bluuebunny/crossref_metadata_2025 huggingface dataset:
On the Quality of Deep Representations for Kepler Light Curves Using Variational Auto-Encoders
Authors: Mena Francisco , Olivares Patricio , Bugueño Margarita , Molina Gabriel , Araya Mauricio
Published: October 2021

Light curve analysis usually involves extracting manually designed features associated with physical parameters and visual inspection. The large amount of data collected nowadays in astronomy by different surveys represents a major challenge of characterizing these signals. Therefore, finding good informative representation for them is a key non-trivial task. Some studies have tried unsupervised machine learning approaches to generate this representation without much effectiveness. In this article, we show that variational auto-encoders can learn these representations by taking the difference between successive timestamps as an additional input. We present two versions of such auto-encoders: Variational Recurrent Auto-Encoder plus time (VRAEt) and re-Scaling Variational Recurrent Auto Encoder plus time (S-VRAEt). The objective is to achieve the most likely low-dimensional representation of the time series that matched latent variables and, in order to reconstruct it, should compactly contain the pattern information. In addition, the S-VRAEt embeds the re-scaling preprocessing of the time series into the model in order to use the Flux standard deviation in the learning of the light curves structure. To assess our approach, we used the largest transit light curve dataset obtained during the 4 years of the Kepler mission and compared to similar techniques in signal processing and light curves. The results show that the proposed methods obtain improvements in terms of the quality of the deep representation of phase-folded transit light curves with respect to their deterministic counterparts. Specifically, they present a good balance between the reconstruction task and the smoothness of the curve, validated with the root mean squared error, mean absolute error, and auto-correlation metrics. Furthermore, there was a good disentanglement in the representation, as validated by the Pearson correlation and mutual information metrics. Finally, a useful representation to distinguish categories was validated with the F1 score in the task of classifying exoplanets. Moreover, the S-VRAEt model increases all the advantages of VRAEt, achieving a classification performance quite close to its maximum model capacity and generating light curves that are visually comparable to a Mandel–Agol fit. Thus, the proposed methods present a new way of analyzing and characterizing light curves.
Features of the Higher Education for the Circular Economy: The Case of Italy
Authors: Giannoccaro Ilaria , Ceccarelli Gaia , Fraccascia Luca
Published: October 2021

The higher education system plays a critical role in supporting the transition towards a circular economy (CE). It helps create business leaders and policymakers having appropriate skills, competences, and consciousness referring to the CE challenges. Nevertheless, few studies have specifically investigated how the higher education system is addressing the CE, how the current academic offering is integrating the CE principles, and which skills and competences are currently provided. This paper overcomes these limitations by investigating the current offering of the higher education for the CE in Italy. We analyze the academic programs, courses, and modules at different levels of 49 Italian universities and, by means of a detailed classification of the learning outcomes, provide a clear picture of the knowledge, skills, and competences offered by the CE education. We finally discuss implications of our findings concerning the development of CE education and CE jobs.
Consumer Perception of the Circular Economy Concept Applied to the Food Domain: An Exploratory Approach
Authors: Sousa Pedro Manuel , Moreira Maria João , de Moura Ana Pinto , Lima Rui Costa , Cunha Luís Miguel
Published: October 2021

Every year, agri-food industries in industrialised countries produce approximately 1.3 billion tonnes of food loss and waste. The adoption of a circular economy policy has received special attention by the agri-food industries, allowing for the creation and development of new food products made of by-products that would otherwise be wasted or used for secondary applications. The present work, of an exploratory nature, aims to assess how consumers conceptualise the circular economy in order to identify consumer recognition of the use of by-products from the food industry to upcycle food products and to evaluate attitudes towards the circular economy. To this end, a mixed-methodology was applied to 340 participants. The first part was qualitative and used free word association to evaluate consumers’ conceptualisation of the circular economy and use of by-products as foods. Data were analysed by grouping the responses into exclusive and exhaustive categories and a correspondence analysis was also performed to originate perceptual maps. Additionally, a questionnaire was designed to evaluate major concepts and attitudes correlated with the circular economy. Data were reduced by principal component analysis (PCA) and participants grouped through clustering. Results showed that consumers understand circular economy as related mainly into Sustainability, Economy, and Circularity dimensions. Participants had great difficulty identifying the by-products used as foods or as food ingredients. From the quantitative data, four groups were identified based on the associations to the six principal components originated by the PCA. However, the results highlighted a very low association with all clusters of the Food Valorisation dimension within the concept of the circular economy, and also a lack of a clear understanding of consumers’ attitudes towards food products from the circular economy. Greater promotion and dissemination by the competent entities aimed at the general public may contribute towards greater integration, participation and acceptance of the circular economy concept for the upscaling of food by-products.
A Short-Term Hybrid Energy System Robust Optimization Model for Regional Electric-Power Capacity Development Planning under Different Pollutant Control Pressures
Authors: Cui Jixian , Liao Chenghao , Ji Ling , Xie Yulei , Yu Yangping , Yin Jianguang
Published: October 2021

This paper is aimed at proposing a short-term hybrid energy system robust optimization model for regional energy system planning and air pollution mitigation based on the inexact multi-stage stochastic integer programming and conditional value-at-risk method through a case study in Shandong Province, China. Six power conversion technologies (i.e., coal-fired power, hydropower, photovoltaic power, wind power, biomass power, and nuclear power) and power demand sectors (agriculture, industry, building industry, transportation, business, and residential department) were considered in the proposed model. The optimized electricity generation, capacity expansion schemes, and economic risks were selected to analyze nine defined scenarios. Results revealed that electricity generations of clean and new power had obvious increasing risks and were key considerations of establishing additional capacities to meet the rising social demands. Moreover, the levels of pollutants mitigation and risk-aversion had a significant influence on different power generation schemes and on the total system cost. In addition, the optimization method developed in this paper could effectively address uncertainties expressed as probability distributions and interval values, and could avoid the system risk in energy system planning problems. The proposed optimization model could be valuable for supporting the adjustment or justification of air pollution mitigation management and electric power planning schemes in Shandong, as well as in other regions of China.
Measurement Quality Appraisal Instrument for Evaluation of Walkability Assessment Tools Based on Walking Needs
Authors: Tabatabaee Sanaz , Aghaabbasi Mahdi , Mahdiyar Amir , Zainol Rosilawati , Ismail Syuhaida
Published: October 2021

Walking is a sustainable commute mode, and walkability is considered an essential sign of sustainable mobility. To date, many walkability assessment tools have been developed to assess the walkability conditions across the world. However, there is a paucity of comprehensive methods to assess current walkability tools based on walking needs and ensure all walking requirements are included. Thus, researchers and experts are unable to select the most comprehensive tool systematically. The present study attempts to develop a system to evaluate the quality of the existing tools. The instrument focuses on factors related to walking needs frequently observed in all types of walkability assessment tools. Hence, a pilot measurement quality appraisal instrument (MQAI) is developed and tested by a research team with planning and public health backgrounds. The final MQAI is tested by suitable reliability, criterion, and content validity tests. Most appraisal scales display moderate to high reliability for both audits and questionnaires. The MQAI appears as ready for use in several applications, including meta-analyses and systematic reviews. Additionally, the MQAI can be used by practitioners and planners to identify the most comprehensive and efficient assessment tools based on their needs.
Agritourism Development in the USA: The Strategy of the State of Michigan
Authors: Jin Xiaowen , Wu Hao , Zhang Jing , He Guangming
Published: October 2021

Agritourism has been widely promoted by governments at many levels, especially in the developed regions of Europe and North America, as a tool to revitalize rural economies and as a sustainable path. Research on agritourism has mainly focused on defining and categorizing agritourism, farmers’ perceptions, tourists’ attitudes, tourism benefits, and marketing. However, little attention has been paid to characterizing the processes and strategies of agritourism development in a relatively large region, for instance, in a state or a province. This article uses the state of Michigan in the Midwest of the USA as a case study, systematically collecting academic publications from several literature databases on agritourism, the state’s regulation and policies on agritourism, the development of agritourism associations, the participation of universities in agritourism related to academic and outreach activities, identifying key and critical developmental events, and reconstructing the historical phases of the agritourism development process. It summarizes the significant characteristics of agritourism’s development in the state of Michigan, the state government’s comprehensive strategy and leadership, the universities’ strong intellectual support, and the consistent involvement of the industrial associations, as well as the interactions of these three parties at the different developmental stages of agritourism. The discussion is set in the wider context of agritourism’s development in the USA. We conclude by presenting the implications and recommendations derived from the agritourism development experience in the state of Michigan. We specifically discuss the relevance of the Michigan experience for agritourism stakeholders in other regions worldwide, especially those that are still in the early stages of agritourism development, such as China.
Cluster Forecasting of Corruption Using Nonlinear Autoregressive Models with Exogenous Variables (NARX)—An Artificial Neural Network Analysis
Authors: Ghahari SeyedAli , Queiroz Cesar , Labi Samuel , McNeil Sue
Published: October 2021

Any effort to combat corruption can benefit from an examination of past and projected worldwide trends. In this paper, we forecast the level of corruption in countries by integrating artificial neural network modeling and time series analysis. The data were obtained from 113 countries from 2007 to 2017. The study is carried out at two levels: (a) the global level, where all countries are considered as a monolithic group; and (b) the cluster level, where countries are placed into groups based on their development-related attributes. For each cluster, we use the findings from our previous study on the cluster analysis of global corruption using machine learning methods that identified the four most influential corruption factors, and we use those as independent variables. Then, using the identified influential factors, we forecast the level of corruption in each cluster using nonlinear autoregressive recurrent neural network models with exogenous inputs (NARX), an artificial neural network technique. The NARX models were developed for each cluster, with an objective function in terms of the Corruption Perceptions Index (CPI). For each model, the optimal neural network is determined by fine-tuning the hyperparameters. The analysis was repeated for all countries as a single group. The accuracy of the models is assessed by comparing the mean square errors (MSEs) of the time series models. The results suggest that the NARX artificial neural network technique yields reliable future values of CPI globally or for each cluster of countries. This can assist policymakers and organizations in assessing the expected efficacies of their current or future corruption control policies from a global perspective as well as for groups of countries.
Cumulative Frequency of Nature Dose: How Continuous and Regular Forest Walking Improves Nature Relatedness, Restorativeness, and Learning Engagement in College Students
Authors: Chou Wan-Yu , Hung Shih-Han
Published: October 2021

Forest is a natural resource that provides natural walking as a popular leisure activity for urban residents. From the perspective of “dose of nature”, continuous contact with natural environments and engagement in natural activities can gradually promote positive health benefits. This study aims to explore the “cumulative frequency of nature dose” through regular forest walking. Ten college students were recruited to walk once a week for 30 min in the campus forest. Eight weeks of forest walking experiences were collected by administering questionnaires on nature relatedness, mental health, restorativeness, and learning engagement before the first walk, as well as after the fourth and the eighth walks. The findings of this study revealed that regular forest activities can induce accumulated natural benefits. By taking at least 30 min of forest walks once a week continuously for eight weeks, the subjects improved their mental health, increased learning engagement in school, gained more attention recovery and reflection experiences, and re-established a relationship with nature. In addition, different doses of natural benefits were observed for different cumulative processes.
A Systematic Review of Factors Affecting Food Loss and Waste and Sustainable Mitigation Strategies: A Logistics Service Providers’ Perspective
Authors: Yan Han , Song Min-Ju , Lee Hee-Yong
Published: October 2021

This study investigates the causes of food loss and waste (FLW) from the perspective of logistics service providers (LSPs) and provides sustainable options for the Chinese market. To this end, this study reviews the literature on FLW and cold chain logistics published from 2008–2021. Until recently, little attention has been paid to understanding FLW drivers from the LSP perspective. This critical systematic literature review (SLR) aims to identify the potential drivers of FLW and provide a coherent and integrated knowledge base regarding these factors. A configurative SLR was performed, and after a filtering process, 43 articles were analyzed. Potential factors were identified and categorized into four groups: (i) poor management, (ii) inappropriate operational practices, (iii) high cost, and (iv) restrictions. The results reveal that technical inefficiency and facility costs are the most serious risks, and the lack of legislation and standards constitutes the second most serious risk for FLW. Sustainable solutions are recommended to address these risks. Finally, the study findings provide guidance for LSPs to achieve sustainability in social, economic, and ecological dimensions.
Land Consumption of Delivery Robots and Bicycle Couriers for On-Demand Meal Delivery Using GPS Data and Simulations Based on the Time-Area Concept
Authors: Schnieder Maren , Hinde Chris , West Andrew
Published: October 2021

Regulating the curbside usage of delivery vehicles and ride-hailing services as well as micromobility has been a challenge in the last years, a challenge which might worsen with the increase of autonomous vehicles. The contribution of the research outlined in this paper is an evaluation method of the land use of on-demand meal delivery services such as Deliveroo and UberEats. It evaluates the effect parking policies, operating strategy changes, and scheduling options have on the land consumption of bicycle couriers and sidewalk automated delivery robots (SADRs). Various operating strategies (i.e., shared fleets and fleets operated by restaurants), parking policies (i.e., parking at the restaurant, parking at the customer or no parking) and scheduling options (i.e., one meal per vehicle, multiple meals per vehicle) are simulated and applied to New York City (NYC). Additionally, the time-area requirements of on-demand meal delivery services are calculated based on GPS traces of Deliveroo and UberEats riders in two UK cities. The simulation in the paper shows that SADRs can reduce the time-area requirements by half compared with bicycle couriers. The effect of operating strategy changes and forbidding vehicles to park at the customer’s home is small. Delivering multiple meals in one tour halves the time-area requirements. The time-area requirements based on GPS traces is around 300 m2·min per order. The study allows policymakers to learn more about the land use of on-demand meal delivery services and how these can be influenced. Hence, they can adjust their policy strategies to ensure that on-demand meal delivery services are provided in a way that they use land effectively, reduce external costs, improve sustainability and benefit everyone.
Temperature Variations and Possible Forcing Mechanisms over the Past 300 Years Recorded at Lake Chaonaqiu in the Western Loess Plateau
Authors: Yu Keke , Wang Le , Liu Lipeng , Sheng Enguo , Liu Xingxing , Lan Jianghu
Published: October 2021

Understanding the synchronicity of and discrepancy among temperature variations on the western Loess Plateau (WLP), China, is critical for establishing the drivers of regional temperature variability. Here we present an authigenic carbonate-content timeseries spanning the last 300 years from sediments collected from Lake Chaonaqiu in the Liupan Mountains, WLP, as a decadal-scale record of temperature. Our results reveal six periods of relatively low temperature, during the intervals AD 1743–1750, 1770–1780, 1792–1803, 1834–1898, 1930–1946, and 1970–1995, and three periods of relatively high temperature during 1813–1822, 1910–1928, and since 2000. These findings are consistent with tree-ring datasets from the WLP and correlate well with extreme cold and warm events documented in historical literature. Our temperature reconstruction is also potentially representative of large-scale climate patterns over northern China and more broadly over the Northern Hemisphere. The Pacific Decadal Oscillation (PDO) might be the dominant factor affecting temperature variations over the WLP on decadal timescales.
Determining the Tiers of a Supply Chain Using Machine Learning Algorithms
Authors: Park Kyoung Jong
Published: October 2021

Companies in the same supply chain influence each other, so sharing information enables more efficient supply chain management. An efficient supply chain must have a symmetry of information between participating entities, but in reality, the information is asymmetric, causing problems. The sustainability of the supply chain continues to be threatened because companies are reluctant to disclose information to others. If companies participating in the supply chain do not disclose accurate information, the next best way to improve the sustainability of the supply chain is to use data from the supply chain to determine each enterprise’s information. This study takes data from the supply chain and then uses machine learning algorithms to find which enterprise the data refer to when new data from unknown sources arise. The machine learning algorithms used are logistic regression, random forest, naive Bayes, decision tree, support vector machine, k-nearest neighbor, and multi-layer perceptron. Indicators for evaluating the performance of multi-class classification machine learning methods are accuracy, confusion matrix, precision, recall, and F1-score. The experimental results showed that LR and MLP accurately predicted companies (tiers), but NB, DT, RF, SVM, and K-NN did not accurately predict companies. In addition, the performance similarity of machine learning algorithms through experiments was classified into LR and MLP groups, NB and DT groups, and RF, SVM, and K-NN groups.
Analysis of Birefringence and Dispersion Effects from Spacetime-Symmetry Breaking in Gravitational Waves
Authors: O’Neal-Ault Kellie , Bailey Quentin G. , Dumerchat Tyann , Haegel Leïla , Tasson Jay
Published: October 2021

In this work, we review the effective field theory framework to search for Lorentz and CPT symmetry breaking during the propagation of gravitational waves. The article is written so as to bridge the gap between the theory of spacetime-symmetry breaking and the analysis of gravitational-wave signals detected by ground-based interferometers. The primary physical effects beyond General Relativity that we explore here are dispersion and birefringence of gravitational waves. We discuss their implementation in the open-source LIGO-Virgo algorithm library suite, and we discuss the statistical method used to perform a Bayesian inference of the posterior probability of the coefficients for symmetry-breaking. We present preliminary results of this work in the form of simulations of modified gravitational waveforms, together with sensitivity studies of the measurements of the coefficients for Lorentz and CPT violation. The findings show the high potential of gravitational wave sources across the sky to sensitively probe for these signals of new physics.
Methods to Measure Antibody Neutralization of Live Human Coronavirus OC43
Authors: Boonyaratanakornkit Jim , Sholukh Anton M. , Gray Matthew , Bossard Emily L. , Ford Emily S. , Corbett Kizzmekia S. , Corey Lawrence , Taylor Justin J.
Published: October 2021

The human Betacoronavirus OC43 is a common cause of respiratory viral infections in adults and children. Lung infections with OC43 are associated with mortality, especially in hematopoietic stem cell transplant recipients. Neutralizing antibodies play a major role in protection against many respiratory viral infections, but to date a live viral neutralization assay for OC43 has not been described. We isolated a human monoclonal antibody (OC2) that binds to the spike protein of OC43 and neutralizes the live virus derived from the original isolate of OC43. We used this monoclonal antibody to develop and test the performance of two readily accessible in vitro assays for measuring antibody neutralization, one utilizing cytopathic effect and another utilizing an ELISA of infected cells. We used both methods to measure the neutralizing activity of the OC2 monoclonal antibody and of human plasma. These assays could prove useful for studying humoral responses to OC43 and cross-neutralization with other medically important betacoronaviruses.
Evaluation of a Modified Bit Device to Obtain Saliva Samples from Horses
Authors: Vincent Aviva , Peth-Pierce Robin Marie , Morrissey Meghan A. , Acri Mary C. , Guo Fei , Seibel Lauren , Hoagwood Kimberly E.
Published: October 2021

(1) Background: Accounting for the well-being of equine partners is a responsibility of those engaged in Equine-Assisted Services (EAS). Researchers took heed of this call to action by developing an innovative way to collect data to assess the physiological indicators of stress in equine participants. The collection of saliva is considered to be a minimally invasive method of data collection and is typically performed using a cotton swab; however, in equines, the introduction of a foreign object may induce stress; (2) Methods: Researchers used a modified bit to collect pooled saliva in an effort to further reduce stress during the saliva collection process. Additionally, the collection of pooled saliva, via the bit, increases the opportunity to consider additional analyses, such as oxytocin, which is more reliable in pooled saliva than site-specific saliva captured with a swab; (3) Results: A data analysis demonstrated that ample saliva was captured using the modified bit. Observational data supported that the horses demonstrated fewer physical stress signals to the bit than to the swab. Thus, the modified bit is a feasible and valid method for equine salivary sample collection; (4) Conclusions: The results suggest that the modified bit provides a viable method to collect equine saliva and supports national calls to prioritize animal welfare analysis, specifically for horses used within EAS. Future research should enhance methodological rigor, including in the process and timing, thereby contributing to the bit’s validation.
The Impact of Maternal and Piglet Low Protein Diet and Their Interaction on the Porcine Liver Transcriptome around the Time of Weaning
Authors: Kroeske Kikianne , Arévalo Sureda Ester , Uerlings Julie , Deforce Dieter , Van Nieuwerburgh Filip , Heyndrickx Marc , Millet Sam , Everaert Nadia , Schroyen Martine
Published: October 2021

Maternal diet during early gestation affects offspring phenotype, but it is unclear whether maternal diet during late gestation influences piglet metabolism. We evaluated the impact of two dietary protein levels in sow late gestation diet and piglet nursery diet on piglet metabolism. Diets met or exceeded the crude protein and amino acid requirements. Sows received either 12% (Lower, L) or 17% (Higher, H) crude protein (CP) during the last five weeks of gestation, and piglets received 16.5% (L) or 21% (H) CP from weaning at age 3.5 weeks. This resulted in a 2 × 2 factorial design with four sow/piglet diet treatment groups: HH and LL (match), HL and LH (mismatch). Piglet hepatic tissues were sampled and differentially expressed genes (DEGs) were determined by RNA sequencing. At age 4.5 weeks, 25 genes were downregulated and 22 genes were upregulated in the mismatch compared to match groups. Several genes involved in catabolic pathways were upregulated in the mismatch compared to match groups, as were genes involved in lipid metabolism and inflammation. The results show a distinct interaction effect between maternal and nursery diets, implying that sow late gestation diet could be used to optimize piglet metabolism.
Quantitative Analysis of Malachite Green in Environmental Samples Using Liquid Chromatography-Mass Spectrometry
Authors: Hussain Hakami Afnan Ali , Ahmed Mohammed Asif , Khan Moonis Ali , AlOthman Zeid A. , Rafatullah Mohd , Islam Md. Ataul , Siddiqui Masoom Raza
Published: October 2021

Water is an essential part of life, however, with continued modernization, it has become a dumping place for many pollutants including dyes. The polluted water can severely affect human health. Polluted water can enter into the human body through different channels, including the food web. Thus, it is very important for human beings and animals to have access to pollution free water. To get the knowledge of the pollutants, in this case, a dye, we need sensitive analytical procedure which could tell the amount of dye in water and also steps to get the pollutant removed from water. In this work, a liquid chromatography–mass spectrometry (LC-MS/MS) based analytical method was developed to determine malachite green. The method was developed after proper optimization of the experimental conditions, where finally, ethanol, a green solvent and formic acid, a food additive was selected to constitute the mobile phase in ratio 1.5:1.0. Different validation parameters were used to authenticate the reliability of the method. Based on the experiment results, the method was found to be linear in the range of 0.1 to 10 mg/L with an excellent correlation coefficient of 0.9995. The corresponding linear regression equation was found to be A = −6863.2 + 105,520 C; where A is the area of the peak and C is the concentration of malachite green. The precision study proves the reproducibility of LC-MS/MS procedure, throughout the precision experiment percent relative standard deviation (% RSD) was found to be between 0.709–1.893%. Similarly, the experiments on the recovery suggest a recovery of 97.28–98.75%. The new method was applied to check the amount of malachite green in environmental samples including the industrial wastewater. The wastewater sample was extracted using the solid phase extraction (SPE) technique, where a new adsorbent—wood apple hydrochar—was synthesized and used as the solid phase for the preparation of a solid phase extraction column to extract the malachite green. The synthesized adsorbent was characterized using different techniques. To conclude, the developed method can be used for determination of malachite green in environmental samples, and the SPE technique using wood apple hydrochar can successfully extract the dye from the water samples.
Understanding the Complexity of Water Supply System Governance: A Proposal for a Methodological Framework
Authors: Gumeta-Gómez Fernando , Sáenz-Arroyo Andrea , Hinojosa-Arango Gustavo , Monzón-Alvarado Claudia , Mesa-Jurado Maria Azahara , Molina-Rosales Dolores
Published: October 2021

The question of how the complexity of water governance may be understood beyond a heuristic concept remains unanswered. In this paper, we propose a Water Governance Complexity Framework to address the complexity of water governance. Through a literature review, rapid surveys, and 79 semi-structured interviews, we propose how this framework may be operationalized using different proxies and by applying it to the case of the water supply system for domestic use in Oaxaca, Mexico. In places such as the rural communities of Oaxaca, where the state plays a partially absent role in the water supply, we found legal pluralism and diverse formal and informal stakeholders in a multi-level structure. At the local level, four modes of governance were identified, resulting from seven institutional change trajectories. These trajectories result from linear (alignment) and non-linear (resistance and adaptation) interactions between local, state, and national institutions over different periods. We provide a pragmatic framework to understand complexity through the organization and historical configurations of water governance that may be applied globally, providing a necessary starting point and solid foundation for the creation of new water policies and law reforms or transitions to the polycentric governance model to ensure the human right to water and sanitation.
Hybrid Beads of Zero Valent Iron Oxide Nanoparticles and Chitosan for Removal of Arsenic in Contaminated Water
Authors: Ahmed Mian Fawaz , Abbas Muhammad Asad , Mahmood Azhar , Ahmad Nasir M. , Rasheed Hifza , Qadir Muhammad Abdul , Khan Asad Ullah , Qiblawey Hazim , Zhu Shenmin , Sadiq Rehan , Khan Niaz Ali
Published: October 2021

Water contaminated with highly hazardous metals including arsenic (As) is one of the major challenges faced by mankind in the present day. To address this pressing issue, hybrid beads were synthesized with various concentrations of zero valent iron oxide nanoparticles, i.e., 20% (FeCh-20), 40% (FeCh-40) and 60% (FeCh-60) impregnated into a polymer of chitosan. These hybrid beads were employed as an adsorbent under the optimized conditions of pH and time to facilitate the efficient removal of hazardous arsenic by adsorption cum reduction processes. X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), Brunauer- Emmett-Teller BET, a porosity test and wettability analysis were performed to characterize these hybrid beads. The porosity and contact angle of the prepared hybrid beads decreased with an increase in nanoparticle concentration. The effects of various adsorption factors such as adsorbent composition, contact period, pH value and the initial adsorbate concentration were also evaluated to study the performance of these beads for arsenic treatment in contaminated water. FeCh-20, FeCh-40 and FeCh-60 have demonstrated 63%, 81% and 70% removal of arsenic at optimized conditions of pH 7.4 in 10 h, respectively. Higher adsorption of arsenic by FeCh-40 is attributed to its optimal porosity, hydrophilicity and the presence of appropriate nanoparticle contents. The Langmuir adsorption kinetics described the pseudo second order. Thus, the novel beads of FeCh-40 developed in this work are a potent candidate for the treatment of polluted water contaminated with highly toxic arsenic metals.
Transboundary Aquifers between Baja California, Sonora and Chihuahua, Mexico, and California, Arizona and New Mexico, United States: Identification and Categorization
Authors: Sanchez Rosario , Rodriguez Laura
Published: October 2021

In 2016, research suggested there might be up to 36 transboundary aquifers located along the border between Mexico and the U.S. The main contribution of this study was to put together the available segments already existent in the literature without considering the validity of the criteria used to define the boundaries of those segments. In 2018, updated research reported 33 hydrogeological units (HGUs) crossing the boundaries between Mexico and Texas. This later analysis included the homogenization of geological nomenclatures, standardization of geological and hydrogeological criteria, using a specific methodology to correlate, identify, and delineate each HGU. The purpose of this paper is to use this latter methodology and expand the same analysis to include the transboundary aquifers between Baja California/California, Sonora/Arizona, and Chihuahua/New Mexico. Results of this study indicate that a total of 39 HGUs have been identified in this region which accounts for an approximate shareable land of 135,000 km2 where both countries share half of the area. From the total shareable area, around 40% reports good to moderate aquifer potential and water quality, of which 65% is in the U.S. and 35% on the Mexico side. Border-wide, the total number of HGUs in the border region between Mexico and the United States is 72, covering an approximate area of 315,000 km2 (180,000 km2 on the U.S. side and 135,000 km2 on the Mexico side). The total area that reports good to moderate aquifer potential as well as good to regular water quality ranges between 50 and 55% (of which approximately 60% is in the U.S. and the rest in Mexico).
Effect of Biochar Amendment in Woodchip Denitrifying Bioreactors for Nitrate and Phosphate Removal in Tile Drainage Flow
Authors: Vismontienė Rasa , Povilaitis Arvydas
Published: October 2021

Biochar has received increased attention in environmental applications in recent years. Therefore, three pilot-scale denitrifying bioreactors, one filled with woodchips only and the other two enriched with 10% and 20% by volume of biochar from deciduous wood, were tested under field conditions for the removal of nitrate (NO3-N) and phosphate (PO4-P) from tile drainage water in Lithuania over a 3-year period. The experiment showed the possibility to improve NO3-N removal by incorporating 20% biochar into woodchips. Compared to the woodchips only and woodchips amended with 10% biochar, the NO3-N removal effect was particularly higher at temperatures below 10.0 °C. The results also revealed that woodchips alone can be a suitable medium for PO4-P removal, while the amendment of biochar to woodchips (regardless of 10% or 20%) can lead to large releases of PO4-P and other elements. Due to the potential adverse effects, the use of biochar in woodchip bioreactors has proven to be very limited and complicated. The experiment highlighted the need to determine the retention capacity of biochar for relevant substances depending on the feedstock and its physical and chemical properties before using it in denitrifying bioreactors.
On the issue of strengthening the criminal and legal protection of employee personal data
Authors: Vered E.B. , Sementsova I.A.
Published: October 2021

The legislation on personal data has undergone significant changes in connection with the manifested trend of a large amount of their unauthorized placement on the Internet. In this regard, we believe, depending on the severity of the consequences of their “leakage”, to criminalize significant harm to the rights and legitimate interests of a person. Since the use of personal data from social networks by commercial organizations, including about their employee, has now become more frequent without their consent, a corresponding ban should be established in federal legislation. In addition, using modern artificial intelligence systems, attackers have almost unlimited capabilities to obtain all information about the employee. For this reason, the authors of the article propose to fix the corresponding feature as qualifying in Art. 137 of the Criminal Code.
Place of religious holidays in the labor legislation of Russia
Authors: Pogodina I.V. , Kulakova O.S.
Published: October 2021

The article draws attention to the normative organization (consolidation) of religious holidays. Only one of them is enshrined in the Labor Code — the Nativity of Christ. The federal legislator transferred the authority to introduce religious holidays to the regional authorities, subjecting such a decision to the national-territorial location of the subjects. It is proposed to consider a version of the norm on weekends and holidays, which provides for the celebration of the most important religious holidays existing in world religions, which will allow to form both cultural and value diversity and civic unity of the population of Russia.
On the share system of wages
Authors: Serova A.V.
Published: October 2021

The admissibility of the introduction and application of the share system of wages by the employer is analyzed in the article. It provides for the payment of monthly salaries and the possibility of lowering them by predetermined coefficients. The size of the coefficients is determined depending on the degree of fulfillment of the production standards. The conclusion is made about its inconsistency with the Labor Code of the Russian Federation.
Aerodynamic design and acoustic effect study of key geometric parameters of a sirocco fan
Authors: Wang Chen , Mai Kai , Fang Lanhao , Liu Naitong
Published: October 2021

A sirocco fan (forward-curved centrifugal fan), including impeller blades and volute, is designed, and the empirical value ranges of several significant design parameters are discussed and summarized fromthe perspective of both aerodynamics and practical structure. Unsteady-flow numerical
simulation and radiated sound-field calculation by indirect boundary element method are combined to evaluate its aerodynamic and acoustic performances. Both the discrete noise source from the rotating impeller and broadband noise source from the volute are considered. Obvious flow separation
occurs in the flow passage of impeller blades due to large angle of attack, and the tongue region is the major noise source area due to the small impeller-tongue gap. Therefore, parametric studies for blade installation angle and impeller-tongue gap are performed. Analyses of flow- and sound-field
indicate that appropriate reduction of blade geometry incidence angle weakens the flow separation, thereby improving both the aerodynamic and acoustic performances, and reasonable increase of the impeller-tongue gap has a remarkable noise reduction effect for the major noise source area near
the volute tongue. The optimized sirocco fan meets the requirement of the industrial project, i.e., the far-field A-weighted sound power level lower than 64.0 dB(A), and achieves larger volume flow rate and total pressure rise. The results also imply that fast steady-flow numerical simulation
result is indicative of the acoustic performance to some extent if the acoustic evaluation is urgent. Furthermore, optimization of the key structural parameters in the stage of design is preferable in practical engineering, instead of taking follow-up noise reduction measures.
Routinely asking patients about income in primary care: a mixed-methods study
Authors: Pinto Andrew David , Shenfeld Erica , Aratangy Tatiana , Wang Ri , Nisenbaum Rosane , Lofters Aisha , Bloch Gary , Kiran Tara
Published: October 2021

Background

Income is a key social determinant of health, yet it is rare for data on income to be routinely collected and integrated with electronic health records.

Aim

To examine response bias and evaluate patient perspectives of being asked about income in primary care.

Design & setting

Mixed-methods study in a large, multi-site primary care organisation in Toronto, Canada, where patients are asked about income in a routinely administered sociodemographic survey.

Method

Data were examined from the electronic health records of patients who answered at least one question on the survey between December 2013 and March 2016 (n= 14 247). The study compared those who responded to the income question with non-responders. Structured interviews with 27 patients were also conducted.

Results

A total of 10 441 (73%) patients responded to both parts of the income question:‘What was your total family income before taxes last year?’and‘How many people does your income support?’. Female patients, ethnic minorities, caregivers of young children, and older people were less likely to respond. From interviews, many patients were comfortable answering the income question, particularly if they understood the connection between income and health, and believed the data would be used to improve care. Several patients found it difficult to estimate their income or felt the options did not reflect fluctuating financial circumstances.

Conclusion

Many patients will provide data on income in the context of a survey in primary care, but accurately estimating income can be challenging. Future research should compare self-reported income to perceived financial strain. Data on income linked to health records can help identify health inequities and help target anti-poverty interventions.
Machine Learning for Investigation on Endocrine-Disrupting Chemicals with Gestational Age and Delivery Time in a Longitudinal Cohort
Authors: Luan Hemi , Zhao Hongzhi , Li Jiufeng , Zhou Yanqiu , Fang Jing , Liu Hongxiu , Li Yuanyuan , Xia Wei , Xu Shunqing , Cai Zongwei
Published: October 2021

Endocrine-disrupting chemicals (EDCs) are widespread environmental chemicals that are often considered as risk factors with weak activity on the hormone-dependent process of pregnancy. However, the adverse effects of EDCs in the body of pregnant women were underestimated. The interaction between dynamic concentration of EDCs and endogenous hormones (EHs) on gestational age and delivery time remains unclear. To define a temporal interaction between the EDCs and EHs during pregnancy, comprehensive, unbiased, and quantitative analyses of 33 EDCs and 14 EHs were performed for a longitudinal cohort with 2317 pregnant women. We developed a machine learning model with the dynamic concentration information of EDCs and EHs to predict gestational age with high accuracy in the longitudinal cohort of pregnant women. The optimal combination of EHs and EDCs can identify when labor occurs (time to delivery within two and four weeks, AUROC of 0.82). Our results revealed that the bisphenols and phthalates are more potent than partial EHs for gestational age or delivery time. This study represents the use of machine learning methods for quantitative analysis of pregnancy-related EDCs and EHs for understanding the EDCs’ mixture effect on pregnancy with potential clinical utilities.
Novel Synergistic Activity of Quercus infectoria Gall Extract with Ceftazidime Against Standard and Multiple Drug Resistant Pseudomonas aeruginosa and Escherichia coli Isolates
Authors: Isaei Elham , Mansouri Shahla , Rahmani Maryam , Sharififar Fariba , Salary Atefeh
Published: October 2021

Background: Multidrug resistance pathogens are important heath challenges. In this study, the antibacterial activity of 20 plant extracts was tested against standard as well as 20 multidrug-resistant (MDR) strains of Pseudomonas aeruginosa and Escherichia coli. The most active plant extract (Quercus infectoria) was selected for the synergistic activity assay. Methods: Plant extracts were prepared by maceration using water, methanol and ethanol. The antibacterial activity of extracts was determined by both broth and agar dilution methods. The synergistic activity of QIG with ceftazidime (CAZ) was evaluated by checker board assay. Antioxidant activity was determined by colorimetric Ferric reducing antioxidant power (FRAP) assay. Results: Only the methanol extract of QIG inhibited the growth of all the bacterial strains at a concentration of 1000 µg/mL. Other active extracts were Myrtus communis and Eucalyptus globulus inhibiting the growth of most bacterial strains tested at 2000 µg/ mL. In checker board assay, the minimum inhibitory concentration (MIC) to both QIG extract and CAZ was reduced. The MIC of CAZ was reduced from 64-4096 µg/mL to 4 µg/mL for P. aeruginosa and to 16 µg/mL for E. coli isolates. Conclusion: The QIG extract exhibited potent antioxidant activity determined by FRAP assay. The result of this study showed a strong synergistic activity between QIC and CAZ on P. aeruginosa and E. coli. The activity within ethyl acetate-methanol (7:3) fraction indicates that the active components of the plant have a semi-polar nature and further work with this fraction may lead to understanding the mechanism of this synergistic activity.
ÜREME ÇAĞINDAKİ MAVİ YAKALI KADIN İŞÇİLERDE ANEMİ: OTOMOTİV SEKTÖRÜ ÖRNEĞİ
Authors: Türkkan Alpaslan , Aslanhan Bülent , Demiralp Nazan , Özdede Ümit , Pala Kayıhan
Published: October 2021

Yetersiz beslenme ve kötü sağlığın göstergesi olan anemi kadınların sağlıkla ilgili sorunlarından birisini oluşturur. Buna karşın kadınların sağlık sorunlarının istihdam edilmelerine etkisi ile çalışma yaşamının sağlıklarına olan etkisini gösteren çalışmalar sınırlıdır. Bu çalışma, üreme çağında gebe olmayan mavi yakalı kadınlarda, anemi sıklığını, etkileyen etmenleri ve aneminin çalışma yaşamındaki seyrini incelemek amacıyla yapılmıştır. Çalışma, Bursa’da tehlikeli iş kolundaki bir otomotiv fabrikasında yürütülmüştür. Çalışma üreme çağında, gebe olmayan mavi yakalı 329 kadın işçinin verisini kapsar. Kadın işçilerin %37,1’inde anemi saptanmıştır. Bekar olan, kalabalık evde yaşayan, daha önce anemi tanısı almış olan, kanama süresi uzun ve kanaması sırasında günde 5 ve üzerinde ped kullanan kadınlarda anemi prevalansı daha yüksektir. Çalışan kadınlarda anemi prevalansının ve şiddetindeki artışın trendi gösterilmiştir. Çalışma, Türkiye’de özellikle çalışan kadınlarda aneminin önlenmesi ve kontrolüne yönelik etkili sağlığı geliştirme programının oluşturulması için önemli çıkarımlara sahiptir.