bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic Effects and Regional Differences of Industrialization and Urbanization on China’s Energy Intensity under the Background of “Dual Carbon”
Authors: Guo Qingran , Ding Cuicui , Guo Tingting , Liu Shuaitao
Published: August 2022

Based on China’s provincial panel data during 2012–2019, this paper performs an empirical analysis of the dynamic effect and regional difference of industrialization and urbanization on the energy intensity in China by separating the energy intensity into three levels including low, middle and high and using the dynamic panel data with system GMM estimation. The results show that the energy intensity will increase by 0.4298% for every 1% increase in the industrialization level on the premise of keeping other variables unchanged. For every 1% increase in the urbanization level, the energy intensity will increase by 0.5674% on average. For every 1% increase in energy intensity in the previous period, the energy intensity in that year will increase by 0.7968% on average. Moreover, there are regional differences in the effects of industrialization and urbanization on the energy intensity in areas with different energy intensities. In addition, all of the factors including the development level of the regional economy, energy price, and technological innovation have different effects on the energy intensity in China. Meanwhile, there exist the rebound effects of the technological innovation in China, and the energy price has an induced effect on the technological innovation. Undoubtedly, industrialization and urbanization jointly promote the increase in energy intensity. At the same time, the level of economic development, energy prices and technological innovation are also reasons for the differences in the energy intensity among regions. Therefore, in order to effectively reduce energy intensity while carrying out technological innovation, promoting high-quality development and increasing income, it is necessary to improve the internal quality of industrialization and urbanization, and to promote new resource-saving and environmentally friendly methods of industrialization and urbanization.
Sustainable Approaches to Microalgal Pre-Treatment Techniques for Biodiesel Production: A Review
Authors: Krishnamoorthy Amarnath , Rodriguez Cristina , Durrant Andy
Published: August 2022

Microalgae are a potential source of numerous nutritional products and biofuels. Their applications range from the food industry to the medical and fuel sectors and beyond. Recently, the conversion of biomass into biodiesel and other biofuels has received a lot of positive attention within the fossil fuel arena. The objective of biorefineries is to focus on utilising biomass efficiently to produce quality biofuel products by minimising the input as well as to reduce the use of chemical or thermal pre-treatments. Pre-treatment processes in biorefineries involve cell disruption to obtain lipids. Cell disruption is a crucial part of bioconversion, as the structure and nature of microalgae cell walls are complex. In recent years, many research papers have shown various pre-treatment methods and their advantages. The objective of this paper was to provide a comprehensive in-depth review of various recent pre-treatment techniques that have been used for microalgal biodiesel production and to discuss their advantages, disadvantages, and how they are applied in algal biorefineries.
Examining the Provincial-Level Difference and Impact Factors of Urban Household Electricity Consumption in China—Based on the Extended STIRPAT Model
Authors: Wang Yuanping , Cai Weiguang , Hou Lingchun , Zhou Zhaoyin , Bian Jing
Published: August 2022

With increasing urbanisation, urban household electricity consumption (UHEC) has become the most dynamic aspect of China’s energy growth. However, existing studies suffer from outdated data, a small scope, and a lack of research into new influencing factors. There are significant challenges to the promotion of urban household energy-efficiency strategies, which may arise from the intervention of several new inter-provincial differences and other influencing factors. To better understand the variability, volatility characteristics, and influencing factors of change in provincial UHEC, this study analyses and assesses the influencing factors based on an extended STIRPAT model of Chinese provincial panel data from 2005 to 2020. The findings revealed rapid increases in provincial urban household electricity consumption and significant provincial differences in UHEC in China stemming from variation in economic level and energy use. Urbanisation, income, the size of the older population, and area per capita contributed to household electricity consumption. Conversely, household size, heating days (HDD), and air conditioning dampened household electricity consumption. However, television and cooling days (CDD) did not accurately explain the variation in household electricity use in this study. Finally, this study suggests targeted policy recommendations that could promote the implementation of energy-efficiency strategies in Chinese urban households.
Application of Machine Learning Algorithms for Sustainable Business Management Based on Macro-Economic Data: Supervised Learning Techniques Approach
Authors: Khan Muhammad Anees , Abbas Kumail , Su’ud Mazliham Mohd , Salameh Anas A. , Alam Muhammad Mansoor , Aman Nida , Mehreen Mehreen , Jan Amin , Hashim Nik Alif Amri Bin Nik , Aziz Roslizawati Che
Published: August 2022

Macroeconomic indicators are the key to success in the development of any country and are very much important for the overall economy of any country in the world. In the past, researchers used the traditional methods of regression for estimating macroeconomic variables. However, the advent of efficient machine learning (ML) methods has led to the improvement of intelligent mechanisms for solving time series forecasting problems of various economies around the globe. This study focuses on forecasting the data of the inflation rate and the exchange rate of Pakistan from January 1989 to December 2020. In this study, we used different ML algorithms like k-nearest neighbor (KNN), polynomial regression, artificial neural networks (ANNs), and support vector machine (SVM). The data set was split into two sets: the training set consisted of data from January 1989 to December 2018 for the training of machine algorithms, and the remaining data from January 2019 to December 2020 were used as a test set for ML testing. To find the accuracy of the algorithms used in the study, we used root mean square error (RMSE) and mean absolute error (MAE). The experimental results showed that ANNs archives the least RMSE and MAE compared to all the other algorithms used in the study. While using the ML method for analyzing and forecasting inflation rates based on error prediction, the test set showed that the polynomial regression (degree 1) and ANN methods outperformed SVM and KNN. However, on the other hand, forecasting the exchange rate, SVM RBF outperformed KNN, polynomial regression, and ANNs.
Multi-Fractional Brownian Motion: Estimating the Hurst Exponent via Variational Smoothing with Applications in Finance
Authors: Di Persio Luca , Turatta Gianni
Published: August 2022

Beginning with the basics of the Wiener process, we consider limitations characterizing the “Brownian approach” in analyzing real phenomena. This leads us to first consider the fractional Brownian motion (fBm)—also discussing the Wood–Chan fast algorithm to generate sample paths—to then focus on multi-fBm and methods to generate its trajectories. This is heavily linked to the Hurst exponent study, which we link to real data, firstly considering an absolute moment method, allowing us to obtain raw estimates, to then consider variational calculus approaches allowing to smooth it. The latter smoothing tool was tested in accuracy on synthetic data, comparing it with the exponential moving average method. Previous analyses and results were exploited to develop a forecasting procedure applied to the real data of foreign exchange rates from the Forex market.
Coupled Fixed Point Theorems with Rational Type Contractive Condition via C-Class Functions and Inverse Ck-Class Functions
Authors: Liu Xiaolan , Zhou Mi , Ansari Arslan H. , Chakrabarti Kalyan , Abbas Mujahid , Rathour Laxmi
Published: August 2022

The purpose of this paper is to develop coupled fixed point theorems by C-class functions with mixed monotonicity, discuss the existence of the coupled fixed point of two mappings and obtain a coupled coincidence point theorem via inverse Ck-class functions in partially ordered H-metric spaces. This improves the existing results. In addition, some instances and an application are given to illustrate the usability and validity of the results.
Fast Shape Recognition via the Restraint Reduction of Bone Point Segment
Authors: Li Zekun , Guo Baolong , Meng Fanjie
Published: August 2022

In computer science, and especially in computer vision, the contour of an object is used to describe its features; thus, the shape descriptor plays an indispensable role in target detection and recognition. Further, Fourier is an important mathematical description method, and the Fourier transform of a shape contour has symmetry. This paper will demonstrate the symmetry of shape contour in the frequency domain. In recent years, increasing numbers of shape descriptors have come to the fore, but many descriptors ignore the details of shape. It is found that the most fundamental reason affecting the performance of shape descriptors is structural restraints, especially feature structure restraint. Therefore, in this paper, the restraint of feature structure that intrinsically deteriorates recognition performance is shown, and a fast shape recognition method via the Bone Point Segment (BPS) restraint reduction is proposed. An approach using the inner distance to find bone shapes and segment the shape contour by these bones is proposed. Then, Fourier transform is performed on each segment to form the shape feature. Finally, the restraints of the shape feature are reduced in order to build a more effective shape feature. What is commendable is that its discriminability and robustness is strong, the process is simple, and matching speed is fast. More importantly, the experiment results show that the shape descriptor has higher recognition accuracy and the matching speed runs up to more than 1000 times faster than the existing description methods like CBW and TCD. More importantly, it is worth noting that the recognition accuracy approaches 100% in the self-build dataset.
A Deep-Learning Method for the Classification of Apple Varieties via Leaf Images from Different Growth Periods in Natural Environment
Authors: Chen Junkang , Han Junying , Liu Chengzhong , Wang Yefeng , Shen Hangchi , Li Long
Published: August 2022

With the continuous innovation and development of technologies for breeding varieties of fruits, there are more than 8000 varieties of apples in existence. The accurate identification of apple varieties can promote the healthy and stable development of the global apple industry and protect the breeding property rights of rights-holders. To avoid economic losses due to the improper identification of varieties at the seedling-procurement stage, this paper proposes the classification of varieties using images of apple leaves in conjunction with the network models of traditional classification methods, supplemented with deep-learning methods, such as AlexNet, VGG, and ResNet, to account for their shortcomings in robustness and generalizability. We used the Multi-Attention Fusion Convolutional Neural Network (MAFNet) classification method for apple leaf images. The convolutional block distribution pattern of [2,2,2,2] is used to drive the feature extraction layer to have a symmetric structure. According to the characteristics of the dataset, the model is based on the ResNet model to optimize the feature extraction module and integrate a variety of attention mechanisms to achieve the weight distribution of channel features, reduce the interference information before and after feature extraction, complete the accurate extraction of image features, from low-dimensional to high-dimensional, and finally obtain the apple classification results through the Softmax function. The experiments were conducted on a mixture of leaves from 30 apple varieties at 2 growth stages: tender and mature. A total of 14,400 images were used for training, 2400 for validation, and 7200 for testing. The model’s classification accuracy was 98.14%, which improved the accuracy and reduced the classification imputation time as compared with the previous model. Among them, the accuracy rate of “Red General”, “SinanoGold”, and “Jonagold” reached 100%, and the accuracy rate of the bud variant of the Fuji line (“Fuji 2001”, “Red General”, “Yanfu 0”. and “Yanfu 3”) also had an accuracy rate of over 90%. The method proposed in this paper not only significantly improves the classification accuracy of apple cultivars, but it also achieves this with a low cost and a high efficiency level, providing a new way of thinking and an essential technical reference for apple cultivar identification by growers, operators, and law enforcement supervisors in the production practice.
Composition, Source Apportionment, and Health Risk of PM2.5-Bound Metals during Winter Haze in Yuci College Town, Shanxi, China
Authors: Li Lihong , Qi Hongxue , Li Xiaodong
Published: August 2022

The composition, source, and health risks of PM2.5-bound metals were investigated during winter haze in Yuci College Town, Shanxi, China. The 24-h PM2.5 levels of 34 samples ranged from 17 to 174 μg·m−3, with a mean of 81 ± 35 μg·m−3. PM2.5-bound metals ranked in the following order: Zn > Cu > Pb > As > Ni > Cr (VI) > Cd > Co. The concentrations of 18% As and 100% Cr (VI) exceeded the corresponding standards of the Ambient Air Quality Standards set by China and the WHO. Subsequently, positive matrix factorization analyses revealed that the three major sources of metals were combustion (37.91%), traffic emissions (32.19%), and industry sources (29.9%). Finally, the non-carcinogenic risks for eight metals indicated that only 2.9% of the samples exceeded a threshold value of one, and As accounted for 45.31%. The total carcinogenic risk values for six metals (As, Cd, Co, Cr (VI), Ni, and Pb) were in the range from 10−6 to 10−4, with Cr (VI) and As accounting for 80.92% and 15.52%, respectively. In conclusion, winter haze in Yuci College Town was characterized by higher metal levels and health risks; among the metals, As and Cr (VI) were probably the main contributors.
Development of a Hydrazine-Based Solid-Phase Extraction and Clean-Up Method for Highly Selective Quantification of Zearalenone in Edible Vegetable Oils by HPLC-FLD
Authors: Koch Matthias , Mauch Tatjana , Riedel Juliane
Published: August 2022

Rapid, cost-efficient, and eco-friendly methods are desired today for routine analysis of the Fusarium mycotoxin zearalenone (ZEN) in edible vegetable oils. Liquid chromatography with fluorescence detection (HPLC-FLD) is commonly used to reliably control the specified ZEN maximum levels, which requires efficient sample clean-up to avoid matrix interferences. Therefore, a highly selective extraction and clean-up method based on reversible covalent hydrazine chemistry (RCHC) using hydrazine-functionalized silica was developed. This efficient solid-phase extraction (SPE) involves reversible hydrazone formation of ZEN with the hydrazine moiety covalently bound to a solid phase. Optimal conditions were achieved with 1 mL SPE cartridges filled with 400 mg of hydrazine-functionalized silica. The developed RCHC-SPE method was validated in an interlaboratory comparison study (ILC) with twelve participants analyzing six edible vegetable oils with a focus on maize oils. The derived method parameters (ZEN recovery 83%, repeatability 7.0%, and reproducibility 18%) meet the performance criteria of Commission Regulation (EC) No 401/2006. The developed RCHC-SPE-based HPLC-FLD method allows the reliable quantification of ZEN in the range of 47–494 µg/kg for different types of edible vegetable oils, also for matrix-reach native oils. Due to the high efficiency, the significantly reduced matrix load helps to extend the lifetime of analytical equipment. Furthermore, the re-useability of the RCHC-SPE cartridges contributes to an eco-friendly approach and reduced analysis costs. To our knowledge, this is the first report on ZEN quantification in edible vegetable oils based on manual RCHC-SPE cartridges. Due to its high performance, the developed RCHC-SPE method is a promising alternative to the current European standard method EN 16924:2017 (HPLC-FLD part).
Analysis of Total-Forms of Cyanotoxins Microcystins in Biological Matrices: A Methodological Review
Authors: Bouteiller Pierre , Lance Emilie , Guérin Thierry , Biré Ronel
Published: August 2022

Microcystins (MCs) are cyclic heptapeptidic toxins produced by many cyanobacteria. Microcystins can be accumulated in various matrices in two forms: a free cellular fraction and a covalently protein-bound form. To detect and quantify the concentration of microcystins, a panel of techniques on various matrices (water, sediments, and animal tissues) is available. The analysis of MCs can concern the free or the total (free plus covalently bound) fractions. Free-form analyses of MCs are the most common and easiest to detect, whereas total-form analyses are much less frequent and more complex to achieve. The objective of this review is to summarize the different methods of extraction and analysis that have been developed for total forms. Four extraction methods were identified: MMPB (2-methyl-3-methoxy-4-phenylbutyric acid) method, deconjugation at basic pH, ozonolysis, and laser irradiation desorption. The study of the bibliography on the methods of extraction and analysis of the total forms of MCs showed that the reference method for the subject remains the MMPB method even if alternative methods and, in particular, deconjugation at basic pH, showed results encouraging the continuation of the methodological development on different matrices and on naturally-contaminated samples.
Using Community Engagement and Geographic Information Systems to Address COVID-19 Vaccination Disparities
Authors: Wu Tsu-Yin , Yang Xining , Lally Sarah , Rainville Alice Jo , Ford Olivia , Bessire Rachel , Donnelly Jessica
Published: August 2022

The COVID-19 pandemic has exacerbated existing health disparities and had a disproportionate impact on racial and ethnic minority groups in the United States. Limited COVID-19 data for Asian Americans have led to less attention for this population; nevertheless, available statistics have revealed lesser known impacts of COVID-19 on this population. Even with significant increases in vaccine supply and recent increases in COVID-19 vaccination rates, racial and ethnic disparities in vaccine uptake still persist. These disparities are amplified for individuals with limited English proficiency (LEP). The purpose of this paper is to apply community-engaged and geographic information system (GIS) strategies to increase equitable access to COVID-19 vaccination uptake by decreasing the structural barriers to COVID-19 vaccine uptake, with a particular focus on Asian Americans with LEP. Building upon existing community-academic partnerships between the academic unit and community-based organizations, the project team established community-led mobile and pop-up COVID-19 vaccination clinics to reach underserved individuals in their communities, worked with commercial pharmacies and reserved appointments for community-based organizations, used GIS to establish COVID-19 vaccination sites close to communities with the greatest need, and deployed trusted messengers to deliver linguistically and culturally relevant COVID-19 vaccine messages which built vaccine confidence among the community members. The implementation of mobile clinics expanded COVID-19 vaccine access and community-driven, multi-sector partnerships can increase the capacity to enhance efforts and facilitate access to COVID-19 vaccination for hard-to-reach populations.
Galaxy Phase-Space Density Data Preclude That Bose–Einstein Condensate Be the Total Dark Matter
Authors: de Vega Héctor J. , Sanchez Norma G.
Published: August 2022

Ultralight scalars with a typical mass of the order m∼10−22 eV and light scalars forming a Bose–Einstein condensate (BEC) exhibit a Jeans length in the kpc scale and were therefore proposed as dark matter (DM) candidates. Our treatment here is generic, independent of the particle physics model and applies to all DM BEC, in both in or out of equilibrium situations. Two observed quantities crucially constrain DM in an inescapable way: the average DM density ρDM and the phase-space density Q. The observed values of ρDM and Q in galaxies today constrain both the possibility to form a BEC, and the DM mass m. These two constraints robustly exclude the axion DM that decouples after inflation. Moreover, the value m∼10−22 eV can only be obtained with a number of ultrarelativistic degrees of freedom at decoupling in the trillions, which is impossible for decoupling in the radiation dominated era. In addition, we find for the axion vacuum misalignment scenario that axions are produced strongly out of thermal equilibrium and that the axion mass in such a scenario turns to be 17 orders of magnitude too large to reproduce the observed galactic structures. Moreover, we also consider inhomogenous gravitationally bounded BEC’s supported by the bosonic quantum pressure independently of any particular particle physics scenario. For a typical size R∼ kpc and compact object masses M∼107M⊙ they remarkably lead to the same particle mass m∼10−22 eV as the BEC free-streaming length. However, the phase-space density for the gravitationally bounded BEC’s turns out to be more than sixty orders of magnitude smaller than the galaxy-observed values. We conclude that the BEC cannot be the total DM. The axion can be candidates to be only part of the DM of the universe. Besides, an axion in the mili-eV scale may be a relevant source of dark energy through the zero point cosmological quantum fluctuations.
MmuPV1-Induced Cutaneous Squamous Cell Carcinoma Arises Preferentially from Lgr5+ Epithelial Progenitor Cells
Authors: Moreno Ruben , Buehler Darya , Lambert Paul F.
Published: August 2022

Murine papillomavirus, MmuPV1, causes natural infections in laboratory mice that can progress to squamous cell carcinoma (SCC) making it a useful preclinical model to study the role of papillomaviruses in cancer. Papillomavirus can infect cells within hair follicles, which contain multiple epithelial progenitor cell populations, including Lgr5+ progenitors, and transgenic mice expressing human papillomavirus oncogenes develop tumors derived from Lgr5 progenitors. We therefore tested the hypothesis that Lgr5+ progenitors contribute to neoplastic lesions arising in skins infected with MmuPV1 by performing lineage tracing experiments. Ears of 6–8-week-old Lgr5-eGFP-IRES-CreERT2/Rosa26LSLtdTomato mice were treated topically with 4-OH Tamoxifen to label Lgr5+ progenitor cells and their progeny with tdTomato and, 72 h later, infected with MmuPV1. Four months post-infection, tissue at the infection site was harvested for histopathological analysis and immunofluorescence to determine the percentage of tdTomato+ cells within the epithelial lesions caused by MmuPV1. Squamous cell dysplasia showed a low percentage of tdTomato+ cells (7%), indicating that it arises primarily from non-Lgr5 progenitor cells. In contrast, cutaneous SCC (cSCC) was substantially more positive for tdTomato+ cells (42%), indicating that cSCCs preferentially arise from Lgr5+ progenitors. Biomarker analyses of dysplasia vs. cSCC revealed further differences consistent with cSCC arising from LGR5+ progenitor cells.
Phylogenetic and Phylogeographic Analysis of the Highly Pathogenic H5N6 Avian Influenza Virus in China
Authors: Liu Hanlin , Wu Changrong , Pang Zifeng , Zhao Rui , Liao Ming , Sun Hailiang
Published: August 2022

The clade 2.3.4.4b H5N8 avian influenza viruses (AIVs) have caused the loss of more than 33 million domestic poultry worldwide since January 2020. Novel H5N6 reassortants with hemagglutinin (HA) from clade 2.3.4.4b H5N8 AIVs are responsible for multiple human infections in China. Therefore, we conducted an epidemiological survey on waterfowl farms in Sichuan and Guangxi provinces and performed a comprehensive spatiotemporal analysis of H5N6 AIVs in China. At the nucleotide level, the H5N6 AIVs isolated in the present study exhibited high homology with the H5N6 AIVs that caused human infections. Demographic history indicates that clade 2.3.4.4b seemingly replaced clade 2.3.4.4h to become China’s predominant H5N6 AIV clade. Based on genomic diversity, we classified clade 2.3.4.4b H5N6 AIV into ten genotypes (2.3.4.4bG1–G10), of which the 2.3.4.4bG5 and G10 AIVs can cause human infections. Phylogeographic results suggest that Hong Kong and Jiangxi acted as important epicentres for clades 2.3.4.4b and 2.3.4.4h, respectively. Taken together, our study provides critical insight into the evolution and spread of H5N6 AIVs in China, which indicates that the novel 2.3.4.4b reassortants pose challenges for public health and poultry.
Progress of Research into Novel Drugs and Potential Drug Targets against Porcine Pseudorabies Virus
Authors: Zhou Mo , Abid Muhammad , Cao Shinuo , Zhu Shanyuan
Published: August 2022

Pseudorabies virus (PRV) is the causative agent of pseudorabies (PR), infecting most mammals and some birds. It has been prevalent around the world and caused huge economic losses to the swine industry since its discovery. At present, the prevention of PRV is mainly through vaccination; there are few specific antivirals against PRV, but it is possible to treat PRV infection effectively with drugs. In recent years, some drugs have been reported to treat PR; however, the variety of anti-pseudorabies drugs is limited, and the underlying mechanism of the antiviral effect of some drugs is unclear. Therefore, it is necessary to explore new drug targets for PRV and develop economic and efficient drug resources for prevention and control of PRV. This review will focus on the research progress in drugs and drug targets against PRV in recent years, and discuss the future research prospects of anti-PRV drugs.
Persistent Fever and Positive PCR 90 Days Post-SARS-CoV-2 Infection in a Rituximab-Treated Patient: A Case of Late Antiviral Treatment
Authors: Ertesvåg Nina Urke , Sakkestad Sunniva Todnem , Zhou Fan , Hoff Ingrid , Kristiansen Trygve , Jonassen Trygve Müller , Follesø Elisabeth , Brokstad Karl Albert , Dyrhovden Ruben , Mohn Kristin G.-I.
Published: August 2022

Background: Persistent fever after SARS-CoV-2 infection in rituximab-treated patients has been reported. Due to reduced sensitivity in conventional sampling methods and unspecific symptoms in these patients, distinguishing between low-grade viral replication or hyperinflammation is challenging. Antiviral treatment is recommended as prophylactic or early treatment in the at-risk population; however, no defined treatment approaches for protracted SARS-CoV-2 infection exist. Results: We present a case of 96 days of persistent fever and SARS-CoV-2 infection in a patient receiving B cell depletion therapy for multiple sclerosis. Migratory lung infiltrates and positive PCR tests from serum (day-58 post infection) and lower airways (day-90 post infection) confirmed continuous viral replication. The dominant symptoms were continuous high fever, dyspnea and mild to moderate hypoxemia, which never developed into severe respiratory failure. The patient was hospitalized three times, with transient improvement after late antiviral treatment and full recovery 6 months post-rituximab infusion. Conclusions: A strategy for securing samples from lower airways and serum should be a prioritization to strengthen diagnostic certainty in immunocompromised patients. B-cell-deprived patients could benefit from late treatment with SARS-CoV-2-specific monoclonal antibodies and antivirals. Importantly, increased intervals between immunosuppressive therapy should be considered where feasible.
Using Active Seat Belt Retractions to Mitigate Motion Sickness in Automated Driving
Authors: Kremer Christina , Tomzig Markus , Merkel Nora , Neukum Alexandra
Published: August 2022

The introduction of automated-driving functions provides passengers with the opportunity to engage in non-driving related tasks during the ride. However, this benefit might be compromised by an increased incidence of motion sickness. Therefore, we investigated the effectiveness of active seat belt retractions as a countermeasure against motion sickness during inattentive automated driving. We hypothesized that seat belt retractions would mitigate motion sickness by supporting passengers to anticipate upcoming braking maneuvers, by actively tensioning their neck muscles and, thereby, reducing the extent of forward head movement while braking. In a motion base driving simulator, 26 participants encountered two 30 min automated drives in slow-moving traffic: one drive with active seat belt retractions before each braking maneuver and a baseline drive without. The results revealed that there was no difference in perceived motion sickness between both experimental conditions. Seat belt retractions resulted in an increased activity of the lateral neck muscles and supported drivers to anticipate braking maneuvers. However, at the same time, the retractions led to an increased magnitude of head movement in response to braking. This research lays the groundwork for future research on active seat belt retractions as a countermeasure against motion sickness and provides directions for future work.
Epidemiological Survey of Four Reproductive Disorder Associated Viruses of Sows in Hunan Province during 2019–2021
Authors: Tang Qiwu , Ge Lingrui , Tan Shengguo , Zhang Hai , Yang Yu , Zhang Lei , Deng Zaofu
Published: August 2022

Porcine reproductive disorders have been considered as the major factors that threaten pig industries worldwide. In this study, 407 aborted-fetus samples were obtained from 89 pig farms in Hunan province, to investigate the prevalence of four viruses associated with porcine reproductive disease, including porcine reproductive and respiratory syndrome virus (PRRSV), porcine circovirus type 2 (PCV2), pseudorabies virus (PRV), and classical swine fever virus (CSFV). Meanwhile, the target gene sequences of representative PRRSV (ORF5), PCV2 (ORF2), CSFV (E2), and PRV (gE) strains were amplified, sequenced, and analyzed. The results showed that the positive rates of PRRSV, PCV2, PRV, and CSFV among the collected samples were 26.29% (107/407), 52.83% (215/407), 6.39% (26/407), and 12.29% (50/407), respectively. Moreover, co-infection with two and three pathogens were frequently identified, with PCV2/PRRSV, PRRSV/CSFV, PRRSV/PRV, PCV2/CSFV, PCV2/PRV, and PRRSV/PCV2/CSFV mix infection rates of 9.09%, 3.19%, 2.95%, 3.69%, 2.21%, and 0.49%, respectively. Moreover, ORF5-based phylogenetic analysis showed that 9, 4, and 24 of 37 PRRSV strains belonged to the PRRSV2 lineages 1, 5, and 8, respectively. ORF2-based phylogenetic analysis revealed that PCV2d and PCV2b were prevalent in Hunan province, with the proportions of 87.5% (21/24) and 12.5% (3/24), respectively. An E2-based phylogenetic tree showed that all 13 CSFV strains were clustered with 2.1 subgenotypes, these isolates were composed of 2.1b (10/13) and 2.1c (3/13) sub-subgenotypes. A gE-based phylogenetic tree showed that all six PRV strains belonged to the genotype II, which were genetically closer to variant PRV strains. Collectively, the present study provides the latest information on the epidemiology and genotype diversity of four viruses in sows with reproductive diseases in Hunan province, China, which would contribute to developing effective strategies for disease control.
Enhancing the Efficiency of Banana Peel Bio-Coagulant in Turbid and River Water Treatment Applications
Authors: Azamzam Abdassalam A. , Rafatullah Mohd , Yahya Esam Bashir , Ahmad Mardiana Idayu , Lalung Japareng , Alam Mahboob , Siddiqui Masoom Raza
Published: August 2022

The aim of the present work is to investigate the potential use of banana peel waste as a natural coagulant and to enhance its coagulation performance using a green modification approach for the removal of synthetic water turbidity and river water treatment. Here, the regular banana peel powder had an average particle size and diameter of 978 ± 37 nm and 602 ± 13 nm, respectively, while the modified powder possessed 571 ± 41 nm and 360 ± 19 nm particle size and diameter, respectively. The coagulation performance was investigated at different pH levels, doses, sedimentation times, and NaCl quantities. The optimum dose was found to be 0.4 g/L for modified banana peel with turbidity removal of up to 90%. NaCl slightly enhanced the coagulation performance at low quantities of less than 0.4 g/L, but the activity was reduced at higher concentrations even in the modified powder. Banana peel powder had a weaker turbidity reduction of 76 and 84% for non-modified and modified powders in river water, respectively, in addition to significant reduction in water color, total dissolved and suspended solids, and chemical and biochemical oxygen demand. SEM and FT-IR characterization were performed to investigate and confirm the coagulation mechanism. Such a green modification of banana peel powder can be an alternative with significantly potential as a low cost and easily available bio-coagulant, which can certainly contribute to the waste reduction.
A Stepwise Modelling Approach to Identifying Structural Features That Control Groundwater Flow in a Folded Carbonate Aquifer System
Authors: Preziosi Elisabetta , Guyennon Nicolas , Petrangeli Anna Bruna , Romano Emanuele , Di Salvo Cristina
Published: August 2022

This paper concerns a stepwise modelling procedure for groundwater flow simulation in a folded and faulted, multilayer carbonate aquifer, which constitutes a source of good quality water for human consumption in the Apennine Range in Central Italy. A perennial river acts as the main natural drain for groundwater while sustaining valuable water-related ecosystems. The spatial distribution of recharge was estimated using the Thornthwaite–Mather method on 60 years of climate data. The system was conceptualized as three main aquifers separated by two locally discontinuous aquitards. Three numerical models were implemented by gradually adding complexity to the model grid: single layer (2D), three layers (quasi-3D) and five layers (fully 3D), using an equivalent porous medium approach, in order to find the best solution with a parsimonious model setting. To overcome dry-cell problems in the fully 3D model, the Newton–Raphson formulation for MODFLOW-2005 was invoked. The calibration results show that a fully 3D model was required to match the observed distribution of aquifer outflow to the river baseflow. The numerical model demonstrated the major impact of folded and faulted geological structures on controlling the flow dynamics in terms of flow direction, water heads and the spatial distribution of the outflows to the river and springs.
Attention-Deficit/Hyperactivity Disorder and the Gut Microbiota–Gut–Brain Axis: Closing Research Gaps through Female Inclusion in Study Design
Authors: Schleupner Hannah V. , Carmichael Mary Jane
Published: August 2022

The gastrointestinal tract harbors a densely populated community of microbes that exhibits sexual dimorphism. Dysbiosis of this community has been associated with chronic human disease states ranging from metabolic diseases to neuropsychiatric disorders (NPDs). The gut microbiota–gut–brain axis (GMGBA) is a bi-directional pathway that facilitates the interaction of the gut microflora with host physiological functions. Recently, research surrounding the potential roles of the GMGBA in the development of NPDs (e.g., depression, anxiety, and autism spectrum disorders (ASDs)) has increased. However, the role of the GMGBA in attention-deficit/hyperactivity disorder (ADHD), an NPD that affects an estimated 8.4% of children (5.1% of female and 11.5% of male children) and 4% of adults (with a male–female odds ratio of 1.6) in the United States, remains understudied. Herein, we synthesize the current literature regarding the GMGBA, ADHD, and the potentially relevant intersections between the GMGBA and ADHD. Recommendations are presented for pathways of future research into the role(s) of the GMGBA in ADHD etiology and symptomatology. Particular focus is given to the potential for the variable of host sex to act as an outcome modifier of the relationship between the GMGBA and ADHD.
School-Based Exercise Programs for Promoting Musculoskeletal Fitness in Children Aged 6 to 10
Authors: Stanković Dušan , Pivač Stefan , Antonijević Maša , Pekas Damir , Trajković Nebojša
Published: August 2022

Musculoskeletal fitness (MF) is a multidimensional construct that combines muscle strength, endurance, and power to allow for the performance of tasks against one’s own body weight or an external resistance. The aim of this study was to determine the effects of school-based programs on promoting MF in children aged 6 to 10. PubMed and Web of Science databases were used as searching tools. A total of 16 studies were included in a systematic review with primary school-based program interventions measuring at least one variable related to musculoskeletal fitness. Parameters for measuring explosive power, especially standing broad jump (SBJ), have a large potential for development throughout school-based programs. Long-lasting interventions did not necessarily improve MF; however, there were shorter interventions that caused the improvement in a larger number of parameters. Our findings imply that increased physical activity during a school week, together with improved lesson content, is crucial for MF development in this age group.
INFLUENCE OF RETARDANTS ON MORPHOGENESIS AND ANATOMICAL STRUCTURE OF A LEAF APPARATUS OF WHITE MUSTARD PLANTS
Authors: Polyvanyi S. , Polivana A. , Shevchuk O. , Tkahuk O. , Khodanitska O.
Published: August 2022

The influence of antigiberrelic preparations on morphogenesis and anatomical structure of a leaf apparatus was studied. It is found that treatment of white mustard plants with chlormequat chloride and follicle caused a decrease in linear size, stem thickening, increase in the number and area of leaves.The influence of growth inhibitors on the mesostructure of white mustard plant leaves (Sinapis alba L.) was investigated. The application of preparations on mustard plantations in the budding phase led to optimization of the leaf anatomical structure, a thickening of the assimilation parenchyma due to the growth of its cells was observed.Under the action of the preparations, the cell volume of the columnar parenchyma in the sample with chlormequat chloride application increased and now is * 2489.86 ± 120.66 μm3, with follicle -2295.36 ± 116.25 μm3, compared to the control sample, where the volume is 2038 ± 101, 92 μm3. At the same time, the cell linear sizes of spongy parenchyma in experimental variants increase. A more expressible effect was observed under the action of chlormequat chloride.Investigation of the effect of synthetic plant growth regulators on the respiratory tract of white mustard leaves reveals that the number of stomata increased in the number of treated plants. The number of stomata in the variant with chlormequat chloride is - 377.79 ± 10.78 μm3, using follicle is * 370.88 ± 12.24 μm3 compared to the control sample of 341.49 ± 12.23 μm3.
THE NATURAL CHANGES OF THE PLANT COVER OF THE NATIONAL NATURE PARK «DZHARYLHATSKYI»
Authors: Davydova A.
Published: August 2022

The paper presents results of the studies on natural changes of the vegetation in the National Nature Park «Dzharylhatsky» (Kherson region, Ukraine). The natural changes of the vegetation are represented by consistent and catastrophic succession. Consistent changes include halobductional (overgrowing of solonchaks), hydroobductional (overgrowing of lakes) and psammoobductional (overgrowing of sands), eologic (caused by winds activity), alluviogenic (occur due to the accumulation of sediments) and climatogenic (caused by changes in temperature and water regime) processes. Catastrophic changes in the study area occur due to geomorphogenic factors, namely – under the influence of storms. Significant development of syngenetic and geomorphogenic successions occurs along the coastline of the island Dzharylhach and mainland sites of the National Nature Park «Dzharylhatsky». This is due to the mobility of the substrate. Halophytic and psammophytic phytocoenoses have the largest areas.These are the most dynamic and vulnerable to natural and anthropogenic factors. The paper presents the results of analysis of vegetation changes on the island of Dzharylhach over an 80-year period: due to increased xerophytization and halophytization Lemnetum minoris Soó 1927 and Typhetum angustifoliae Pignatti 1953 communities and phytocoenoses with species from the genus Salix L. disappeared, significantly reduced areas of Schoenoplectetum lacustris Chouard 1924 and Junco maritimi-Cladietum marisci (Br.-Bl. & O. de Bolòs 1957) Géhu & Biondi 1988. Thus, the consequences of climatogenic changes are the degradation and disappearance of several communities.
ORGANIC AGRICULTURE LAND IN THE STRUCTURE OF POLTAVA REGION REGIONAL ECO NETWORK
Authors: Ishchenko V. , Smolar N.
Published: August 2022

In order to improve the healthy environment conditions formation, increase natural resource potential of the regions of Ukraine, fully preserve biotic and landscape diversity, maintain ecological balance of ecosystems, national and regional ecological networks are being developed. Theoretical and methodological approaches to the development of the regional ecological network have been developed for Poltava region. The article is devoted to the idea of expanding the concept of regional ecological network building in Poltava region at the expense of organic farming lands, the use of which is based on technologies appliance and resources that promote ecological balance in natural systems and sustainable and balanced agroecosystems. They are considered not only as objects of economic activity, but also as centers of biodiversity conservation, including natural ones. Information on the principles of organic farming implementingexperience in the Poltava region in activities of agricultural enterprises «Agrofirma «Mayak» (Poltava district) and «Agroecologiia» (Myrhorod and Poltava districts), which provides for the use of environmentally friendly agronomic and biocenotic agricultural measures in the Poltava region. It is determined that one of the effective ways to preserve lands used for organic farming is their preservation and including them into the regional ecological network as important natural resource components. It is advisable to protect the land of organic farming in the national natural and regional landscape parks by introducing them into economic zones, which provide for their traditional rational use.
Factores determinantes de la producción forestal en la región Puno - Perú, 2019
Authors: Quispe Mamani Julio Cesar , Hancco Gomez Miriam Serezade , Aguilar Pinto Santotomas Licimaco , Carpio Maraza Amira , Cutipa Quilca Balbina Esperanza , Arce-Coaquira Ronald Raúl
Published: August 2022

El objetivo de esta investigación fue encontrar los factores determinantes de la producción forestal en la región de Puno en Perú, para lo cual se aplicó el enfoque cuantitativo, correlacional y transversal, utilizando datos de la Encuesta Nacional de Hogares del Instituto Nacional de Estadística e Informática, del año 2019; se consideró una muestra de 408 observaciones, con la aplicación del modelo ANCOVA. Se estableció que los factores determinantes de la producción forestal son la explotación agrícola, explotación pecuaria, parcelas trabajadas, gasto en transporte y tenencia de tierra; además, la explotación pecuaria, las parcelas trabajadas, el uso de un sistema de riego y la realización del gasto en transporte influyen de manera directa sobre la producción forestal y la explotación agrícola y la tenencia de tierra influyen de manera negativa en la producción forestal en la región de Puno.
A aplicação da gramática da forma no conjunto habitacional Parque da Lagoa em Blumenau
Authors: Carniel Camila Nunes , Nardelli Eduardo Sampaio
Published: August 2022

Este artigo refere-se ao estudo do Conjunto Habitacional Parque da Lagoa – Blumenau, Santa Catarina utilizando-se a metodologia da gramática da forma, no sentido de identificar a possibilidade de propor a customização das unidades de habitação a partir do registro das queixas dos seus moradores em relação à respectiva padronização de suas unidades. Inicia-se com uma explicação da metodologia de sistemas generativos, salientando o sistema de gramática da forma, utilizado para aplicação do método e contextualizado no referencial teórico das Tecnologias da Informação e Comunicação (TICs). Na sequência, apresenta-se o estudo de caso do Conjunto Habitacional Parque da Lagoa, a partir da dissertação de mestrado da arquiteta e urbanista Keila Peixer (2014) estabelecendo os parâmetros de alteração demandados pelos moradores. Finalmente, a partir destes parâmetros, define-se a sintaxe formal para as alterações consideradas realizáveis com fundamento na planta chave da unidade habitacional. E, a partir desta, o algoritmo correspondente, estruturado no plug-in Grasshopper do programa de modelagem 3D Rhinoceros.
Insuficiência cardíaca: perfil epidemiológico da II macrorregião de saúde do estado de Rondônia entre os anos de 2011 a 2021
Authors: Benetti Henrique Aprijo , Santana Carine Thais Dias , Rodrigues Julliana de Souza , Silva Monica Fernandes Sartori da , Cruz Gesnaquele Souza da , Souza Loara de Assis , Sena Vitor Hugo Alves de , Santos Juliana Peixoto dos
Published: August 2022

Insuficiência cardíaca (IC) e caracterizada como uma síndrome devido a um distúrbio cardíaco, dificultando a irrigação sanguínea para todo o organismo, ocasionando perda metabólica. Nisto o músculo cardíaco é incapaz de realizar a ejeção apropriada do sangue, e manter devidamente a pressão corpórea adequada. Objetivou em caracterizar o perfil epidemiológico dos pacientes hospitalizado por Insuficiência Cardíaca na II macrorregião de saúde do estado de Rondônia no ano de 2011 - 2021. Tratou-se de um estudo epidemiológico a partir de dados secundário entre os anos de 2011 a 2021 no site do Departamento de Informática do Sistema Único de Saúde (DATASUS), de domínio público no Brasil. OS resultados obtidos no período houve 11.504 internações, 1.308 óbitos, sendo que o ano que houve maior número de hospitalização foi 2011 com 1.278 (11,11%), sendo do sexo masculino 57%, da raça/cor parda 21, 69%, com a faixa etária de 70 a 79 anos 29, 42%. Pode-se concluir que houve uma diminuição da taxa de paciente hospitalizado por IC nos últimos anos tendo um percentual de 19,39% nos últimos 3 anos.