Miracle-dz/UniFAR-FTUs huggingface dataset:
Food bank drive-through distribution during COVID-19: A reflective essay

The COVID-19 pandemic has created an unprece­dented surge in food insecurity and demand for free food. In response, Foodshare, the regional food bank serving Greater Hartford, Connecticut, created a drive-through distribution program to meet the immediate food needs of residents. Our team at Foodshare’s Institute for Hunger Research & Solutions conducted two surveys of people receiving food at the drive-through distribution to help inform Foodshare’s programming and response to the pandemic. Results show that 70% of households receiving food had never gone to a food pantry or other program to receive free food prior to COVID-19, and 67% said they come at least once a week. Additionally, 86% of guests are not going elsewhere to receive free food and only 37% know of other places to get free food. The majority of people receiving food at the drive-through distribution were people of color, who are those most affected by COVID-19 from both health and financial perspectives. From April to August 2020, Foodshare served an average of 1,500 households each day and more than 150,000 cars total at the drive-through distribution alone. Despite serving an immediate need for food, the drive-through model presents challenges, particu­larly during the New England winter with snow and freezing temperatures, and is an expensive endeavor. Foodshare and other food banks will need to pivot again from short-term pandemic assistance to longer-term approaches to create dignified, convenient, and sustainable access to healthy food for additional people struggling with food insecurity. Food banks can also leverage their extensive platforms of volunteers and donors to advocate for policy changes that will ensure eco­nomic stability and food security.
Wildfire as a natural stressor and its effect on female phenotype and ornament development

Abstract Controlled low‐intensity fires are commonly used in ecosystem management for both habitat restoration and wildfire management. Animals in those ecosystems may respond to fire by shifting energy allocation away from reproduction and growth, and toward maintenance. Stress‐induced shifts in energy allocation may affect the expression of condition‐dependent sexual signals, which are sensitive to energetic and physiological trade‐offs mediated by glucocorticoids. Here, we examine the effect of fire on ornament expression, corticosterone, and other phenotypic traits in a population of striped plateau lizards, Sceloporus virgatus, affected by the Horseshoe 2 Fire in the Chiricahua Mountains, Arizona, USA. The condition‐dependent female ornament was significantly smaller the month following the fire than 2 years prior and was both smaller and less orange on the burned site relative to a nearby unburned site. These patterns are similar to those found in a previous experimental study examining the response of the ornament to corticosterone manipulations. Yet, in the current study, corticosterone levels were not different in lizards on the burned and unburned sites. Perhaps glucocorticoid levels already returned to baseline, or do not adequately track environmental change. Females tended to be smaller and lighter on the burned site than the unburned site; however, the year after the fire, body condition was higher for females on the burned site, indicating a rapid recovery and potential long‐term benefits in response to low‐intensity fires in this fire‐adapted ecosystem. We found that the lizards adjusted energy allocation away from sexual signaling and growth in response to low‐intensity fires. As fires and fire management are likely to increase in response to changing fire regimes across the globe, it will be important to consider behavioral and physiological responses of impacted species, as well as population‐, community‐, and ecosystem‐level responses.
Adaptive Prediction of Water Droplet Infiltration Effectiveness of Sprinkler Irrigation Using Regularized Sparse Autoencoder–Adaptive Network-Based Fuzzy Inference System (RSAE–ANFIS)

As the high productive efficiency of sprinkler irrigation is largely based on balanced soil moisture distribution, it is essential to study the exact effectiveness of water droplet infiltration, which provides a theoretical basis for rationally scheduling the circulation efficiency of groundwater in agricultural irrigation performance. This research carried out adaptive prediction of the droplet infiltration effectiveness of sprinkler irrigation by using a novel approach of a regularized sparse autoencoder–adaptive network-based fuzzy inference system (RSAE–ANFIS), for the purpose of quantifying actual water droplet infiltration and effectiveness results of precision irrigation in various environmental conditions. The intelligent prediction experiment we implemented could be phased as: the demonstration of governing equations of droplet infiltration for sprinkler irrigation modeling; the measurement and computation of probability densities in water droplet infiltration; innovative establishment and working analysis of RSAE–ANFIS; and the adaptive prediction of infiltration effectiveness indexes, such as average soil moisture depth increment (θ, mm), irrigation infiltration efficiency (ea, %), irrigation turn duration efficiency (et, mm/min), and the uniformity coefficient of soil moisture infiltration (Cu, %), which were implemented to provide a comprehensive illustration for the effective scheduling of sprinkler irrigation. Result comparisons indicated that when jetting pressure (Pw) was 255.2 kPa, the impinge angle (Wa) was 42.5°, the water flow rate (Fa) was 0.67 kg/min, and continuous irrigation time (Tc) was 32.4 min (error tolerance = ±5%, the same as follows), thereby an optimum and stable effectiveness quality of sprinkler irrigation could be achieved, whereas average soil moisture depth increment (θ) was 57.6 mm, irrigation infiltration efficiency (ea) was 62.5%, irrigation turn duration efficiency (et) was 34.5 mm/min, and the uniformity coefficient of soil moisture infiltration (Cu) was 53.6%, accordingly. It could be concluded that the proposed approach of the regularized sparse autoencoder–adaptive network-based fuzzy inference system has outstanding predictive capability and possesses much better working superiority for infiltration effectiveness in accuracy and efficiency; meanwhile, a high agreement between the adaptive predicted and actual measured values of infiltration effectiveness could be obtained. This novel intelligent prediction system has been promoted constructively to improve the quality uniformity of sprinkler irrigation and, consequently, to facilitate the productive management of sprinkler irrigated agriculture.
Energy consumption in the glass melting process. I: Theoretical relations

Formulae have been proposed expressing the influence of internal melting factors such as temperature, external pressure, glass composition, size distribution of sand and intensity of glass stirring on the specific energy consumption of glass melting, and the appropriate partial derivatives have been given. The possible ways of exploiting the melting reserve have been discussed. Using the mentioned formulae, the results of laboratory experiments and single glass flow models, the energetic trends resulting from the variation of melting conditions may be revealed
Eigen microstates and their evolutions in complex systems

Emergence refers to the existence or formation of collective behaviors in complex systems. Here, we develop a theoretical framework based on the eigen microstate theory to analyze the emerging phenomena and dynamic evolution of complex system. In this framework, the statistical ensemble composed of M microstates of a complex system with N agents is defined by the normalized N × M matrix A , whose columns represent microstates and order of row is consist with the time. The ensemble matrix A can be decomposed as A=∑I=1rσIUI⨂VI , where r=min(N,M) , eigenvalue σ I behaves as the probability amplitude of the eigen microstate U I so that ∑I=1rσI2=1 and U I evolves following V I . In a disorder complex system, there is no dominant eigenvalue and eigen microstate. When a probability amplitude σ I becomes finite in the thermodynamic limit, there is a condensation of the eigen microstate U I in analogy to the Bose–Einstein condensation of Bose gases. This indicates the emergence of U I and a phase transition in complex system. Our framework has been applied successfully to equilibrium three-dimensional Ising model, climate system and stock markets. We anticipate that our eigen microstate method can be used to study non-equilibrium complex systems with unknown order-parameters, such as phase transitions of collective motion and tipping points in climate systems and ecosystems.
A Survey on Low-Thrust Trajectory Optimization Approaches

In this paper, we provide a survey on available numerical approaches for solving low-thrust trajectory optimization problems. First, a general mathematical framework based on hybrid optimal control will be presented. This formulation and their elements, namely objective function, continuous and discrete state and controls, and discrete and continuous dynamics, will serve as a basis for discussion throughout the whole manuscript. Thereafter, solution approaches for classical continuous optimal control problems will be briefly introduced and their application to low-thrust trajectory optimization will be discussed. A special emphasis will be placed on the extension of the classical techniques to solve hybrid optimal control problems. Finally, an extensive review of traditional and state-of-the art methodologies and tools will be presented. They will be categorized regarding their solution approach, the objective function, the state variables, the dynamical model, and their application to planetocentric or interplanetary transfers.
Sensitivities of the Madden–Julian oscillation forecasts to configurations of physics in the ECMWF global model

Abstract. The sensitivities of the Madden–Julian oscillation (MJO) forecasts to various different configurations of the parameterized physics are examined with the global model of ECMWF's Integrated Forecasting System (IFS). The motivation for the study was to simulate the MJO as a nonlinear free wave under active interactions with higher-latitude Rossby waves. To emulate free dynamics in the IFS, various momentum-dissipation terms (“friction”) as well as diabatic heating were selectively turned off over the tropics for the range of the latitudes from 20 ∘ S to 20 ∘ N. The reduction of friction sometimes improves the MJO forecasts, although without any systematic tendency. Contrary to the original motivation, emulating free dynamics with an operational forecast model turned out to be rather difficult, because forecast performance sensitively depends on the specific type of friction turned off. The result suggests the need for theoretical investigations that much more closely follow the actual formulations of model physics: a naive approach with a dichotomy of with or without friction simply fails to elucidate the rich behaviour of complex operational models. The paper further exposes the importance of physical processes other than convection for simulating the MJO in global forecast models.
A new single‐stage continuous input current‐based high gain boost inverter: Analysis and implementation

This paper proposes a wide input voltage range‐based high gain boost inverter. The proposed single power stage inverter provides a high voltage gain direct current (DC) to alternating current (AC) conversion with good AC power quality. The circuit also exhibits a continuous input current feature that reduces the additional filtering requirement and suitable for various sources, for example, solar photovoltaic (PV), battery, and fuel cell. Additionally, this topology uses reduced number of semiconductor switches as compared to similar voltage gain conventional inverter topologies. An exhaustive steady‐state mathematical analysis has been performed to obtain various voltage and current relationships including DC to AC voltage conversion ratio. A comprehensive performance comparison has been presented to highlight the key advantages of the proposed topology as compared to existing boost inverters. A 300‐W prototype has been built to validate the operating principle and performance of the proposed boost inverter.
Serum Correlation of Nesfatin-1 with Angiographic, Echocardiographic, and Biochemical Findings in Patients with Coronary Artery Disease

Background: Nesfatin, as an adipokine, has been shown to have a number of metabolic effects associated with a variety of inflammatory diseases. The current study aimed at investigating the relationship of nesfatin-1 levels with biochemical, echocardiographic, and angiographic findings, especially with the epicardial fat thickness (EFT) in patients with coronary artery disease. Methods: This cross-sectional study was conducted on 90 patients who were candidates for angiography. The patients were then divided into one control group (with normal angiography but a history of chest pain; n=30), as well as stable-AP (with a diagnosis of stable angina pectoris; n=30) and acute-MI groups (with a diagnosis of acute myocardial infarction; n=30). Demographic, biochemical, angiographic, and echocardiographic parameters of all subjects were evaluated in this study. Results: Serum levels of nesfatin-1 in acute-MI and stable-AP groups were significantly reduced, compared to the healthy subjects (P<0.001 and P<0.01, respectively); however, there was no significant difference between acute-MI and stable-AP groups. In addition, the findings demonstrated a negative relationship of nesfatin-1 with low-density lipoprotein, Gensini score, white blood cell, troponin T, EFT, and creatine kinase-MB (CK-MB). However, there was a positive association between nesfatin-1 and left ventricle ejection fraction (%). Conclusion: Decreased levels of nesfatin-1 in acute-MI and stable-AP groups as well as its association with several parameters, such as EFT, CK-MB, and Gensini score, may indicate the potential role of nesfatin-1 in the process of atherosclerosis, which requires further studies.
Toward travel pattern aware tourism region planning: a big data approach

Purpose The purpose of this paper is to propose and demonstrate how Tourism2vec, an adaptation of a natural language processing technique Word2vec, can serve as a tool to investigate tourism spatio-temporal behavior and quantifying tourism dynamics. Design/methodology/approach Tourism2vec, the proposed destination-tourist embedding model that learns from tourist spatio-temporal behavior is introduced, assessed and applied. Mobile positioning data from international tourists visiting Tuscany are used to construct travel itineraries, which are subsequently analyzed by applying the proposed algorithm. Locations and tourist types are then clustered according to travel patterns. Findings Municipalities that are similar in terms of their scores of their neural embeddings tend to have a greater number of attractions than those geographically close. Moreover, clusters of municipalities obtained from the K-means algorithm do not entirely align with the provincial administrative segmentation.
Healthcare fraud detection using primitive sub peer group analysis

Healthcare fraud is a significant problem greatly affecting the quality of healthcare services. Manual auditing of insurance claims extends to the delay in finding fraudulent behaviors causing huge financial loss and also putting the patients' health conditions at risk. Since the past decade, the automation of fraud detection using machine learning techniques has become a prominent research topic. Several automated fraud detection systems using machine learning techniques have been proposed so far. However, developing a healthcare fraud detection system that is adaptive to the systematic changes is still missing. Therefore, in this article, we develop primitive sub peer group analysis (PSPGA) for identifying the suspicious behaviors in health insurance claims. PSPGA is inspired by peer group analysis, a popular unsupervised learning technique, which identifies suspicious behaviors based on local pattern analysis. PSPGA distinguishes between the concept drifts and the sudden drifts and flags the sudden drifts as fraudulent. Moreover, PSPGA makes the fraud detection system adaptive to the concept drifts by considering the updates for peer groups over time.
The Wellbeing and Mental Health Care Experiences of Adults with Intellectual and Developmental Disabilities during COVID-19

ABSTRACT Introduction: COVID-19 has adversely impacted the health and wellbeing of people with intellectual and developmental disabilities (IDD). While there is emerging research examining how to support the mental health of this population during the pandemic, the perspectives and experiences of people with IDD have been largely absent.Methods: Nine virtual interviews were conducted with adults with IDD to explore the impact of the COVID-19 pandemic on their wellbeing and mental health care. Interview transcripts were analyzed thematically.Results: Findings centered around three main themes: (1) the impact of the pandemic on daily life and wellbeing; (2) a need for connection; and (3) availability and access to mental health supports.Conclusion: Participants described significant challenges to their health and wellbeing related to the pandemic and public health measures, but also demonstrated remarkable resilience in the face of this new adversity. Findings highlight ways to support the wellbeing of adults with IDD and how social determinants impact mental health.
Performance analysis of NR Polar Codes at short information blocks for control channels

One important innovation in information and coding theory is polar code, which delivers capacity attaining error correction performance varying code rates and block lengths. In recent times, polar codes are preferred to offer channel coding in the physical control channels of the 5G (5 th Generation) wireless standard by 3GPP (Third Generation Partnership Project) New Radio (NR) group. Being a part of the physical layer, Channel coding plays key role in deciding latency and reliability of a communication system. However, the error correction performance degrades with decreased message lengths. 5G NR requires channel codes with low rates, very low error floors with short message lengths and low latency in coding process. In this work, Distributed Cyclic Redundancy Check Aided polar (DCA-polar) code along with Cyclic Redundancy Check Aided polar (CA-polar) code, the two variant of polar codes have been proposed which provide significant error-correction performance in the regime of short block lengths and enable early termination of decoding processes. While CRC bits improve the performance of SCL (successive cancellation list) decoding by increasing distance properties, distributed CRC bits permit path trimming and early-termination of the decoding process. The design can reduce the decoding latency and energy consumption of hardware, which is crucial for mobile applications like 5G. The work also considers the performance analysis of NR polar codes over AWGN (Additive White Gaussian Noise) for short information block lengths at low code rates in the uplink and downlink control channels using SNR (Signal to Noise Ratio) and FAR (False Alarm Rate) as the performance measures. Simulation results illustrate different trade-offs between error-correction and detection performances comparing proposed NR polar coding schemes.
A Reflective Practitioner: An Undeniable Urgent Role for EFL Teachers in Digital Era

This study aims to investigate the phenomenon on how English teachers run their roles as a reflective practitioner. It was analyzed based on the way the teachers reflect their teaching activities; how the English teachers evaluated their performance, their students and their class; how the English teachers spend efforts to improve their competence and performance. Moreover, this research, which was further developed based on research conducted on 2014, involved 5 English teachers at MAN Kota Solok, one of Islamic state senior highs school in Solok City. The research was conducted under qualitative approach through observing those English teachers and compiled by such interviews. The result shows that the English teachers at this school did not optimally run their role as reflective practitioner. It cannot be denied that many factor beyond the teachers itself which influences this phenomenon. This article discusses this phenomenon significantly in order to give a consideration for the stakeholder and the English teachers in making any decisions related to teachers’ role as a reflective practitioner and its impact on achieving the educational goals, especially in this digital era.
Synthesis of inorganic-polymer nanocomposites by atom transfer radical polymerization using initiators or polymerizable groups attached to transition metals via bidentate ligands

Metal alkoxides were functionalized by bidentate ligands based on p-diketones or acetoacetoxy-derivatives. The resulting complexes either carried initiator or polymerizable groups for ATRP. In addition these compounds were used as precursors for the sol-gel process. Depending on the functional group attached to the metal and the further processing of the derived compounds core-shell nanoparticles or crosslinked materials were obtained. Atom transfer radical polymerization proved that it is a valuable tool for the controlled formation of inorganic-organic hybrid materials.
The influence of interest groups on the EU’s foreign policy: assessing and explaining the influence of human rights NGOs on the EU’s human rights promotion in the post-Soviet space

ABSTRACT This article examines to what extent human rights NGOs influence the European Union (EU)’s promotion of human rights in the post-Soviet space, and what factors explain that influence. The article hypothesises that there will be variation in the extent to which human rights NGOs influence the EU’s human rights promotion depending on a number of factors relating to how human rights NGOs gather and transmit information. To test the hypothesised explanations, a multivariate regression analysis is applied based on data retrieved through an online survey with human rights NGOs. The article finds that human rights NGOs have a moderate degree of influence on the EU’s human rights promotion in post-Soviet countries. The NGOs’ influence depends on whether they provide information timely, whether the information provided fulfils the officials’ informational needs and is based on (scientific) research, and whether the NGOs use different tactics for conveying the information to the officials.