TVD damping force. Finally, the thrust ripple rate is selected as a performance index of TVD in reducing the thrust ripple. Simulation is performed to confirm the theoretical analysis. A prototype of PMSLM with TVD is manufactured and experiments are conducted to validate the effectiveness of the proposed auxiliary suppression device.
Fractal Analysis of BOLD Time Series in a Network Associated With Waiting Impulsivity

Fractal phenomena can be found in numerous scientific areas including neuroscience. Fractals are structures, in which the whole has the same shape as its parts. A specific structure known as pink noise (also called fractal or 1/f noise) is one key fractal manifestation, exhibits both stability and adaptability, and can be addressed via the Hurst exponent (H). FMRI studies using H on regional fMRI time courses used fractality as an important characteristic to unravel neural networks from artificial noise. In this fMRI-study, we examined 103 healthy male students at rest and while performing the 5-choice serial reaction time task. We addressed fractality in a network associated with waiting impulsivity using the adaptive fractal analysis (AFA) approach to determine H. We revealed the fractal nature of the impulsivity network. Furthermore, fractality was influenced by individual impulsivity in terms of decreasing fractality with higher impulsivity in regions of top-down control (left middle frontal gyrus) as well as reward processing (nucleus accumbens and anterior cingulate cortex). We conclude that fractality as determined via H is a promising marker to quantify deviations in network functions at an early stage and, thus, to be able to inform preventive interventions before the manifestation of a disorder.
Differences in secretome in culture media when comparing blastocysts and arrested embryos using multiplex proximity assay

Abstract Objectives: The aim of this study was to assess different patterns of the human embryo secretome analysed as protein levels in culture media. Furthermore, analyses to correlate protein levels with quality and timing to development of human embryos were performed. Material and methods: Human day-2 cryopreserved embryos were cultured for four days in an EmbryoScope® with a time-lapse camera, and embryo quality was evaluated retrospectively. After culture, the media were collected and relative levels of secreted proteins were analysed using Proseek Multiplex Assays. Protein levels were evaluated in relation to timing to development and the ability to form a blastocyst. Results: Specific patterns of timing of development of blastocysts were found, where a difference in time to start of cavitation was found between high- and low-quality blastocysts. There appeared to be a correlation between specific protein patterns and successful formation of morulae and blastocysts. Embryos developing into blastocysts had higher levels of EMMPRIN than arrested embryos, and levels of caspase-3 were lower in high- versus low-quality blastocysts. Also, higher levels of VEGF-A, IL-6, and EMMPRIN correlated with shorter times to morula formation. Conclusions: The secretome and timing to development differ in embryos forming blastocysts and those that become arrested, and in high- versus low-quality blastocysts. The levels of certain proteins also correlate to specific times to development.
Axillary Lymph Node Dissection for Breast Cancer: Efficacy and Complication in Developing Countries

Purpose Axillary lymph node dissection (ALND) frequently is performed as part of the surgical management of breast cancer as a therapeutic and prognostic index, but increasingly has been perceived as associated with significant complications. Data on efficacy and complications of ALND in Sudan are lacking. The aim of this study was to assess the efficacy and complications of ALND in patients with breast cancer treated with mastectomy and breast-conserving surgery. Methods We performed a prospective, hospital-based study in women with invasive breast cancer who underwent modified radical mastectomy or breast-conserving surgery with ALND between September 2014 and August 2015. The efficacy of ALND was defined as retrieval of ≥ 10 lymph nodes. Complications of ALND were assessed objectively and subjectively and defined as either present or absent. Results Of 96 patients with breast cancer included in the study, 40 (42%) developed postaxillary clearance complications. The median follow-up time was 18 months (range, 12 to 24 months). Numbness was reported by 21.9% of patients. Seroma was noted in 15.6% and lymphedema in 9.4%. Approximately 9% reported episodes of infection or inflammation at the surgical site. None of the studied factors were found to affect the incidence of complications significantly. Ten or more lymph nodes were retrieved in 81.3% of patients, and nodal metastasis was found in 62.5%. Conclusion This study shows that the prevalence of undesirable adverse effects after ALND is 42%, with paresthesia and seroma being the most prevalent. The lymphedema prevalence was low in relation to other evaluated symptoms.
Cosine Efficiency Distribution of Rotating Heliostat Field

The rotating heliostat field represents a new concept in solar thermal tower power plants. It has a low cosine effect loss than of a static field. This loss can be also minimized by finding the optimal arrangement of the heliostats on the field. In this paper we present an algorithm giving the cosine efficiency distribution of rotating heliostat field in solar tower power plants. A radial staggered configuration is used to locate heliostats on the field. The results of the average cosine efficiency distribution were compared with those found in the literature. It can be noted that our optimization of rotating heliostat field has higher cosine efficiency.
The central amygdala to periaqueductal gray pathway comprises intrinsically distinct neurons differentially affected in a model of inflammatory pain

The central nucleus of the amygdala (CeA) encompasses the main output pathways of the amygdala, a temporal lobe structure essential in affective and cognitive dimensions of pain. A major population of neurons in the CeA send projections to the periaqueductal gray (PAG), a key midbrain structure that mediates coping strategies in response to threat or stress. CeA‐PAG neurons are topographically organized based on their targeted subregion within the PAG. PAG‐projecting neurons in the central medial (CeM) and central lateral (CeL) regions of CeA are intrinsically distinct. CeL‐PAG neurons are a homogeneous population of intrinsically distinct neurons while CeM‐PAG neurons are intrinsically heterogeneous. Membrane properties of distinct CeM‐PAG subtypes are altered in the complete Freund's adjuvant model of inflammatory pain.
Percutaneous Peripheral Nerve Stimulation (PNS) for the Treatment of Chronic Low Back Pain Provides Sustained Relief

The objective of this study was to evaluate the use of percutaneous peripheral nerve stimulation (PNS) for the treatment of chronic low back pain (LBP). Percutaneous PNS offers the potential to provide an effective neuromodulation therapy using a system and fine‐wire leads designed specifically for percutaneous use with history of an excellent safety profile.
A deep learning pipeline for product recognition on store shelves

Recognition of grocery products in store shelves poses peculiar challenges. Firstly, the task mandates the recognition of an extremely high number of different items, in the order of several thousands for medium-small shops, with many of them featuring small inter and intra class variability. Then, available product databases usually include just one or a few studio-quality images per product (referred to herein as reference images), whilst at test time recognition is performed on pictures displaying a portion of a shelf containing several products and taken in the store by cheap cameras (referred to herein as query images). Moreover, as the items on sale in a store as well as their appearance change frequently overtime, a practical recognition system should handle seamlessly new products/packages. We developed a deep learning based pipeline to solve this task. First we deploy state of the art object detectors to obtain an initial product-agnostic item detection, then, we pursue product recognition through a similarity search between global descriptors computed on reference and cropped query images. To maximize performance, we learn an ad-hoc global descriptor by a CNN trained on reference images based on an image embedding loss. We have tested our pipeline on the standard grocery product [1] dataset and improved the currents state of the art. While computationally expensive at training time our system turn out not only accurate but also quite fast at test time.
Medical Treatment of COPD.

BACKGROUND Chronic obstructive pulmonary disease (COPD) is common around the world and carries a high morbidity and mortality. Symptom- and risk-oriented drug treatment is recommended, both in Germany and in other countries. It is not yet known to what extent the treatment that is actually delivered in Germany corresponds to the current recommendations in the guidelines. METHODS As recommended by the Global Initiative for Chronic Obstructive Lung Disease (GOLD) in 2017, 2281 patients of the national COPD cohort COSYCONET (COPD and Systemic Consequences-Comorbidities Network) were classified into Gold classes A-D on the basis of disease-specific manifestations and the frequency of exacerbations. Moreover, the regular use of medications was documented and categorized according to active substance groups. For all groups, the documented treatment that was actually given was compared to the recommended treatment. RESULTS 67.6% of the patients received a combination of a long-acting anticholinergic drug (LAMA) and a long-acting beta-mimetic drug (LABA), while 65.8% received inhaled corticosteroids (ICS), 11.7% theophylline, and 12.6% oral corticosteroids (OCS). Despite recommendations to the contrary, 66% of the patients in Groups A and B (low exacerbation rates) were treated with ICS; some of these patients carried an additional diagnosis of bronchial asthma. There was evidence of undertreatment mainly in groups C and D (high exacerbation rate), because many of the patients in these groups were not treated with LAMA or LAMA/LABA as recommended. CONCLUSION The observed deviations from the recommended treatment, some of which were substantial, might lead to suboptimal treatment outcomes as well as to avoidable side effects of medication.
Associations of objective versus subjective social isolation with sleep disturbance, depression, and fatigue in community-dwelling older adults

Abstract Objective: Older adults are at higher risk of experiencing social isolation, which has been linked to impaired physical and mental health. The link between social isolation and health might be due to objective deprivation of social network and/or subjective experience of loneliness. This community-based cross-sectional study examined whether the associations between social isolation and behavioral symptoms including sleep disturbance, depression, and fatigue are mostly explained by its subjective component. Methods: Randomly selected 2541 community-dwelling individuals in Los Angeles aged ≥60 years were telephone-interviewed regarding their objective and subjective social isolation (respectively social network size and loneliness), sleep disturbance, depression, and fatigue. Results: When objective and subjective social isolation were separately included in multivariate regression models, both were significantly associated with behavioral symptoms. However, once they were simultaneously included in the same multivariate models, while subjective social isolation remained strongly associated (adjusted beta 0.24 for sleep disturbance [P < 0.001], 0.44 for depression [P < 0.001], 0.17 for fatigue [P < 0.001]), objective social isolation was weakly or non-significantly associated (-0.04 for sleep disturbance [P = 0.03], -0.01 for depression [P = 0.48], -0.003 for fatigue [P = 0.89]). Additionally, those with objective social isolation were found to have worse symptoms mostly when they also experienced subjective social isolation. Conclusions: Older adults with objective social isolation may experience sleep disturbance, depression, and fatigue because they feel socially isolated, not just because they are deprived of social networks. Interventions that target social isolation might serve as potential treatments for improving behavioral health of older adults, especially by targeting its subjective component.
Neural Segmental Hypergraphs for Overlapping Mention Recognition

In this work, we propose a novel segmental hypergraph representation to model overlapping entity mentions that are prevalent in many practical datasets. We show that our model built on top of such a new representation is able to capture features and interactions that cannot be captured by previous models while maintaining a low time complexity for inference. We also present a theoretical analysis to formally assess how our representation is better than alternative representations reported in the literature in terms of representational power. Coupled with neural networks for feature learning, our model achieves the state-of-the-art performance in three benchmark datasets annotated with overlapping mentions.