Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence of Diabetes among Tuberculosis Patients and Associated Risk Factors in Kathmandu Valley

Introduction : Diabetes among tuberculosis patients is a growing concern. The prevalence of diabetes among tuberculosis patients in Nepal is not known. The objective of this study was to determine the prevalence of diabetes among tuberculosis patients and to identify the associated risk factors. Methodology : A descriptive, cross-sectional study was conducted in Kathmandu valley of Nepal. Face to face interviews using structured questionnaire were conducted to collect socio-demographic and behavioral risk factors. A random blood sugar test was carried out using glucometer. Measurements on height, weight and waist circumference were taken to obtain the anthropometric information. Results : Out of 407 tuberculosis patients recruited in the study, 37 (9.1%) were found to have diabetes. Among them 28 (6.9%) were self reported cases of diabetes while 9 (2.2%) were found with random blood sugar level >200mg/dl. Tuberculosis patients aged 50 years and above (OR 7.5; 95% CI 2.72-20.66), ever tobacco users (OR 3.5; 95% CI 1.19-10.74), high income status (OR 5.2; 95% CI 1.59-17.26) and self history of high blood pressure (OR 20.0; 95% CI 5.07-79.50) were found significantly associated with diabetes. Conclusion : Overall, the prevalence of diabetes among tuberculosis patients was 9.1%. Older age, tobacco use, high income status and history of high blood pressure were identified as associated risk factors. SAARC J TUBER LUNG DIS HIV/AIDS, 2015 XII (2), Page: 20-27
Detection of Hard Exudates in Retinal Fundus Images based on Important Features Obtained from Local Image Descriptors

Diabetic retinopathy is one of the main complications of diabetes mellitus and it is a progressive ocular disease, the most significant factor contributing to blindness in the later stages of the disease. It has been a subject of many studies in the medical image processing field for a long time. Hard exudates are one of the primary signs of early stage diabetic retinopathy diagnosis. Immediately identifying hard exudates is of great importance for the blindness and coexistent retinal edema. There are various ways of achieving meaningful information from an image and one of them is key point extraction method. In this study, we presented a technique based on the acquisition of important information by utilizing the description information about the image within the framework of the learning approach in order to identify hard exudates. This technique includes the learning and testing processes of the system in order to make the right decisions in the analysis of new retinal fundus images. We performed experimental validation on DIARETDB1 dataset. The obtained results showed us the positive effects of machine learning technique suggested by us for the detection of hard exudates.
Secure Information Fusion using Local Posterior for Distributed Cyber-Physical Systems

In modern distributed cyber-physical systems (CPS), information fusion often plays a key role in automate and self-adaptive decision making process. However, given the heterogeneous and distributed nature of modern CPSs, it is a great challenge to operate CPSs with the compromised data integrity and unreliable communication links. In this paper, we study the distributed state estimation problem under the false data injection attack (FDIA) with probabilistic communication networks. We propose an integrated ”detection + fusion” solution, which is based on the Kullback-Leibler divergences (KLD) between local posteriors and therefore does not require the exchange of raw sensor data. For the FDIA detection step, the KLDs are used to cluster nodes in the probability space and to partition the space into secure and insecure subspaces. By approximating the distribution of the KLDs with a general <inline-formula><tex-math notation="LaTeX">$\chi ^2$</tex-math><alternatives><mml:math><mml:msup><mml:mi>χ</mml:mi><mml:mn>2</mml:mn></mml:msup></mml:math><inline-graphic xlink:href="ngai-ieq1-2969352.gif"/></alternatives></inline-formula> distribution and calculating its tail probability, we provide an analysis of the detection error rate. For the information fusion step, we discuss the potential risk of double counting the shared prior information in the KLD-based consensus formulation method. We show that if the local posteriors are updated from the shared prior, the increased number of neighbouring nodes will lead to the diminished information gain. To overcome this problem, we propose a near-optimal distributed information fusion solution with properly weighted prior and data likelihood. Finally, we present simulation results for the integrated solution. We discuss the impact of network connectivity on the empirical detection error rate and the accuracy of state estimation.
From alpha to beta functional and phylogenetic redundancy

Plot‐level redundancy or alpha redundancy is usually defined as the fraction of species diversity not expressed by functional or phylogenetic diversity. Redundancy is zero when all species in one plot are maximally dissimilar from each other. In contrast, redundancy tends to its maximum if the functional or phylogenetic differences between species tend to be minimal. To explore the ecological drivers of community assembly, ecologists also use dissimilarity measures between pairs of plots (a component of beta diversity). Traditional dissimilarity measures summarize compositional differences between pairs of plots based either on species presence and absence data or on species abundances, thus attributing equal distinctiveness between any two species. In the last decades a number of dissimilarity measures which incorporate information on functional or phylogenetic differences among species have been proposed. On the basis of such improved measures, we can define an index of beta redundancy for a pair of plots as the fraction of species dissimilarity not expressed by functional or phylogenetic dissimilarity. A necessary condition to get a meaningful index of beta redundancy is that for a given pair of plots, the functional or phylogenetic dissimilarity is always lower or equal to the corresponding species dissimilarity. However, many of the existing indices of functional or phylogenetic dissimilarity can lead to values greater than for species dissimilarity. The aim of this paper was thus to introduce a new family of tree‐based measures of phylogenetic and functional dissimilarity that conform to this requirement. To show the behaviour of the proposed measures, a worked example with data on Alpine vegetation is used.
Extra-Abdominal Musculo-Aponeurotic Fibromatosis: A Case with Metachronous Multicentric Lesions of the Right Thigh

Abstract Fibromatoses are a group of benign proliferations of fibrous tissue with clinical behaviour ranging from that of truly malignant tumours to that of benign reactive fibrous proliferations. Some of the superficial fibromatoses are fairly common but deep ones, also known as desmoid tumours or musculoaponeurotic fibromatoses, are rare. We describe a case of extra-abdominal musculo- aponeurotic fibromatosis in a 22-years old male. He underwent 14 operations for a period of 9 years for fibromatosis of the posterior surface of the right lower limb. The histological findings of the lesions were similar consistent across surgeries and consistent with a diagnosis of aggressive extra-abdominal fibromatosis.
PROMs and PREMs in Dutch integrated head and neck cancer care: Measurements and evaluation.

209Background: Providing patient-centred care is an essential component of high quality integrated care. Nowadays, patient reported outcomes and experiences are increasingly used to measure quality of care. As part of a quality registration, the Dutch Head and Neck Audit, patient reported outcomes (PROs) and experiences (PREs) of patients with head and neck cancer (HNC) are measured with questionnaires and evaluated to increase patient-centred care. Methods: Patientswere recruited from nine hospitals participating in the DHNA. Validated questionnaires were distributed at baseline, 3, 6 and 12 months follow-up. Included PROMs were EQ-5D-3L, EORTC QLQ-C30 and EORTC QLQ-H&N35. Included PREMs were Consumer Quality index for Oncologic care (CQO) and Radiotherapeutic care (CQR). CQO and CQR have similar domains with different questions. With descriptive analysis, ANOVA and mixed model analysis, differences over time and between treatment groups were analyzed. Results: Questionnaires were filled in by 238 patien.
Livelihoods of households living near Yangambi Biosphere Reserve, Democratic Republic of Congo

Forests in the Democratic Republic of Congo (DRC) cover more than 100 million hectares (ha), are home to thousands of plant and animal species, and regulate continental scale water cycles and global climate change [1]. Nearly 40 million people live in or near these forests. They are amongst the poorest and most vulnerable globally, despite the wealth of natural resources around them. Increasing demand for food, shelter, energy and income contributes significantly to deforestation and forest degradation [2] and links critical development and environmental challenges with local and global implications. The future of DRC’s Forests depends on creating pathways out of poverty for those living around and within the forests while sustainably managing resources.
What is the Impact of Lifestyle on the Incidence of Cancer

In the year 2012, more than 14 million people were diagnosed with cancer and 8.2 million people died of cancer worldwide [1]. With the number of cancer cases increasing worldwide; it is important to decipher the role that lifestyle plays in the development of this disease. It has been estimated that around 42% of cancer cases each year in the UK are linked to 14 major lifestyle habits and other factors [2]. There are multiple internal and external factors related to lifestyle that can lead to cancer including tobacco smoke, UV and ionising radiation, occupational exposure to harmful chemical and biological substances, alcohol, obesity and lack of physical activity.
Sustainable Development Model and Innovation of Mineral Resources

Mineral resources are important material resources for the development of national economy, but the long-term linear and extensive mining mode leads to low exploitation and utilization of resources and serious waste of resources on the one hand; on the other hand, the environment of mining areas is deteriorating, and safety problems are prominent. Correctly handling the relationship between mineral resources, environment, and economic development has become the main problem of sustainable development of mineral enterprises. There are still some problems in the mine. Therefore, it is particularly necessary to explore the construction path model of green mine under the background of the new era. Based on the coordinated development of resources, environment, and regional economy, this chapter studies the green mine construction mode by using the knowledge of resource economics, mining science, and sustainable development theory, combining theory with empirical analysis and qualitative and quantitative analysis.
Robust non-Gaussian semantic simultaneous localization and mapping

The recent success of object detection systems motivates object-based representations for robot navigation; i.e. semantic simultaneous localization and mapping (SLAM), in which we aim to jointly estimate the pose of the robot over time as well as the location and semantic class of observed objects. A solution to the semantic SLAM problem necessarily addresses the continuous inference problems where am I? and where are the objects? , but also the discrete inference problem what are the objects? We consider the problem of semantic SLAM under non-Gaussian uncertainty. The most prominent case in which this arises is from data association uncertainty, where we do not know with certainty what objects in the environment caused the measurement made by our sensor. The semantic class of an object can help to inform data association; a detection classified as a door is unlikely to be associated to a chair object. However, detectors are imperfect, and incorrect classification of objects can be detrimental to data association. While previous approaches seek to eliminate such measurements, we instead model the robot and landmark state uncertainty induced by data association in the hopes that new measurements may disambiguate state estimates, and that we may provide representations useful for developing decisionmaking strategies where a robot can take actions to mitigate multimodal uncertainty. The key insight we leverage is that the semantic SLAM problem with unknown data association can be reframed as a non-Gaussian inference problem. We present two solutions to the resulting problem: we first assume Gaussian measurement models, and non-Gaussianity only due to data association uncertainty. We then relax this assumption and provide a method that can cope with arbitrary non-Gaussian measurement models. We show quantitatively on both simulated and real data that both proposed methods have robustness advantages as compared to traditional solutions when data associations are uncertain. Thesis Supervisor: John J. Leonard Title: Samuel C. Collins Professor of Mechanical and Ocean Engineering
SOCIODEMOGRAPHIC CLINICAL ASPECTS AND QUALITY OF LIFE IN PATIENTS WITH RHEUMATOID ARTHRITIS Aspecto sociodemográfico, clínico e qualidade de vida em pacientes com artrite reumatoide Aspecto sociodemográfico, clínico y calidad de vida de pacientes con artritis reumatoide

Objective: To characterize the sociodemographic clinical aspects and quality of life of patients with rheumatoid arthritis (RA). Methods: This was a descriptive, cross-sectional quantitative research that evaluated 22 individuals with RA over 18 years old, regardless of sex. Participants were referred to the Multisectoral Analysis Laboratory of the State University of Santa Catarina by rheumatologists of the Brazilian National Health System in the period from June to September 2010. It was used a form to obtain sociodemographic and clinical data, the level of disease activity (Disease Activity Score 28) and the Quality of Life Questionnaire (36 Item Short-Form Health Survey). Results: There was a prevalence of female gender, with 81.8% (n=18); white ethnicity, with 90.9% (n=20); and sixth decade of life, with 60 (±12.9) years for male gender. Among the symptoms, 17 individuals (77.3%) reported pain as the main complaint. Regarding the level of disease activity, the mean values were 4.47±1.56 with a prevalence of 10 patients (45.5%) presenting moderate activity. Concerning QoL, it was found a significant difference in the domains pain / social aspect and the level of disease activity (p <0.05). Regarding the domain pain, there was a significant difference when comparing the groups high and low disease activity (p<0.01) and between the low and moderate groups (p <0.01). Conclusion: It was possible to identify in the individuals with RA participating in this study a deficit in their general state of health. Additionally, the high level of disease activity interfered with painful symptomatology and hindered social aspects.
Unified Entanglement Scaling for Flexible, Semiflexible, and Stiff Polymer Melts and Solutions

The entanglement length Nₑ is a key parameter for all entangled polymer fluids for which no comprehensive scaling theory yet exists. We have pieces of a theory; the Lin-Noolandi (LN) argument predicts Nₑ scaling for flexible chains that agrees with data on polymer melts. There are arguments for how Nₑ should depend on polymer concentration, but which are not obviously consistent with LN. Morse scaling describes entanglement for solutions of stiff chains, consistent with data. Everaers proposed an ansatz that Nₑ depends only on the arclength concentration, as if chains were uncrossable threads of vanishing thickness. This ansatz is consistent with simulations of bead-spring chains, but not with LN, as it has no role for packing length, the central parameter in LN scaling. We propose a comprehensive scaling theory that includes LN in one limit, thread ansatz in another, and reduces to Morse scaling for stiff chains. One new ingredient is that the typical distance of closest approach between two chains is governed by the packing length or chain diameter, whichever is larger. If a chain is sufficiently flexible and bulky, the packing length is relevant; but for stiffened bead-spring chains without side groups, the packing length is smaller than the chain diameter, so thread scaling applies. Our approach presents a consistent physical picture of entanglements in all regimes as close encounters between two chains. For solutions, we determine the entanglement probability between chain segments, and consistently describe the crossover between the Edwards and semidilute regimes.
Exploring spatially varying relationships between forest fire and environmental factors at different quantile levels

The effect of driving factors on forest fire occurrence at various risk levels beyond average fire risk is of great interest to forest fire managers in practice. Using forest fire occurrence data collected in Fujian province, China, global quantile regression (QR) and geographically weighted quantile regression (GWQR) were applied to investigate the spatially varying relationships between forest fire and environmental factors at different quantiles (e.g. 0.50, 0.75, 0.90 and 0.99) of fire occurrence. These results indicated that: (1) at each quantile, the regression coefficients of both global QR and GWQR were negative for elevation, slope and Normalised Difference Vegetation Index, and positive for settlement density, national road density and grass cover; (2) low number of pixels with high fire occurrence in space might dramatically affect the analysis and modelling of the relationship between fire occurrence and a specific environmental factor; (3) according to GWQR, the relationships between forest fire and environmental factors significantly varied across the study area at different quantiles of fire occurrence; and (4) the GWQR models performed better in model fitting and prediction than the QR models at all quantiles. Therefore, the GWQR models could help decision makers to better plan for forest fire management and prevention strategies.
Kathleen Mears lecture : Allied health issues and actions

ABSTRACT.The term “allied health” is used to identify a cluster of health professions, encompassing as many as 100 occupational titles, exclusive of physicians and nurses. Approximately two million allied health professionals are employed in the United States. Neurodiagnostics is just one of many fields that fall under the domain of allied health. As the number of older Americans increases, so does the need for allied health professionals.There are many issues that affect allied health professionals. These issues include licensure, education, and research, to name a few. All allied health professions will need to search for opportunities to collaborate on common issues. Health Professions Network is an organization formed to link these individual organizations together. Through collaboration we can find more effective solutions and have a stronger voice when faced with legislative issues. This presentation highlights some issues and suggests some action we can take to position our profession and allied he.
ДИСКУРС ПОДВИЖНЫХ ИГР АНГЛИЙСКОГО ШКОЛЬНИКА КАК ПОЛИМОДАЛЬНАЯ КОММУНИКАЦИЯ

Гаранина Наталья Викторовна, Ююкина Людмила Викторовна ДИСКУРС ПОДВИЖНЫХ ИГР АНГЛИЙСКОГО ШКОЛЬНИКА КАК ПОЛИМОДАЛЬНАЯ КОММУНИКАЦИЯ В статье рассматривается игровой дискурс английского школьника как вербальная коммуникация, в которой реализуются модальность действительности и модальность недействительности (необходимости/долженствования; возможности/невозможности; побудительная; интенциональная; оптативная; гипотетическая). Анализируются лексико-грамматические средства реализации данных видов модальности в дискурсе английского школьника на всех этапах подвижной игры (зачин, ход игры, окончание). Игровой дискурс представлен как полимодальная коммуникация. Адрес статьи: www.gramota. net/materials/2/2019/11/61.html
Algebraic expressions for estimating the impact depths of a surface barrier over a homogeneous soil

Engineered surface barriers are used to isolate subsurface contaminants for effective long‐term containment of waste of a variety of types. The impact depths of a surface barrier are affected by the pre‐barrier recharge rate and the properties of the soil beneath the barrier. In this paper, algebraic expressions are developed to estimate drainage velocities and barrier impact depths after the emplacement of a surface barrier. Four impact depth terms are used to convey barrier impact: the near‐zero‐, 50%, average‐, and full‐impact depths. The algebraic expressions show that the average‐impact depth is no more than one‐third of the near‐zero‐impact depth, whereas the 50% impact depth is slightly larger than one‐half of the near‐zero‐impact depth. The full‐impact depth, depending on the final recharge rate from the surface barrier, is usually much smaller than the other impact depths. These differences lead to a very large transition zone beneath a surface barrier. A field drainage experiment and a series of numerical simulations were used to test the algebraic expressions. The experimental data and numerical results corroborated the analytical models by predicting very similar water content profiles and/or near‐zero‐, 50%, average‐, and full‐impact depths during the drainage process. The algebraic expressions provided are useful for quickly identifying sites where the depth of the existing contaminants could be beyond the protection of a surface barrier.