bluuebunny/crossref_metadata_2025_split huggingface dataset:
Zooplankton shifts from headwater to lowland streams: Insights into the role of water quality to assist the protection and restoration of agricultural waterways
Authors: Gutierrez María Florencia , Mayora Gisela , Licursi Magdalena , Michlig Melina , Repetti María Rosa , Negro Leandro 
Published: May 2022

AbstractDespite the critical importance of zooplankton for many ecological processes, knowledge of its structure and distribution patterns in small streams subject to intensive land uses remains limited. Here we analysed changes in zooplankton community and composition in 10 sites located in streams from first‐order to sixteenth‐order, according to Shreve's classification, in a small catchment influenced by intensive agriculture. Using univariate and multivariate methods, we investigated the extent to which local scale environmental factors explained the spatial patterns of zooplankton community. We found that environmental conditions of headwaters differed markedly from those of lowland streams, especially with respect to nutrient levels, which were higher in the former than the latter. Zooplankton community was mainly composed by microphagous rotifers, and the overall species composition differed with the stream order. While zooplankton diversity and evenness increased with stream order and correlated negatively with nutrient level, zooplankton abundance and biomass showed the opposite trend. The mechanistic processes creating these patterns remain unknown but are likely linked to the effects of greater water mixing and dilution in lowland streams, as well as ecological processes such as predation and resource diversification. No clear pattern was found for presence or concentrations of pesticides in relation to the stream order. However, water quality seemed to be an important factor influencing zooplankton assemblages, which were significantly associated with pesticides and trophic state variables. Our findings suggest that agricultural pollution is impacting the zooplankton community, which may have implications for the food webs and overall health of the stream systems.
Determination of parabens in wastewater samples via robot‐assisted dynamic single‐drop microextraction and liquid chromatography–tandem mass spectrometry
Authors: Bocelli Marcio David , Vargas Medina Deyber Arley , Rodriguez Julie Paulin García , Lanças Fernando Mauro , Santos‐Neto Álvaro José 
Published: May 2022

AbstractDynamic single‐drop microextraction (SDME) was automatized employing an Arduino‐based lab‐made Cartesian robot and implemented to determine parabens in wastewater samples in combination with liquid chromatography–tandem mass spectrometry. A dedicated Arduino sketch controls the auto‐performance of all the stages of the SDME process, including syringe filling, drop exposition, solvent recycling, and extract collection. Univariate and multivariate experiments investigated the main variables affecting the SDME performance, including robot‐dependent and additional operational parameters. Under selected conditions, limit of detections were established at 0.3 µg/L for all the analytes, and the method provided linear responses in the range between 0.6 and 10 µg/L, with adequate reproducibility, measured as intraday relative standard deviations (RSDs) between 5.54% and 17.94%, (n = 6), and inter‐days RSDs between 8.97% and 16.49% (n = 9). The robot‐assisted technique eased the control of dynamic SDME, making the process more feasible, robust, and reliable so that the developed setup demonstrated to be a competitive strategy for the automated extraction of organic pollutants from water samples.
Determination of multiclass pesticides in river sediments via matrix solid‐phase dispersion extraction and gas chromatography–tandem mass spectrometry
Authors: Mateus Elizabeth Gonzalez , Vargas Nelson Omar , Rodriguez Julie Paulin Garcia 
Published: May 2022

AbstractA fast and environment‐friendly analytical method was implemented to determine multiclass pesticides in river sediments. Twenty‐three pesticides—organochlorine pesticides, organophosphorus pesticides, and triazines—were extracted via matrix solid‐phase dispersion (MSPD) and analyzed by gas chromatography–tandem mass spectrometry (GC–MS/MS). Florisil demonstrated excellent analytes uptake capability as the extractant phase, with suitable selectivity for treating complex sediment samples. Under defined extraction conditions, the MSPD–GC–MS/MS method demonstrated robustness in the n inter‐day analysis of sediments from different sources, providing limit of quantifications (LOQs) between 5 and 15 ng/g, linear responses in the range between LOQs and 150 ng/g, extraction recoveries of 71%–106%, and precision, assessed as relative standard deviation below 20%. The MSPD significantly reduced samples and solvents’ consumption, providing critical environmental gains compared to traditional extraction methods like Soxhlet. Finally, the method was applied to analyze sediment samples from three different collection areas of the Subachoque River (Cundinamarca, Colombia), demonstrating a fast, efficient, confident, and profitable analytical tool for pollution control and monitoring in environmental samples. The method allowed us to determine the current use in Colombia of banned pesticides under the 2001 Stockholm Convention.
Real‐time traceability of sorghum origin by soldering iron‐based rapid evaporative ionization mass spectrometry and chemometrics
Authors: Liu Tong , Wang Wei , He Muyi , Chen Fengming , Liu Jialing , Yang Minli , Guo Wei , Zhang Feng 
Published: May 2022

AbstractSorghum is an important grain with a high economic value for liquor production. Tracing the geographical origin of sorghum is vital to guarantee the liquor flavor. Soldering iron‐based rapid evaporative ionization mass spectrometry (REIMS) combined with chemometrics was developed for the real‐time discrimination of the sorghum's geographical origin. The working conditions of soldering iron‐based ionization were optimized, and then the obtained MS profiling data were processed using chemometrics analysis methods, including principal component analysis–linear discriminant analysis and orthogonal projection to latent structures discriminant analysis (OPLS‐DA). A recognition model was established, and discriminations of sorghum samples from 10 provinces in China were achieved with a correct rate higher than 90%. On the basis of OPLS‐DA, the specific ions of m/z 279.2327, 281.2479, and 283.2639 had relatively strong discrimination power for the geographical origins of sorghum. The developed method was successfully applied in the discrimination of sorghum origins. The results indicated that the soldering iron‐based REIMS technique combined with chemometrics is a useful tool for direct, fast, and real‐time ionization of poor conductivity samples and acquisition of metabolic profiling data.
Continuous model averaging for benchmark dose analysis: Averaging over distributional forms
Authors: Wheeler Matthew W. , Cortiñas Abrahantes Jose , Aerts Marc , Gift Jeffery S. , Allen Davis Jerry 
Published: May 2022

AbstractWhen estimating a benchmark dose (BMD) from chemical toxicity experiments, model averaging is recommended by the National Institute for Occupational Safety and Health, World Health Organization and European Food Safety Authority. Though numerous studies exist for model average BMD estimation using dichotomous responses, fewer studies investigate it for BMD estimation using continuous response. In this setting, model averaging a BMD poses additional problems as the assumed distribution is essential to many BMD definitions, and distributional uncertainty is underestimated when one error distribution is chosen a priori. As model averaging combines full models, there is no reason one cannot include multiple error distributions. Consequently, we define a continuous model averaging approach over distributional models and show that it is superior to single distribution model averaging. To show the superiority of the approach, we apply the method to simulated and experimental response data.
Assessing the environmental benefits of battery packs from multi‐vehicle and multi‐region perspective: Aiming for lightweight and carbon neutrality
Authors: Li Xi , Wu Haohui , Hu Yuchen , Liu Hui , Yu Yajuan , Huang Kai , Zhang Zhiqi , Xue Bingya , Gong Yuan 
Published: May 2022

AbstractVehicle lightweight and carbon neutrality turn out to be the critical goals in developing new energy vehicles. As an important part of electric vehicles, power battery packs have an impact on the environment. In this study, multiple environmental assessment indicators were grouped into a comprehensive index, namely the green characteristic index, and the green characteristic index was used to comprehensively evaluate the environmental impact of 11 kinds of battery packs. This study calculates and analyzes the environmental impact values of battery packs in different regions for four types of small, medium, intermediate, and limousine cars. Finally, the uncertainty analysis was carried out. Research has found that micro battery packs have a lower potential environmental impact than advanced battery packs, so smaller, more energy‐efficient battery electric vehicles (BEVs) generally perform better than larger BEVs for vehicle models. During the operation stage of the battery pack, the environmental impact value of carbon footprint and ecological footprint is greatly affected by the regional power structure. Running the battery pack in China will generate higher carbon footprint and ecological footprint. In addition, the green characteristic index is more affected by the stage of use. When the scene is switched, the larger the model of the electric vehicle, the more obvious its environmental emission reduction capability. This highlights the benefits of high‐efficiency electrical structures in large electric vehicles, which can reduce environmental impact by increasing lifetime and charging efficiency, reducing the loss of transport power in the area, and improving the weight‐to‐energy relationship for BEVs.
Greening of roofs as an adaptive measure for climate change
Authors: Radujković Milana , Papuga Saša 
Published: May 2022

AbstractThe negative impact of climate change, especially in urban areas, requires the use of new construction technologies and materials, harmonized with environmental aspects. One such approach is the construction of green areas on flat roofs of buildings. The positive impact of greening roofs is reflected in several important aspects: environmental, economic, and social. The pilot area that was researched is characterized by a high coefficient of construction. All this affects the creation of the so‐called heat island and bad microclimatic conditions, as well as the lack of areas that can be arranged for the rest of the local population. In addition to the impact of this type of urban planning on the preservation of the city's environment, the costs of building green roofs are also presented. In the final part of the article, the life cycle impact assessment (LCIA) of green roof layers is presented, using the Eco‐indicator method to show the environmental impact of a materials based on data from a life cycle assessment.
Effect of poly(acrylic acid) binder on the stability of sulfur‐enriched crystalline Mo3S13 clusters for high capacity of Li‐ion batteries
Authors: Lee Hae Ri , Lee Youn‐Ki , Park Gwan Gyu , Lee Sungho , Joh Han‐Ik 
Published: May 2022

SummaryMolybdenum sulfide (MoSx)‐based materials have been extensively studied as a potential alternative of low‐capacity graphite anode, owing to their remarkable capacity through intercalation and conversion reactions. However, these materials should be electrochemically activated at a low potential in first discharge and simultaneously degrade, owing to their inert basal plane and unstable sulfur configuration, respectively, leading to unexpectedly low performance. Hence, it is necessary to apply sulfur‐enriched crystalline Mo3S13 clusters as an anode material to increase the number of active sites and energy densities. Unlike MoS2 possessing only terminal sulfur, Mo3S13 clusters have higher sulfur content with various and stable configuration in their structure, which can act as additional active sulfur sites. To realize an electrode with high energy density, we used the Mo3S13 clusters without any carbon supports as active materials. In the electrode preparation, we confirmed that employing poly(acrylic acid) and isopropyl alcohol as a binder and solvent, respectively, was appropriate for retaining the cluster crystallinity, resulting in the enhanced cycling stability. The Mo3S13 cluster‐based electrode as a carbon‐free electrode exhibited capacity of 1192 mAh g−1 at 0.1 A g−1 and good C‐rate capability. The significant capacity variation with the selective removal of sulfur configuration in Mo3S13 clusters indicates that the increased sulfur contents were provided as additional sources for (de)lithiation.
Mn2V2O7 spiked ball‐like material as bifunctional oxygen catalyst for zinc‐air batteries
Authors: Krishna B. N. Vamsi , Kammari Sasidharachari , Yu Jae Su 
Published: May 2022

SummaryHierarchical micro/nanostructures are believed to be magnificent electrocatalyst materials capable of competing with noble metals and the most expensive catalyst materials for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Herein, Mn2V2O7‐based hierarchical spiked ball structures (MVO SBs) were synthesized using a simple hydrothermal technique as a bifunctional oxygen catalyst for rechargeable Zn‐air batteries. The linear sweep voltammetry by a rotating disc electrode was used to investigate the ORR and OER properties and their mechanisms, and the charge transfer mechanism was also studied by electrochemical impedance spectroscopy analysis. When compared with platinum with carbon black (Pt/C), the MVO SB catalyst material exhibited comparable ORR and OER properties. Furthermore, the MVO SB material revealed a 4e− transfer pathway in an electrolyte solution. Furthermore, the prepared MVO SB material demonstrated a lower charge‐discharge voltage gap when compared with Pt/C material, which is lower than 180 mV at 45 mA cm−2. The cycling test result of MVO SB catalyst sample revealed excellent cycling stability over 50 charging and discharging cycles (~800 min) than the Pt/C sample (30 cycles [~520 min]). The good catalytic activity and excellent structural stability of the MVO SB material are especially due to the more active sites enhanced by the unique spiked ball‐like morphology and high specific surface area (11.70 m2 g−1) properties. The achieved results suggest that the synthesized catalyst material could be employed as an oxygen catalyst material for rechargeable Zn‐air batteries.
Proposal and evaluation of a solar‐based polygeneration system: Development, exergoeconomic analysis, and multi‐objective optimization
Authors: Azizi Saeid , Nedaei Navid , Yari Mortaza 
Published: May 2022

SummaryThis article reviews a novel poly‐generation system based on a solar power tower for power generation, cooling capacity, freshwater creation, and hydrogen production. Comprehensive thermodynamic assessments are conducted to determine the performance of the proposed model. At basic operating circumstances, the simulation results in the generation of 7.871 MW of electricity, 10.05 kg/s of drinking water, 8.788 MW cooling capacity, and hydrogen at a rate of 0.2445 kg/h accompanied by 41.18% energy efficiency and a sum unit cost of products of 6.583 $/GJ. Then, parametric research is going to determine the influence of the proposed system's primary parameters on its performance. Additionally, the gray wolf optimization technique is used to optimize the exergetic efficiency with sum unit cost products and freshwater rate of production under various multi‐objective optimization situations. The first optimization scenario's results indicate that the 53.06% exergetic efficiency and 5.44 $/GJ sum unit cost products are the optimum point, and in the second optimization scenario, the optimum point is 47.64% exergetic efficiency and 9.61 kg/s freshwater production rate. Finally, the performance of the suggested method is demonstrated using a case study of New York, United States of America, and represented the maximum performance in July with 5.2 MW net power and 39.6% exergetic efficiency.
A novel reed‐leaves like aluminum‐doped manganese oxide presetting sodium‐ion constructed by coprecipitation method for high electrochemical performance sodium‐ion battery
Authors: Cai Kedi , Jing Xueqin , Zhang Yuting , Li Lan , Lang Xiaoshi 
Published: May 2022

SummaryIn this paper, Al‐doped manganese oxide with presetting sodium‐ion (NaxMnyAlzO2) is synthesized by a facile coprecipitation method and combines with Na3V2(PO4)3 cathode active materials for sodium‐ion battery in order to optimize the electrochemical performances. During the coprecipitation, a stable NaxMnyAlzO2 polynary metal oxide with Mn and Al molar ratio to 3:1 shows a special micromorphology similar to that of reed leaves, which makes it have a more ideal electrochemical specific surface area and ample mass transfer channels for rapid sodium‐ion insertion and desorption. Electrochemical test indicates that reed‐leaves like NaxMnyAlzO2 polynary metal oxides as active material for sodium‐ion capacitor exhibit a very excellent reversibility and low electrochemical (Rct = 434 Ω) and concentration polarization (DNa+ = 2.2728 × 10−11 cm2 s−1). Specific discharge capacity can achieve to 73.76 F g−1 at 100 mA g−1 current density corresponding to 368.8 m2 g−1 electrochemical specific surface area. After 200 cycles, the capacity retention rate can be maintained at 81.81%. In addition, reed‐leaves like NaxMnyAlzO2 polynary metal oxide playing a good depolarization role combined with Na3V2(PO4)3 active materials in the mass ratio to 7:3 can bring about the most excellent electrochemical performances.
Blowout dynamics in lime‐rich and lime‐poor coastal dunes in the Netherlands
Authors: Kooijman Annemieke , Schouten Michelle , Postema Agnethe , Cammeraat Erik , Arens Bas 
Published: May 2022

AbstractBlowouts can mitigate the negative effects of acidification in the topsoil, especially in industrialized countries with high atmospheric nitrogen (N) deposition. However, blowout activity may differ between lime‐rich and lime‐poor dunes, which creates different regional responses and interactions between processes and patterns.To further explore this, five Dutch dune sites were selected over the gradient from lime‐rich and lime‐poor dunes. We mapped blowout activity in 5 years between 1996 and 2017 with aerial photographs, and used transport potential, atmospheric N‐deposition and rabbit density as explanatory variables. We also studied soil and plant parameters in the field in different stages of succession.All sites showed fluctuations, but blowout activity net increased in the lime‐rich sites, and decreased in the lime‐poor sites. Differences in blowout activity could not be explained by sand transport potential, which differed between years, but not sites. Differences in blowout activity could to some extent be explained by rabbit density and exceedance of the critical N load, although the transition site between lime‐rich and lime‐poor dunes showed high blowout activity despite low rabbit density.Differences in blowout activity between lime‐rich and lime‐poor dunes were also related to differences in topsoil chemistry, especially with respect to lime content, Fe content and different forms of phosphorus (P). High pH was a key factor, which reduced sensitivity to high N deposition through reduced P‐availability to the vegetation, higher proportion of arbuscular mycorrhizal plants, which may improve food quality for rabbits, and lower root biomass, which may increase erodibility of the dune soil. High pH and low P availability may even occur in lime‐poor dunes with a little lime, as long as blowouts stay active and counteract acidification. However, when pH values drop below 6.5, P availability to the vegetation will increase and start feedback processes leading to blowout stabilization.
Confinement forest‐based enhanced min‐min and max‐min technique for secure multicloud task scheduling
Authors: Jawade Prashant , Borkar Gautam M. , Ramachandram S. 
Published: May 2022

AbstractTask scheduling is the most important issue in the cloud computing environment since its implementation is largely dependent on it. However, due to its weaknesses in energy consumption for resource usage, high computational complexity, and memory needs, Virtual Machine (VM) cannot manage large amounts of workload. Furthermore, by reducing the number of active hosts' data assignments while utilizing the resources, a security risk occurs. To address these challenges, a Grey‐wolf with Deadline Restrictions approach was developed to allocate tasks and resources in less time while maintaining fixed interval constraints. Moreover, the Cognizing Anomaly detection method is utilized to find even the most recent abnormalities in the data. Furthermore, using the Confinement Forest‐based augmented Min‐Min and Max‐Min approach, the task scheduling process provides an efficient workload balancing mechanism by restricting makespan, energy consumption, load balancing, and fault tolerance. In contrast, enabling a security‐aware multicharacteristic‐based heuristic technique is employed to provide secure placement of data in the appropriate location. The proposed technique outperforms existing methods in terms of makespan and memory consumption.
Dynamic placement of virtual machines using an improved multi‐objective teaching‐learning based optimization algorithm in cloud
Authors: Wang Na , Osmani Amjad , Mirzaei Siamak 
Published: May 2022

AbstractRecently, cloud computing is growing rapidly and contributing to the realization of other technologies. Cloud data centers use a lot of energy to host applications, which leads to high operating costs and increased carbon dioxide emissions into the environment. Dynamic consolidation of virtual machines (VMs) into the minimum number of physical servers is an efficient approach to managing energy consumption in cloud. Virtual machines placement (VMP) is an important problem in the proper consolidation of VMs and is the most common way to improve resource utilization. In VMP problem, VMs are consolidated to minimize the number of active physical servers. This consolidation is done using migration of VMs. After placement, the VMs execute on selected physical servers and the underloaded physical servers are off to optimize energy consumption. Basically, the purpose of VMP is to allocate a set of VMs to a subset of physical servers, taking into account some objectives such as reducing energy consumption and violating the service level agreement (SLA). In this article, an improved teaching‐learning based optimization (TLBO) algorithm is formulated to solve VMP as a multi‐objective problem, which we call VMP‐TLBO. VMP‐TLBO can perform optimal placement of migrated VMs to physical servers with the purpose of reducing energy consumption and SLA violation. VMP‐TLBO is implemented in MATLAB and the experimental results show that proposed algorithm does not violate SLA and compared to the best equivalence algorithm (ie, PAPSO), it improves energy consumption and SLA violation by 1.8% and 5.6%, respectively. In addition, VMP‐TLBO consolidates migrated VMs into the minimum number of physical servers to minimize the number of overloaded hosts as much as possible.