bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving the Oxidation Resistance of Phenolic Resin Pyrolytic Carbons by In Situ Catalytic Formation of Carbon Nanofibers via Copper Nitrate
Authors: Wu Zhi , Jiang Pengcheng , Pang Hongxing , Cheng Guanghai , Li Jiajun , Liu Hao , Ma Yan , Dong Yunjie , Wang Zhoufu
Published: July 2024

Phenolic resin pyrolytic carbons were obtained by catalytic pyrolysis of phenolic resin at 500 °C, 600 °C, 700 °C, and 800 °C for 3 h in an argon atmosphere using copper nitrate as a catalyst precursor. The effects of copper salts on the pyrolysis process of phenolic resin as well as the structural evolution and oxidation resistance of phenolic resin pyrolytic carbons were studied. The results showed that copper oxide (CuO) generated from the thermal decomposition of copper nitrate was reduced to copper (Cu) by the gas generated from the thermal decomposition of the phenolic resin. Carbon nanofibers with tapered structures were synthesized by Cu catalysis of pyrolysis gas at 500–800 °C. The catalytic pyrolysis of phenolic resin with Cu increased the graphitization degree and reduced the pore volume of the phenolic resin pyrolytic carbons. The combined action improved the oxidation resistance of phenolic resin pyrolytic carbons.
Insight into Role of Arc Torch Angle on Wire Arc Additive Manufacturing Characteristics of ZL205A Aluminum Alloy
Authors: Wang Bingqiu , Li Ruihan , Zhou Xiaohui , Liu Fuyun , Wei Lianfeng , Tian Lei , Song Xiaoguo , Tan Caiwang
Published: July 2024

The arc torch angle greatly affected the deposition characteristics in the wire arc additive manufacturing (WAAM) process, and the relation between the droplet transition behavior and macrostructure morphology was unclear. This work researched the effect of torch angle on the formation accuracy, droplet transition behavior and the mechanical properties in the WAAM process on a ZL205A aluminum alloy. The results suggested that at the obtuse torch angle, part of the energy input was used to heat the existing molten pool, which was optimized for the longer solidification period of the molten pool. Therefore, the greater layer penetration depth at 100° resulted in the improved layer-by-layer combination ability. The obtuse torch angle was associated with the better formation accuracy on the sidewall surface due to the smaller impact on the molten pool, which was influenced by both the arc pressure and droplet impact force. The eliminated pores were optimized for the mechanical properties of depositions at a torch angle of 100°; thus, the tensile strength and elongation attained maximum values of 258.6 MPa and 17.1%, respectively. These aspects made WAAM an attractive mode for manufacturing large structural components on ZL205A aluminum alloy.
Data-Driven Batch Process Monitoring for Continuous Annealing of Cold-Rolled Strip Steel
Authors: Zhou Yujie , He Fei , Zhang Yutao , Zhou Hang
Published: July 2024

The continuous annealing process (CAP) is a crucial process of steel production, which has a significant impact on the uniformity and stability of mechanical properties. A novel batch monitoring process based on kernel dissimilarity (KDISSIM) and Kmeans++ is proposed in this paper, focusing on problems such as unequal sample lengths between batches and nonlinearity between variables. First, KDISSIM is used to describe the dissimilarity between batches. Secondly, Kmeans++ is employed to improve the accuracy of clustering tasks based on historical batches. The largest cluster is considered to be at a relatively stable control level, and these batches are further used as training data. Then, the center batch and boundary batch of the training set are used as the reference batch and monitoring threshold for the monitoring model, respectively. Finally, the effectiveness of the proposed method is verified via the actual CAP data, providing a feasible solution for CAP batch monitoring.
Multi-Physics Simulation and Optimization of Jet Electrodeposition for Ni–Diamond Composite Coatings
Authors: Wang Xiaoli , Chou Chau-Chang , Zhou Xin , Bao Xin , Zhang Qian
Published: July 2024

This work investigated the influence of current density, plating solution flow rate, and nozzle outlet-to-cathode distance on the properties of Ni–diamond composite coatings. A multi-physics field simulation was employed to analyze the interplay between current density, plating solution flow rate, and nozzle outlet-to-cathode distance on the flow field and electric field distribution. Additionally, particle tracing simulations were incorporated into the model to evaluate the incorporation efficiency of diamond particles during composite electrodeposition. It was found that when the inlet flow rate of the electrolyte was 5 L/min, the distance between the nozzle outlet and the cathode was 3 mm, and the current density was 60 A/dm2, the composite electrodeposited coating had a higher particle content and better uniformity. The simulation results were validated through experimental preparation and performance testing. This combined approach provides valuable insights for optimizing the jet electrodeposition process for Ni–diamond composite coatings with superior properties.
Development and Evaluation of the Reliability of a Semi-Quantitative Food Frequency Questionnaire to Assess the Intake in the Serbian Population
Authors: Garcia Silvia , Vidović Bojana , Tijerina Alexandra , Tur Josep A. , Bouzas Cristina
Published: July 2024

Assessing dietary habits with validated questionnaires is crucial for achieving reliable results in health research. The aim of this study was the development and validation of a semi-quantitative food frequency questionnaire (FFQ) in an 18–30-year-old Serbian population. A total of 93 participants completed the FFQ and three 24 h dietary recalls (24 hR). Pearson and intraclass correlations between FFQ and 24 hR intakes were assessed and were de-attenuated and energy-adjusted. Bland–Altman plots were generated, and quintiles of energy, water, fiber, and macronutrient intake were analyzed with contingency tables. Adjustments for sex differences were included. The validity of the FFQ varied, with significant correlations for energy, carbohydrates, cholesterol, and vitamin B12, vitamin C and vitamin D. Misclassification rates were generally low. Bland–Altman plots indicated good agreement between methods. It can be concluded that the validated FFQ is a promising tool for dietary assessment in the Serbian population. Results for several nutrients align closely with previous studies. The new FFQ is a useful tool for dietary assessment in the Serbian population.
Non-Pharmacological Treatment for Cardiovascular Risk Prevention in Children and Adolescents with Obesity
Authors: Genovesi Simonetta , Vania Andrea , Caroli Margherita , Orlando Antonina , Lieti Giulia , Parati Gianfranco , Giussani Marco
Published: July 2024

In younger generations, excess weight has reached very alarming levels. Excess weight in adults is associated with increased mortality and morbidity from cardiovascular disease. However, it is not easy to distinguish to what extent these effects are the result of obesity itself or how much is due to the various cardiovascular risk factors that often accompany excess weight. Several risk factors, such as hypertension, dyslipidemia, hyperuricemia, glucose intolerance, and type 2 diabetes mellitus, are already present in pediatric age. Therefore, early intervention with the goal of correcting and/or eliminating them is particularly important. In the child and adolescent with obesity, the first approach to achieve weight reduction and correct the risk factors associated with severe excess weight should always be non-pharmacologic and based on changing poor eating habits and unhealthy lifestyles. The purpose of this review is to give an update on non-pharmacological interventions to be implemented for cardiovascular prevention in children and adolescents with obesity, and their effectiveness. In particular, interventions targeting each individual cardiovascular risk factor will be discussed.
Insights into Peptidyl-Prolyl cis-trans Isomerases from Clinically Important Protozoans: From Structure to Potential Biotechnological Applications
Authors: Aranda-Chan Verónica , Cárdenas-Guerra Rosa Elena , Otero-Pedraza Alejandro , Pacindo-Cabrales Esdras Enoc , Flores-Pucheta Claudia Ivonne , Montes-Flores Octavio , Arroyo Rossana , Ortega-López Jaime
Published: July 2024

Peptidyl-prolyl cis/trans isomerases (PPIases) are present in a wide variety of microorganisms, including protozoan parasites such as Trypanosoma cruzi, Trypanosoma brucei, Trichomonas vaginalis, Leishmania major, Leishmania donovani, Plasmodium falciparum, Plasmodium vivax, Entamoeba histolytica, Giardia intestinalis, Cryptosporidium parvum, and Cryptosporidium hominis, all of which cause important neglected diseases. PPIases are classified as cyclophilins, FKBPs, or parvulins and play crucial roles in catalyzing the cis-trans isomerization of the peptide bond preceding a proline residue. This activity assists in correct protein folding. However, experimentally, the biological structure–function characterization of PPIases from these protozoan parasites has been poorly addressed. The recombinant production of these enzymes is highly relevant for this ongoing research. Thus, this review explores the structural diversity, functions, recombinant production, activity, and inhibition of protozoan PPIases. We also highlight their potential as biotechnological tools for the in vitro refolding of other recombinant proteins from these parasites. These applications are invaluable for the development of diagnostic and therapeutic tools.
Hypermucoviscous Multidrug-Resistant Klebsiella variicola Strain LL2208 Isolated from Chinese Longsnout Catfish (Leiocassis longirostris): Highly Similar to Human K. variicola Strains
Authors: Li Qingyong , Yu Xin , Ye Lin , Hou Tongyu , Liu Yi , Liu Guiming , Wang Qing , Zhang Defeng
Published: July 2024

Outbreaks of bacterial diseases occur in farmed Chinese longsnout catfish (Leiocassis longirostris). Due to limited information on aquatic Klebsiella variicola-infected animals, this study aimed to identify strain LL2208 isolated from diseased L. longirostris, determine its biological features, and evaluate its risk to public health. Strain LL2208 was tested for molecular identification, challenge, string, biofilm formation, and antimicrobial susceptibility. Furthermore, the whole genome of the strain was sequenced and analyzed. Based on molecular identification, strain LL2208 was identified as K. variicola. Artificial infection showed that this strain was moderately virulent to L. longirostris with an LD50 = 7.92 × 107 CFU/mL. Antibiotic sensitivity tests showed that this strain was resistant to penicillins, macrolides, aminoglycosides, amphenicols, glycopeptides, and lincosamide, indicating multidrug resistance. Strain LL2208 has a genome size of 5,557,050 bp, with a GC content of 57.38%, harboring 30 antimicrobial resistance genes and numerous virulence-related genes. Its molecular type was ST595-KL16-O5. Collinearity analysis showed that strain LL2208 was highly similar to the human-derived K. variicola strain. In conclusion, the multidrug-resistant and virulent K. variicola strain LL2208 was isolated from fish and may have originated from humans. These results provide a foundation for further studies on the transmission of K. variicola between humans and aquatic animals.
Misuse, Abuse and Medication Errors’ Adverse Events Associated with Opioids—A Systematic Review
Authors: Gustafsson Moa , Silva Vítor , Valeiro Carolina , Joaquim João , van Hunsel Florence , Matos Cristiano
Published: July 2024

Opioids are the strongest analgesics available and are crucial in the treatment of acute and chronic pain. The line between these critical medications and how they are used beyond standard therapeutics in cases such as abuse, misuse, and medication errors needs to be understood, as it affects their safety, efficacy, and manner of use. The aim of this systematic review was to identify what is known about the adverse events resulting from the abuse, misuse, and medication errors associated with opioid use. A systematic search was conducted in the PubMed®, Scopus® and, EBSCO® databases to retrieve studies from the inception to December 2023 reporting abuse, misuse, and medication errors associated with medicinal opioid use. Two authors independently screened titles and abstracts and full text according to eligibility using Covidence® software. Full articles were examined by two independent reviewers, and disagreements were resolved by a third reviewer. The risk of bias was assessed by the JBI’s critical appraisal tools. A total of 934 articles were screened by their title and abstract. Then, 151 articles were selected for full text screening. Of these, 34 studies were eligible for inclusion in this review. The included studies varied significantly in their population sizes, ranging from 9 individuals to 298,433 patients, and encompassed a diverse demographic, including all ages and both sexes. The studies consistently reported a range of adverse events associated with opioid use. Fentanyl, morphine, oxycodone, tramadol, and hydrocodone were frequently implicated. The data heterogeneity in this field resulted in challenges in drawing conclusions. The review highlights that some opioids, particularly fentanyl, morphine, and oxycodone, are frequently associated with preventable adverse drug reactions, abuse, and medication errors, underscoring the need for robust preventative measures and ongoing research to mitigate opioid-related harm.
Mitigation of Suppressive Interference in AMPC SAR Based on Digital Beamforming
Authors: Xiao Zhipeng , He Feng , Sun Zaoyu , Zhang Zehua
Published: July 2024

Multichannel Synthetic Aperture Radar (MC-SAR) systems, such as Azimuth Multi-Phase Centre (AMPC) SAR, provide an effective solution for achieving high-resolution wide-swath (HRWS) imaging by reducing the pulse repetition frequency (PRF) to increase the swath width. However, in an Electronic Countermeasures (ECM) environment, the image quality of multichannel SAR systems can be significantly degraded by electromagnetic interference. Previous research into interference and counter-interference techniques has predominantly focused on single-channel SAR systems, with relatively few studies addressing the specific challenges faced by MC-SAR systems. This paper uses the classical spatial filtering technique of adaptive digital beamforming (DBF). Considering the Doppler ambiguity present in the echoes, two schemes—Interference Reconstruction And Cancellation (IRC) and Channel Grouping Nulling (CGN)—are designed to effectively eliminate suppressive interference. The IRC method eliminates the effects of interference without losing spatial degrees of freedom, ensuring effective suppression of Doppler ambiguity in subsequent processing. This method shows significant advantages under conditions of strong Doppler ambiguity and low jammer-to-signal ratio. Conversely, the CGN method mitigates the effect of interference on multichannel imaging at the expense of degrees of freedom redundant to Doppler ambiguity suppression. It shows remarkable interference suppression performance under weak-Doppler-ambiguity conditions, allowing for better image recovery. Simulations performed on point and distributed targets have validated that the proposed methods can effectively remove interfering signals and achieve high-resolution wide-swath (HRWS) SAR images.
SimNFND: A Forward-Looking Sonar Denoising Model Trained on Simulated Noise-Free and Noisy Data
Authors: Yang Taihong , Zhang Tao , Yao Yiqing
Published: July 2024

Given the propagation characteristics of sound waves and the complexity of the underwater environment, denoising forward-looking sonar image data presents a formidable challenge. Existing studies often add noise to sonar images and then explore methods for its removal. This approach neglects the inherent complex noise in sonar images, resulting in inaccurate evaluations of traditional denoising methods and poor learning of noise characteristics by deep learning models. To address the lack of high-quality data for FLS denoising model training, we propose a simulation algorithm for forward-looking sonar data based on RGBD data. By utilizing rendering techniques and noise simulation algorithms, high-quality noise-free and noisy sonar data can be rapidly generated from existing RGBD data. Based on these data, we optimize the loss function and training process of the FLS denoising model, achieving significant improvements in noise removal and feature preservation compared to other methods. Finally, this paper performs both qualitative and quantitative analyses of the algorithm’s performance using real and simulated sonar data. Compared to the latest FLS denoising models based on traditional methods and deep learning techniques, our method demonstrates significant advantages in denoising capability. All inference results for the Marine Debris Dataset (MDD) have been made open source, facilitating subsequent research and comparison.
A Lightweight CNN Based on Axial Depthwise Convolution and Hybrid Attention for Remote Sensing Image Dehazing
Authors: He Yufeng , Li Cuili , Li Xu , Bai Tiecheng
Published: July 2024

Hazy weather reduces contrast, narrows the dynamic range, and blurs the details of the remote sensing image. Additionally, color fidelity deteriorates, causing color shifts and image distortion, thereby impairing the utility of remote sensing data. In this paper, we propose a lightweight remote sensing-image-dehazing network, named LRSDN. The network comprises two tailored, lightweight modules arranged in cascade. The first module, the axial depthwise convolution and residual learning block (ADRB), is for feature extraction, efficiently expanding the convolutional receptive field with little computational overhead. The second is a feature-calibration module based on the hybrid attention block (HAB), which integrates a simplified, yet effective channel attention module and a pixel attention module embedded with an observational prior. This joint attention mechanism effectively enhances the representation of haze features. Furthermore, we introduce a novel method for remote sensing hazy image synthesis using Perlin noise, facilitating the creation of a large-scale, fine-grained remote sensing haze image dataset (RSHD). Finally, we conduct both quantitative and qualitative comparison experiments on multiple publicly available datasets. The results demonstrate that the LRSDN algorithm achieves superior dehazing performance with fewer than 0.1M parameters. We also validate the positive effects of the LRSDN in road extraction and land cover classification applications.
AI Optimization-Based Heterogeneous Approach for Green Next-Generation Communication Systems
Authors: Khaled Haitham , Alkhazraji Emad
Published: July 2024

Traditional heterogeneous networks (HetNets) are constrained by their hardware design and configuration. These HetNets have a limited ability to adapt to variations in network dynamics. Software-defined radio technology has the potential to address this adaptability issue. In this paper, we introduce a software-defined radio (SDR)-based long-term evolution licensed assisted access (LTE-LAA) architecture for next-generation communication networks. We show that with proper design and tuning of the proposed architecture, high-level adaptability in HetNets becomes feasible with a higher throughput and lower power consumption. Firstly, maximizing the throughput and minimizing power consumption are formulated as a constrained optimization problem. Then, the obtained solution, alongside a heuristic solution, is compared against the solutions to existing approaches, showing our proposed strategy is drastically superior in terms of both power efficiency and system throughput. This study is then concluded by employing artificial intelligence techniques in multi-objective optimization, namely random forest regression, particle swarm, and genetic algorithms, to balance out the trade-offs between maximizing the throughput and power efficiency and minimizing energy consumption. These investigations demonstrate the potential of employing the proposed LTE-LAA architecture in addressing the requirements of next-generation HetNets in terms of power, throughput, and green scalability.
A Combined Data-Driven and Model-Based Algorithm for Accurate Battery Thermal Runaway Warning
Authors: Chen Qingyang , He Yinghui , Fang Nengjie , Yu Guanding
Published: July 2024

With the increasingly widespread application of large-scale energy storage battery systems, the demand for battery safety is rising. Research on how to detect battery anomalies early and reduce the occurrence of thermal runaway (TR) accidents has become particularly important. Existing research on battery TR warning algorithms can be mainly divided into two categories: model-driven and data-driven methods. However, the common model-driven methods are often of high complexity, with poor versatility and low early warning capability; and the common data-driven methods are mostly based on neural networks, requiring substantial training costs, with better early warning capabilities but higher false alarm probabilities. To address the limitations of existing works, this paper proposes a combined data-driven and model-based algorithm for accurate battery TR warnings. Specifically, the K-Means algorithm serves as the data-driven module, capturing outliers in battery data, and the Bernardi equation serves as the model-driven module used to evaluate battery temperature. Ultimately, the outputs of the weighted model-driven module and data-driven module are combined to comprehensively assess whether the battery is abnormal. The proposed algorithm combines the advantages of model-driven and data-driven approaches, achieving a 25 min advance warning for thermal runaway, with a significantly reduced probability of false alarms.
Analysis of Variance Combined with Optimized Gradient Boosting Machines for Enhanced Load Recognition in Home Energy Management Systems
Authors: Cabral Thales W. , Neto Fernando B. , de Lima Eduardo R. , Fraidenraich Gustavo , Meloni Luís G. P.
Published: July 2024

Load recognition remains not comprehensively explored in Home Energy Management Systems (HEMSs). There are gaps in current approaches to load recognition, such as enhancing appliance identification and increasing the overall performance of the load-recognition system through more robust models. To address this issue, we propose a novel approach based on the Analysis of Variance (ANOVA) F-test combined with SelectKBest and gradient-boosting machines (GBMs) for load recognition. The proposed approach improves the feature selection and consequently aids inter-class separability. Further, we optimized GBM models, such as the histogram-based gradient-boosting machine (HistGBM), light gradient-boosting machine (LightGBM), and XGBoost (extreme gradient boosting), to create a more reliable load-recognition system. Our findings reveal that the ANOVA–GBM approach achieves greater efficiency in training time, even when compared to Principal Component Analysis (PCA) and a higher number of features. ANOVA–XGBoost is approximately 4.31 times faster than PCA–XGBoost, ANOVA–LightGBM is about 5.15 times faster than PCA–LightGBM, and ANOVA–HistGBM is 2.27 times faster than PCA–HistGBM. The general performance results expose the impact on the overall performance of the load-recognition system. Some of the key results show that the ANOVA–LightGBM pair reached 96.42% accuracy, 96.27% F1, and a Kappa index of 0.9404; the ANOVA–HistGBM combination achieved 96.64% accuracy, 96.48% F1, and a Kappa index of 0.9434; and the ANOVA–XGBoost pair attained 96.75% accuracy, 96.64% F1, and a Kappa index of 0.9452; such findings overcome rival methods from the literature. In addition, the accuracy gain of the proposed approach is prominent when compared straight to its competitors. The higher accuracy gains were 13.09, 13.31, and 13.42 percentage points (pp) for the pairs ANOVA–LightGBM, ANOVA–HistGBM, and ANOVA–XGBoost, respectively. These significant improvements highlight the effectiveness and refinement of the proposed approach.
Performance Analysis of Lake Water Cooling Coupled with a Waste Heat Recovery System in the Data Center
Authors: Yin Peng , Guo Yang , Zhang Man , Wang Jiaqiang , Zhang Linfeng , Feng Da , Ding Weike
Published: July 2024

Data centers (DCs) require continuous cooling throughout the year and produce a large amount of low-grade waste heat. Free cooling and waste heat recovery techniques are promising approaches to reduce DC energy consumption. Although previous studies have explored diverse waste heat utilization strategies, there is a significant gap in combining waste heat recovery with lake water cooling in DCs. Therefore, this study proposed a system integrating lake water cooling with waste heat recovery for DCs. To evaluate the energy-saving performance of the suggested system, the influence of waste heat recovery locations and volumes has been investigated. An analysis of the improvement in system parameters is also conducted. The study’s findings highlight that targeted recovery of waste heat from sources like chilled water or air in server rooms can significantly reduce the cooling energy demand of the system. The results show that recovering heat from the return air of IT equipment can yield a remarkable power usage effectiveness (PUE) and coefficient of performance (COP) of 1.19 and 10.17, and the energy consumption of the cooling system is reduced to 10.06%. Moreover, the outcomes reveal the potential for substantial energy savings of up to 26.05% within the proposed system by setting the chilled water and air supply temperatures to 16 and 20 °C, respectively.
Optimization Design Methods for Thermal Environment Problems in Chinese University Teaching Buildings at Various Periods
Authors: Fan Liping , Yang Xiyue , Han Xiao , Liu Qibo
Published: July 2024

Chinese universities have gone through three periods of centralized construction and significant differences in the design of teaching buildings in different periods may cause various thermal environment problems. This study takes a city in a cold region in northern China as an example and selects three teaching buildings built during three concentrated construction periods: 1950s to 1960s, 1980s to 1990s, and early 21st century as common cases. Based on field research, thermal environment measurement, APMV and PMV-PPD evaluation, and DeST simulation methods, it was found that the average summer APMV of the three teaching buildings was 1.37, indicating poor thermal comfort. In winter, the ambient temperature of the classrooms was below 18 °C for about 30% to 40% of the whole year, the average PMV value was −2.36, and the PPD value was obtained as 83.28%, far exceeding the standard requirements. The obtained results form a design strategy to optimize the thermal environment of teaching buildings. By considering the teaching building of historical architecture from the 1950s to 1960s as an example, the optimization design was carried out from three aspects to improve the indoor thermal environment and reduce the building’s cooling and heating load. The cumulative load of the building throughout the year was reduced by 21%, the cumulative heat load was reduced by 28.3%, and the cumulative cooling load was reduced by 10.1%. This research is anticipated to be of great reference significance for enhancing the thermal comfort of existing buildings, promoting energy conservation, and reducing carbon emissions. At the same time, it contributes to the protection and optimal use of historical buildings.
Indoor Environmental Quality and Effectiveness of Portable Air Cleaners in Reducing Levels of Airborne Particles during Schools’ Reopening in the COVID-19 Pandemic
Authors: Villanueva Florentina , Felgueiras Fátima , Notario Alberto , Cabañas Beatriz , Gabriel Marta Fonseca
Published: July 2024

Educational buildings tend to fail in the contagion containment of airborne infectious diseases because of the high number of children, for several hours a day, inside enclosed environments that often have inadequate indoor air quality (IAQ) conditions. This study aimed to assess indoor environmental quality and test the effectiveness of portable air cleaners (PACs) in alleviating airborne particle levels in schools of Central–Southern Spain during the period of reopening after the lockdown due to the COVID-19 outbreak. To accomplish this, three sampling campaigns were organized from September to December 2020 to consistently monitor temperature and relative humidity, carbon dioxide, and particulate matter in nineteen classrooms (seven school buildings). Results showed that although the recommendation of maintaining the windows open throughout the day seemed to be effective in promoting, in general, proper ventilation conditions (based on CO2 levels). For the colder campaigns, this practice caused notorious thermal comfort impairment. In addition, a great number of the surveyed classrooms presented levels of PM2.5 and PM10, attributable to outdoor and indoor sources, which exceeded the current WHO guideline values. Moreover, considering the practice of having the windows opened, the installation of 1 unit of PACs per classroom was insufficient to ensure a reduction in particle concentration to safe levels. Importantly, it was also found that children of different ages at different education levels can be exposed to significantly different environmental conditions in their classrooms; thus, the corrective measures to employ in each individual educational setting should reflect the features and needs of the target space/building.
Evolution and Projection of Carbon Storage in Important Ecological Functional Areas of the Minjiang River Basin, 1985–2050
Authors: Huang Xiaobin , Liu Xiaosheng , Chen Youliang , Jin Yuanhang , Gao Xue , Abbasi Raihana
Published: July 2024

The alteration of land use and cover (LULC) and the landscape ecological risk index (LERI) significantly impact carbon storage. Examining the carbon storage services in ecologically significant places is crucial for achieving a harmonious relationship between economic development in the region, conservation of terrestrial ecosystems, and mitigation of carbon sink depletion. This study aims to provide a complete framework that integrates the PLUS, Fragstats, and InVEST models. This framework will be utilized to optimize LULC and LERI, specifically maximizing carbon storage. The analysis will be carried out over an extended duration and from various viewpoints. The results indicate that the MJRB ecosystem experienced three clearly defined phases: enhancement (1985–1995), degradation (1995–2010), and subsequent enhancement (2010–2020). The LERI of high-level and carbon storage patterns showed similar trends. The degradation of local terrestrial ecosystems can primarily be due to the widespread use of ecological land caused by socio-economic development. The Ecological Preservation Scenario is projected to increase 41.97 Tg and 115.18 Tg in carbon storage. In contrast, the urban development scenario showed a substantial decrease in carbon storage rates, namely 0.89% and 1.34%, primarily evident in the Chengdu urban zone. An analysis of coupling coordination revealed a negative relationship between carbon storage and high LERI, while a positive connection was observed with low LERI. This study established a framework for rapidly assessing and forecasting the trajectory of carbon storage. It aids in optimizing land use patterns, conserving areas with high carbon sequestration, and ensuring the establishment of high-quality ecosystems. This study serves as a guide for achieving regional “dual carbon” objectives.
The Use of Agricultural Databases for Crop Modeling: A Scoping Review
Authors: Mthembu Thando Lwandile , Kunz Richard , Gokool Shaeden , Mabhaudhi Tafadzwanashe
Published: July 2024

There is growing interest in promoting neglected and underutilized crop species to enhance agrobiodiversity and contribute to food systems transformation under climate change. A lack of available measured data has hindered the mainstreaming of these crops and limited the ability of agricultural databases to be used for calibrating and validating crop models. This study conducts a systematic scoping review and bibliometric analysis to assess the use of agricultural databases for crop modeling. The Biblioshiny App v4.1.2 and VOSviewer software v1.6.20 were used to analyze 51 peer-reviewed articles from Scopus and Web of Science. Key findings from this review were that agricultural databases have been used for estimating crop yield, assessing soil conditions, and fertilizer management and are invaluable for developing decision support tools. The main challenges include the need for high-quality datasets for developing agricultural databases and more expertise and financial resources to develop and apply crop and machine learning models. From the bibliometric dataset, only one study used modeled data to develop a crop database despite such data having a level of uncertainty. This presents an opportunity for future research to improve models to minimize their uncertainty level and provide reliable data for crop database development.
Assessing Spatial–Temporal Characteristics of Land Desertification from 1990 to 2020 in the Heihe River Basin Using Landsat Series Imagery
Authors: Liao Jie , Yang Xianzhong , Ye Qiyan , Wan Kaiming , Sheng Jixing , Zhang Shengyin , Song Xiang
Published: July 2024

Monitoring the status and dynamics of desertification is one of the most important parts of combating it. In this study, 30 m high-resolution information on land desertification and restoration in the Heihe River basin (HRB) was extracted from the land cover database. The results indicate that land desertification coexists with land restoration in the HRB. In different periods, the area of land restoration was much larger than the area of land desertification in the HRB, and the HRB has undergone land restoration. Upstream of the HRB, there is a continuing trend of increasing land desertification associated with overgrazing in a context where climate change favors desertification reversal. In the middle and lower reaches, although climate variability and human activities favor land desertification, land desertification is still being reversed, and land restoration dominates. Implementing the eco-environmental protection project and desertification control measures, especially the Ecological Water Distribution Project (EWDP), contributes to the reversal of desertification in the middle and lower reaches of the HRB. However, the EWDP has indirectly led to the lowering of the water table in the middle reaches, resulting in local vegetation degradation. Therefore, there is an urgent need to transform the economic structure of the middle reaches to cope with water scarcity and land desertification.
Sustainable Building Construction Materials in the United Arab Emirates: A Review
Authors: Sadar Din Khalid Mehmood , Ishak Md Sayuti
Published: July 2024

The construction industry, a major player in economic development, is facing increased pressure to address sustainability concerns amidst rapid population growth and urbanization. With global projections indicating a significant rise in building demand by 2050, sustainability has emerged as a crucial focus area and paradigm shift to enhance environmental friendliness, quality, and project outcomes. The UAE, renowned for its vibrant construction industry, offers a unique context for examining the integration of sustainable practices. The use of sustainable construction practices is growing in the UAE, where the built environment plays a key role in economic growth and environmental stewardship. The United Arab Emirates (UAE) aims to foster long-term sustainability while enhancing the standard of living for current and future generations by integrating social, environmental, and economic aspects within construction projects, while also reevaluating conventional sustainable development frameworks and embracing a triple bottom line approach. This research was conducted to explore sustainable construction material usage and evaluation in the United Arab Emirates. The literature was reviewed for sustainable building construction materials across the UAE in the SCOPUS index from 2014 to 2024, as well as the regional regulations concerning the subject. This study evaluated the increasing trend of sustainable construction material research works, as well as the sound regional parameters of sustainable construction materials implemented across the country. Through an exploration of the significance of sustainable construction materials, this research underscores the multifaceted benefits of locally sourced, recyclable, and renewable materials in reducing environmental impacts, fostering economic and social well-being, and improving overall project performance and project management practices. The construction sector’s role in economic development and its substantial environmental impact are discussed in alignment with sustainable construction materials, sustainable construction practices, and the need to enhance environmental sustainability and create healthier built environments. In the realm of sustainable construction materials, project management knowledge areas encompass a range of factors. These include the properties of materials sourced regionally; the incorporation of recycled content; considerations for indoor air quality, energy, and water efficiency parameters; and how these properties relate to project scopes, scheduling constraints, and challenges. Additionally, the availability of resources and competency levels, quality control standards, specifications, communication strategies, and stakeholder involvement play crucial roles. It is important to assess both the positive and negative risks associated with these elements across construction projects.
Variability in Paralytic Shellfish Toxin Profiles and Dinoflagellate Diversity in Mussels and Seawater Collected during Spring in Korean Coastal Seawater
Authors: Choi Dong Han , Yang Wonseok , Kim Young-Eun , Park Bum Soo , Sung Jiyeon , Choi Jaeho , Rho Jung-Rae , Han Young Seok , Lee Yeonjung
Published: July 2024

Paralytic shellfish toxins (PSTs) are potent neurotoxins produced by certain microalgae, particularly dinoflagellates, and they can accumulate in shellfish in coastal seawater and thus pose significant health risks to humans. To explore the relationship between toxicity and PST profiles in seawater and mussels, the spatiotemporal variations in PST concentrations and profiles were investigated along the southern coast of Korea under peak PST levels during spring. Seawater and mussel samples were collected biweekly from multiple stations, and the toxin concentrations in the samples were measured. Moreover, the dinoflagellate community composition was analyzed using next-generation sequencing to identify potential PST-producing species. The PST concentrations and toxin profiles showed substantial spatiotemporal variability, with GTX1 and GTX4 representing the dominant toxins in both samples, and C1/2 tending to be higher in seawater. Alexandrium species were identified as the primary sources of PSTs. Environmental factors such as water temperature and salinity influenced PST production. This study demonstrates that variability in the amount and composition of PSTs is due to intricate ecological interactions. To mitigate shellfish poisoning, continuous monitoring must be conducted to gain a deeper understanding of these interactions.
Editorial: Infectious Disease Epidemiology and Transmission Dynamics 2.0
Authors: Bai Yuan , Ertem Zeynep , Diestra Jose Luis Herrera , Wang Lin , Du Zhanwei
Published: July 2024

This Special Issue includes six original articles and one review article, all reflecting the unified scientific research endeavors and professional expertise for a shared objective, which were published between July 2023 and November 2023 [...]
Bridging Hepatitis C Care Gaps: A Modeling Approach for Achieving the WHO’s Targets in Ontario, Canada
Authors: Sahakyan Yeva , Erman Aysegul , Wong William W. L. , Greenaway Christina , Janjua Naveed , Kwong Jeffrey C. , Sander Beate
Published: July 2024

Background: The World Health Organization (WHO) has set hepatitis C (HCV) elimination targets for 2030. Understanding existing gaps in the “HCV care-cascade” is essential for meeting these targets. We aimed to identify the level of service scale-up needed along the “HCV care-cascade” to achieve the WHO’s HCV elimination targets in Ontario, Canada. Methods: By employing a decision analytic model, we projected the quality-adjusted life years (QALYs) and healthcare costs for individuals with HCV in Ontario. We increased RNA testing and treatment rates to 98%, followed by increasing antibody testing uptake until we achieved the WHO’s mortality target (i.e., a 65% reduction in liver-related mortality by 2030 vs. 2015). Results: Without scaling up by 2030, the expected QALYs and costs per person were 9.156 and CAD 48,996, respectively. Improved RNA testing and treatment rates reduced liver-related deaths to 3.3/100,000, a 57% reduction from 2015. Further doubling the antibody testing rates can achieve the WHO’s mortality target in 2035, but not in 2030. Compared to the status quo, such program would be cost-effective considering a 50,000 CAD/QALY gained threshold if annual implementation costs stayed under 2.3 M CAD/100,000 people. Conclusions: Doubling the antibody testing rates, along with increased RNA testing and treatment rates, showed promise in meeting the WHO’s goals by 2035.
The Virome of Cocoa Fermentation-Associated Microorganisms
Authors: Santos João Pedro Nunes , Rodrigues Gabriel Victor Pina , Ferreira Lucas Yago Melo , Monteiro Gabriel Pereira , Fonseca Paula Luize Camargo , Lopes Ícaro Santos , Florêncio Brenno Santos , da Silva Junior Aijalon Brito , Ambrósio Paulo Eduardo , Pirovani Carlos Priminho , Aguiar Eric Roberto Guimarães Rocha
Published: July 2024

Theobroma cacao plantations are of significant economic importance worldwide, primarily for chocolate production. During the harvest and processing of cocoa beans, they are subjected to fermentation either by microorganisms present in the environment (spontaneous fermentation) or the addition of starter cultures, with different strains directly contributing distinct flavor and color characteristics to the beans. In addition to fungi and bacteria, viruses are ubiquitous and can affect the quality of the fermentation process by infecting fermenting organisms, destabilizing microbial diversity, and consequently affecting fermentation quality. Therefore, in this study, we explored publicly available metatranscriptomic libraries of cocoa bean fermentation in Limon Province, Costa Rica, looking for viruses associated with fermenting microorganisms. Libraries were derived from the same sample at different time points: 7, 20, and 68 h of fermentation, corresponding to yeast- and lactic acid bacteria-driven phases. Using a comprehensive pipeline, we identified 68 viral sequences that could be assigned to 62 new viral species and 6 known viruses distributed among at least nine families, with particular abundance of elements from the Lenarviricota phylum. Interestingly, 44 of these sequences were specifically associated with ssRNA phages (Fiersviridae) and mostly fungi-infecting viral families (Botourmiaviridae, Narnaviridae, and Mitoviridae). Of note, viruses from those families show a complex evolutionary relationship, transitioning from infecting bacteria to infecting fungi. We also identified 10 and 3 viruses classified within the Totiviridae and Nodaviridae families, respectively. The quantification of the virus-derived RNAs shows a general pattern of decline, similar to the dynamic profile of some microorganism genera during the fermentation process. Unexpectedly, we identified narnavirus-related elements that showed similarity to segmented viral species. By exploring the molecular characteristics of these viral sequences and applying Hidden Markov Models, we were capable of associating these additional segments with a specific taxon. In summary, our study elucidates the complex virome associated with the microbial consortia engaged in cocoa bean fermentation that could contribute to organism/strain selection, altering metabolite production and, consequently, affecting the sensory characteristics of cocoa beans.
Detection of Bombali Virus in a Mops condylurus Bat in Kyela, Tanzania
Authors: Düx Ariane , Lwitiho Sudi E. , Ayouba Ahidjo , Röthemeier Caroline , Merkel Kevin , Weiss Sabrina , Thaurignac Guillaume , Lander Angelika , Kouadio Leonce , Nowak Kathrin , Corman Victor , Drosten Christian , Couacy-Hymann Emmanuel , Krüger Detlev H. , Kurth Andreas , Calvignac-Spencer Sébastien , Peeters Martine , Ntinginya Nyanda E. , Leendertz Fabian H. , Mangu Chacha
Published: July 2024

Bombali virus (BOMV) is a novel Orthoebolavirus that has been detected in free-tailed bats in Sierra Leone, Guinea, Kenya, and Mozambique. We screened our collection of 349 free-tailed bat lungs collected in Côte d’Ivoire and Tanzania for BOMV RNA and tested 228 bat blood samples for BOMV antibodies. We did not detect BOMV-specific antibodies but found BOMV RNA in a Mops condylurus bat from Tanzania, marking the first detection of an ebolavirus in this country. Our findings further expand the geographic range of BOMV and support M. condylurus’ role as a natural BOMV host.
Monitoring of Astroviruses, Brno-Hantaviruses, Coronaviruses, Influenza Viruses, Bornaviruses, Morbilliviruses, Lyssaviruses and Pestiviruses in Austrian Bats
Authors: Fereidouni Sasan , Keleş Sinan Julian , Schlottau Kore , Bagó Zoltán , Reiter Guido , Milchram Markus , Hoffmann Bernd
Published: July 2024

Here, we report the results of a monitoring study of bat viruses in Austria to strengthen the knowledge of circulating viruses in Austrian bat populations. In this study, we analyzed 618 oropharyngeal and rectal swab samples from 309 bats and 155 pooled tissue samples from dead bats. Samples were collected from 18 different bat species from multiple locations in Austria, from November 2015 to April 2018, and examined for astroviruses, bornaviruses, coronaviruses, hantaviruses, morbilliviruses, orthomyxoviruses (influenza A/C/D viruses), pestiviruses and rhabdoviruses (lyssaviruses) using molecular techniques and sequencing. Using RT-qPCR, 36 samples revealed positive or suspicious results for astroviruses, Brno-hantaviruses, and coronaviruses in nine different bat species. Further sequencing revealed correspondent sequences in five samples. In contrast, none of the tested samples was positive for influenza viruses A/C/D, bornaviruses, morbilliviruses, lyssaviruses, or pestiviruses.
Computer Vision Techniques for Morphological Analysis and Identification of Two Pseudo-nitzschia Species
Authors: Marzidovšek Martin , Mozetič Patricija , Francé Janja , Podpečan Vid
Published: July 2024

The diversity of phytoplankton influences the structure of and processes that occur in marine ecosystems, with size and other morphological traits being crucial for nutrient uptake and retention in the euphotic zone. Our research introduces a machine learning method that can facilitate the analysis of phytoplankton functional traits from image data. We use computer vision to identify and quantify phytoplankton species and estimate size-related traits based on cell morphology. The study uses transfer learning, where generic, pre-trained YOLOv8 computer vision models are fine-tuned with microscope image data from the Adriatic Sea. The study shows that, for this task, it is possible to effectively fine-tune models trained on out-of-domain images and that this is possible with a small training dataset. The results show high accuracy in detecting and segmenting phytoplankton cells from the microscopic images of the two selected phytoplankton taxa. For detection, the model achieves AP scores of 88.1% for Pseudo-nitzschia cf. delicatissima and 90.9% for Pseudo-nitzschia cf. calliantha, while for segmentation, the scores are 88.4% for Pseudo-nitzschia cf. delicatissima and 91.2% for Pseudo-nitzschia cf. calliantha. Compared to manual image analysis, the developed automatic method significantly increases the number of samples that can be processed.