Miracle-dz/UniFAR-FTUs huggingface dataset:
Preventing childhood obesity in early care and education programs : selected standards from caring for our children : national health and safety performance standards; guidelines for early care and education programs

All-new set of national standards describing evidence-based best practices in nutrition, physical activity, and screen time for early care and education programs. The all-new Preventing Childhood Obesity in Early Care and Education is the new set of national standards describing evidence-based best practices in nutrition, physical activity, and screen time for early care and education programs. The standards are for all types of early care and education settings - centers and family child care homes. Areas of coverage: General nutrition requirements - Meal and snack patterns - Requirements for infants including supporting breastfeeding - Requirements for toddlers and preschoolers - Meal service and supervision - Food brought from home - Nutrition education - Active opportunities for physical activities - Outdoor and indoor play time Caregivers/teachers' encouragement of physical activity - Screen time limits - Policies on infant feeding, food and nutrition services, and physical activity.
Demethylation Therapy As A Novel Treatment For Human Papilloma Virus-Associated Head And Neck Cancer

DEMETHYLATION THERAPY AS A NOVEL TREATMENT FOR HUMAN PAPILLOMA VIRUS-ASSOCIATED HEAD AND NECK CANCER. Michael A. Hajek, Natalia Issaeva, and Wendell G. Yarbrough. Section of Otolaryngology, Department of Surgery, Yale University, School of Medicine, New Haven, CT. 5-azacytidine (5-aza) and its structural analog 5-aza-2’-deoxycytidine (decitabine) are demethylating agents currently used to treat myelodysplastic syndrome and acute myeloid leukemia. In addition to demethylating DNA, they are known to cause DNA damage and activate DNA damage response pathways, but our mechanistic understanding of these processes is incomplete. Given the unique epigenetic profile of human papilloma virus-associated (HPV+) head and neck squamous cell carcinoma (HNSCC), we sought to develop demethylation therapy as a novel, targeted treatment for this subset of cancer that has less morbidity than current treatments. We wanted to characterize the DNA damage and describe the mechanism of damage induced by 5-aza in these cells, as well as the cellular response and effect on metastatic potential in cells, xenograft models, and tumors from patients treated in a clinical trial at the Yale Cancer Center. By using pulsed-field gel electrophoresis, we found that demethylation treatment induces DNA double strand break formation exclusively in HPV+ head and neck cancer cells, and that these breaks depend on active transcription, replication, and expression of a known antiviral enzyme, apolipoprotein B mRNA editing enzyme catalytic polypeptide-like 3 (APOBEC3B). Furthermore, we found that demethylation therapy also reactivates p53, downregulates HPV genes, reduces the expression of matrix metalloproteinases, and reduces the metastatic potential in cells, xenograft models, and in patient tumors. In addition, we sought to discover biomarkers to identify a subset of HPV+ head and neck cancer patients that may be amenable to de-escalated treatment. In doing so, by analyzing The Cancer Genome Atlas (TCGA), we found that roughly one third of HPV+ head and neck tumors harbor inactivating mutations in TRAF3 (TNF receptor associated factor 3) or CYLD (cylindromatosis) that predict a lack of viral integration and improved patient survival, thus questioning the canonical model of HPV-driven carcinogenesis and identifying a group of patients that may respond to de-escalation therapy.
Hepatitis C knowledge among new injection drug users

Aims: New injection drug users (IDUs) are vulnerable to hepatitis C infection from risky injection practices. This article considers the range of hepatits C virus (HCV) knowledge among participants in a 2-year study examining the behaviours of new IDUs. Methods: Respondents (n = 36) were members of a cohort of new IDUs recruited in the New York City metropolitan area whose first injection occurred within the previous 18 months. Respondents were offered human immuno virus (HIV), hepatits B virus (HBV) and HCV testing. Two tested HIV positive and 12 tested HCV positive. During pre-test counselling they completed a qualitative interview focusing on aspects of HCV including: transmission, symptoms, long-term effects, prevention, treatment, concern regarding contracting HCV and how this concern impacted drug use and injection practices. Findings: Substantial gaps were seen in HCV knowledge. While respondents were aware that HCV is a blood-borne virus, the majority had only approximate knowledge regarding transmission, symptoms and effects. Respondents reported little discussion of HCV with peers and minimal concern about contracting HCV, especially compared with HIV. Conclusion: Accurate HCV information is failing to reach new IDUs, and new IDUs may not value the little information they do receive. More effective and innovative efforts are required to disseminate effective HCV prevention information to new IDUs.
Kernel Methods and Frequency Domain Independent Component Analysis for Robust Speaker Identification

OF THESIS Kernel Methods and Frequency Domain Independent Component Analysis for Robust Speaker Identification The speaker identification is one of the key technologies for person identification in humanoid robots. Especially, when the face information is not available, the speaker identification is the only way to identify person, thus, to improve the speaker identification performance is an important issue for person identification tasks. There are four major issues in speaker identification for humanoid robots in practice. First, the humanoid robots should identify the speaker in real-time with high identification rates. In these days, the kernel methods such as the support vector machine (SVM) and kernel logistic regression (KLR) are popular for speaker identification tasks, and the kernel based systems outperform the conventional Gaussian Mixture Model (GMM) based system. However, the kernel based speaker identification systems are usually computationally intensive, and this is of course not preferable for real-time implementation. To deal with the computational issue, we propose a method of approximating the sequence kernel that is shown to be computationally very efficient in Chapter 3. More specifically, we formulate the problem of approximating the sequence kernel as the problem of obtaining a pre-image in a reproducing kernel Hilbert space. The effectiveness of the proposed approximation is demonstrated in text-independent speaker identification experiments with 10 male speakers—our approach provides significant reduction in computation time while performance degradation is kept moderately. Based on the proposed method, we develop
Measuring Security in Requirements Engineering

The aim of this paper is to measure the security and related verification method in requirements engineering (RE). There are a few existing approaches to measure RE performance like IEEE Software Requirements Specification (SRS) and Security Quality Requirements Engineering (SQUARE). However, these existing approaches have some limitations such as lack of flexibility and require long implementation period. In order to address these issues, this paper intends to propose a new set of tools. First is the Effective Security Check List (ESCL), which is a check list with security questions that should be considered for measuring security. Secondly, the Traceability Matrix(TM), which is a two dimensional matrix to measure security during RE. Thirdly, Requirement Engineering Assessment Document (READ), which is a tool containing all statistical information about security performance during RE. The combination of presented approaches had been implemented in a case study. The outcome results are encouraging and illustrated integrated outcomes within existing RE model. The security level had also been properly measured. DOI: http://dx.doi. org/10.11591/ij-ict.v1i2. 695
Reliability evaluation and error mitigation in pedestrian detection algorithms for embedded GPUs

Pedestrian detection reliability is a fundamental problem for autonomous or aided driving. Methods that use object detection algorithms such as Histogram of Oriented Gradients (HOG) or Convolutional Neural Networks (CNN) are today very popular in automotive applications. Embedded Graphics Processing Units (GPUs) are exploited to make object detection in a very efficient manner. Unfortunately, GPUs architecture has been shown to be particularly vulnerable to radiation-induced failures. This work presents an experimental evaluation and analytical study of the reliability of two types of object detection algorithms: HOG and CNNs. This research aim is not just to quantify but also to qualify the radiation-induced errors on object detection applications executed in embedded GPUs. HOG experimental results were obtained using two different architectures of embedded GPUs (Tegra and AMD APU), each exposed for about 100 hours to a controlled neutron beam at Los Alamos National Lab (LANL). Precision and Recall metrics are considered to evaluate the error criticality. The reported analysis shows that, while being intrinsically resilient (65% to 85% of output errors only slightly impact detection), HOG experienced some particularly critical errors that could result in undetected pedestrians or unnecessary vehicle stops. This works also evaluates the reliability of two Convolutional Neural Networks for object detection: You Only Look Once (YOLO) and Faster RCNN. Three different GPU architectures were exposed to controlled neutron beams (Kepler, Maxwell, and Pascal) detecting objects in both Caltech and Visual Object Classes data sets. By analyzing the neural network corrupted output, it is possible to distinguish between tolerable errors and critical errors, i.e., errors that could impact detection. Additionally, extensive GDB-level and architectural-level fault-injection campaigns were performed to identify HOG and YOLO critical procedures. Results show that not all stages of object detection algorithms are critical to the final classification reliability. Thanks to the fault injection analysis it is possible to identify HOG and Darknet portions that, if hardened, are more likely to increase reliability without introducing unnecessary overhead. The proposed HOG hardening strategy is able to detect up to 70% of errors with a 12% execution time overhead.
SITS: A solution-based intelligent tutoring system for students’ acquisition of problem-solving skills in computer programming

Abstract In learning systems and environment research, intelligent tutoring and personalisation are considered the two most important factors. An Intelligent Tutoring System can serve as an effective tool to improve problem-solving skills by simulating a human tutor’s actions in implementing one-to-one adaptive and personalised teaching. Thus, in this research, a solution-based intelligent tutoring system (SITS) is proposed. It benefits from Bayesian networks in managing uncertainty based on the probability theory for the process of decision-making so as to aid students learn computer programming. Additionally, SITS benefits from a multi-agent system that employs an automatic text-to-flowchart conversion approach to engage novice programmers in flowchart development with the aim of improving their problem-solving skills. Finally, the performance of SITS is investigated through an experimental study. It is revealed that SITS is not only capable of boosting students’ learning interest, attitude and technology acceptance, but it also helps students achieve more in terms of problem-solving activities.
Wearable health care system for vital signs monitoring

A new concept in healthcare, aimed to providing continuous remote monitoring of user vital signs, is emerging. An innovative system named WEALTHY is presented, were smart material in fiber and yarn form endowed with a wide range of electrophysical properties (conducting, piezoresistive, etc) are integrated and used as basic elements to be woven or knitted in fabric form. The simultaneous recording of vital signs allows parameters' extrapolation and inter-signal elaboration that contribute to make alert messages and synoptic patient table. WEALTHY system is implemented by integrating computing techniques, smart sensors, portable devices and telecommunications, together with local intelligence and decision support system. The system will assist cardiopathic patients during rehabilitation or subjects working in extreme stressful environment conditions.
Remarkable Efficacy of Vitamin D in Improving Ventricular Dysfunction in Transfusion-Dependent Thalassemia Patients

Background: The purpose of this study was to investigate efficacy of high dose vitamin D in improving left ventricular ejection fraction (LVEF) in thalassemia patients with heart failure and vitamin D deficiency. Materials and Methods: This clinical trial study was conducted on 16 chronically transfused thalassemia patients and ventricular dysfunction with vitamin D deficiency between December and Jun 2018 in Thalassemia clinic, Tabriz Children Hospital. Mean age of the patients was 11.15 ± 3.61 years ranged from 8 to 18 years old. A serum 25-hydroxy vitamin D3 (25-OHD3) level less than 30ng/dl was considered vitamin D deficiency in this study. LVEF less than 55% was indicated as poor pump function. The patients received 50,000 IU of vitamin D3 weekly for 8 weeks. Data on LVEF and serum 25-OHD3 were compared before and after completing the treatment. Moreover, adverse effects were recorded during the study. Results: Means of serum 25-OHD3 levels, before and after the study, were 13.10±5.91ng/ml and 51.03±4.31ng/ml, respectively (p=0.01). Means of LVEF were13.10±5.91% and 50.27±11.93% before and after the study, respectively (p=0.03). Means of serum ferritin levels were 3913±2229 ng/ml (ranged from 1246 to11000ng/ml). Mean of cardiac magnetic resonance imaging (MRI) T2* of the patients was 11.51±5.34ms. Serum parathyroid hormone (PTH) levels of the patients decreased from the beginning of the study to the end of the eighth week (94.28 ± 18.35 vs 43.66 ± 17.31ng/ml) (p=0.03). There was a positive correlation between mean of serum 25-OHD3 level and cardiac MRI T2* parameter at the beginning of the study (r=0.001). There was a positive correlation between in the increase of mean serum 25-OHD3 and LVEF percent at the end of study (r=0.001). Conclusion: Results showed that vitamin D3 was effective and safe in improving LVEF and cardiac dysfunction in transfusion-dependent thalassemia patients with vitamin D deficiency.
Distributed Collision Avoidance Method based on Consensus among Mobile Robotic Agents

This paper presents a new methodical approach to the problem of collision avoidance of mobile robots taking advantages of multi-agents systems to deliver solutions that benefit the whole system. The proposed method has the next phases: collision detection, obstacle identification, negotiation and collision avoidance. In addition of simulations with virtual robots in a 2D and 3D space, an implementation with real mobile robots has been developed in order to validate the proposed algorithm. The robots are based on Lego NXT, and they are equipped with a ring of proximity sensors for the collisions detections. The platform for the implementation and management of the multi-agent system is JADE.
Scottish physical activity research collaboration

This paper examines the Scottish physical activity research collaboration. The Scottish physical activity research collaboration aims to contribute to the evidence base on physical activity and health by evaluating the effectiveness of specific practice-based interventions. Also aims to disseminate the above evidence amongst practitioners, policy makers and academics in appropriate ways and to facilitate the use of evidence to inform policy and practice. Raises the profile of research on health-related physical activity in Scotland with the academic community, research funding bodies, policy makers and practitioners.
Heterogenous Lists of Named Objects

A heterogenous list of objects is introduced, in which the objects can be retrieved by name. An implementation of iterators for this list is discussed, along with algorithms that operate on them, and it is shown how these can be used to generate a substantial proportion of a class definition. It is demonstrated that the ability to attach meta-information to the objects in the list allows for code to be generated from higher level semantic specifications than has previously been possible.
A user modelling approach for computer-based critiquing

Theoretical studies and implementations of computer-based critiquing systems indicate that it is desirable to enhance that approach to better support human-computer collaborative effort. A user model will enable these systems to individualize explanations of their advice to provide better support for cooperative problem solving and enhance user learning. User modelling research in advice-giving dialog and intelligent educational systems was studied together with theoretical analyses of the limitations of human-computer interaction, and empirical observations of human-to-human collaborative effort. A framework for a user modelling component for a critiquing system was developed and implemented in a critic for LISP programs. The user models developed by the system were compared to self-assessment questionnaires completed by subjects learning the LISP language. The analyses indicated a favorable correlation and potential improvements to the framework. The user model is based on the conceptual domain model required for explanations; its semantic structure allows the system to implicitly enrich the user model contents. The significance of this work is a framework for a user modelling component that can be used for a more general class of cooperative knowledge-based systems. Additionally, using the structure of the conceptual domain model as the basis for the indirect implicit inference techniques is unique. The theoretical foundations for the work, the framework developed, and an analysis of the implementation are presented.
Perceived barriers to physical activity among nurses in Bandar Abbas, Iran: A qualitative approach

Background: Despite the importance of physical activity in improving health, involvement in physical activity declines during the past decades. Identifying barriers of physical activity helps researchers to design better and more effective strategies. Qualitative data are extremely valuable for providing insight into health determinants. The aim of this study was to determining nurses’ perceived barriers to physical activities. Methods: A qualitative approach using content analysis was used. Individual semistructured interviews were conducted with a convenience sample of 30 nurses who had been minimum one year working experience in hospital. The interviews continued until data saturation was reached. Interviews were transcribed, coded, and systematically analyzed between February-March 2013 to identify themes related to barriers to physical activity. Results: Two main themes emerged from the analysis of the interviews: internal and external barriers. Internal barriers were including: lack of time, lack of motivation, inability of planning, prioritizing other activities over sports, fatigue induced by overwork and external barriers were cost and rotating working shift. Conclusion: This study provided a better understanding of physical activity barriers among Nurses. Identifying and removing barriers can help researches to develop physical activity which has a main role in human health promotion. Keywords: Barriers, physical activity, nurses, qualitative approach, Iran.
Optimizing AspectJ for Java ME Software Product Lines

Software Product Lines (SPL) are defined as sets of software systems that satisfy the needs of a particular market, share a common set of characteristics, being, however, sufficiently distinct among each other, and developed from a set of reusable artifacts. Among the possible benefits of using SPL we can cite large scale reuse and productivity increase. A key factor in the development of a SPL is the mechanism used to structure source code variations. One of the most commonly used techniques for structuring code variations is conditional compilation, also called preprocessing. Despite being widely used, conditional compilation incurs in problems of legilibility, modularity, maintenability and quality. Aspect-Oriente Programming (AOP) is an alternative to conditional compilation for structuring code variations in SPL that can present better legilibility, modularity, maintenability and quality, among other factors, than conditional compilation. However, the use of AspectJ, the most popular AOP implementation over the Java language, as a variation structuring mechanism leads to a size overhead in the final compiled code. In the context of SPLs for mobile devices, with platforms such as Java ME, which have strict memory requirements, this overhead can make the final product unviable for release. In this work, we analyze the impact of using AspectJ as a variation structuring mechanism over the size of compiled code and investigate the motives behind this increase. For such, we use BestLap and Juggling, two SPLs of games for Java ME devices that have a purely preprocessed version and a hybrid version, with preprocessing and AspectJ. We used BestLap in the size analysis to quantify this overhead with two AspectJ compilers, ajc and abc. Next, we analyze the compiled code of a subset of AspectJ constructs, in order to identify which constructs generate overhead in the compiled code and the reasons behind this overhead. This subset consisted of all AspectJ constructs used in the hybrid version of BestLap and Juggling, the latter used only for eliciting the list of constructs. Based on this investigation, we developed four optimizations for the abc compiler that
ENHANCED GAIN AND BANDWIDTH OF PATCH ANTENNA USING EBG SUBSTRATES

Microstrip patch antenna becomes very popular day by day because of its ease of analysis and fabrication, low cost, light weight, easy to feed and their attractive radiation characteristics. Although patch antenna has numerous advantages, it has also some drawbacks such as restricted bandwidth, low gain and a potential decrease in radiation pattern. In recent years, attention to use Electromagnetic Band Gap (EBG) substrates to overcome the limitations of patch antenna. In this paper, we propose a rectangular microstrip patch antenna with EBG substrates and compare the performance of the proposed antenna with a conventional patch antenna in the same physical dimension. Due to the presence of the EBG structure in the dielectric substrates, the electromagnetic band gap is created that reduces the surface waves considerably. As a result, the performance of the proposed antenna is better comparing the conventional existing microstrip patch antenna.