Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of educational school meal programs in Gyeonggi province, South Korea

Purpose: School meal programs should be part of the educational process to promote good eating habits for students. The purpose of this study was to develop an evaluation scale for educational school meal programs and evaluate the achievement level of educational school meal programs using the developed scale. Methods: The evaluation scale for educational school meal programs consisted of 23 items in eight categories and was developed using content validity ratio (CVR) analysis and analytic hierarchy process (AHP) by 15 related experts. The results of a survey on nutrition teachers or dietitians at 91 elementary, middle, and high schools in Gyeonggi province, South Korea were analyzed to evaluate the achievement levels of educational school meal programs. Results: Overall, total average score was 45.7 out of 100, with significant differences among schools (p = 0.005). Elementary schools (51.9) showed a higher average score than middle (41.5) and high schools (37.1). The score for the category of regular nutrition and dietary education was the lowest (5.7 out of 33.7). In addition, school meal environment (5 out of 10), educational activities through school meal time (9.2 out of 19), and extra-curricular experiential activities (3.5 out of 10) also showed inadequate levels. Conclusion: The results show that the overall level of educational school meal programs is not adequate and needs to be improved, especially at middle and high schools. Government support polices need to be implemented to encourage educational activities related to school meal programs.
A BIG PUSH TO DETER CORRUPTION:EVIDENCE FROM ITALY

During the first half of the 1990s a pool of Italian judges carried out an investigation, named Mani Pulite (literally clean hands), that led many public officials to be prosecuted and convicted because of bribery and embezzlement. The impact of Mani Pulite was so much influential that since then many indicators suggest a steadily decreasing path for corruption in Italy. This paper shows that Mani Pulite was mainly effective in deterring corruption as it broke up the feed due to spending in health and social security as well as infrastructure investments, mainly those related to public buildings, sanitation, and land reclamation.
Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model

Abstract. The LPJ-GUESS dynamic vegetation model uniquely combines an individual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C–N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness of fit for broadleaved forests. N limitation associated with low N-mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N limitation associated with low N-mineralisation rates of colder soils reduces CO2 enhancement of net primary production (NPP) for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by ca. 10%; additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C–N interactions in studies of global terrestrial N cycling, and as a basis for understanding mechanisms on local scales and in different regional contexts.
Encapsulating Effects in Frank

Plotkin and Pretnar’s effect handlers offer a versatile abstraction for modular programming with user-defined effects. Alas, many implementations are not as modular as they may at first seem. Naive composition of a pair of effect handlers, one a producer, and the other a consumer of an intermediate effect, leads to effect pollution: the intermediate effect leaks and external instances are accidentally captured. We extend the Frank programming language with adaptors, which provide general remapping, and in particular hiding, of effect names in order to support effect encapsulation. Frank is a strict bidirectionally typed effect handler oriented programming language with a parsimonious effect type system in which effect polymorphism is almost always invisible. As a case study, we compose a concurrent actor handler from a collection of more primitive effect handlers using Frank. The naive implementation without adaptors yields an actor handler that suffers from effect pollution. Using adaptors we define an unpolluted actor handler whose type is also five times shorter than that of the naive version. As well as formalising adaptors, we also extend the formalism with other features necessary for the case study including polymorphic commands and a built-in top-level reference effect. We give a type system and an operational semantics and prove type soundness.
Evaluating the Effect of Smart Parking Technology on Campus Parking System Efficiency using Discrete Event Simulation

This study investigated the effect of smart parking systems (SPS) on parking search times (PST) in large parking lots. SPSs are systems that disseminate parking spot availability to drivers. The parking lot selected for data collection was a university parking lot with 234 spaces. The data collected included arrival rates, departure rates, the geometric properties of the parking lot, preferred parking search strategies, and driving speeds. Arena 13.9, by Rockwell Automation, Inc, was utilized as the modeling software. The base model was built from observed parking search strategies (PSS) of drivers. The model was validated using a t-test for independent samples to compare the PSTs of the base model and actual parking lot. Once the base model was verified and validated, the logic was altered to reflect (PSS) (IV) with real-time parking availability (i.e. simulating the presence of an SPS). The PSTs (DV) for the base and experimental models were compared using a t-test for independent samples. It was found that SPSs reduce PSTs by an average of only 11 seconds over a 2 week period for a single-lot SPS. However, this shows potential for a multi-lot SPS that might save more time and harmful vehicle emissions.
Global environmental drivers of marine fish egg size

Methods: We compiled the largest geo-located dataset of marine fish egg size (diameter) to date (n51,078 observations; 192 studies; 288 species; 242 localities). We decomposed sea surface temperature (SST) and chlorophyll-a time series into mean and predictability (seasonality and colour of environmental noise – i.e. how predictable the environment is between consecutive time steps), and used these as predictors of egg size in a Bayesian phylogenetic hierarchical model. We test four specific hypotheses based on the classic discussion by Rass (1941), as well as contemporary life-history theory, and the conceptual model of Winemiller and Rose (1992).
Pseudo-Differential Operators, Wigner Transform and Weyl Systems on Type I Locally Compact Groups

Let $G$ be a unimodular type I second countable locally compact group and $\hat G$ its unitary dual. We introduce and study a global pseudo-differential calculus for operator-valued symbols defined on $G\times\hat G$, and its relations to suitably defined Wigner transforms and Weyl systems. We also unveil its connections with crossed products $C^*$-algebras associated to certain $C^*$-dynamical systems, and apply it to the spectral analysis of covariant families of operators. Applications are given to nilpotent Lie groups, in which case we relate quantizations with operator-valued and scalar-valued symbols.
Usage of fiber Bragg grating sensors in low earth orbit environment

It is widely known that materials exposed to the severe low earth orbit (LEO) environment undergo degradations. For the evaluation of fiber Bragg grating (FBG) sensors in the LEO environment, the reflective spectrum change and the Bragg wavelength shift of FBG sensor were measured during aging cycles simulating the LEO environment. The LEO environment was simulated by high vacuum (~10-5 Torr), ultraviolet (UV) radiation (<200nm wavelength), temperature cycling (-30°C~100°C), and atomic oxygen atmosphere (AO flux of 9.12×1014 atoms/cm2/s and kinetic energy of ~0.04 eV). FBG sensor arrays were embedded into the graphite/epoxy composite material. Through the aging cycles simulated for the LEO environment, the change in the reflective spectrums and the Bragg wavelengths from FBG sensors were investigated.
4 Virtual Screening of Acetylcholinesterase Inhibitors

AD is associated with low in vivo level of acetylcholinesterase. The consistent neuropathologic hallmark of the disorder is a massive deposit of aggregated protein degradation products, amyloid-β (Aβ) plaques and neurofibrillary tangles (Haviv et al., 2005). Even if the primary cause of AD is still speculative, Aβ aggregates are thought to be mainly responsible for the pathogenesis of the disease (Hardy & Selkoe, 2002). In recent years, significant research has been devoted to the role of free radical formation, oxidative cell damage, and inflammation in the pathogenesis of AD, providing new promising targets and validated animal models (Capsoni et al., 2000).
Clustering Ensemble for Identifying Defective Wafer Bin Map in Semiconductor Manufacturing

Wafer bin map (WBM) represents specific defect pattern that provides information for diagnosing root causes of low yield in semiconductor manufacturing. In practice, most semiconductor engineers use subjective and time-consuming eyeball analysis to assess WBM patterns. Given shrinking feature sizes and increasing wafer sizes, various types of WBMs occur; thus, relying on human vision to judge defect patterns is complex, inconsistent, and unreliable. In this study, a clustering ensemble approach is proposed to bridge the gap, facilitating WBM pattern extraction and assisting engineer to recognize systematic defect patterns efficiently. The clustering ensemble approach not only generates diverse clusters in data space, but also integrates them in label space. First, the mountain function is used to transform data by using pattern density. Subsequently, k-means and particle swarm optimization (PSO) clustering algorithms are used to generate diversity partitions and various label results. Finally, the adaptive response theory (ART) neural network is used to attain consensus partitions and integration. An experiment was conducted to evaluate the effectiveness of proposed WBMs clustering ensemble approach. Several criterions in terms of sum of squared error, precision, recall, and F-measure were used for evaluating clustering results. The numerical results showed that the proposed approach outperforms the other individual clustering algorithm.
Public Accounting Reform from Institutional Theory Perspectives: Case of Turkey

In the literature, it is often found that institutional theory is used as the theoretical framework to explain the development and application of accounting. By means of these studies, it becomes easier to understand accounting as a social and political activity within itself and thus to be able to understand the economic, institutional, political and social environment of the turnover of the practices. In this regard, the main aim of this study is to explain the development of the public accounting system in Turkey with the help of institutional theory. Thus, it is aimed to explain all the dynamics that provide the institutionalization of state account in the national sense, together with the economic, political and social processes of the period in question. It is revealed that the regulatory arrangements directly contribute to the institutionaliza‐ tion of a field, and as a result, how the public organizations directly contribute to the institutionalization process. specialization are important in terms of isomorphism. While the educational and cognitive‐based legitimacy provided by the universities is mainly provided, the second is the establish- ment and expansion of professional relations and therefore the dissemination. Universities and voca-tional training institutions are important for the development of organizational norms [14].
Target‐oriented efficient illumination imaging and acquisition design

Target-oriented efficient illumination imaging and acquisition design are investigated by combining controlled illumination and local plane wave decomposition. Based on the plane source synthesis and the local plane wave decomposition, the target-oriented illumination-controlled areal source is synthesized and analyzed, and ranges of efficient illumination sources and directions can be selected. Under the guidance of the range information, the targetoriented efficient illumination source imaging and acquisition design can be implemented. For the target layer of Marmousi model with complex overlaying structures, the above targetoriented efficient illumination source imaging method is applied, and the results show the feasibility and great potential of the method.
Optimal Refrigeration Control for Soda Vending Machines

The prevalent soda vending machine industry in the US could yield reductions in energy consumption by addressing operational use. A study by the National Renewable Energy Laboratory estimates that each of the 4.6 million vending machines in the US consumes between 7 and 13kWh per day. [1] Currently, soda vending machines keep their products at a consistent temperature regardless of the time of day. Although no formal soda vending machine usage patterns have been observed, we hypothesize that usage patterns primarily follow time of day with high utilization during midday and afternoon and low utilization during the night and morning. However, soda is generally non-perishable and does not need to be refrigerated during periods of low to no soda demand. In this report, we construct a thermodynamic, state space refrigerator model and integrate a hypothetical soda demand schedule in order to optimize the operation of a soda vending machine that minimizes energy and carbon impact while maximizing the delivery of the appropriately chilled soda.
Risk Adjusted Business Intelligence Architecture (RABIA) for Cloud Computing: An Evaluation of Evolving Infrastructure in Banking Industry

The promise of cloud services is hard to dism iss and business intelligence (BI) and data mining applications in cloud computing environments are becoming commonplace. The decision to migrate BI applications to clouds not only involves various business, technological, service, strategic, and risk factors and criteria but also involves various BI architects to choose from. The importance of making the right decision is more important where data is of critical nature and sensitive as is in banking industry. Using pair wise comparisons and analytical hierarchy process, various BI architects have been ranked and the importance of each sub-criterion in five global criteria of Benefit, cost, opportunity, value, and risk (BCOVR) has been determined. With the criteria used in this study, moving selected ETL procedures (MSEP) to cloud has got the first place as compared to other alternatives like moving data analysis functionality (MDAF), mloving OLAP front-end (MOFE), moving operational BI (MOBI), on-premises application deployment (OPAD) or Idealistic BI Private Cloud (IBPC). The study has attempted to consider multi dimensional, risk focused factors to develop a method for evaluation of best strategy for migration of BI to cloud services and that best option was named as risk adjusted business intelligence architecture (RABIA).
A Review of Figure Plagiarism Detection Techniques

Plagiarism detection and prevention became one of the research and educational challenges. Many students and researchers tend to copy other works and idea when doing researches, projects, and assigned tasks. Most of the papers that are meant for Plagiarism detection are focusing on the Plagiarism from text point of view. So far there is no significant work in figure Plagiarism detection. This paper is a review paper that point out the main methods and techniques that are used for plagiarism detection.
Thermal Fatigue Analysis of an Emergency Core Cooling System Nozzle of a BWR Reactor, by the Finite Element Metod

1 Autonomous University of Baja California Engineering Faculty. Unidad Universitaria, Blvd. Benito Juárez s/n, 21900, Mexicali, B.C. 2 Superior School of Mechanical and Electrical Engineering, National Polytechnic Institute. Sección de Estudios de Posgrado e Investigación; Edificio Núm. 5, Tercer Piso, UPALM, Col. Lindavista, Delegación Gustavo A. Madero, 07738 , México, DF. 3 Superior School of Mechanical and Electrical Engineering, National Polytechnic Institute. Unidad Profesional, Azcapotzalco, Av. de las Granjas No. 682, Col. Sta. Catarina Azcapotzalco, 02550, México, DF. MÉXICO.
Energy-Aware Key Exchange for Securing Implantable Medical Devices

Implantable medical devices (IMDs) continuously monitor the condition of a patient and directly apply treatments if considered necessary. Because IMDs are highly effective for patients who frequently visit hospitals (e.g., because of chronic illnesses such as diabetes and heart disease), their use is increasing significantly. However, related security concerns have also come to the fore. It has been demonstrated that IMDs can be hacked—the IMD power can be turned off remotely, and abnormally large doses of drugs can be injected into the body. Thus, IMDs may ultimately threaten a patient’s life. In this paper, we propose an energy-aware key exchange protocol for securing IMDs. We utilize synchronous interpulse intervals (IPIs) as the source of a secret key. These IPIs enable IMDs to agree upon a secret key with an external programmer in an authenticated and transparent manner without any key material being exposed either before distribution or during initialization. We demonstrate that it is difficult for adversaries to guess the keys established using our method. In addition, we show that the reduced communication overhead of our method enhances battery life, making the proposed approach more energy-efficient than previous methods.
Reference Fields Analysis of a Markov Random Field Model to Improve Image Segmentation

In Markov random field (MRF) models, parameters such as internal and external reference fields are used. In this paper, the influence of these parameters in the segmentation quality is analyzed, and it is shown that, for image segmentation, a MRF model with a priori energy function defined by means of non-homogeneous internal and external field has better segmentation quality than a MRF model defined only by a homogeneous internal reference field. An analysis of the MRF models in terms of segmentation quality, computational time and tests of statistical significance is done. Significance tests showed that the segmentations obtained with MRF model defined by means of non-homogeneous reference fields are significant at levels of 85% and 75%.
A Repeated Sampling and Clustering Method for Intrusion Detection

Various tools, methods and techniques have been developed in recent years to deal with intrusion detection and ensure network security. However, despite all these efforts, gaps remain, apparently due to insufficient data sources on attacks on which to train and test intrusion detection algorithms. We propose a data-flow adaptive method for intrusion detection based on searching through high-dimensional dataset for naturally arising structures. The algorithm is trained on a subset of 82332 observations on 25 numeric variables and one cyber-attack label and tested on another large subset of similar structure. Its novelty derives from iterative estimation of cluster centroids, variability and proportions based on repeated sampling. Data visualisation and numerical results provide a clear separation of a set of variables associated with two types of attacks. We highlight the algorithm’s potential extensions – its allurement to predictive modelling and adaptation to other dimensional-reduction techniques.
Transformed Locally Linear Manifold Clustering

Transform learning is a relatively new analysis formulation for learning a basis to represent signals. This work incorporates the simplest subspace clustering formulation - Locally Linear Manifold Clustering, into the transform learning formulation. The core idea is to perform the clustering task in a transformed domain instead of processing directly the raw samples. The transform analysis step and the clustering are not done piecemeal but are performed jointly through the formulation of a coupled minimization problem. Comparison with state-of-the-art deep learning-based clustering methods and popular subspace clustering techniques shows that our formulation improves upon them.
HERB YIELD AND BIOACTIVE COMPOUNDS OF TARRAGON ( Artemisia dracunculus L . ) AS INFLUENCED BY PLANT DENSITY

Growth and yield of herbal plants are closely connected with meteorological conditions and agrotechnical procedures. We undertook studies on determining the effect of tarragon planting density upon fresh and dry herb yield, as well as the contents of nutritious and physiologically active substances: L-ascorbic acids, chlorophylls, carotenoids, tannins and flavonoids, as well as the contents, yield and chemical composition of essential oil. Significant effect of estragon planting density was demonstrated upon fresh and air-dry herb yield, grated herb yield and essential oil yield. Tarragon plants growing in higher density (40 × 40 cm) had higher yield of fresh, dry and de-stalked herb, as well as higher oil yield than the plants growing less densely (50 × 50 cm). The biological value of analyzed plant material was high and depended upon planting density to a really insignificant extent. Plants growing more densely had significantly higher concentration of carotenoids and significantly lower contents of essential oil compared to the remaining ones. The essential oil of Artemisia dracunculus L. was characterized by the presence of 46 compounds of the share >0.05% and 23 compounds occurring in trace amounts. The predominant compound in the examined tarragon oil was methyl eugenol, which occurred in larger quantity in the year 2012 (37.56%), than in 2011 (34.33%). Other main compounds were: elemicin, determined in the amount of 21.95 and 26.22%; sabinene, in the amount of 14.16 and 16.37%, as well as E-asarone, in the concentrations of 8.68 and 3.49% (respectively: in 2011 and 2012). A. dracunculus presented in the foregoing studies can be defined as a methyl eugenol-elemicin/sabinene chemotype (respectively: 36, 24