Miracle-dz/UniFAR-FTUs huggingface dataset:
A comparative study of mid-day meal beneficiaries and private school attendees

Background: India is undergoing a rapid demographic transition accompanied by an epidemiologic and nutritional transition. The nutritional status of school-going children who form a major section of the population, can give an indication of the changing trends in nutritional profile of the population. According to Planning Commission report, 2010, Mid Day Meal (MDM) Program has been successful in addressing classroom hunger and the objective of social equity in government school attendees. Aims & Objectives: To study the pattern of school lunch intake and nutritional status in private and government school-going children of district Dehradun. Material & Methods: This was an observational cross-sectional study in district Dehradun in government and private schools, with participants from class 1 to 12. A 24-hour dietary recall was done to measure caloric intake. Height and weight were measured using Microtoise (accuracy 0.1cm) and digital weighing machine (Omron Model: HN286, accuracy 100 gm). Statistical analysis was done using SPSS, version 22. Nutritional status was classified using WHO cut-offs and analyzed using AnthroPlus Software. Student t-test was used to compare caloric intake of subgroups. Association between nutritional status and other variables was assessed using Chi-squared test. Results: Using WHO cut-offs, the proportion of thin children was 5.4% in private school and 21.5% in MDM beneficiaries of government schools. The proportion of children who were overweight was 27.7% in private schools and 3.6% in government schools (p<.0.05). The caloric content of school lunch was 271 Kcal in private school attendees and 375 Kcal in MDM beneficiaries. Proportion of children who skipped school lunch increased as they progressed in higher classes, and this proportion was greater in students of government schools beyond class VIII. Conclusion: The study highlights the need for more large scale nutritional surveys with school lunch in focus.
Autonomous Extraction of a Hierarchical Structure of Tasks in Reinforcement Learning, A Sequential Associate Rule Mining Approach

Reinforcement learning (RL) techniques, while often powerful, can suffer from slow learning speeds, particularly in high dimensional spaces. Decomposition of tasks into a hierarchical structure holds the potential to significantly speed up learning, generalization, and transfer learning. However, the current task decomposition techniques often rely on high-level knowledge provided by an expert (e.g. using dynamic Bayesian networks) to extract a hierarchical task structure; which is not necessarily available in autonomous systems. In this paper, we propose a novel method based on Sequential Association Rule Mining that can extract Hierarchical Structure of Tasks in Reinforcement Learning (SARM-HSTRL) in an autonomous manner for both Markov decision processes (MDPs) and factored MDPs. The proposed method leverages association rule mining to discover the causal and temporal relationships among states in different trajectories, and extracts a task hierarchy that captures these relationships among sub-goals as termination conditions of different sub-tasks. We prove that the extracted hierarchical policy offers a hierarchically optimal policy in MDPs and factored MDPs. It should be noted that SARM-HSTRL extracts this hierarchical optimal policy without having dynamic Bayesian networks in scenarios with a single task trajectory and also with multiple tasks' trajectories. Furthermore, it has been theoretically and empirically shown that the extracted hierarchical task structure is consistent with trajectories and provides the most efficient, reliable, and compact structure under appropriate assumptions. The numerical results compare the performance of the proposed SARM-HSTRL method with conventional HRL algorithms in terms of the accuracy in detecting the sub-goals, the validity of the extracted hierarchies, and the speed of learning in several testbeds.
Lineament extraction from Landsat TM, JERS-1 SAR, and DEM for geological applications

The Hough transform is an efficient numerical method for extracting lineaments or linear features from 2-D geological and geophysical data, including satellite images. Analysis of lineaments has also been widely carried out in geological research, and Landsat TM data have been used most extensively for geological lineament investigations. However, there has been less geological application research carried out in the lineament extraction from synthetic aperture radar (SAR) data. This research has tested several spatial data including Landsat TM, JERS-1 SAR and DEM data for automatic geological lineament analyses. The Hough transform technique is applied here for the extraction of lineaments from preprocessed binary spatial data. The multiresolution method is tested to extract lineaments efficiently, because geological lineaments usually appear in various length scales. The Kyungsang Basin in the southeastern part of the Korean peninsula was selected as the test site in this research. The lineaments are extracted from JERS-1 SAR, Landsat TM, and DEM data using both manual and the automatic Hough transform method. The results of lineament extraction indicate that the predominant direction is the NNE direction of azimuth angle 0/spl deg/-30/spl deg/, and the second dominant directions are the NNW, NE, and WNW directions. The results obtained in this research agree well with the regional trends and also with the local geological maps.
Function of BRD4 in the pathogenesis of high glucose-induced cardiac hypertrophy

Diabetic cardiomyopathy is one of the major complications of diabetes, and due to the increasing number of patients with diabetes it is a growing concern. Diabetes-induced cardiomyopathy has a complex pathogenesis and histone deacetylase-mediated epigenetic processes are of prominent importance. The olfactory bromodomain-containing protein 4 (BRD4) is a protein that recognizes and binds acetylated lysine. It has been reported that the high expression of BRD4 is involved in the process of cardiac hypertrophy. The aim of the present study was to investigate the function of BRD4 in the process of high glucose (HG)-induced cardiac hypertrophy, and to clarify whether epigenetic regulation involving BRD4 is an important mechanism. It was revealed that BRD4 expression levels were increased in H9C2 cells following 48 h of HG stimulation. This result was also observed in a diabetic rat model. Furthermore, HG stimulation resulted in the upregulation of the myocardial hypertrophy marker, atrial natriuretic peptide, the cytoskeletal protein α-actin and fibrosis-associated genes including transforming growth factor-β, SMAD family member 3, connective tissue growth factor and collagen, type 1, α1. However, administration of the specific BRD4 inhibitor JQ1 (250 nM) for 48 h reversed this phenomenon. Furthermore, protein kinase B (AKT) phosphorylation was activated by HG stimulation and suppressed by JQ1. In conclusion, BRD4 serves an important role in the pathogenesis of HG-induced cardiomyocyte hypertrophy through the AKT pathway.
Vegetation mapping using multi-temporal ETM+ data and a decision tree classifier

Decision tree classifiers have received much recent attention, particularly with regards to land cover classifications at continental to global scales. Their usage with high spatial resolution data, however, has not yet been fully explored. In support of the National Park Service Vegetation Mapping Program, we have examined the feasibility of using a commercially available decision tree classifier with multitemporal satellite data from the Enhanced Thematic Mapper-Plus instrument to map 11 land cover types at the Delaware Water Gap National Recreation Area near Milford, PA. Using land cover classes as specified by the National Vegetation Classification Standard at the Formation level, the final land cover map has an overall accuracy of 83.6% when tested against a validation data set acquired on the ground. This same accuracy is 98.6% when considering only forest vs. non-forest classes. Usage of multiple dates improves the accuracy over the use of a single date, particularly for the different forest types. These results demonstrate the potential applicability of such an approach to the entire National Park system and to high spatial resolution land cover and forest mapping applications.
DEVELOPING LISTENING TASKS FOR GRADE VIII STUDENTS IN THE FIRST SEMESTER AT SMP NEGERI 2 GRABAG IN THE ACADEMIC YEAR OF 2012/2013

The objectives of this study are to identify the target needs and learning needs of Grade VIII students of SMP Negeri 2 Grabag in teaching and learning process of listening and to develop the appropriate listening tasks for Grade VIII students of SMP Negeri 2 Grabag in the academic year of 2012/2013. This study was classified as a research and development (R & D) study. The instruments used in this study were interview guidelines and questionnaires. The data from the need analysis and evaluation were analyzed quantitatively, while the data from the interviews were analyzed qualitatively. Meanwhile, the development procedure comprised of identification of needs for materials (needs analysis), exploration of needs, production of materials, student use of the materials (try-out), evaluation of materials, revision of the materials, and production of the final draft. The results of the research were as follows. The average scores obtained from the evaluation questionnaires ranging from 3.04 to 4.37 show the students’ agreements on the developed tasks. Based on the try-out and evaluations results, listening tasks that are suitable for Grade VIII students of SMP Negeri 2 Grabag are those which help them explore their listening skills. Meanwhile, the characteristics of listening tasks that are suitable for Grade VIII students of SMP Negeri 2 Grabag are that: (1) the goals of the tasks should be feasible and appropriate to the indicators stated in the course grids; (2) the inputs should be comprehensible, not be too long, be in interesting and familiar topics, use brief and motivating explanations, and use simple vocabulary which might help the students to accomplish the tasks and improve their vocabulary mastery; (3) the activities should be varied, interesting, challenging, simple, motivating, sequenced from guided to free, and from easy to difficult; (4) the teacher should play roles as a prompter, a resource, a tutor, an instructor, a facilitator, and a monitor; (5) the students should play roles as active and responsive participants; (6) the setting should be varied from individual, pairs, small groups, or whole class works; and (7) the instruction should be clear, the vocabulary should be simple and understandable, the illustration should be clear, interesting, and understandable, and the recording should be clear.
Deep Unfolded Robust PCA with Application to Clutter Suppression in Ultrasound

Contrast enhanced ultrasound is a radiation-free imaging modality which uses encapsulated gas microbubbles for improved visualization of the vascular bed deep within the tissue. It has recently been used to enable imaging with unprecedented subwavelength spatial resolution by relying on super-resolution techniques. A typical preprocessing step in super-resolution ultrasound is to separate the microbubble signal from the cluttering tissue signal. This step has a crucial impact on the final image quality. Here, we propose a new approach to clutter removal based on robust principle component analysis (PCA) and deep learning. We begin by modeling the acquired contrast enhanced ultrasound signal as a combination of a low rank and sparse components. This model is used in robust PCA and was previously suggested in the context of ultrasound Doppler processing and dynamic magnetic resonance imaging. We then illustrate that an iterative algorithm based on this model exhibits improved separation of microbubble signal from the tissue signal over commonly practiced methods. Next, we apply the concept of deep unfolding to suggest a deep network architecture tailored to our clutter filtering problem which exhibits improved convergence speed and accuracy with respect to its iterative counterpart. We compare the performance of the suggested deep network on both simulations and in-vivo rat brain scans, with a commonly practiced deep-network architecture and the fast iterative shrinkage algorithm, and show that our architecture exhibits better image quality and contrast.
Rosuvastatin protects against oxidized low-density lipoprotein-induced endothelial cell injury of atherosclerosis in vitro

Atherosclerosis-induced cardiovascular diseases (CVDs) are accompanied by substantial morbidity and mortality. The loss and injury of endothelial cells is the primary cause of atherosclerosis. Rosuvastatin is an alternative agent used to reduce the risk of cardiovascular disease. Subsequently, the present study aimed to investigate the protective effects of rosuvastatin on oxidized-low-density lipoprotein (ox-LDL)-induced human umbilical vein endothelial cell (HUVEC) injury. The viability of ox-LDL-cultured HUVECs with or without rosuvastatin (0.01, 0.1 and 1 µmol/l) pretreatment, and pretreatment at different time points (3, 6, 12 and 24 h) was determined using an MTT assay. Morphological changes and the extent of apoptosis were detected; the anti-oxidase activity, including superoxide dismutase (SOD) and catalase (CAT), was examined, and the contents of malondiahdehyde (MDA) and nitric oxide (NO) were measured. The phosphorylation levels of endothelial nitric oxide synthase (eNOS), protein kinase B (Akt) and phosphoinositide 3 kinase (PI3K) were detected using western blot analysis. The results demonstrated that pretreatment with 0.01–1 µmol/l rosuvastatin decreased cell apoptosis caused by ox-LDL. Notably, pretreatment with 1 µmol/l rosuvastatin for >12 h increased cell viability. Additionally, DAPI staining revealed that rosuvastatin inhibited HUVEC apoptosis. Rosuvastatin treatment also resulted in increased SOD and CAT activities and decreased MDA content in ox-LDL-stimulated HUVECs. Furthermore, pretreatment with 0.01–1 µmol/l rosuvastatin significantly increased` the NO content compared with HUVECs treated with ox-LDL alone. Western blot analyses demonstrated that rosuvastatin upregulated the phosphorylation of eNOS, Akt and PI3K. These findings indicated that rosuvastatin could protect HUVECs against ox-LDL-induced injury through its anti-oxidant effect and its ability to upregulate the expression of vascular endotheliocyte-protecting factors.
Cognitive impairment does not cause invalid performance: analyzing performance patterns among cognitively unimpaired, impaired, and noncredible participants across six performance validity tests

Abstract Objective: Performance validity tests (PVTs) are essential in neuropsychological evaluations; however, it has been questioned how PVTs function in the context of cognitive impairment, and whether cognitive impairment alone is sufficient to cause PVT failure. Further, there is concern that some clinicians will disregard failed PVTs due to their perception that failures represent false-positive errors secondary to cognitive impairment. This study examined patterns associated with cognitively impaired versus noncredible performance across a battery of PVTs and neuropsychological tests. Additionally, the impact of VA service-connection and disability-seeking status on test validity was investigated. Method: A mixed-clinical sample of 103 veterans were administered six PVTs and neuropsychological tests. Performance was compared across three groups: valid-cognitively unimpaired, valid-cognitively impaired, and noncredible. Results: Significant PVT score differences and failure rates emerged across the three groups, with nonsignificant to small differences between valid-unimpaired and valid-impaired groups, and large differences between impaired and noncredible groups. In contrast, there were nonsignificant to small differences on neuropsychological tests between the valid-impaired and noncredible groups, indicating that impaired participants performed significantly better on PVTs despite comparable neurocognitive test scores. Service-connection rating itself was not associated with PVT failure, but an active disability claim to increase and/or establish service connection was associated with worse PVT performance. Conclusion: This study supports the use of multiple PVTs during evaluations of patients with varied cognitive abilities. Results indicated increased risk of PVT failure in patients who were seeking initiation/increase in service-connected payments, and shows that cognitive impairment does not cause PVT failure.
An artificial neuron approach to speech processing based on a hidden Markov model

The paper discusses possible designs for a hidden Markov model using artificial neural network techniques. Applications are speech generation and speech recognition. The designs could be the basis for a computer program to realise an HMM; or they could be inspiration for a special purpose piece of hardware. The designs have two parts. The first determines the time sequence of hidden states. Although the design uses mainly standard logic components, the behaviour will be similar to a backpropagation layer of ANNs. The second part consists of one or more layers of feedforward AN processing elements in a standard backpropagation network with final outputs coded speech data. For training an HMM recognizer, the normal approach is to use the Viterbi Algorithm followed by fine tuning using the Baum Welch re-estimation algorithm. The ANN-HMM can be trained this way, but it can also be trained by the backpropagation algorithm, BP. The latter ties very directly to the unknown weights in the ANN circuits and may facilitate topological design.
Mobility-Aware Cell Clustering Mechanism for Self-Organizing Networks

Self-Organizing Networks (SON) which automate the mobile networks in a cost-efficient way can provide extensive benefits for mobile network operators that are facing several challenges, such as providing maximum coverage and balanced/efficient usage of spectrum and energy. However, a major challenge in future wireless cellular systems is the design of self-organizing architecture that can enable re-configurable, scalable, flexible, low-cost, and efficient solutions for supporting increasingly diverse applications, products, and services of user and network requirements. In this paper, we discuss the benefits and opportunities of mobility-aware clustering capability on different conventional SON functions and advanced Long-Term Evolution features. We further propose a novel cell clustering methodology, which utilizes handover attempt data and aims to collect the cells that have higher mobility activity with each other in a single cluster. One of the main benefits of the clustering mechanism is to reduce the complexity of network optimization processes via checking smaller number of cells instead of evaluating entire network, as their number is gradually increasing. We consider real-world data of evolved Node-Bs (eNodeBs) in one of the major cities while evaluating our novel clustering technique that considers the mobility activities and location information of eNodeBs. In our evaluations, ${k}$ -means clustering is used as a benchmark. The clustering technique provides the detection of the cells whose serving regions are overlapped. Our results indicate that up to %6 increment is achieved in number of the ratio of intra-cluster handover attempts to total handover attempts. Additionally, the results further show a reduction in the standard deviation of the number of cells within a single cluster with a ratio of %8, which yields more uniform distribution of the cells across different clusters.
Soil moisture dynamics under two rainfall frequency treatments drive early spring CO2 gas exchange of lichen-dominated biocrusts in central Spain

Background Biocrusts, communities dominated by mosses, lichens, cyanobacteria, and other microorganisms, largely affect the carbon cycle of drylands. As poikilohydric organisms, their activity time is often limited to short hydration events. The photosynthetic and respiratory response of biocrusts to hydration events is not only determined by the overall amount of available water, but also by the frequency and size of individual rainfall pulses. Methods We experimentally assessed the carbon exchange of a biocrust community dominated by the lichen Diploschistes diacapsis in central Spain. We compared the effect of two simulated precipitation patterns providing the same overall amount of water, but with different pulse sizes and frequency (high frequency: five mm/day vs. low frequency: 15 mm/3 days), on net/gross photosynthesis and dark respiration. Results Radiation and soil temperature, together with the watering treatment, affected the rates of net and gross photosynthesis, as well as dark respiration. On average, the low frequency treatment showed a 46% ± 3% (mean ± 1 SE) lower rate of net photosynthesis, a 13% ± 7% lower rate of dark respiration, and a 24% ± 8% lower rate of gross photosynthesis. However, on the days when samples of both treatments were watered, no differences between their carbon fluxes were observed. The carbon flux response of D. diacapsis was modulated by the environmental conditions and was particularly dependent on the antecedent soil moisture. Discussion In line with other studies, we found a synergetic effect of individual pulse size, frequency, environmental conditions, and antecedent moisture on the carbon exchange fluxes of biocrusts. However, most studies on this subject were conducted in summer and they obtained results different from ours, so we conclude that there is a need for long-term experiments of manipulated precipitation impacts on the carbon exchange of biocrusts. This will enable a more complete assessment of the impacts of climate change-induced alterations in precipitation patterns on biocrust communities.
Utility of SARs for mapping forest disturbance in Siberia

Radar backscatter data from multiple SAR satellites were acquired and analyzed for two sites subject to the forest disturbances in Western Siberia, Russia. The backscatter from disturbed and non-disturbed sites were analyzed and the individual and combined capabilities of ERS, JERS, and Radarsat evaluated. JERS was the single most useful radar for this analysis. The combination of radars improved the results.
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