bluuebunny/crossref_metadata_2025 huggingface dataset:
The Imbalance of Embodied CO2 in China’s Imports, Exports and Its Causes
Authors: Chen Zhiheng , Tan Yaru
Published: May 2022

Constraining the embodied CO2 from international trade is a crucial part of China’s efforts to achieve emission peak and carbon neutrality. By referring to the WIOD, this article applies the Global Multi-Regional Input-Output (GMRIO) Model and the Value-added Trade Accounting Method to calculate the amount of embodied CO2 in China’s international trade from 2000 to 2014. Results indicate that China’s embodied CO2 in imports and exports is imbalanced in three dimensions: product, region, and industry. One direct cause of this phenomenon is China’s higher carbon emission factors compared to its trading partner. However, the real cause is the global relocation of energy-intensive industries, which leads China to undertake the production of high-carbon industries. To achieve the 3060 Dual Carbon Goal and high-quality economic development, China needs comprehensive and systematic reforms in its economic structure.
Research on Ecological Compensation of National Parks Based on Tourism Concession Mechanism
Authors: Rao Didi , Wang Jiaran , Liu Moucheng , Ma Nan , Li Zhidong , Bai Yunxiao
Published: May 2022

The Chinese government has already proposed to build a nature protected area system composed mainly of national parks and encourages the development of concession operations in national parks. The establishment of a long-term ecological compensation mechanism under the concession mode is of great significance to promoting the harmonious development of man and nature in national parks. This paper selects the Pilot Programs for Shennongjia National Park System (PPSNPS) as the research area and constructs a long-term ecological compensation mechanism under the concession model of tourism back-feeding communities in PPSNPS. Through the questionnaire survey (516 valid questionnaires in 2018), based on the Travel Cost Interval Analysis (TCIA) and Contingent Valuation Method (CVM), the landscape value of the study area is monetized. Combined with the investment cost of concession enterprises, we construct the quantitative distribution ratio of the ecological compensation standard and get the amount of ecological compensation. On this basis, a long-term ecological compensation scheme is constructed. This specific scheme content is as below: on the one hand, Shennongjia National Park Administration (SNPA) is the beneficiary of ecological compensation, and the Shennong Tourism Investment Group Co, Ltd. (STIC) is the provider of ecological compensation; on the other hand, the travel tickets income is the only source of ecological compensation funds (back-feeding funds). Specifically, the landscape value of PPSNPS in 2018 was 604,230.3 × 104 yuan, the input cost of STIC was 140,696 × 104 yuan, the income after deducting tax from tourism tickets was 15,200 × 104 yuan, and the distribution ratio of back-feeding funds is 1:4.29 with the back-feeding funds provided to SNPA from STIC of 12,326.65 × 104 yuan. Through this paper, we know that landscape value monetization can provide ideas for quantitative accounting of the ecological compensation standard for national park tourism concession. In the future, this subject needs more theoretical and practical research on multiple long-term ecological compensation mechanisms.
Numerical Modeling and Symmetry Analysis of a Pine Wilt Disease Model Using the Mittag–Leffler Kernel
Authors: Padmavathi V. , Magesh N. , Alagesan K. , Khan M. Ijaz , Elattar Samia , Alwetaishi Mamdooh , Galal Ahmed M.
Published: May 2022

The existence of man is dependent on nature, and this existence can be disturbed by either man-made devastations or by natural disasters. As a universal phenomenon in nature, symmetry has attracted the attention of scholars. The study of symmetry provides insights into physics, chemistry, biology, and mathematics. One of the most important characteristics in the expressive assessment and development of computational design techniques is symmetry. Yet, mathematical models are an important method of studying real-world systems. The symmetry reflected by such a mathematical model reveals the inherent symmetry of real-world systems. This study focuses on the contagious model of pine wilt disease and symmetry, employing the q-HATM (q-Homotopy Analysis Transform Method) to the leading fractional operator Atangana–Baleanu (AB) to arrive at better understanding. The outgrowths are exhibited in the forms of figures and tables. Finally, the paper helps to analyze the practical theory, assisting the prediction of its manner that corresponds to the guidelines when contemplating the replica.
Measures of Departure from Local Marginal Homogeneity for Square Contingency Tables
Authors: Saito Ken , Takakubo Nozomi , Ishii Aki , Nakagawa Tomoyuki , Tomizawa Sadao
Published: May 2022

When focusing on changes in political party support, it is crucial to determine whether or not there has been a change in the aggregate. From this perspective, various types of marginal homogeneity models have been proposed. We propose local marginal homogeneity models, which indicate that there are symmetric structures of probabilities for only one pair of symmetric marginal probabilities or cumulative probabilities. In addition, we propose two measures, one for nominal categories and one for ordered categories, to express the degree of departure from local marginal homogeneity models. We also apply the measures to data and confirm that the measures help compare the degree of departure from the model in several tables.
Image Segmentation via Multiscale Perceptual Grouping
Authors: Feng Ben , He Kun
Published: May 2022

The human eyes observe an image through perceptual units surrounded by symmetrical or asymmetrical object contours at a proper scale, which enables them to quickly extract the foreground of the image. Inspired by this characteristic, a model combined with multiscale perceptual grouping and unit-based segmentation is proposed in this paper. In the multiscale perceptual grouping part, a novel total variation regularization is proposed to smooth the image into different scales, which removes the inhomogeneity and preserves the edges. To simulate perceptual units surrounded by contours, the watershed method is utilized to cluster pixels into groups. The scale of smoothness is determined by the number of perceptual units. In the segmentation part, perceptual units are regarded as the basic element instead of discrete pixels in the graph cut. The appearance models of the foreground and background are constructed by combining the perceptual units. According to the relationship between perceptual units and the appearance model, the foreground can be segmented through a minimum-cut/maximum-flow algorithm. The experiment conducted on the CMU-Cornell iCoseg database shows that the proposed model has a promising performance.
Identification of Material Properties of Elastic Plate Using Guided Waves Based on the Matrix Pencil Method and Laser Doppler Vibrometry
Authors: Golub Mikhail V. , Doroshenko Olga V. , Arsenov Mikhail A. , Bareiko Ilya A. , Eremin Artem A.
Published: May 2022

Ultrasonic based inspection of thin-walled structures often requires prior knowledge of their mechanical properties. Their accurate estimation could be achieved in a non-destructive manner employing, e.g., elastic guided waves. Such procedures require efficient approaches for experimental data extraction and processing, which is still a challenging task. An advanced automated technique for material properties identification of an elastic waveguide is proposed in this investigation. It relies on the information on dispersion characteristics of guided waves, which are extracted by applying the matrix pencil method to the measurements obtained via laser Doppler vibrometry. Two objective functions have been successfully tested, and the advantages of both approaches are discussed (accuracy vs. computational costs). The numerical analysis employing the synthetic data generated via the mathematical model as well as experimental data shows that both approaches are stable and accurate. The influence of the presence of various modes in the extracted data is investigated. One can conclude that the influence of the corruptions related to the extraction of dispersion curves is not critical if the majority of guided waves propagating in the considered frequency range are presented. Possible extensions of the proposed technique for damaged and multi-layered structures are also discussed.
Nuclear Mass Predictions of the Relativistic Density Functional Theory with the Kernel Ridge Regression and the Application to r-Process Simulations
Authors: Guo Lihan , Wu Xinhui , Zhao Pengwei
Published: May 2022

The kernel ridge regression (KRR) and its updated version taking into account the odd-even effects (KRRoe) are employed to improve the mass predictions of the relativistic density functional theory. Both the KRR and KRRoe approaches can improve the mass predictions to a large extent. In particular, the KRRoe approach can significantly improve the predictions of the one-nucleon separation energies. The extrapolation performances of the KRR and KRRoe approaches to neutron-rich nuclei are examined, and the impacts of the KRRoe mass corrections on the r-process simulations are studied. It is found that the KRRoe mass corrections for the nuclei in the r-process path are remarkable in the light mass region, e.g., A<150, and this could influence the corresponding r-process abundances.
Particle Swarm Optimization Embedded in UAV as a Method of Territory-Monitoring Efficiency Improvement
Authors: Kim Iuliia , Matos-Carvalho João Pedro , Viksnin Ilya , Simas Tiago , Correia Sérgio Duarte
Published: May 2022

Unmanned aerial vehicles have large prospects for organizing territory monitoring. To integrate them into this sphere, it is necessary to improve their high functionality and safety. Computer vision is one of the vital monitoring aspects. In this paper, we developed and validated a methodology for terrain classification. The overall classification procedure consists of the following steps: (1) pre-processing, (2) feature extraction, and (3) classification. For the pre-processing stage, a clustering method based on particle swarm optimization was elaborated, which helps to extract object patterns from the image. Feature extraction is conducted via Gray-Level Co-Occurrence Matrix calculation, and the output of the matrix is turned into the input for a feed-forward neural network classification stage. The developed computer vision system showed 88.7% accuracy on the selected test set. These results can provide high quality territory monitoring; prospectively, we plan to establish a self-positioning system based on computer vision.
A Survey of Battery–Supercapacitor Hybrid Energy Storage Systems: Concept, Topology, Control and Application
Authors: Dong Zheng , Zhang Zhenbin , Li Zhen , Li Xuming , Qin Jiawang , Liang Chenxuan , Han Minghao , Yin Yafei , Bai Jinzhe , Wang Chunyue , Wang Ruiqi
Published: May 2022

A hybrid energy-storage system (HESS), which fully utilizes the durability of energy-oriented storage devices and the rapidity of power-oriented storage devices, is an efficient solution to managing energy and power legitimately and symmetrically. Hence, research into these systems is drawing more attention with substantial findings. A battery–supercapacitor hybrid energy-storage system (BS-HESS) is widely adopted in the fields of renewable energy integration, smart- and micro-grids, energy integration systems, etc. Focusing on the BS-HESS, in this work we present a comprehensive survey including technologies of the battery management system (BMS), power conversion system (PCS), energy management system (EMS), predictive control techniques of the underlying system, application and cost-effective feasibility aspects, etc. This work reflects strong symmetry on different aspects of designing an HESS, and provides guidelines and design references for the research and application of an HESS.
The Human Health Risk Assessment of Heavy Metals Impurities (Cd and Pb) in Herbal Medicinal Products as Menthae piperitae tinctura (Mentha × piperita L., folium) Available in Pharmacies from Poland
Authors: Jurowski Kamil , Krośniak Mirosław
Published: May 2022

Appropriate human health risk assessment (HHRA) is desire in modern regulatory toxicology, especially for elemental impurity studies. The aim of this article is the comprehensive HHRA of two heavy metals impurities—Cd and Pb in herbal medicinal products (HMP) as Menthae piperitae tinctura (Mentha × piperita L., folium) available in Polish pharmacies. These phytopharmaceuticals registered in EU are very common and usually applied OTC products by adults and also children/adolescents. For this purpose, we applied double regulatory approach, including: (1) requirements of ICH Q3D R1 guideline about elemental impurities and (2) additionally margin of exposure (MoE)-based concept to cover also specific population groups. Raw results shows that Cd and Pb were present in all analyzed HMP with Mentha × piperita L., folium (PTM1–PTM10) available in Polish pharmacies. In all samples, Cd impurities (in the range: 0.305–0.506 µg/L) were greatly lower than Pb impurities (in the range: 1.122–4.4921 µg/L). The HHRA of Cd and Pb impurities considering ICH Q3D R1 guideline-based approach made it possible to conclude that all results were below the permissible limit set by FAO/WHO for medicinal herbs and plants in different countries (300 µg/kg for Cd and 10,000 µg/kg for Pb). Additionally, the estimated daily intake of investigated elemental impurities compared to the PDE value confirm all samples safety. The second approach, an MoE-based strategy, indicated that the obtained values of MoE for Cd and Pb in daily dose for each samples were above 10,000; hence, exposure to these elemental impurities would not cause a health risk for all investigated population groups (children, adolescents, and adults). To the best our knowledge, this article is the first study about heavy metals impurities level in final HMPs as Menthae piperitae tinctura (Mentha × piperita L., folium) available in Polish pharmacies.
CRISPR/Cas9-Mediated Disruption of the lef8 and lef9 to Inhibit Nucleopolyhedrovirus Replication in Silkworms
Authors: Liu Yujia , Zhang Xiaoqian , Chen Dongbin , Yang Dehong , Zhu Chenxu , Tang Linmeng , Yang Xu , Wang Yaohui , Luo Xingyu , Wang Manli , Huang Yongping , Hu Zhihong , Liu Zulian
Published: May 2022

Bombyx mori nucleopolyhedrovirus (BmNPV) is a pathogen that causes severe disease in silkworms. In a previous study, we demonstrated that by using the CRISPR/Cas9 system to disrupt the BmNPV ie-1 and me53 genes, transgenic silkworms showed resistance to BmNPV infection. Here, we used the same strategy to simultaneously target lef8 and lef9, which are essential for BmNPV replication. A PCR assay confirmed that double-stranded breaks were induced in viral DNA at targeted sequences in BmNPV-infected transgenic silkworms that expressed small guide RNAs (sgRNAs) and Cas9. Bioassays and qPCR showed that replication of BmNPV and mortality were significantly reduced in the transgenic silkworms in comparison with the control groups. Microscopy showed degradation of midgut cells in the BmNPV-infected wild type silkworms, but not in the transgenic silkworms. These results demonstrated that transgenic silkworms using the CRISPR/Cas9 system to disrupt BmNPV lef8 and lef9 genes could successfully prevent BmNPV infection. Our research not only provides more alternative targets for the CRISPR antiviral system, but also aims to provide new ideas for the application of virus infection research and the control of insect pests.
Protective Immune Responses Induced by an mRNA-LNP Vaccine Encoding prM-E Proteins against Japanese Encephalitis Virus Infection
Authors: Chen Tao , Zhu Shuo , Wei Ning , Zhao Zikai , Niu Junjun , Si Youhui , Cao Shengbo , Ye Jing
Published: May 2022

Japanese encephalitis virus (JEV) is an important zoonotic pathogen, which causes central nervous system symptoms in humans and reproductive disorders in swine. It has led to severe impacts on human health and the swine industry; however, there is no medicine available for treating yet. Therefore, vaccination is the best preventive measure for this disease. In the study, a modified mRNA vaccine expressing the prM and E proteins of the JEV P3 strain was manufactured, and a mouse model was used to assess its efficacy. The mRNA encoding prM and E proteins showed a high level of protein expression in vitro and were encapsulated into a lipid nanoparticle (LNP). Effective neutralizing antibodies and CD8+ T-lymphocytes-mediated immune responses were observed in vaccinated mice. Furthermore, the modified mRNA can protect mice from a lethal challenge with JEV and reduce neuroinflammation caused by JEV. This study provides a new option for the JE vaccine and lays a foundation for the subsequent development of a more efficient and safer JEV mRNA vaccine.
Decades of Genetic Research on Soybean mosaic virus Resistance in Soybean
Authors: Usovsky Mariola , Chen Pengyin , Li Dexiao , Wang Aiming , Shi Ainong , Zheng Cuiming , Shakiba Ehsan , Lee Dongho , Canella Vieira Caio , Lee Yi , Wu Chengjun , Cervantez Innan , Dong Dekun
Published: May 2022

This review summarizes the history and current state of the known genetic basis for soybean resistance to Soybean mosaic virus (SMV), and examines how the integration of molecular markers has been utilized in breeding for crop improvement. SVM causes yield loss and seed quality reduction in soybean based on the SMV strain and the host genotype. Understanding the molecular underpinnings of SMV–soybean interactions and the genes conferring resistance to SMV has been a focus of intense research interest for decades. Soybean reactions are classified into three main responses: resistant, necrotic, or susceptible. Significant progress has been achieved that has greatly increased the understanding of soybean germplasm diversity, differential reactions to SMV strains, genotype–strain interactions, genes/alleles conferring specific reactions, and interactions among resistance genes and alleles. Many studies that aimed to uncover the physical position of resistance genes have been published in recent decades, collectively proposing different candidate genes. The studies on SMV resistance loci revealed that the resistance genes are mainly distributed on three chromosomes. Resistance has been pyramided in various combinations for durable resistance to SMV strains. The causative genes are still elusive despite early successes in identifying resistance alleles in soybean; however, a gene at the Rsv4 locus has been well validated.
Mongolia Gerbils Are Broadly Susceptible to Hepatitis E Virus
Authors: Zhang Wenjing , Ami Yasushi , Suzaki Yuriko , Doan Yen Hai , Muramatsu Masamichi , Li Tian-Cheng
Published: May 2022

Although cell culture systems for hepatitis E virus (HEV) have been established by using cell lines such as PLC/PRF/5 and A549, small-animal models for this virus are limited. Since Mongolia gerbils are susceptible to genotype 1, 3 and 4 HEV (HEV-1, HEV-3 and HEV4), we intraperitoneally inoculated Mongolia gerbils with HEV-5, HEV-7, HEV-8, rabbit HEV or rat HEV in addition to the above three genotypes to investigate the infectivity and to assess whether Mongolia gerbil is an appropriate animal model for HEV infection. The results indicated that (i) HEV-5 and rat HEV were effectively replicated in the Mongolia gerbils in the same manner as HEV-4: large amounts of the viral RNA were detected in the feces and livers, and high titers of the serum anti-HEV IgG antibodies were induced in all animals. The feces were shown to contain HEV that is infectious to naïve gerbils. Furthermore, HEV-4, HEV-5 and rat HEV were successfully transmitted to the gerbils by oral inoculation. (ii) Although the viral RNA and serum anti-HEV IgG antibodies were detected in all animals inoculated with HEV-1 and HEV-8, both titers were low. The viral RNA was detected in the feces collected from two of three HEV-3-inoculated, and one of three HEV-7-inoculated gerbils, but the titers were low. The serum antibody titers were also low. The viruses excreted into the feces of HEV-1-, HEV-3-, HEV-7- and HEV-8-inoculated gerbils failed to infect naïve Mongolia gerbils. (iii) No infection sign was observed in the rabbit HEV-inoculated gerbils. These results demonstrated that Mongolia gerbils are broadly susceptible to HEV, and their degree of sensitivity was dependent on the genotype. Mongolia gerbils were observed to be susceptible to not only HEVs belonging to HEV-A but also to rat HEV belonging to HEV-C1, and thus Mongolia gerbil could be useful as a small-animal model for cross-protection experiments between HEV-A and HEV-C1. Mongolia gerbils may also be useful for the evaluation of the efficacy of vaccines against HEV.
Novel Pegylated Interferon for the Treatment of Chronic Viral Hepatitis
Authors: Huang Yi-Wen , Qin Albert , Tsai Chan-Yen , Chen Pei-Jer
Published: May 2022

Ropeginterferon alfa-2b is a novel mono-pegylated and extra-long-acting interferon, being developed for the treatment of myeloproliferative neoplasm (MPN) and chronic viral hepatitis. It has a favorable pharmacokinetic profile and less frequent dosing schedule, i.e., once every two to four weeks, compared to conventional pegylated interferon products, which have multiple isomers and are administered weekly. It was approved for the long-term treatment of polycythemia vera, an MPN, and has been included in the NCCN clinical practice guidelines for this indication. Ropeginterferon alfa-2b has demonstrated efficacy and showed a favorable safety profile for the treatment of chronic viral hepatitis in several clinical studies. In this article, we review its pharmacokinetics and available clinical data and suggest that ropeginterferon alfa-2b administered once every two weeks can serve as a new treatment option for patients with chronic viral hepatitis, including chronic hepatitis B, C, and D.
In Silico Screening and Testing of FDA-Approved Small Molecules to Block SARS-CoV-2 Entry to the Host Cell by Inhibiting Spike Protein Cleavage
Authors: Ozdemir E. Sila , Le Hillary H. , Yildirim Adem , Ranganathan Srivathsan V.
Published: May 2022

The COVID-19 pandemic began in 2019, but it is still active. The development of an effective vaccine reduced the number of deaths; however, a treatment is still needed. Here, we aimed to inhibit viral entry to the host cell by inhibiting spike (S) protein cleavage by several proteases. We developed a computational pipeline to repurpose FDA-approved drugs to inhibit protease activity and thus prevent S protein cleavage. We tested some of our drug candidates and demonstrated a decrease in protease activity. We believe our pipeline will be beneficial in identifying a drug regimen for COVID-19 patients.
Evidence of RedOX Imbalance during Zika Virus Infection Promoting the Formation of Disulfide-Bond-Dependent Oligomers of the Envelope Protein
Authors: Lebeau Grégorie , Turpin Jonathan , Frumence Etienne , El Safadi Daed , Harrabi Wissal , Desprès Philippe , Krejbich-Trotot Pascale , Viranaïcken Wildriss
Published: May 2022

Flaviviruses replicate in membrane factories associated with the endoplasmic reticulum (ER). Significant levels of flavivirus viral protein accumulation contribute to ER stress. As a consequence, the host cell exhibits an Unfolded Protein Response (UPR), subsequently stimulating appropriate cellular responses such as adaptation, autophagy or apoptosis. The correct redox conditions of this compartment are essential to forming native disulfide bonds in proteins. Zika virus (ZIKV) has the ability to induce persistent ER stress leading to the activation of UPR pathways. In this study, we wondered whether ZIKV affects the redox balance and consequently the oxidative protein folding in the ER. We found that ZIKV replication influences the redox state, leading to the aggregation of the viral envelope protein as amyloid-like structures in the infected cells.
Detection of Platelet-Activating Antibodies Associated with Vaccine-Induced Thrombotic Thrombocytopenia by Flow Cytometry: An Italian Experience
Authors: Cesari Francesca , Sorrentino Silvia , Gori Anna Maria , Rogolino Angela , De Cristofaro Raimondo , Giusti Betti , Sticchi Elena , De Candia Erica , Marcucci Rossella
Published: May 2022

Rare cases of thrombocytopenia and thrombosis after anti-COVID-19 adenovirus-associated mRNA vaccines (VITT) due to platelet-activating anti-platelet-factor 4 (PF4)/polyanion antibodies have been reported. VITT laboratory diagnosis, similarly to heparin-induced thrombocytopenia (HIT) diagnosis, requires immunoassays for anti-PF4/polyanion antibodies identification, such as ELISA assays and platelet-activating functional tests, such as heparin-induced platelet activation test (HIPA), to confirm their pathogenicity. We compared the flow cytometry (FC) measurement of platelet p-selectin exposure to the gold standard functional test HIPA for diagnosis confirmation in 13 patients with a clinical VITT syndrome (6M/7F; median age 56 (33–78)) who resulted positive to anti-PF4/polyanion antibodies ELISA assays (12/13). FC and HIPA similarly identified three different patterns: (1) a typical non-heparin-dependent VITT pattern (seven and six patients by FC and HIPA, respectively); (2) low/no platelet activation in patients under IvIg therapy (five out of five and two out of four patients by FC and HIPA, respectively); (3) a HIT pattern. Antibodies investigated by FC became negative after 7, 17, and 24 days of therapy in three patients. FC measurement of P-selectin exposure was as sensitive as HIPA but simpler to detect anti-PF4/polyanion antibodies in VITT patients. FC could reliably discriminate VITT from HIT, thus helping for the choice of the anticoagulant.
Current View on Genetic Relationships within the Bunyamwera Serological Group
Authors: Dolgova Anna S. , Safonova Marina V. , Faye Oumar , Dedkov Vladimir G.
Published: May 2022

The Bunyamwera serological group includes a number of geographically widespread viruses that are related but not identical and have serological cross-reactivity. As the first group members were obtained in the pre-sequencing era, their classifications (group attribution, species differentiation) were originally based on serological reactions. At the same time, the accuracy of the typing in each case depended on the variety of viruses that the researcher had as a comparison panel. With the advent of sequencing techniques, it has become customary to use identity thresholds (nucleotide or amino acid composition) as demarcation criteria for the interspecific differentiation of viral species. Identity thresholds are determined by the International Committee on Taxonomy of Viruses (ICTV) and are regularly reviewed. Similar criteria were established for the Orthobunyavirus genus, which includes members of the Bunyamwera serological group. On the basis of these criteria, the species attributions of some members of the serological group need to be clarified. For this purpose, we analyzed sequences (available in NCBI GenBank) of viruses belonging to the Bunyamwera serological group in order to clarify their phylogenetic positions on the basis of the current demarcation criteria established by the ICTV.
Evaluation of the Real-World Effectiveness of Vaccines against COVID-19 at a Local Level: Protocol for a Test-Negative Case–Control Study
Authors: Brazete Cátia , Pinto Marta , Sá Lígia , Aguiar Ana , Alves Filipe , Duarte Raquel
Published: May 2022

Vaccines against COVID-19 approved for use in the EU/EEA have been shown to be highly effective against wild-type SARS-CoV-2. However, their effectiveness against new variants may be reduced. This study aims to evaluate the effectiveness of vaccines against COVID-19 in the prevention of symptomatic and severe disease, during pre- and post-omicron phases. Individuals who sought treatment at the emergency department of a Portuguese hospital with COVID-19-like disease and were tested for SARS-CoV-2 are the subjects of the study. Patients who received a positive result are considered cases, while those with negative results are the controls. The test-negative case–control method is one of the study designs recommended by WHO to estimate the effectiveness of vaccines against COVID-19. The main advantage of this design is that it controls for the healthcare seeking bias, commonly present in traditional cohort and case–control designs. This study may have broad implications for understanding the real-world performance of the COVID-19 vaccines at the local level, which may play a key role in promoting adherence to vaccination. Moreover, this study may contribute to inform decisions regarding booster doses and variant-specific vaccine formulations leading to the control of this and future pandemics.
B Cell Responses upon Human Papillomavirus (HPV) Infection and Vaccination
Authors: Prabhu Priya R. , Carter Joseph J. , Galloway Denise A.
Published: May 2022

Infection with human papillomavirus (HPV) is the necessary cause of cervical cancer. Availability of vaccines against HPV makes it a highly preventable disease. HPV vaccines act through type-specific neutralizing antibodies produced by antigen-specific plasma cells known as long-lived plasma cells (LLPC). However, just as any other vaccine, success of HPV vaccine is attributed to the immunologic memory that it builds, which is largely attained through generation and maintenance of a class of B cells named memory B cells (Bmem). Both LLPCs and Bmems are important in inducing and maintaining immune memory and it is therefore necessary to understand their role after HPV vaccination to better predict outcomes. This review summarizes current knowledge of B-cell responses following HPV vaccination and natural infection, including molecular signatures associated with these responses.
Time Series Features for Supporting Hydrometeorological Explorations and Predictions in Ungauged Locations Using Large Datasets
Authors: Papacharalampous Georgia , Tyralis Hristos
Published: May 2022

Regression-based frameworks for streamflow regionalization are built around catchment attributes that traditionally originate from catchment hydrology, flood frequency analysis and their interplay. In this work, we deviated from this traditional path by formulating and extensively investigating the first regression-based streamflow regionalization frameworks that largely emerge from general-purpose time series features for data science and, more precisely, from a large variety of such features. We focused on 28 features that included (partial) autocorrelation, entropy, temporal variation, seasonality, trend, lumpiness, stability, nonlinearity, linearity, spikiness, curvature and others. We estimated these features for daily temperature, precipitation and streamflow time series from 511 catchments and then merged them within regionalization contexts with traditional topographic, land cover, soil and geologic attributes. Precipitation and temperature features (e.g., the spectral entropy, seasonality strength and lag-1 autocorrelation of the precipitation time series, and the stability and trend strength of the temperature time series) were found to be useful predictors of many streamflow features. The same applies to traditional attributes such as the catchment mean elevation. Relationships between predictor and dependent variables were also revealed, while the spectral entropy, the seasonality strength and several autocorrelation features of the streamflow time series were found to be more regionalizable than others.
Characteristics of Plant Community and Its Relationship with Groundwater Depth of the Desert Riparian Zone in the Lower Reaches of the Ugan River, Northwest China
Authors: Zhang Tianju , Chen Yaning , Wang Wanrui , Chen Yongjin , Liu Xigang
Published: May 2022

The vegetation in the desert riparian zone represents a critical barrier in the maintenance of the ecosystem’s balance. However, in recent years, the vegetation degradation of the riparian zone has seriously hindered economic development and ecological environment conservation. Based on a field investigation and literature, the mechanisms of vegetation degradation in the lower reaches of the Ugan River are discussed in this study through the analysis of plant coverage, diversity, substitution rate, distribution pattern, grey correlation analysis, and the relationship with groundwater depth. The results showed that the vegetation coverage in this region is relatively low when the water depth exceeds 4 m. Furthermore, the Shannon–Wiener index, the Simpson index, and the Pielou index all decreased with increases in water depth. Woody plants are the main species maintaining the ecological balance of the region with an aggregation distribution pattern. The degradation of vegetation is the result of the lack of water sources and the intense water consumption caused by human activities (especially agricultural). To promote ecological balance and vegetation restoration, the relative optimal water depth range should be maintained within 2 to 5 m as well as proper control of human activities. In addition, the degraded vegetation can gradually be restored using point and surface (i.e., flowering in the center and spreading to the surrounding areas). The results can provide a scientific basis for vegetation restoration and ecological conservation in the lower reaches of China’s Ugan River.
Socio-Economic Aspects of Centralized Wastewater System for Rural Settlement under Conditions of Eastern Poland
Authors: Brzusek Aleksandra , Widomski Marcin K. , Musz-Pomorska Anna
Published: May 2022

This paper presents a case study concerning multivariate analysis, including social and financial aspects, as well as environmental impacts, of the organized sanitation development under conditions of the selected rural settlement in Poland. Three technologically up-to-date variants of sanitary sewerage network concepts with the different assumed sewage transport, i.e., pressure, pressure-gravity and gravity, were proposed together with the investment and operation and maintenance costs estimation. The willingness-to-accept (WTA) and willingness-to-pay (WTP) survey was used to analyze the level of social acceptance and involvement. The financial analysis covered two economic and cost-efficiency dynamic indicators, benefits–costs ratio (BCR) and dynamic generation cost (DGC), commonly used to support the decision-making process. The environmental aspects were assessed by the possible anthropopressure caused by sewerage leakage and odor emissions. Results of the WTA and WTP survey presented a significant level of acceptance and involvement of the local population to sustain the improved sanitation. The determined values of DGC indicated low cost-efficiency of the gravity system, while obtained values of BCR for all variants and the actual regional sewage fees showed the low profitability of improved sanitation, i.e., BCR < 1.0. All studied sanitation systems were assessed positively due to their environmental impacts. The performed studies showed that, despite the declared willingness to accept the organized sanitation and to pay the sewage fees, the economical sustainability of the proposed designs is doubtful over the longer time duration due to the significant capital and operation costs affecting the sewerage payment value.
Spatial and Temporal Variability of Rainfall Trends in Response to Climate Change—A Case Study: Syria
Authors: Zeleňáková Martina , Abd-Elhamid Hany F. , Krajníková Katarína , Smetanková Jana , Purcz Pavol , Alkhalaf Ibrahim
Published: May 2022

Recent climate changes have prompted changes in the hydrological cycle at a global scale, creating instability when predicting future climate conditions and related changes. Perturbations in global climate models have created the need to concentrate consequent changes in hydro climatic factors to comprehend the regional and territorial impacts of climate and environmental changes. Syria, as a Middle East country, is exposed to extreme climate events such as drought and flood. The aim of this study is to analyze rainfall trends in Syria in response to the likely climate change. The analysis was conducted for rainfall data collected from 71 stations distributed all over the country for the period (1991–2009). The trend analysis was performed in monthly and seasonal scales using Mann–Kendall non-parametric statistical tests. The results attained from Mann–Kendall trend analysis revealed decreasing trends at most of the stations. Additionally, rainfall analysis was conducted for the stations with significant trends for wet and dry periods, which also revealed decreasing trends at almost all the stations. From the analysis of the results, it is obvious that slight increasing trends in rainfall in Syria occurred in the fall period. However, in the winter and spring periods, significant decreasing trends have been observed at almost all the stations. This reveals that the country will suffer from shortage of water, because most rainfall occurs in the winter and spring, infrequently in fall and rarely in summer. The results are consistent with the IPCC’s fifth report that predicted a decrease in rainfall in the Mediterranean and southern Asia. The results of this paper could help the management of water resources in Syria considering future climate changes.
Spatiotemporal Distribution Pattern of Phytoplankton Community and Its Main Driving Factors in Dongting Lake, China—A Seasonal Study from 2017 to 2019
Authors: Yin Xueyan , Yan Guanghan , Wang Xing , Huang Daizhong , Li Liqiang
Published: May 2022

As it is the second-largest freshwater lake downstream of the Three Gorges Dam and an important international wetland for migratory birds, there have been concerns about the ecological water health of Dongting Lake for a long time. In the present study, we studied the evolutionary characteristics of water quality in Dongting Lake in three recent years. Moreover, the evolution rules and dominant groups of the phytoplankton community were explored, and the major influencing factors of phytoplankton and their distribution were assessed based on the field survey and detection data from 2017 to 2019. The results indicated that the water quality of Dongting Lake improved in recent years. The concentration of dissolved oxygen (DO) increased by 6.91%, whereas the concentrations of the five-day biochemical oxygen demand (BOD5), chemical oxygen demand (CODCr), ammonia nitrogen (NH4+–N), total phosphorus (TP), and total nitrogen (TN) decreased by 17.5%, 13.0%, 33.8%, 7.6%, and 13.3%, respectively. The mean phytoplankton density reached 4.15 × 105 cells·L−1 in September 2017, whereas it was only 1.62 × 105 cells·L−1 in December 2018. There were 15 dominant species belonging to Cyanobacteria, Chlorophyta, Bacillariophyta, Cryptophyta, and Miozoa. Moreover, Fragilaria radians (Kützing) D.M.Williams & Round and Aulacoseiragranulata (Ehrenberg) Simonsen were the dominant populations in all seasons. The Pearson and linear regression analysis also indicated that the composition and distribution of phytoplankton in Dongting Lake were mainly affected by electrical conductivity (Cond), BOD5, potassium permanganate (CODMn), and CODCr, especially in Eastern Dongting Lake. Of course, NH4+–N, TN, and TP were also the main factors affecting the density and species of the phytoplankton community, especially in Western Dongting Lake. Finally, we suggested that local government could take “The relationship between Yangtze River and Dongting Lake”, “The relationship between the seven fed rivers and Dongting Lake”, and “The relationship between human activities and Dongting Lake” as the breakthrough points to guarantee the ecological flow, water environment, and ecological quality of Dongting Lake.
Revealing Virtual Water Transfers and Imbalanced Economic Benefits Hidden in China’s Interprovincial Trade
Authors: Zheng Jie , Wu Sanmang , Li Li , Li Shantong , Li Qiuping , An Qi
Published: May 2022

Interprovincial trade has expanded China’s virtual water consumption and economic development. This study uses an environmental–economic inequality index to calculate the virtual water and economic benefit transfer imbalances in interprovincial trade and applies a structural path analysis (SPA) model to find the imbalances on the key virtual water supply chain paths between provinces. The findings are fourfold. (1) The developed provinces, such as Guangdong, Jiangsu, and Shandong, had more virtual water on the consumption side from 2002 to 2017 and had the most value added on the consumption and production sides. (2) The developing provinces in northwest and central China suffered from net virtual water outflows and negative value-added gains in bilateral trade with developed provinces. (3) The developed provinces, such as Beijing, acquired more virtual water from other provinces in 0–5 production tiers, but only a small part of the value added was transferred out. (4) All of the four top ranking virtual water supply chain paths of Beijing came from other provinces, accounting for 28.22% of the total virtual water flowing to Beijing, but their value added only accounted for 1.44%. It is suggested that provinces adopt differentiated water-use systems to reduce virtual water transfer imbalances and provide subsidies to the nodes to compensate the economic benefits on key virtual water supply chain paths.
Risks of Climate Change on Future Water Supply in Smallholder Irrigation Schemes in Zimbabwe
Authors: Mwadzingeni Liboster , Mugandani Raymond , Mafongoya Paramu
Published: May 2022

Smallholder irrigation schemes (SISs) have been portrayed as a panacea to climate change adaptation. However, there is an emerging discourse that established schemes are becoming vulnerable to increased climate variability and change, particularly increased water stress. This paper reviews the existing knowledge on risks of climate change and variability in water supply in smallholder irrigation farming in Zimbabwe. In addition, this paper highlights adaptation options to climate change in SISs. Data for this review were collected systematically from peer-reviewed and published literature. The literature used for this study showed that SISs in Zimbabwe are beset with water stress, competing water needs and the outbreak of pests and diseases, which have been related with climate change and variability. Climate change is making Zimbabwe more arid through decreasing precipitation and warming. Droughts and floods are increasing in frequency and severity. Damage by floods is increasing exponentially, impacting environments, ecological systems and national economies. Climate change affects SISs’ productivity and decimates the livelihoods of scheme farmers. The review suggests that there is a need for increased adsorptive, adoptive and transformational capacity for SISs to obtain a new state of resilience from adverse effects of increased climate variability and change. This review recommends understanding and prioritizing solutions to vulnerability to climate change in SISs.
Northward Expansion of a Warm-Water Doliolid Dolioletta gegenbauri (Uljanin, 1884) into a Temperate Bay, China
Authors: Wang Shiwei , Wan Aiyong , Zhang Guangtao , Sun Song
Published: May 2022

A warm-water doliolid species Dolioletta gegenbauri (Uljanin, 1884) was firstly recorded in Jiaozhou Bay (JZB) during the autumn of 2019–2020. As a warm-water species, its native habitat lies in the East China Sea Shelf, >1000 km south of JZB. Distribution, abundance, stage composition, size frequency distribution, and relationships with environmental factors were studied. Both asexual and sexual reproduction stages were observed. Gonozooids generally dominated the population, indicating an active population development status. Abundance was significantly correlated to temperature. Water temperature in the two consecutive years was among the highest levels during the recent 3–4 decades. The continuous warming trends both in the China coastal seas and JZB likely expanded the biogeographic range. The sub branches of a boundary current, the Kuroshio Current, especially the Yellow Sea Warm Current, may play a central role during the northward extension. Moreover, its feeding, growth, reproduction, and recruitment could also be benefited from the neritic food environment. Finally, when the temperature dropped below 15 °C in the early winter, it disappeared in JZB. The seasonal expansion of D. gegenbauri in JZB could be facilitated by current transportation, warming, and the neritic environment.
A Comparative Analysis of Infiltration Models for Groundwater Recharge from Ephemeral Stream Beds: A Case Study in Al Madinah Al Munawarah Province, Saudi Arabia
Authors: Niyazi Burhan , Masoud Milad , Elfeki Amro , Rajmohan Natarajan , Alqarawy Abdulaziz , Rashed Mohamed
Published: May 2022

Groundwater recharge is strongly influenced by the infiltration process. In this research, the Philip, Horton, Kostiakov, and Green–Ampt infiltration models were tested for the ability to describe the infiltration process in the ephemeral stream beds located in Al Madinah Al Munawarah Province in Saudi Arabia. Infiltration data were obtained from double-ring infiltrometer tests in 14 locations distributed over the province. The method of least squares through an objective function optimization formalism is utilized to estimate the parameters of each model. The results show high variability in the parameters of each model over the tests. Individual tests showed that some models were better for representing specific tests than other models. On average, the Kostiakov empirical model was the best at describing the 14 infiltration tests with only 2 empirical parameters, since it had the minimum root mean square error (RMSE) for the cumulative infiltration depth F (1.13 cm), and it also had the same RMSE for the infiltration rates f (0.1 cm/min), similar to other models. Moreover, the Kostiakov model had an acceptable correlation coefficient R = 0.61 for f, and R = 0.99 for F. The results imply significant variability in the groundwater recharge rates from flash floods in the region.
Development of a Neural Network Model for Recognizing Red Palm Weevil Insects Based on Image Processing
Authors: SALEH Radhwan Alı Abdulghanı , ERTUNÇ Hüseyin Metin
Published: May 2022

The red palm weevil (RPW) is an invasive pest insect that attacks palm trees and threatens their existence. Accordingly, RPW causes significant and massive economic losses during the last two decades. This issue makes the early detection of RPW is a hot research topic. This study proposes a machine learning technique based on image processing to easily recognize these insect species for people who do not know them. The basic idea of the proposed research is to develop a neural network model that can use image processing to identify RPW and distinguish it from other insects found in palm tree habitats. This model consists of three stages: image pre-processing (image enhancement and segmentation using Otsu's thresholding), feature extraction (texture and color moments features), and classification (artificial neural network). The dataset used in this study includes 913 images, where 448 are RPWs' images, and the rest are ants' images. The experimental results of the ten-fold cross-validation show that the accuracy of the proposed model is 92.22%.