bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing Ecological Compensation Policy Effectiveness: A Case Study in the Inner Mongolia Autonomous Region, China
Authors: Lu Yiwen , Yang Xining , Xie Yichun
Published: September 2024

As a vital component of the terrestrial ecosystem, grassland accounts for one-third of the global vegetation system. Grassland degradation has been exacerbated due to extreme overgrazing in China’s Inner Mongolia Autonomous Region (IMAR). While conservation was carried out via the Ecological Subsidy and Award Program (ESAP) to mitigate grassland degradation, little is known about its effectiveness in improving the biophysical conditions of grassland. This paper integrates the conceptual frameworks of total socio-environmental systems (TSESs) to assess how ecological systems respond to the ESAP, investigate the spatial heterogeneity of the ESAP, and explore the meddling effects of socio-environmental interactions on the ESAP. We integrated ecological, climate, and socioeconomic data and developed several hierarchical linear mixed models (HLMMs) to investigate how these factors interact with the ESAP in the IMAR. Our findings prove that the above-ground biomass between 2011 and 2015 responds significantly to variations in socioeconomic conditions and ecological communities. Available land resources, hospital and medical facilities, and net farmer and herdsman income are the most critical factors positively related to grassland productivity. Primary industries like mining, total consumer retail value, farming, forestry, animal husbandry, fishery productions, and GDP are the most damaging factors affecting biomass. Our study recommends a regionally or locally tailored ecological recovery policy, instead of a generalized one, in future efforts to conserve grassland.
Carbon Emission Accounting Model of Three-Stage Mechanical Products for Manufacturing Process
Authors: Wang Minjie , Wu Yuanbo , Wang Bin
Published: September 2024

Carbon accounting is critical to manufacturing and achieving a low-carbon transition and lean carbon management. A comprehensive understanding of carbon emissions in manufacturing is essential to calculate a product’s carbon footprint accurately. Based on the life cycle assessment (LCA) method, this study divides the whole process of mechanical products from parts to finished products into three stages: parts (P), assembly (A), and testing (T). By decomposing each stage’s carbon emission sources and combining each stage’s characteristics, a series of corresponding carbon emission accounting models is established. Finally, the three-stage carbon emission model of the manufacturing process of a three-piece ball valve is established, and the validity and feasibility of the proposed model are verified. The results show that raw material consumption, energy consumption, and transportation are the primary sources of carbon emissions in the manufacturing process of three-piece ball valves, accounting for 35.6%, 38.8%, and 17.6%, respectively. The corresponding carbon emissions were 17.854 kgCO2e, 19.405 kgCO2e, and 8.8 kgCO2e, respectively. Through these results, we can provide some theoretical and data support for the low-carbon transformation of manufacturing enterprises as well as some research ideas for realizing low-carbon production through process planning and shop scheduling.
Enhancing Government Services to Rice Farmers in the Philippines: A Service Quality–Sustainability-Focused Approach for Long-Term Agricultural Resilience
Authors: Ituriaga Jenel , Mariñas Klint Allen , Saflor Charmine Sheena
Published: September 2024

In the Philippines, where agriculture plays a vital role in the economy, nearly half of the country’s 30 million hectares of land is used for agricultural purposes. Despite government efforts to support rice farmers, challenges, such as production failures and profit losses, remain prevalent. This study evaluates the quality of government services provided to rice farmers through a service quality-based framework (SERVQUAL), assessing five key dimensions: assurance (AS), empathy (EM), reliability (RL), responsiveness (RS), and tangibility (TA). Structural equation modeling (SEM) is employed to examine the relationships among these service quality dimensions and other latent variables, including service quality (SQ), farmers’ satisfaction (FS), farmers’ trust (FT), perceived security (PS), and perceived effectiveness (PE). Data were gathered from 400 respondents using a 55-item survey. The findings indicate that perceived security (PS) is the most critical factor in enhancing the overall quality of government services. The study emphasizes the importance of adopting a SERVQUAL-based approach, with a focus on reliability and responsiveness to improve farmers’ satisfaction and trust. Additionally, fostering trust between farmers and the government is crucial to increasing the effectiveness of government programs and strengthening farmer–government collaboration. The study further advocates for prioritizing sustainable agricultural practices to ensure long-term productivity and environmental resilience. By improving service quality with a focus on sustainability, the Philippines can work towards achieving broader sustainable development goals.
Forest Therapy as an Alternative and Sustainable Rehabilitation Practice: A Patient Group Attitude Investigation
Authors: Bassi Ivana , Deotto Vanessa , Pagani Laura , Iseppi Luca
Published: September 2024

The objective of this research is to investigate the awareness and opinions concerning forest therapy within a public health institution, specifically as a green prescription for patients with stable chronic disease. Through qualitative preliminary analysis, this study compared the responses of a group to gather physical activity and wood frequentation insights, as well as forest therapy patients’ attitudes. The results underline a general predisposition among respondents to engage in moderate physical activity and visit natural environments for relaxation purposes. Emerging parallelly is how forest therapy is largely an unknown practice, although it draws considerable interest and a general predisposition to participate. This research outlines the ideal conditions that emerge for participating in forest therapy sessions, including the availability to pay, pointing toward environmentally and socio-economically sustainable reflections. Further studies should extend this preliminary investigation using appropriate statistical methodologies on larger samples, involving different regions and medical conditions.
Farmers’ Willingness and Adoption of Water-Saving Agriculture in Arid Areas: Evidence from China
Authors: Tai Xiujun , Feng Feng , Sun Fengluan
Published: September 2024

Enhancing water resource utilization efficiency is crucial for achieving sustainable development in arid and semi-arid regions. In promoting water-saving agriculture technologies, there is often a phenomenon of “willingness without behavior”. Therefore, investigating how willingness translates into behavior is of significant importance for improving water resource utilization. This study utilized data from a survey of 494 households in Ulanqab City, Inner Mongolia Autonomous Region, China, and employed Probit models to analyze the factors influencing farmers’ willingness towards water-saving technologies and their adoption. Prospect theory and mental accounting theory were introduced to understand the mechanism of transformation from farmers’ willingness to adoption. The study found that farmers’ willingness is a crucial prerequisite for their adoption. Farmers’ income perception towards adopting water-saving technologies can facilitate the transformation from willingness to adoption, while cost perception can inhibit this transformation. Both small and large-scale farmers’ perception of the benefits of water-saving technologies significantly increased their likelihood of translating their willingness to adopt into actual action. Compared with large-scale farmers, small-scale farmers are more sensitive to the perception of economic costs in the decision-making process. For both types of farmers, the perception of learning cost inhibits their willingness to adopt water-saving technologies to a certain extent. Farmers’ perception of the prospects of adopting water-saving technologies leads to a psychological segmentation effect, and the ultimate adoption depends on the psychological game between farmers’ income and cost perception.
Fairness in E-Recruitment: Examining Procedural Justice Perceptions and Job Seekers’ Intentions
Authors: Lo Piccolo Elena , Petruzziello Gerardo , Chiesa Rita , Pietrantoni Luca , Mariani Marco Giovanni
Published: September 2024

Corporate websites are crucial in recruitment, as the prospective applicants’ experiences in digital recruitment may influence their intentions. Therefore, understanding how opportunity-to-perform perceptions (OPP) integral to procedural justice experienced by potential applicants while visiting a corporate recruitment website impact their reactions towards the company can be key. This study aims to elucidate the influence of OPP on applicants’ intentions to apply (ITA) via corporate websites. Specifically, it explores the indirect relationship between OPP during recruitment and ITA one month after visiting a company website, mediated by organizational attractiveness and ITA measured immediately after and one week after the website visit. This multi-wave study collected 260 cases from master’s students in psychology who completed a questionnaire across waves. Hypotheses were tested using the PROCESS macro in SPSS. The findings highlighted a serial mediation pathway, wherein the indirect connection between OPP and ITA after one month was mediated through organizational attractiveness, ITA immediately after, and one week after website visits. The results highlight the importance of enhancing procedural justice corporate websites to influence applicants’ perceptions and intentions positively and improve recruitment outcomes. Future research should explore the effect of long-term justice perceptions as a basis for a sustainable employee–employer relationship.
Characteristics and Effects of the Last Kilometre of the Tourist City from the Dynamic and Static Perspectives
Authors: Xiong Yajun , Guo Xinwei , Gao Junbo
Published: September 2024

The accessibility of the “last kilometre” of a tourist city has a profound impact on the travelling experience of tourists. In-depth understanding of the characteristics and spatial effects of the “last-kilometre” traffic accessibility in tourist cities is conducive to further enhancing the accessibility of traffic travel and forming a new industry development pattern of deep integration of traffic and tourism. The results show that: (1) Private transport accessibility is significantly better than public transport accessibility, and the strong economic strength of large cities such as Peking, Shanghai, and Nanjing support a wider coverage of public transport compared with cities such as Qinhuangdao, Dalian, Ningbo, etc. Even for the middle-income and high-income groups of the large cities, the advantage of the broader travelling cost of public transport is still significant. (2) The average values of the fluctuation coefficients of travel time of public transport in tourist cities are all smaller than those of private transport, and public transport is less sensitive to traffic congestion, making it a more reliable choice for tourist travel. The higher number of public transport grids with more anomalous fluctuations and much larger fluctuations than private transport grids suggests that there is an urgent need to strengthen the standardisation of public transport services in the corresponding areas. (3) Urban tourism development has been moving from single-line to network development, and the impact of urban transport on urban–regional tourism development has been manifested in the place fission effect, corridor diffusion effect, and regional equilibrium effect. In general, our findings have been useful in understanding the accessibility characteristics of the “last kilometre” in tourist cities, optimizing the efficiency of inter-regional and intra-city transport connections, constructing a fast and convenient travel transport system, improving the accessibility of transport trips, and forming a new development pattern for the deep integration of transport and tourism.
Stabilization and Remediation of Arsenic-Contaminated Soil: Fly Ash-Based Technology for Industrial Site Restoration
Authors: Yu Jiang , Bao Jianguo , Su Qu , Zhang Wuzhu , Ye Bei , Zhou Xingzhu , Li Hongcheng , Li Xing
Published: September 2024

Arsenic contamination of various environmental components poses a serious threat to human and animal health. Soil As contamination is particularly hazardous, as soil is a vital pathway to the food chain. We conducted experiments on soil from a typical pharmaceutical and chemical industry relocation site in Hubei Province, focusing on modification using fly ash through mechanical and chemical mechanisms. We subjected varying proportions of lime, ferrous sulfate, and fly ash to mechanical ball milling and used these mixtures to perform remediation of arsenic-contaminated soil and site restoration. Our findings are as follows: in soil culture experiments, the As stabilization efficiency reached 90% within 90 days with ferrous salt-modified fly ash. In actual site restoration, As-stabilization efficiency exceeded 95% across different soil depths within 30 days, demonstrating significant stabilization effects. Optimal modified dosages were determined as 2% ferrous sulfate and 2% fly ash. After stabilization, As in the soil primarily existed in amorphous iron-aluminum oxide-bound (F3) and crystalline iron-aluminum oxide-bound (F3 + F4) and residual (F5) states. Fluctuations in the moisture content and pH mainly activated F3 and F4, transitioning them into exchangeable (F1) and surface-adsorbed (F2) states. Arsenic leaching was predominantly associated with the F1 form. Fly ash-based restoration technology demonstrates promising capabilities in waste treatment and pollution control, offering significant potential for widespread application.
Spatiotemporal Distribution and Habitat Characteristics of Shorebirds in the Coastal Wetlands of Dalian, Liaoning, China
Authors: Luo Hao , Li Qing , Yu Yang , Kang Jing , Lei Wei , Zhang Demin
Published: September 2024

The coast of Dalian in Liaoning Province, China, is one of the most important habitats for migratory shorebirds along the East Asia–Australasian Flyway. However, the coastal areas of Dalian have been modified extensively by various projects, including reclamation and the construction of aquaculture and port facilities, embankment buildings, cross-sea passages, and wind farms, which have led to significant damage to the coastal habitats of shorebirds. Assessing the spatiotemporal distribution and habitat characteristics of shorebirds is of great importance to biodiversity conservation. The present study involved a 15-month-long survey of shorebirds in nine coastal wetlands of Dalian from August 2021 to October 2022. In total, 31 species of shorebirds, belonging to five families, were recorded. Migratory shorebirds were the most frequently observed, accounting for 77% of the recorded shorebirds. Dunlin (Calidris alpina), Kentish plover (Charadrius alexandrinus), Eurasian curlew (Numenius arquata), and Far Eastern curlew (Numenius madagascariensis) were the most abundant species. Both species richness and species abundance peaked in May and again in September. The Zhuanghe Estuary boasted the highest species diversity, while the Huli Estuary wetland exhibited the greatest species abundance. The type of habitat and the spatial extent of natural wetlands were the main variables influencing the spatial distribution of waterbirds. By identifying the population characteristics and habitat status of shorebirds in Dalian, the results provide support for shorebird conservation and habitat management.
Shanghai Transport Carbon Emission Forecasting Study Based on CEEMD-IWOA-KELM Model
Authors: Gu Yueyang , Li Cheng
Published: September 2024

In the light of the worsening of, and the adverse effects produced by, global warming, a study of Shanghai’s transport carbon emissions can provide an advanced model that can be replicated throughout other cities, thus assisting in the management and reduction of carbon emissions. Considering the volatility and nonlinearity of the carbon emission data series of the transport industry, a prediction model combining complementary ensemble empirical modal decomposition (CEEMD), the improved whale optimization algorithm (IWOA), and the Kernel Extreme Learning Machine (KELM) is proposed for a more accurate prediction of the forecasting of carbon emissions from Shanghai’s transport sector. First, nine indicators were screened as the influencing factors of Shanghai’s transport carbon emissions through the STIRPAT model, and the corresponding carbon emissions were calculated with data related to Shanghai’s transport carbon emissions from 1995 to 2019; Secondly, CEEMD was used to decompose the original data into multiple smooth series and one residual term, and KELM was applied to build a prediction model for each decomposition result, and IWOA was used to optimize the model parameters. The experimental results also demonstrate that CEEMD can effectively reduce model errors. Comparative experiments show that the IWOA algorithm can significantly enhance the stability of machine learning models. The outcomes of various experiments indicate that the CEEMD-IWOA-KELM model produces optimal results with the highest accuracy. Additionally, this model exhibits high stability, as it provides a wider range of methods for predicting carbon emissions and contributing to carbon reduction targets.
Tool-Emitted Sound Signal Decomposition Using Wavelet and Empirical Mode Decomposition Techniques—A Comparison
Authors: Joseph Emerson Raja , Jakir Hossen , Thangavel Bhuvaneswari , Nor Azlina , Lim Thong Leng , Mariathangam Pushpa Rani
Published: September 2024

Analysis of non-stationary and nonlinear sound signals obtained from dynamical processes is one of the greatest challenges in signal processing. Turning machine operation is a highly dynamic process influenced by many events, such as dynamical responses, chip formations and the operational conditions of machining. Traditional and widely used fast Fourier transformation and spectrogram are not suitable for processing sound signals acquired from dynamical systems as their results have significant deficiencies because of stationary assumptions and having an a priori basis. A relatively new technique, discrete wavelet transform (DWT), which uses Wavelet decomposition (WD), and the recently developed technique, Hilbert–Huang Transform (HHT), which uses empirical mode decomposition (EMD), have notably better properties in the analysis of nonlinear and non-stationary sound signals. The EMD process helps the HHT to locate the signal’s instantaneous frequencies by forming symmetrical envelopes on the signal. The objective of this paper is to present a comparative study on the decomposition of multi-component sound signals using EMD and WD to highlight the suitability of HHT to analyze tool-emitted sound signals received from turning processes. The methodology used to achieve the objective is recording a tool-emitted sound signal by way of conducting an experiment on a turning machine and comparing the results of decomposing the signal by WD and EMD techniques. Apart from the short mathematical and theoretical foundations of the transformations, this paper demonstrates their decomposition strength using an experimental case study of tool flank wear monitoring in turning. It also concludes HHT is more suitable than DWT to analyze tool-emitted sound signals received from turning processes.
Balance Controller Design for Inverted Pendulum Considering Detail Reward Function and Two-Phase Learning Protocol
Authors: Liu Xiaochen , Wang Sipeng , Li Xingxing , Cui Ze
Published: September 2024

As a complex nonlinear system, the inverted pendulum (IP) system has the characteristics of asymmetry and instability. In this paper, the IP system is controlled by a learned deep neural network (DNN) that directly maps the system states to control commands in an end-to-end style. On the basis of deep reinforcement learning (DRL), the detail reward function (DRF) is designed to guide the DNN learning control strategy, which greatly enhances the pertinence and flexibility of the control. Moreover, a two-phase learning protocol (offline learning phase and online learning phase) is proposed to solve the “real gap” problem of the IP system. Firstly, the DNN learns the offline control strategy based on a simplified IP dynamic model and DRF. Then, a security controller is designed and used on the IP platform to optimize the DNN online. The experimental results demonstrate that the DNN has good robustness to model errors after secondary learning on the platform. When the length of the pendulum is reduced by 25% or increased by 25%, the steady-state error of the pendulum angle is less than 0.05 rad. The error is within the allowable range. The DNN is robust to changes in the length of the pendulum. The DRF and the two-phase learning protocol improve the adaptability of the controller to the complex and variable characteristics of the real platform and provide reference for other learning-based robot control problems.
Three-Dimensional Printing by Vat Photopolymerization on Textile Fabrics: Method and Mechanical Properties of the Textile/Polymer Composites
Authors: Gruhn Philipp , Koske Daniel , Storck Jan Lukas , Ehrmann Andrea
Published: September 2024

Composites of textile fabrics and 3D-printed layers have been investigated thoroughly during the last decade. Usually, material extrusion such as the fused deposition modeling (FDM) technique is used to build such composites, revealing challenges in preparing form-locking connections between both materials due to the highly viscous polymer melt, which can hardly be pressed into textile fabrics. Resins used for 3D printing by vat photopolymerization, i.e., for stereolithography (SLA), are less viscous and can thus penetrate deeper into textile fabrics; however, fixing a textile on the printing bed that is fully dipped into the resin is more complicated. Here, we present one possible solution to easily fix textile fabrics for SLA printing with consumer printers according to the digital light processing (DLP) sub-method. Also, we show the results of a study of the mechanical properties of the resulting textile/polymer composites, as revealed by three-point bending tests.
The Effect of Resveratrol on Gamma Globin Gene Expression in Patients with Beta Thalassemia: The Role of Adaptation to Cellular Stress
Authors: Jalali Hossein , Mahdavi Mohammad Reza , Kosaryan Mehrnoush , Najafi Ahmad , Aliasgharian Aily , Salehifar Ebrahim
Published: September 2024

HbF induction is an appropriate strategy to ameliorate the severity of β-thalassemia symptoms. Hydroxyurea (HU) is the most common chemical agent introduced as an HbF inducer but responsiveness to HU is variable and the introduction of HbF inducers alternative to HU with low cytotoxicity has been a crucial challenge. Resveratrol is an HbF inducer agent that may have favorable effects on the differentiation of hematopoietic erythroid progenitors (HEPs). The present study aimed to investigate the effect of resveratrol on γ-globin, stress response, and anti-apoptotic gene expression among hydroxyurea (HU)-responders and HU-nonresponders (HU-NR). Four cases of HU-R and four cases of HU-NR were studied. HEPs of the patients were cultured, and the expression of γ-globin, Foxo3, and Bclxl was assessed. Moreover, the differentiation and apoptotic rate of the cells were investigated using flow cytometry analysis. In three cases, the γ-globin gene expression increased after resveratrol treatment. All of the HU-NR patients were also non-responders to resveratrol (Res-NR). The expression of Foxo3 and Bclxl genes was higher in responders to resveratrol (Res-R) compared to non-responders (Res-NR). The rate of apoptosis in Res-R patients was also lower than in Res-NR. Responders to resveratrol also had a higher rate of HEP maturation. The cells of both HU–NR and Res-NR patients could not adapt to stress conditions and proceed to the erythroid differentiation. In conclusion, resveratrol increased the γ-globin expression in HEPs of β-thalassemia patients. The response was observed only in R-HU patients with similar cellular pathways.
Occupational Exposure of On-Shift Ottawa Firefighters to Flame Retardants and Polycyclic Aromatic Hydrocarbons
Authors: Papas William , Aranda-Rodriguez Rocio , Fan Xinghua , Kubwabo Cariton , Lee Janet , Fantin Emma , Zheng Elita , Keir Jennifer , Matschke Dave , Blais Jules , White Paul
Published: September 2024

Firefighters can be exposed to complex mixtures of airborne substances, including hazardous substances released during structural fires. This study employed silicone wristbands (SWBs) as passive samplers to investigate potential exposure to polycyclic aromatic hydrocarbons (PAHs) and flame retardants (FRs). SWBs were deployed at different areas of four fire stations, in four truck cabins, and at an office control location; they were also donned outside the jackets of 18 firefighters who responded to fire calls. Overall, office areas had significantly lower PAHs than fire station areas. Vehicle bays and truck cabins had significantly higher concentrations of low molecular weight (LMW) PAHs than sleeping and living room areas. For organophosphate ester flame retardants (OPFRs), tri-n-butyl phosphate (TnBP) and tris(1-chloro-2-propyl) phosphate (TCPP) were detected in all the samples; 2-ethylhexyl diphenyl phosphate (EHDPP) was more frequently detected in the fire station areas. Triphenyl phosphate (TPP) concentrations were highest in the truck cabin and office areas, and tris(1,3-dichloro-2-propyl)phosphate (TDCPP) was highest in truck cabins. Thirteen of 16 PAHs and nine of 36 OPFRs were detected in all the SWBs worn by firefighters, and tris (2-butoxyethyl) phosphate (TBEP) was the predominant OPFR. Levels of LMW PAHs were significantly lower when firefighters did not enter the fire. LMW PAHs, HMW (high molecular weight) PAHs, and EHDPP were significantly elevated when heavy smoke was reported. This work highlights the potential for occupational exposure to PAHs and flame retardants in some fire station areas; moreover, factors that may influence exposure during fire suppression. Whilst firefighters’ occupational exposure to PAHs is likely related to fire suppression and exposure to contaminated gear and trucks, exposure to OPFRs may be more related to their presence in truck interiors and electronics.
Per- and Polyfluoroalkyl Substances (PFAS) Affect Female Reproductive Health: Epidemiological Evidence and Underlying Mechanisms
Authors: Qu Rui , Wang Jingxuan , Li Xiaojie , Zhang Yan , Yin Tailang , Yang Pan
Published: September 2024

PFAS (per- and polyfluoroalkyl substances) have been extensively used across numerous industries and consumer goods. Due to their high persistence and mobility, they are ubiquitous in the environment. Exposure to PFAS occurs in people via multiple pathways such as dermal contact, water supply, air inhalation, and dietary intake. Even if some PFAS are being phased out because of their persistent presence in the environment and harmful impacts on human health, mixes of replacement and legacy PFAS will continue to pollute the ecosystem. Numerous toxicological investigations have revealed harmful effects of PFAS exposure on female reproductive health, e.g., polycystic ovaries syndrome, premature ovarian failure, endometriosis, reproductive system tumors, pregnancy complications, and adverse pregnancy outcomes. Despite extensive epidemiological studies on the reproductive toxicity of PFAS, research findings remain inconsistent, and the underlying mechanisms are not well understood. In this review, we give an in-depth description of the sources and pathways of PFAS, and then review the reproductive toxicity of PFAS and its possible mechanisms.
Global Perspectives on Mycotoxin Reference Materials (Part I): Insights from Multi-Supplier Comparison Study Including Aflatoxin B1, Deoxynivalenol and Zearalenone
Authors: Steiner David , Bartók Tibor , Sulyok Michael , Szekeres András , Varga Mónika , Horváth Levente , Rost Helmut
Published: September 2024

We conducted a comprehensive examination of liquid mycotoxin reference standards. A total of 30 different standards were tested, each containing 10 samples of three distinct substances: Aflatoxin B1, Deoxynivalenol, and Zearalenone. The standards were sourced from 10 different global market leading manufacturers. To facilitate comparison, all the standard sets were adjusted to the same concentration level. The standards were analyzed using the techniques LC-MS/MS, HPLC-DAD, and LC-HRMS to assess their quality attributes. Regarding the validation of the reference values, it was observed that 30% of the suppliers provided reference standards that were either below the lower acceptance limit or above the higher acceptance limit, confirmed by both the LC-MS/MS and HPLC-DAD methods. Furthermore, a total of 12 impurities were found in the DON standards, 10 in the AFB1 standards, and 8 in the ZON standards, distributed across all the suppliers. Therefore, this study suggests relevant adjustments to the ISO 17034 standard, proposing that the purity of a raw material should be uniformly based on q-NMR analysis, as most manufacturers state the purity of their certificates is determined using HPLC-UV or LC-MS/MS. Liquid standards with a shelf life of ≤1 year should not exceed an uncertainty of 3%. Standards that have a longer shelf life should not have more than 5% uncertainty. This study also emphasizes the importance of stability. The standards should undergo continuous long-term monitoring; otherwise, products may exhibit a target value of only 80%, as seen in one instance. It is also recommended to include proof of HPLC and LC-MS/MS analyses on the certificate of each released batch of a final product.
Transcriptomic Analysis Reveals Diverse Expression of Scorpion Toxin Genes in Mesobuthus martensii
Authors: Yang Zhongxian , Wang Haiquan , Zhao Yan , Huang Jianyu , Zhang Chao , Di Zhiyong
Published: September 2024

Scorpions, an ancient group of venomous invertebrates, have existed for over 430 million years. Their toxins, important for predation and defense, exhibit a variety of biological and pharmacological activities. Research on scorpion toxins has spanned decades. Notably, the toxin genes of Mesobuthus martensii (Scorpiones: Buthidae), a well-known Chinese herbal medicine, have been described at genomic and proteomic levels. However, previous studies primarily focused on the toxin genes expressed in the venom glands, overlooking their expression in multiple tissues. This study analyzed transcriptomes from 14 tissues of M. martensii. Gene annotation revealed 83 toxin and toxin-like genes, including those affecting sodium, potassium, calcium, and chloride ion channels. Approximately 70% of toxin genes were highly expressed in the vesicle; additionally, some exhibited low or no expression in the vesicle while showing high expression in other tissues. Beyond the vesicle, high expression levels of toxin genes were observed in metasoma segments II-V, blood, lateral eyes, chelicerae, legs, pedipalp chelae, femurs, and patellae. This expression pattern suggests that toxin genes are recruited from multiple tissues and may help prevent intraspecific harm during courtship and competition for prey. These findings inspire further research into the evolutionary recruitment process of scorpion toxins.
Exposure of Cattle Breeding Herds to Naturally Co-Contaminated Zearalenone and Deoxynivalenol: The Relevance of a Urinary Mycotoxin Monitoring System for Herd Health and Food Safety
Authors: Widodo Oky Setyo , Uno Seiichi , Kokushi Emiko , Yamato Osamu , Mardianto M. Fariz Fadillah , Shinya Urara , Kano Yuto , Kawashima Chiho , Fushimi Yasuo , Ono Tetsushi , Taniguchi Masayasu , Takagi Mitsuhiro
Published: September 2024

The widespread presence of Fusarium mycotoxins in animal feed is a global issue, not only for the health of livestock but also for ensure the safety of food as an end product. High concentrations of zearalenone (ZEN) and deoxynivalenol (DON) have been detected in the diets of Japanese Black (JB) and Holstein Friesian (HF) breeding herds. Consequently, we monitored serum biochemical parameters over a long time in both herds, focusing on anti-Müllerian hormone (AMH) levels and acute-phase inflammation. Additionally, urinary 8-hydroxy-2′-deoxyguanosine (8-OHdG) and progesterone levels were measured in the HF herd. The JB herd, a ZEN-dominant model with low DON contamination, demonstrated ZEN levels that exceeded the Japanese limit in the purchased total mixed rations (TMR). Conversely, the HF herd, which primary consumes DON-dominant feed with low ZEN contamination, had high DON levels in the dent corn silage. Specifically, the JB herd’s TMR contained 1.79 mg/kg ZEN and 0.58 mg/kg DON, whereas the HF herd’s silage had 15.3 mg/kg DON (dried sample) and 0.1 mg/kg ZEN. Enzyme-linked immunoassay were used to measure urinary ZEN-DON levels following confirmation through liquid chromatography-tandem mass spectrometry. Urinary ZEN-DON levels measured were significantly correlated (p < 0.05, r > 0.6) in both herds. In the HF herd, AMH levels increased (p = 0.01) and serum amyloid A (SAA) levels decreased (p = 0.02) when contaminated and at the end of the monitoring period. Additionally, urinary ZEN and DON levels were significantly correlated with SAA levels (ZEN: p = 0.00, r = 0.46; DON: p = 0.03, r = 0.33), with an increase in ZEN and DON levels resulting in higher SAA levels. The JB herd showed no significant differences. Additionally, in the HF herd, 8-OHdG/Cre levels increased significantly during major contamination periods (p < 0.05). Clinical data from the HF herd indicated an increase in mastitis cases and treatment rates during periods of major contamination. Abortion rates in the HF herd decreased from 22.9% (before monitoring) to 8.9% (during the high contamination period) and finally to 1% (at the end of the monitoring period), with corresponding increases in progesterone levels. ZEN-DON contamination adversely affects breeding cattle’s productivity, reproductive performance, and health. Therefore, monitoring urinary ZEN-DON is valuable for detecting contaminants and ensuring the safety of food products.
Multiplex Microscopy Assay for Assessment of Therapeutic and Serum Antibodies against Emerging Pathogens
Authors: Sartingen Nuno , Stürmer Vanessa , Kaltenböck Matthias , Müller Thorsten G. , Schnitzler Paul , Kreshuk Anna , Kräusslich Hans-Georg , Merle Uta , Mücksch Frauke , Müller Barbara , Pape Constantin , Laketa Vibor
Published: September 2024

The emergence of novel pathogens, exemplified recently by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), highlights the need for rapidly deployable and adaptable diagnostic assays to assess their impact on human health and guide public health responses in future pandemics. In this study, we developed an automated multiplex microscopy assay coupled with machine learning-based analysis for antibody detection. To achieve multiplexing and simultaneous detection of multiple viral antigens, we devised a barcoding strategy utilizing a panel of HeLa-based cell lines. Each cell line expressed a distinct viral antigen, along with a fluorescent protein exhibiting a unique subcellular localization pattern for cell classification. Our robust, cell segmentation and classification algorithm, combined with automated image acquisition, ensured compatibility with a high-throughput approach. As a proof of concept, we successfully applied this approach for quantitation of immunoreactivity against different variants of SARS-CoV-2 spike and nucleocapsid proteins in sera of patients or vaccinees, as well as for the study of selective reactivity of monoclonal antibodies. Importantly, our system can be rapidly adapted to accommodate other SARS-CoV-2 variants as well as any antigen of a newly emerging pathogen, thereby representing an important resource in the context of pandemic preparedness.
Increased Virulence of Culicoides Midge Cell-Derived Bluetongue Virus in IFNAR Mice
Authors: Drolet Barbara S. , Reister-Hendricks Lindsey , Mayo Christie , Rodgers Case , Molik David C. , McVey David Scott
Published: September 2024

Bluetongue (BT) is a Culicoides midge-borne hemorrhagic disease affecting cervids and ruminant livestock species, resulting in significant economic losses from animal production and trade restrictions. Experimental animal infections using the α/β interferon receptor knockout IFNAR mouse model and susceptible target species are critical for understanding viral pathogenesis, virulence, and evaluating vaccines. However, conducting experimental vector-borne transmission studies with the vector itself are logistically difficult and experimentally problematic. Therefore, experimental infections are induced by hypodermic injection with virus typically derived from baby hamster kidney (BHK) cells. Unfortunately, for many U.S. BTV serotypes, it is difficult to replicate the severity of the disease seen in natural, midge-transmitted infections by injecting BHK-derived virus into target host animals. Using the IFNAR BTV murine model, we compared the virulence of traditional BHK cell-derived BTV-17 with C. sonorensis midge (W8) cell-derived BTV-17 to determine whether using cells of the transmission vector would provide an in vitro virulence aspect of vector-transmitted virus. At both low and high doses, mice inoculated with W8-BTV-17 had an earlier onset of viremia, earlier onset and peak of clinical signs, and significantly higher mortality compared to mice inoculated with BHK-BTV-17. Our results suggest using a Culicoides W8 cell-derived inoculum may provide an in vitro vector-enhanced infection to more closely represent disease levels seen in natural midge-transmitted infections while avoiding the logistical and experimental complexity of working with live midges.
Evaluation of Vaccine Strategies among Healthcare Workers during COVID-19 Omicron Outbreak in Taiwan
Authors: Lin Min-Ru , Huang Chung-Guei , Chiu Cheng-Hsun , Chen Chih-Jung
Published: September 2024

Background/Objectives: This study aimed to assess the reactogenicity and immunogenicity of various SARS-CoV-2 vaccines and compare their protective effects against COVID-19 among healthcare workers (HCWs) during the Omicron outbreak in Taiwan. Methods: Conducted from March 2021 to July 2023, this prospective observational study included healthy HCWs without prior COVID-19 immunization. Participants chose between adenovirus-vectored (AstraZeneca), mRNA (Moderna, BioNTech-Pfizer), and protein-based (Medigen, Novavax) vaccines. Blood samples were taken at multiple points to measure neutralizing antibody (nAb) titers, and adverse events (AEs) were recorded via questionnaires. Results: Of 710 HCWs, 668 (94.1%) completed three doses, and 290 (40.8%) received a fourth dose during the Omicron outbreak. AEs were more common with AstraZeneca and Moderna vaccines, while Medigen caused fewer AEs. Initial nAb titers were highest with Moderna but waned over time regardless of the vaccine. Booster doses significantly increased nAb titers, with the highest levels observed in Moderna BA1 recipients. The fourth dose significantly reduced COVID-19 incidence, with Moderna BA1 being the most effective. Conclusions: Regular booster doses, especially with mRNA and adjuvant-protein vaccines, effectively enhance nAb levels and reduce infection rates, providing critical protection for frontline HCWs during variant outbreaks.
Machine Learning Algorithms for Water Quality Management Using Total Dissolved Solids (TDS) Data Analysis
Authors: Garcia Julio , Heo Joonghyeok , Kim Cheolhong
Published: September 2024

Our research project specifically focuses on evaluating groundwater quality in six West Texas counties. We aim to determine whether environmental changes have any impact on the levels of Total Dissolved Solids (TDS) in the water supplied to the public. To achieve this goal, we will be utilizing advanced machine learning algorithms to analyze TDS levels and create geospatial maps for each year between the 1990s and 2010s. To ensure the accuracy of our data, we have gathered information from two trusted sources: the Texas Water Development Board (TWDB) and the Groundwater Database (GWDB). We have analyzed the TDS and other elemental analyses from TWDB–GWDB lab reports and compared them with the quality cutoff set by the World Health Organization (WHO). Our approach involves a thorough examination of the data to identify any emerging patterns. The machine learning algorithm has been successfully trained and tested, producing highly accurate results that effectively predict water quality. Our results have been validated through extensive testing, highlighting the potential of machine learning approaches in the fields of environmental research. Overall, our findings will contribute to the development of more effective policies and regulations in predicting groundwater quality and improving water resource management in Texas. Therefore, this research provides important information for groundwater protection and the development of plans for water resource use in the future.
Assessment of Potential Aquifer Recharge Zones in the Locumba Basin, Arid Region of the Atacama Desert Using Integration of Two MCDM Methods: Fuzzy AHP and TOPSIS
Authors: Pocco Víctor , Mendoza Arleth , Chucuya Samuel , Franco-León Pablo , Huayna Germán , Ingol-Blanco Eusebio , Pino-Vargas Edwin
Published: September 2024

Natural aquifers used for human consumption are among the most important resources in the world. The Locumba basin faces significant challenges due to its limited water availability for the local population. In this way, the search for possible aquifer recharge zones is crucial work for urban development in areas that have water scarcity. To evaluate this problem, this research proposes the use of the hybrid Fuzzy AHP methodology in conjunction with the TOPSIS algorithm to obtain a potential aquifer recharge map. Ten factors that influence productivity and capacity in an aquifer were implemented, which were subjected to Fuzzy AHP to obtain their weighting. Using the TOPSIS algorithm, the delineation of the most favorable areas with high recharge potential was established. The result shows that the most influential factors for recharge are precipitation, permeability, and slopes, which obtained the highest weights of 0.22, 0.19, and 0.17, respectively. In parallel, the TOPSIS result highlights the potential recharge zones distributed in the Locumba basin, which were classified into five categories: very high (13%), high (28%), moderate (15%), low (28%), and very low (16%). The adapted methodology in this research seeks to be the first step toward effective water resource management in the study area.
The Impact of Catastrophic Floods on Macroinvertebrate Communities in Low-Order Streams: A Study from the Apennines (Northwest Italy)
Authors: Marino Anna , Fenoglio Stefano , Bo Tiziano
Published: September 2024

Floods are normal components of many river regimes and, as such, they exert a significant influence at the ecosystem level. In recent decades, however, climate change has increased the frequency and intensity of floods, with serious consequences for lotic biota, particularly benthic macroinvertebrates, due to their limited mobility and sensitivity to disturbance. The impact of floods varies according to different biological parameters including the characteristics of the macrobenthic communities (taxonomic composition, morphology, behaviour, and life history traits) on one hand and various nonbiological parameters such as flood intensity, artificialisation of the river bed, the presence of dams, and many other factors on the other. Understanding these dynamics is pivotal to improve the effective management and conservation of aquatic ecosystems in the context of current climate change. The aim of this short communication is to evaluate the impact of a catastrophic flood on the macroinvertebrate community of a low-order Appennine stream (NW Italy). This will provide data regarding the varying impacts on different taxa and the recovery pattern of this significant component of the ecosystem.
Characterization of Wastewater in an Activated Sludge Treatment Plant of the Food Sector
Authors: Yáñez-Hernández Oscar , Ríos-Lira Armando Javier , Pantoja-Pacheco Yaquelin Verenice , Ruelas-Santoyo Edgar Augusto , Asato-España Martha Laura , Valdovinos-García Esveidi Montserrat
Published: September 2024

Recently, water has become a resource that generates controversy due to shortage alarms and high consumption by production companies. Making good use of water has become the main objective of government institutions. The food industry generates a large amount of wastewater, concentrating the largest number of contaminants originated in its processes. Wastewater from the food industry is characterized by having a large amount of organic matter, especially fats and oils, as well as suspended solids. The objective of this research is to carry out a characterization of effluents generated in a wastewater treatment plant in the food sector based on Mexican and international regulations to determine whether it is reusable. This article addresses Mexico’s lag in the reuse of treated wastewater in the face of the water crisis, highlighting the urgency of adopting these practices to mitigate water scarcity. For the development of this investigation, samples were collected at the discharge point produced by the company’s effluents, followed by an evaluation of their physical, chemical, and biological parameters, and finally, it was determined that the effluent follows the regulatory standards for discharge into the city sewer but outside the range for reuse in productive processes or irrigation of green areas.
Energy Management Strategies for Hybrid Electric Vehicles: A Technology Roadmap
Authors: Mittal Vikram , Shah Rajesh
Published: September 2024

Hybrid electric vehicles (HEVs) are set to play a critical role in the future of the automotive industry. To operate efficiently, HEVs require a robust energy management strategy (EMS) that decides whether the vehicle is powered by the engine or electric motors while managing the battery’s state of charge. The EMS must rapidly adapt to driver demands and optimize energy usage, ideally predicting battery charge rates and fuel consumption to adjust the powertrain in real time, even under unpredictable driving conditions. As HEVs become more prevalent, EMS technologies will advance to improve predictive capabilities. This analysis provides an overview of current EMS systems, including both rule-based and optimization-based approaches. It explores the evolution of EMS development through a technology roadmap, highlighting the integration of advanced algorithms such as reinforcement learning and deep learning. The analysis addresses the technologies that underly this evolution, including machine learning, cloud computing, computer vision, and swarm technology. Key advances and challenges in these technologies are discussed, along with their implications for the next generation of EMS systems for HEVs. The analysis of these technologies indicates that they will play a key role in the evolution of EMS technology, allowing it to better optimize driver needs and fuel economy.