Miracle-dz/UniFAR-FTUs huggingface dataset:
Childhood Food Insecurity in the U.S.: Trends, Causes, and Policy Options

In 2012, nearly 16 million U.S. children, or over one in five, lived in households that were food-insecure, which the U.S. Department of Agriculture defines as “a household-level economic and social condition of limited access to food. ” Even when we control for the effects of other factors correlated with poverty, these children are more likely than others to face a host of health problems, including but not limited to anemia, lower nutrient intake, cognitive problems, higher levels of aggression and anxiety, poorer general health, poorer oral health, and a higher risk of being hospitalized, having asthma, having some birth defects, or experiencing behavioral problems. Many government programs aim explicitly to reduce food insecurity, including the Supplemental Nutrition Assistance Program (SNAP), the National School Lunch Program (NSLP), the School Breakfast Program (SBP), the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), and the Child and Adult Care Food Program (CACFP). (Other social safety-net programs—for example, the Earned Income Tax Credit—can also help alleviate food insecurity by increasing household income.) The fact that food insecurity remains so high even though the government spent over $100 billion on the various federal food-assistance programs in fiscal year 2012 poses a significant policy challenge.Food insecurity rates remain stubbornly high for a number of reasons. One is that we don’t fully understand what causes food insecurity or how food assistance and other programs can help alleviate it. Food insecurity has been researched extensively, and this research has helped policy makers and program administrators better address the problem. However, relatively little research has looked at what causes food insecurity among children in the first place, or the effectiveness of public policies, especially on more severe forms of food hardship.In this policy report, we highlight new research that seeks to fill this gap. Much of this work comes from the Research Program on Childhood Hunger at the University of Kentucky Center for Poverty Research, which was underwritten by the Food and Nutrition Service of the U.S. Department of Agriculture (USDA).
Kernel Entropy-Based Unsupervised spectral Feature Selection

Most existing feature selection methods focus on ranking individual features based on a utility criterion, and select the optimal feature set in a greedy manner. However, the feature combinations found in this way do not give optimal classification performance, since they neglect the correlations among features. In an attempt to overcome this problem, we develop a novel feature selection technique using the spectral data transformation and by using l1-norm regularized models for subset selection. Specifically, we propose a new two-step spectral regression technique for unsupervised feature selection. In the first step, we use kernel entropy component analysis (kECA) to transform the data into a lower-dimensional space so as to improve class separation. Second, we use l1-norm regularization to select the features that best align with the data embedding resulting from kECA. The advantage of kECA is that dimensionality reducing data transformation maximally preserves entropy estimates for the input data whilst also best preserving the cluster structure of the data. Using l1-norm regularization, we cast feature discriminant analysis into a regression framework which accommodates the correlations among features. As a result, we can evaluate joint feature combinations, rather than being confined to consider them individually. Experimental results demonstrate the effectiveness of our feature selection method on a number of standard face datasets.
Research and analysis of hull form of small fishing vessels in Southeast Asia

There are many fishing vessels in Southeast Asia (SEA), and fish products produced by SEA countries support people in this area. Japanese-imported fishery products from SEA countries, and some Japanese fishing vessels, share fishing grounds. Japanese government has supported many projects to maintain sustainable fisheries in SEA. These projects are implemented by the Southeast Asia Fisheries Development Center (SEAFDEC). SEAFDEC is an international organization in the region. To recognize fishing vessel hydrostatics, performance, and vessels catch capacity in SEA countries, we measured the vessel dimensions and hull form of fishing vessels. In this paper, we introduce the features of fishing vessels in SEA, a measurement method uses a 3D stereo camera to capture the hull form, an analysis of hydrostatics (including block coefficient (Cb) that is used to calculate gross tonnage), and a speed power curve.
Transfer Learning Enabled Process Recognition for Module Installation of High-rise Modular Buildings

High-rise modular buildings (HMB), based on the advanced approach of modular construction, have gained momentum in practice due to their offered benefits in accelerated construction, improved quality, reduced health and safety risks, and enhanced productivity. Modular construction with standard design of modules and repetitive processes of module installation is in favor of the development of construction automation. As module installation is one of the critical activities in the delivery of HMBs, it is important to recognize the module installation process automatically so as to facilitate automation in modular construction. However, there is no detailed phase-division of module installation process. Also, little research has been carried out on intelligent process recognition for module installation due to the limited amount of images of real-life projects. To fill in the knowledge gaps, this paper aims to build a transfer learning enabled process recognition model using convolutional neural network (CNN) for module installation of HMBs. The study first divided the module installation process into three stages: hooking, lifting and positioning, with a comprehensive literature review. Then the recognition model for module installation process was created and trained with the adoption of CNN-based transfer learning, and verified with images taken from real-life projects. The results show that the three stages of module installation process are effectively recognized with the proposed model. The transfer learning enabled image recognition model for module installation process accelerates automation in the construction of HMBs for enhanced productivity and accuracy.
Estimation of hydraulic conductivity without computing fluxes

Field estimates of the hydraulic conductivity (K) have large variances resulting from interpolating and differencing errors, in addition to instrumental and other errors in the observed water contents (8) and pressure heads (h). The resulting total error can easily be larger than the estimated value of K, thus producing poor results when analytical functions are fitted to the data. In contrast to K, the slope of K, i.e., dK/di, can be estimated without differencing field data, and hence always produces stable (i.e., positivej estimates. The purpose of this study was to compare hydraulic functions fitted to different combinations of measured field data of 0, h, K, and K’ =dK/dB, where K’ =z/t during the drainage phase of infiltration-drainage experiments. Five combinations of data sets were used in the fitting process, i.e., h-8; K-8; K’ -8; h-B-K, and h-0-K’. The data sets were for the Norfolk sand, Troup loamy sand Bethany loam, and Muir silt loam soils. The h-0-K or h-8-K’ data consistently produced good tits to both the K(8) and h(8) data sets. While nearly overlapping curves were produced over the range of measured field data, the fitted values of the parameters were not always similar. Likewise, using either 9-K or 8-K observations resulted in similar curves, although the results were less consistent than those obtained with the more complete h-0-K or h-0-K’ data sets. For the soils studied, the K and K’ data produced very similar curves indicating that differencing field data can be avoided since neither water fluxes nor gradients in the pressure head are needed to estimate K’ .
History of the medical home concept.

“Every child deserves a medical home” is one of the American Academy of Pediatrics’ (AAP) essential child health outcomes for the 21st century. With increasing health care costs, technology, survivorship, specialization, and fragmentation of care, the medical home is steadily gaining interest and standing in the public eye. Today’s policy makers, those who are involved with children, and parents are increasingly using the term to describe the concept as the form of high-quality health care. With so much attention focused on this concept as the standard of care for all infants, children, adolescents, young adults, and particularly children with special health care needs (CSHCN), it is important to define this term and how its definition has evolved. Whereas the term was originally used to describe a place—a single source of all medical information about a patient—the term now refers to a partnership approach with families to provide primary health care that is accessible, family centered, coordinated, comprehensive, continuous, compassionate, and culturally effective.1 The first known documentation of the term “medical home” appeared in Standards of Child Health Care, a book published by the AAP in 1967 and written by the AAP Council on Pediatric Practice (COPP). The book defines a medical home as one central source of a child’s pediatric records and emphasizes the importance of centralized medical records to CSHCN. “For children with chronic diseases or disabling conditions, the lack of a complete record and a ‘medical home’ is a major deterrent to adequate health supervision. Wherever the child is cared for, the question should be asked, ‘Where is the child’s medical home? ’ and any pertinent information should be transmitted to that place” (pp 77–79). 2 The COPP, noting that care for CSHCN is often provided by many different practitioners who work in disparate locations independent of each … Reprint requests to (C.S.) 656 Paikau St, Honolulu, HI 96816-4406. E-mail: Calsia{at}pol.net
Does a Reliable Decline in Mini Mental State Examination Total Score Predict Dementia?

Background/Aim: Norms for change in Mini Mental State Examination (MMSE) total score suggest that only a decline of at least 2–4 points indicates a reliable change. However, it is unknown whether change norms (Reliable Change Indices, RCIs) of the MMSE total score are suitable to predict future dementia. Methods: 554 elderly individuals aged 75 and over without dementia at the first 2 visits were tested with the MMSE at a maximum of 6 visits with 1.5-year intervals. Two different RCIs for change in MMSE score (first to second visit) were computed – one RCI which corrects for practice and one RCI which corrects for regression to the mean. The main outcome measure was the diagnosis of dementia. Results: During the study, 88 persons developed dementia. RCIs were significantly associated with future dementia diagnosis. The best cutoff for raw change in MMSE total score to predict dementia was –1 point (sensitivity = 48%, specificity = 67%, relative risk = 1.6). With the RCI + regression to the mean, the diagnostic accuracy was moderate (sensitivity = 61%, specificity = 72%, relative risk = 3.2). Conclusion: A change in MMSE total score is significantly associated with future dementia, but the diagnostic accuracy for dementia prediction is rather low.
Automatic crater classification framework based on shape parameters

This communication presents a framework for automatically classifying a crater image into one of its preservation states namely fresh, floor-fractured and degraded introducing a class of algorithms known as crater classification algorithms (CCA). This study involves identification of discriminatory parameters of classes, development and implementation of algorithms to automatically evaluate the parameters from a given Digital Elevation Model testing on representative craters of each class and evolve a decision tree framework for automatically classifying given crater image into its preservation class. This classification can be applied to craters that exhibit ambiguous topographies to test whether they were formed by impact erosion or igneous modification.
Emergence of Social Punishment and Cooperation through Prior Commitments

Social punishment, whereby cooperators punish defectors, has been suggested as an important mechanism that promotes the emergence of cooperation or maintenance of social norms in the context of the one-shot (i.e. non-repeated) interaction. However, whenever antisocial punishment, whereby defectors punish cooperators, is available, this antisocial behavior outperforms social punishment, leading to the destruction of cooperation. In this paper, we use evolutionary game theory to show that this antisocial behavior can be efficiently restrained by relying on prior commitments, wherein agents can arrange, prior to an interaction, agreements regarding posterior compensation by those who dishonor the agreements. We show that, although the commitment mechanism by itself can guarantee a notable level of cooperation, a significantly higher level is achieved when both mechanisms, those of proposing prior commitments and of punishment, are available in co-presence. Interestingly, social punishment prevails and dominates in this system as it can take advantage of the commitment mechanism to cope with antisocial behaviors. That is, establishment of a commitment system helps to pave the way for the evolution of social punishment and abundant cooperation, even in the presence of antisocial punishment.
Galley Proof PATHOLOGY OF REGIONAL DEVELOPMENT MANAGEMENT IN IRAN

There is a consensus among the Iranian researchers that during the period 2005-2015, the Regional Development Management has been ineffective in Iran. To explain this issue, the role of internal and external factors is emphasized. In this paper, the Management Model for Regional Development in Iran was pathologized and the Ideal Management Model was selected. 370 experts were questioned and in order to choose an ideal model, 30 experts were interviewed through Delphi technique. Content validity of measurement instrument using the experts’ opinion and CVR coefficient was evaluated. The instrument reliability, using the Cronbach’s alpha and Gutmann method were 0.814 and 0.827 respectively. The X 2 tests and Spearman correlation coefficient were used to statistical analysis and the ANP method was used to determine the criteria weights. Also the PROMETEE II method was used for ranking and selecting the ideal model of management. The research findings indicate that 100% of experts believe that the management model for regional development in Iran has been completely inefficient during the investigated period and needs serious reforms. Among various management models, “the Network Governance” was proposed as an ideal model. Finally, some recommendation was provided for implementation of this model.
Thermal Studies of Polypyrrole and Cobalt Aluminum Oxide Nano Composites

In the present work Cobalt Aluminum Oxide (CAO) Nano powder was used as loading particles in conducting polymer pyrrole to synthesis Polypyrrole Nano composites (PPy/CAO) by in situ chemical polymerization technique. Thermal studies of different weight percent Nano composites were done by Thermo gravimetric/Differential thermal analysis (TG/DTA). To understand the thermo gravimetric analysis, Nano composites were exposed to different temperatures in muffle furnace for 2 hours and FTIR was recorded immediately for these samples. TGA data reveals that the PPy/CAO has good thermal stability almost same as that of polypyrrole. FTIR data of the Nano composites after exposure to different temperatures supports to the TG/DTA analysis. Keywords— Polypyrrole; Cobalt Aluminum Oxide; Thermal studies; Nano composites
Estimation of Source Parameters of Mega-Fault Systems for Strong Ground Motion Prediction-Test Case : Arima-Takatsuki Fault Zone -

ABSTRACT : Predicting strong ground motion by earthquakes occurring on crustal mega-fault systems is crucial when we need to consider low occurrence-rate strong ground motion for seismic design of buildings. In order to predict strong ground motion by earthquakes occurring on inland crustal mega-fault systems, we need to estimate fault parameters for earthquakes of this kind. Since instrumental recording started in Japan, we have not encountered any inland crustal earthquakes that exceed magnitude 8. The source parameters of a mega-fault system from recorded earthquakes on the same fault system are estimated. The Headquarters for Earthquake Research Promotion (HERP) of Japan has evaluated several inland crustal mega-fault systems that will exceed magnitude 8 in Japan. For a test case the Arima-Takatsuki fault zone that extends about 130 km is considered. Source parameters of the Keicho-Fushimi earthquake of 1596, that ruptured the whole mega-fault system of the Arima-Takatsuki fault zone is estimated. Source parameters of the Hyogoken Nanbu (Kobe) earthquake of 1995 that occurred on the south-western portion of the same fault system have been estimated by Matsushima and Kawase (2006). Source parameters of the two earthquakes are compared, and the distribution of the stress drop seems to resemble each other. Although his result needs further investigation, it may be an indication that it can be used to estimate parameters for future earthquakes of mega-fault system from smaller earthquakes occurring on the same fault system.
PRODUCTION TECHNIQUES AND VERSATILE APPLICATIONS OF MICROPARTICLES AS CONTROLLED DRUG DELIVERY SYSTEM

Controlled drug delivery technology is concerned with systematic release of pharmaceutical agent to maintain therapeutic level of drug in body for sustained period of time. Conventional drug delivery system results in undesirable side effects due to fluctuating plasma drug level, high peak-to-trough variations, inability to maintain plasma drug concentration in therapeutic range, larger doses in order to obtain adequate therapeutic effect may result in undesirable, toxicological and immunological effects in non-target tissues. An appropriately designed controlled release system can be a major step toward solving the problem associated with conventional drug delivery system. This review article includes the history and basic rationale behind controlled drug delivery system. A variety of approaches have been investigated for controlled release of drugs and targeting to selective sites which includes polymeric microspheres, liposomes and solid lipid nanoparticles. Microparticles are characteristically free flowing powders consisting of proteins or synthetic polymers having a particle size ranging from 1-1000 μm. Microparticles have numerous medical applications such as oral, vaccine, intranasal and ocular delivery of drugs. A detailed focus has been given on preparation techniques of microparticles viz. solvent evaporation method, spray drying method, freeze drying technique, hot pressure homogenization method, thermal cross-linking method and coacervation phase separation method. The range of techniques for preparation of microparticles offers a variety of opportunities to control aspects of drug administration and enhance therapeutic efficacy.
Minimally Invasive Reconstruction of the Lateral Ankle Ligaments Using Semitendinosus Autograft or Tendon Allograft

Background: The purpose of the study was to retrospectively compare the therapeutic effect between semitendinosus autograft and tendon allograft for lateral ankle ligaments reconstruction. Methods: From September 2006 to June 2011, 68 patients (41 males, 27 females) with chronic ankle instability underwent anatomical reconstruction of the lateral ligaments using semitendinosus autograft (autograft group, 32 patients) or tendon allograft (allograft group, 36 patients) via a minimally invasive approach. All patients were followed up for at least 12 months. The American Orthopaedic Foot and Ankle Society Ankle-Hindfoot Scale score (AOFAS score) and stress tests were used to evaluate the clinical outcomes. Operation time, time to heal and complications were also recorded. Results: Compared with allograft group, the average operation time was significantly increased (85.5 ± 11.5 minutes vs 58.1 ± 10.2 minutes, P < .0001), but the mean time to heal was significantly shorter (11.2 ± 4.1 months vs 13.5 ± 5.2 months, P = .0458) in the autograft group. Although the mean AOFAS score was significantly increased at the final follow-up in the autograft group (95.1 ± 7.5 vs 62.3 ± 8.2, P = .0001) and allograft group (94.8 ± 5.5 vs 60.2 ± 8.4, P < .0001), no significant difference in AOFAS was found between these 2 groups. Similarly, there was no significant difference in talar tilt or shift between autograft and allograft groups. In addition, no patients complained of weakness or disability at the donor site in the autograft group, while incisional swelling was observed in 4 patients in the allograft group, which was resolved via dressing change, oral use of indomethacin or dexamethasone. Conclusion: Reconstruction of the lateral ankle ligaments using a semitendinosus tendon autograft and a minimally invasive approach was safe and effective for ankle instability with a relatively short time for healing and minimal donor site problems. Level of Evidence: Level III, comparative case series.
Numerical Modeling of Dielectric Barrier Discharge Based Plasma Actuators for Flow Control : the COPAIER/CEDRE Example

N umerical simulation of active flow control using plasma actuators is dependent upon the development of models accounting for the effects of the actuators on the flow. These can be obtained either by using experimental results coupled with strong assumptions regarding the plasma force distribution, or through numerical simulation. The objective of this paper is to investigate the characteristics of DBD plasma source terms obtained using direct numerical simulation. Using ONERA's in-house plasma solver COPAIER, we propose an insight of a complete chain of numerical models, ranging from the plasma discharge description to the computation of a DBD-induced ionic wind.
A Low-power Shared Cache Design with Modified PID Controller for E ffi cient Multicore Embedded Systems

Nowadays, on-chip cache scales are oversized in multicore embedded systems, and those caches even consume half of the total energy debit. However, we observe that a large portion of cache banks are wasted, meaning that those banks are rarely used but consume a great deal of energy during their entire lifetime. In this paper, we propose a controllable shared last level cache (SLLC) scheme to dynamically trace cache bank demands for each thread. Thus, energy on useless banks can be largely saved. Specifically, we (1) propose an effective cache bank allocating policy to explore bank demands corresponding to executed applications, (2) discuss the interrelations between application locality change and bank demands for further energy saving and (3) represent a modified PID controller to generate optimal banks for each thread. Experimental results show that our controllable SLLC design can save on average 39.7 percent shared cache access energy over conventional cache, while its performance is slightly improved and additional hardware overhead is less than 0.6 percent.