bluuebunny/crossref_metadata_2025 huggingface dataset:
Participatory Approach to Planning Urban Resilience to Climate Change: Brescia, Genoa, and Matera—Three Case Studies from Italy Compared
Authors: Palla Anna , Pezzagno Michele , Spadaro Ilenia , Ermini Ruggero
Published: March 2024

Urban resilience must consider the ability of cities to cope with the effects of climate change. Community awareness raising and sustainable urban drainage systems (SUDs) are often mentioned in the literature as effective adaptation actions while the success of these solutions is highly context-dependent and improved planning procedures are urgently needed. In this framework, the URCA! project represents a good practice aiming to strengthen the resilience of urban areas by promoting the implementation of SUDs in territorial planning. The main objective of the present research deals with the role of participation in promoting the use of SUDs and their uptake in town planning and land management involving local communities, students, experts, local authorities, and enterprises. To this end, the research adopts a participatory approach to SUDs urban planning for three case studies in Italy selected under the criterion of maximum variation (Brescia, Genoa, and Matera). For the three case studies, participatory approaches are at different stages of development thus requiring appropriate ways of interacting and resulting in different impacts on decisions. Preliminary results, drivers, and barriers in the application of the participatory approach are discussed and compared in order to bring innovation into planning practices, stimulating a revision of typical governance mechanisms.
Navigating Carbon Offsetting: How User Expertise Influences Digital Platform Engagement
Authors: Armisen Albert , de-Uribe-Gil Clara-Eugènia , Arimany-Serrat Núria
Published: March 2024

Exploring the nexus of technology and sustainability, this research delves into user engagement patterns on digital carbon offsetting platforms such as KlimaDAO. Drawing from the digital platform and storytelling literature, a set of hypotheses is put to the test using data from KlimaDAO’s initiative, which includes 1331 carbon offsets from 524 individuals. A stepwise logistic regression analysis confirms a curvilinear relationship: experts typically opt for a moderate level of offsetting, while the behavior of regular users spans a broad spectrum, from minimal to substantial offsetting. The analysis also confirms that experts are inclined to share their stories with a sense of optimism, whereas regular users seek out green credentials and prioritize high-quality carbon offsets. These insights not only enrich academic discourse but also have practical implications, underscoring the need to design carbon offsetting platforms that harness the positive narratives of experts while meeting the needs of regular users.
Environmental Data, Modeling and Digital Simulation for the Evaluation of Climate Adaptation and Mitigation Strategies in the Urban Environment
Authors: Verde Sara , Dell’Acqua Federica , Losasso Mario
Published: March 2024

The worsening effects of climate change in urban settings imply the application of effective measures for climate adaptation and mitigation actions on the building–open space system. It means the development of innovative climate-resilient design approaches through the elaboration of knowledge processes and methodological workflows supported by key enabling technologies (KETs). This paper presents the middle results of the research project PRIN (Progetti di Rilevante Interesse Nazionale) 2017 “TECH-START—key enabling TECHnologies and Smart environmenT in the Age of gReen economy. Convergent innovations in the open space/building system for climaTe mitigation”. The goal of this paper is to show a methodological workflow and an operational protocol for digital modeling and simulation for the evaluation of climate adaptation and mitigation strategies in urban settings, applied to the case of the former Centro Polifunzionale Marianella in the northern area of Naples. The results of the experimental application demonstrate the effectiveness of the meta-design proposals, with particular reference to the reduction of vulnerability to the heat wave phenomenon. The experimentation expresses the consistency of the methodological workflow. The results obtained demonstrate that the methodological approach based on KETs is effective in the evaluation of climate-resilient design actions through the definition of a set of indicators whose values return performance and characteristics of the design solutions.
Motivators of Circular Fashion: The Antecedents of Chinese Consumers’ Fashion Renting Intentions
Authors: Lang Chunmin , Zhang Ruirui
Published: March 2024

This study investigates how intrinsic (i.e., shopping values, frugality, and perceived enjoyment) and extrinsic factors (i.e., perceived risks) influence Chinese consumers’ intentions regarding fashion renting. A quantitative study was conducted with data collected from a Chinese online research platform named Wenjuanxing. Data cleaning generated 322 valid samples out of 354 returned responses. Both SPSS 23.0 and Mplus 7 were used for data analysis. The hypotheses were tested through a structural equation model (SEM). The results theoretically confirm and expand the knowledge regarding what conceptual constructs impel or restrain consumers’ renting behaviors. The positive influences of frugality, perceived enjoyment, and attitude regarding fashion renting intention are also confirmed. The statistics also indicate the negative influences of perceived social risk on attitude and perceived enjoyment. This study aims to investigate both the motivations and barriers to fashion renting intention among Chinese consumers. It echoes the current rising research demand of investigating consumers’ responses to circular fashion, specifically fashion renting. The results of this study are expected to shed light on the understanding of Chinese consumers’ renting intentions, which could help to improve the efficiency of marketing strategies of fashion rental businesses and increase fashion circulation.
Drivers That Affect Households to Reduce Food Waste: A UK Qualitative Study
Authors: Jansson-Boyd Cathrine V. , Mul Cari-lène
Published: March 2024

Individual households make significant contributions to food waste. Combating this waste would allow for better food distribution globally that can help combat global hunger. As there is currently a limited understanding as to why people waste food, we conducted semi-structured interviews with people that had taken part in a food waste reduction study, to explore drivers that contribute to reduced food waste within UK homes. Using a thematic analysis, four themes were identified based around the importance of thinking about food waste, having a flexible approach to food waste, as well as being emotionally engaged in food waste reduction processes. It was also explored if others have a role to play in whether people try to reduce their waste; however, contrary to previous findings, such a notion was not supported here. The implications of the findings are discussed.
Investigation on the Confined Breakage Characteristics of Calcareous Sand in the South China Sea Integrated Using Relative Breakage Ratio and Fractal Dimension
Authors: Zhu Jianfeng , Zheng Qiqi , Yang Hao
Published: March 2024

Calcareous sand, ubiquitous in the geotechnical makeup of the South China Sea, exhibits both compressibility and vulnerability to fragmentation when subjected to external loading, spanning a spectrum from typical to extreme conditions. This investigation aims to quantitatively assess the compression and particle breakage characteristics of calcareous sand under varied parameters, including relative density, saturation, applied loads, and loading paths, specifically focusing on sustainable geotechnical methodologies. Through a series of confined compression tests, this evaluation employed the relative breakage ratio and fractal dimension as key evaluative metrics. The results indicated that employing this integrated approach offered a more comprehensive understanding of calcareous sand breakdown mechanisms than relying on a singular particle breakage index. Furthermore, an increase in relative density can induce a transition in particle contact behavior, shifting from point-to-point interactions to face-to-face contact, thereby reducing inter-particle stress and minimizing grain breakage, particularly under loads below 200 kPa. Increasing loads exacerbated particle breakage, with finer particles predominantly initiating this process. During reloading, pore ratios across various load levels surpass those observed during initial loading, except at 1600 kPa, where a decline in pore ratio was noted, coinciding with pore water extrusion and the onset of new particle fracturing. The lubricating effect of water reduces inter-particle friction, enhancing stress concentration at particle edges and localized particle breakage, thereby increasing the presence of finer particles without significantly altering the overall structure. Notably, the influence of pore water pressure is evident during the reloading phase. These findings contribute to a refined theoretical framework for predicting coastal erosion risks and devising effective environmental protection strategies for sustainable coastal engineering practices.
Research on the Measurement and Influencing Factors of Carbon Emissions in the Swine Industry from the Perspective of the Industry Chain
Authors: Yu Yaguai , Li Qiong , Bao Yinzi , Fu Ersheng , Chen Yiting , Ni Taohan
Published: March 2024

From the perspective of the industry chain, this paper uses the life cycle assessment (LCA) method to divide the swine industry into six production stages: feed crop cultivation, feed crop transportation and processing, intestinal fermentation, manure management, energy consumption in pig farming, and slaughtering and processing. Using the LCA method, the carbon emissions from the swine industry are measured from 2001 to 2020 for the whole country and 31 provincial regions. Based on the measurement results, this paper analyzes the dynamic evolution of carbon emissions from the national swine industry during the study period. Meanwhile, the spatial divergence in carbon emissions from the swine industry and the share of carbon emissions from each production stage were further analyzed by combining different provincial regions and production stages. Afterward, this paper uses the Logarithmic Mean Divisia Index (LMDI) model to decompose the influencing factors of carbon emissions at the national and provincial levels, and in each production stage. It is found that (1) The dynamic evolution of China’s swine industry carbon emissions from 2001 to 2020 roughly follows a trend of “slow growth—sharp decline—fluctuating rise—fluctuating decline.” The fluctuations are influenced by multiple factors, including the industry structure, agricultural policy, and farming scale. The primary driver for the increase in carbon emissions from the swine industry is the growth in demand for pork consumption, leading to the rise in swine supply. (2) In terms of spatial divergence at the provincial level, the regional differences in carbon emissions from the swine industry are significant, the total carbon emissions and unit carbon emissions of Jiangsu, Anhui, and Henan are higher than the national average. (3) In the production stages of the swine industry, feed crop cultivation and manure management are the primary sources of carbon emissions, associated with factors such as substantial feed consumption, crop production patterns, and backward manure management practices. (4) Regarding influencing factors, production efficiency, industry structure, and urbanization level have inhibiting effects on carbon emissions in the swine industry. Economic development and population scale have promoting effects. Production efficiency is the most significant inhibiting factor, and economic development is the most significant promoting factor. Finally, suggestions are made to curb carbon emissions in China’s swine industry, including strengthening environmental control, formulating long-term plans for carbon emission reduction, delineating key areas and demonstration bases for carbon emission reduction, enhancing expertise in fertilizer application and manure treatment, and improving agricultural machinery and equipment.
Assessment of Groundwater Potential Zones Utilizing Geographic Information System-Based Analytical Hierarchy Process, Vlse Kriterijumska Optimizacija Kompromisno Resenje, and Technique for Order Preference by Similarity to Ideal Solution Methods: A Case Study in Mersin, Türkiye
Authors: Çelik Mehmet Özgür , Kuşak Lütfiye , Yakar Murat
Published: March 2024

The indiscriminate use of surface water has heightened the demand for groundwater supplies. Therefore, it is critical to locate potential groundwater sources to develop alternative water resources. Groundwater detection is tremendously valuable, as is sustainable groundwater management. Mersin, in southern Türkiye, is expected to confront drought shortly due to increased population, industry, and global climate change. The groundwater potential zones of Mersin were determined in this study by GIS-based AHP, VIKOR, and TOPSIS methods. Fifteen parameters were used for this goal. The study area was separated into five categories. The results show that the study area can be divided into “Very High” zones (4.98%, 5.94%, 7.96%), followed by “High” zones (10.89%, 10.32%, 16.50%), “Moderate” zones (60.68%, 52.41%, 51.56%), “Low” zones (21.28%, 28.53%, 20.90%), and “Very Low” zones (2.18%, 2.80%, 3.07%) in turn. Data from 60 wells were used to validate potential groundwater resources. The ROC-AUC technique was utilized for this. It was seen that the performance of the VIKOR model is better than that of the AHP and TOPSIS (76.5%). The findings demonstrated that the methods and parameters used are reliable for sustainable groundwater management. We believe that the study will also help decision makers for this purpose.
A Quantitative Risk Analysis during Truck-to-Ship Ammonia Bunkering
Authors: Duong Phan Anh , Kim Hee Jin , Ryu Bo Rim , Kang Hokeun
Published: March 2024

A primary objective for the sustainable development of the maritime sector is to transition toward carbon-neutral fuels, with the aim to reduce emissions from maritime transportation. Ammonia emerges as a promising contender for hydrogen storage, offering the potential for CO2-free energy systems in the future. Notably, ammonia presents advantageous attributes for hydrogen storage, such as its high volumetric hydrogen density, low storage pressure requirements, and long-term stability. However, it is important to acknowledge that ammonia also poses challenges due to its toxicity, flammability, and corrosive nature, presenting more serious safety concerns that need to be addressed compared with other alternative fuels. This study sought to explore the dispersion characteristics of leaked gas during truck-to-ship ammonia bunkering, providing insights into the establishment of appropriate safety zones to minimize the potential hazards associated with this process. The research encompassed parametric studies conducted under various operational and environmental conditions, including different bunkering conditions, gas leak rates, wind speeds, and ammonia toxic doses. EFFECTS, which is commercial software for consequence analysis, was utilized to analyze specific scenarios. The focus was on a hypothetical ammonia bunkering truck of 37,000 L refueling an 8973 deadweight tonnage (DWT) service vessel with a tank capacity of 7500 m3 in the area of Mokpo Port, South Korea. The study’s findings underscore that the ammonia leak rate, ambient temperature, and wind characteristics significantly impacted the determination of safety zones. Additionally, the bunkering conditions, leak hole size, and surrounding traffic also played influential roles. This study revealed that bunkering in winter resulted in a larger safety zone compared with bunkering in summer. The lethality dose of ammonia was affected by the leak hole size, time for dispersion, and the amount of ammonia released. These observed variations imply that ammonia truck-to-ship bunkering should be undertaken with carefully chosen suitable safety criteria, thereby significantly altering the scope of safety zones. Consequently, the risk assessment method outlined in this paper is expected to assist in determining the appropriate extent of safety zones and provide practical insights for port authorities and flag states contributing to the future sustainable development of the maritime industry.
Measuring the Industry 5.0-Readiness Level of SMEs Using Industry 1.0–5.0 Practices: The Case of the Seafood Processing Industry
Authors: Madhavan Meena , Sharafuddin Mohammed Ali , Wangtueai Sutee
Published: March 2024

SMEs across the globe have witnessed increasing internal and external pressure to adopt the recent industrial revolution (4.0 & 5.0). There has been pressure for SMEs to adopt Industry 4.0 technologies, but this did not transpire in traditional industries such as agricultural and seafood processing. Also, there is no published evidence of Industry 4.0 technologies’ support for food processing industries to achieve the United Nations Sustainable Development Goals (UNSDGs). Hence, Industry 5.0 is conceptualized to be (a) human-centric, (b) sustainable, and (c) resilient. However, most of the earlier studies conducted to assess the “Industry 4.0 adoption level” failed to address the respondents’ current level of industrial practices. Therefore, to overcome the research gap, this research aims to measure the current level of industrial practices and I5.0 readiness level of seafood processing SMEs in Thailand. Thus, this research developed a seven-factor framework including “production line”; “major energy source”; “seafood processing”; “packaging”; “labelling”; “anti-bacterial testing methods sensory, texture analyzing and quality control”; and “business process, documentation, and communication”, with forty-two questions related to Industry 1.0–5.0 practices in the context of seafood processing SMEs. The findings reveal that the SMEs are still in I1.0, 2.0, and 3.0 practices. There is minimal adoption of I4.0. However, there is a comparatively higher level of Industry 5.0 readiness among SMEs in terms of business processes, documentation, and communication. Thus, SMEs can adopt Industry 5.0 partially, and escalate step-by-step from Industry 1.0–Industry 4.0 according to changing trends and demand.
Distinguishing between Low- and High-Cost Pro-Environmental Behavior: Empirical Evidence from Two Complementary Studies
Authors: Rau Henriette , Nicolai Susanne , Franikowski Philipp , Stoll-Kleemann Susanne
Published: March 2024

To reach sustainability goals, researchers and policymakers must focus on addressing changes toward more pro-environmental behavior (PEB). Therefore, this study shows evidence-based perceptions of low- and high-cost behaviors and deduces recommendations for PEB interventions. We applied a multi-step mixed-method approach: First, a representative online survey was conducted to collect a general quantitative overview and classify low- and high-cost behavior based on past behavior and behavioral intentions. Second, a gamification intervention that aimed to gain quantitative data about certain behaviors and perceived low- and high-costs was conducted with university students. The results of the two studies showed that PEB can easily be categorized into high-, rather-high-, rather-low-, and low-cost behavior. However, this classification is not based on emission sectors, e.g., mobility, but on the specific behavior. Interventions can be recommended according to subjective costs: For example, low-cost behavior does not need additional interventions in most cases but must be maintained as is. According to the empirical findings, high-cost behavior needs top-down interventions, while rather-high- and rather-low-cost behavior requires bottom-up interventions to achieve behavior changes. In summary, managing interventions using this classification and focusing on high-impact behavior can lead to successful behavior changes and emission reductions.
A Perspective on Solar-Driven Electrochemical Routes for Sustainable Methanol Production
Authors: Pendse Aaditya , Prajapati Aditya
Published: March 2024

The transition towards sustainable and renewable energy sources is imperative in mitigating the environmental impacts of escalating global energy consumption. Methanol, with its versatile applications and potential as a clean energy carrier, a precursor chemical, and a valuable commodity, emerges as a promising solution within the realm of renewable energy technologies. This work explores the integration of electrochemistry with solar power to drive efficient methanol production processes, focusing on electrochemical reduction (ECR) of CO2 and methane oxidation reaction (MOR) as pathways for methanol synthesis. Through detailed analysis and calculations, we evaluate the thermodynamic limits and realistic solar-to-fuel (STF) efficiencies of ECR and MOR. Our investigation encompasses the characterization of multijunction light absorbers, determination of thermoneutral potentials, and assessment of STF efficiencies under varying conditions. We identify the challenges and opportunities inherent in both ECR and MOR pathways, shedding light on catalyst stability, reaction kinetics, and system optimization, thereby providing insights into the prospects and challenges of solar-driven methanol synthesis, offering a pathway towards a cleaner and more sustainable energy future.
Unsymmetrical and C3-Symmetrical Partially Fluorinated Hexaarylbenzenes: Effect of Terminal Alkoxy Chain Length on Photophysical and Thermophysical Behavior
Authors: Wang Yizhou , Yamada Shigeyuki , Yasui Motohiro , Konno Tsutomu
Published: March 2024

Solution-state photoluminescence (PL) is affected by the electronic state; however, solid-state PL varies widely depending on the aggregated state. Although the synthesis and photophysical properties of unsymmetrical and C3-symmetrical hexaarylbenzenes (HABs) have been reported, the influence of their terminal alkoxy chains on their physical properties remains unclear. Therefore, we synthesized a series of unsymmetrical and C3-symmetrical partially fluorinated HABs with different alkoxy chains and investigated the effects of alkoxy chain length on the thermophysical and photophysical properties. While investigating phase transition behavior, the ethoxy-substituted unsymmetrical derivative revealed a columnar liquid-crystalline phase, whereas the other derivatives only exhibited a phase transition between crystalline and isotropic phases. While evaluating PL behavior, both the unsymmetrical and C3-symmetrical analogs exhibited relatively strong blue PL, independent of the alkoxy chain length. Through-space π-conjugation caused the PL spectra of C3-symmetrical derivatives to redshift compared to those of unsymmetrical derivatives. Partially fluorinated HABs exhibited relatively strong fluorescence, even in the crystalline state, depending on the alkoxy chain length, owing to the formation of various aggregated structures. Crystalline fluorinated HABs exhibited photochromism, resulting in the appearance of long-wavelength PL bands when exposed to ultraviolet (UV) irradiation, making them promising candidates for PL sensing materials for UV detection.
A Dynamic Collision Risk Assessment Model for the Traffic Flow on Expressways in Urban Agglomerations in North China
Authors: Li Bing , Sun Xiaoduan , He Yulong , Zhang Meng
Published: March 2024

Expressways in urban agglomerations are important in connecting cities, thus attracting great attention from researchers in the expressways risk assessment. However, there is a lack of safety assessment models suitable for the characteristics of expressways in Chinese urban agglomerations, and the nature and mode of dynamic risks on Chinese highways are still unclear. Therefore, this study adopts the Adaptive Neural Fuzzy Inference System (ANFIS) and the method of decision tree, combined with data from the Beijing section of the Beijing Harbin Expressway, to model the risk of accident-prone highways in urban agglomerations. To determine the optimal model, we evaluated the model’s bias at different time intervals. In addition, key factors affecting highway safety were analyzed, providing scientific support for the risk prevention of highways in urban agglomerations in China.
Simple Lévy α-Stable Model Analysis of Elastic pp and pp¯ Low-|t| Data from SPS to LHC Energies
Authors: Csörgő Tamás , Hegyi Sándor , Szanyi István
Published: March 2024

A simple Lévy α-stable (SL) model is used to describe the data on elastic pp and pp¯ scattering at low-|t| from SPS energies up to LHC energies. The SL model is demonstrated to describe the data with a strong non-exponential feature in a statistically acceptable manner. The energy dependence of the parameters of the model is determined and analyzed. The Lévy α parameter of the model has an energy-independent value of 1.959 ± 0.002 following from the strong non-exponential behavior of the data. We strengthen the conclusion that the discrepancy between TOTEM and ATLAS elastic pp differential cross section measurements arises only in the normalization and not in the shape of the distribution of the data as a function of t. We find that the slope parameter has different values for pp and pp¯ elastic scattering at LHC energies. This may be the effect of the odderon exchange or the jump in the energy dependence of the slope parameter in the energy interval 3 GeV ≲s≲ 4 GeV.
Re-Examination of the Effect of Pairing Gaps on Gamow–Teller Strength Distributions and β-Decay Rates
Authors: Nabi Jameel-Un , Riaz Muhammad , Mehmood Arslan
Published: March 2024

β-decay is one of the key factors for understanding the r-process and evolution of massive stars. The Gamow–Teller (GT) transitions drive the β-decay process. We employ the proton–neutron quasiparticle random phase approximation (pn-QRPA) model to calculate terrestrial and stellar β-decay rates for 50 top-ranked nuclei possessing astrophysical significance according to a recent survey. The model parameters of the pn-QRPA model affect the predicted results of β-decay. The current study investigates the effect of nucleon–nucleon pairing gaps on charge-changing transitions and the associated β decay rates. Three different values of pairing gaps, namely TF, 3TF, and 5TF, were used in our investigation. It was concluded that both GT strength distributions and half-lives are sensitive to pairing gap values. The 3TF pairing gap scheme, in our chosen nuclear model, resulted in the best prediction with around 80% of the calculated half-lives within a factor 10 of the measured ones. The 3TF pairing scheme also led to the calculation of the biggest β-decay rates in stellar matter.
Xanthomonas Phage PBR31: Classifying the Unclassifiable
Authors: Tarakanov Rashit I. , Evseev Peter V. , Vo Ha T. N. , Troshin Konstantin S. , Gutnik Daria I. , Ignatov Aleksandr N. , Toshchakov Stepan V. , Miroshnikov Konstantin A. , Jafarov Ibrahim H. , Dzhalilov Fevzi S.-U.
Published: March 2024

The ability of bacteriophages to destroy bacteria has made them the subject of extensive research. Interest in bacteriophages has recently increased due to the spread of drug-resistant bacteria, although genomic research has not kept pace with the growth of genomic data. Genomic analysis and, especially, the taxonomic description of bacteriophages are often difficult due to the peculiarities of the evolution of bacteriophages, which often includes the horizontal transfer of genes and genomic modules. The latter is particularly pronounced for temperate bacteriophages, which are capable of integration into the bacterial chromosome. Xanthomonas phage PBR31 is a temperate bacteriophage, which has been neither described nor classified previously, that infects the plant pathogen Xanthomonas campestris pv. campestris. Genomic analysis, including phylogenetic studies, indicated the separation of phage PBR31 from known classified bacteriophages, as well as its distant relationship with other temperate bacteriophages, including the Lederbervirus group. Bioinformatic analysis of proteins revealed distinctive features of PBR31, including the presence of a protein similar to the small subunit of D-family DNA polymerase and advanced lysis machinery. Taxonomic analysis showed the possibility of assigning phage PBR31 to a new taxon, although the complete taxonomic description of Xanthomonas phage PBR31 and other related bacteriophages is complicated by the complex evolutionary history of the formation of its genome. The general biological features of the PBR31 phage were analysed for the first time. Due to its presumably temperate lifestyle, there is doubt as to whether the PBR31 phage is appropriate for phage control purposes. Bioinformatics analysis, however, revealed the presence of cell wall-degrading enzymes that can be utilised for the treatment of bacterial infections.
Machine Learning Techniques for Canine Myxomatous Mitral Valve Disease Classification: Integrating Anamnesis, Quality of Life Survey, and Physical Examination
Authors: Engel-Manchado Javier , Montoya-Alonso José Alberto , Doménech Luis , Monge-Utrilla Oscar , Reina-Doreste Yamir , Matos Jorge Isidoro , Caro-Vadillo Alicia , García-Guasch Laín , Redondo José Ignacio
Published: March 2024

Myxomatous mitral valve disease (MMVD) is a prevalent canine cardiac disease typically diagnosed and classified using echocardiography. However, accessibility to this technique can be limited in first-opinion clinics. This study aimed to determine if machine learning techniques can classify MMVD according to the ACVIM classification (B1, B2, C, and D) through a structured anamnesis, quality of life survey, and physical examination. This report encompassed 23 veterinary hospitals and assessed 1011 dogs for MMVD using the FETCH-Q quality of life survey, clinical history, physical examination, and basic echocardiography. Employing a classification tree and a random forest analysis, the complex model accurately identified 96.9% of control group dogs, 49.8% of B1, 62.2% of B2, 77.2% of C, and 7.7% of D cases. To enhance clinical utility, a simplified model grouping B1 and B2 and C and D into categories B and CD improved accuracy rates to 90.8% for stage B, 73.4% for stages CD, and 93.8% for the control group. In conclusion, the current machine-learning technique was able to stage healthy dogs and dogs with MMVD classified into stages B and CD in the majority of dogs using quality of life surveys, medical history, and physical examinations. However, the technique faces difficulties differentiating between stages B1 and B2 and determining between advanced stages of the disease.
A Retrospective Study (2015–2020) on the Risk Factors Associated with the Persistence and Spread of Brucellosis in Buffalo Farms in Caserta Province, Italy
Authors: Ottaiano Maria , Brunetti Roberta , Limone Antonio , Capone Maria Rosaria , Di Giuseppe Alessandra , Conte Annamaria , De Massis Fabrizio , Chiodini Paolo , Signoriello Simona , Baldi Loredana , De Carlo E.
Published: March 2024

Bovine and bubaline brucellosis is still present in some regions of Italy. Although control and eradication measures have been implemented for several years, the brucellosis situation remains problematic in the Campania region. The infection is present in the provinces of Salerno and Caserta, with the latter experiencing a drastic increase in the prevalence and incidence of infection in buffalo species (Bubalus bubalis) in recent years. The brucellosis eradication plan in Italy is subject to the European co-financing system, and failure to achieve the objectives of the plan has resulted in economic cuts for the Campania Region for years. This study aimed to evaluate the possible risk factors associated with the spread and persistence of brucellosis infection on buffalo farms in the Province of Caserta. The results of official controls carried out from 2015 to 2020 on the buffalo farms of the Province were analyzed. Statistical analysis was performed by means of the R software (version 4.1.0) on a final dataset consisting of 4583 observations. The possible association between covariates and outcome (presence/absence of infection) was evaluated (T-Fisher and Wilcoxon). A logistic regression model with mixed effects was carried out. The study shows that the risk of infection is statistically associated with the density of farms per square km and previous notifications of abortions on the same farms. Furthermore, animal movements constitute a risk factor for the permanence of infection over time (OR > 1), and herds already infected prior to 2015 were seen to have an almost three-fold higher risk of developing the disease (OR = 3.35).
Design and Validation of RT-PCR Assays to Differentiate Salmonella Vaccine Strains from Wild-Type Field Isolates
Authors: Ceyssens Pieter-Jan , Mueller-Doblies Doris , Mattheus Wesley
Published: March 2024

The timely differentiation of the AviPro Salmonella VAC T and VAC E strains from the wild-type Salmonella enterica ser. Typhimurium and ser. Enteritidis isolates is crucial for effectively monitoring veterinary isolates. Currently, the distinction between field and vaccine strains has been conducted routinely via phenotypic antimicrobial resistance testing since the vaccines were first introduced more than 20 years ago, and the differentiation based on the antimicrobial resistance profile is still a valid and well-established method. However, an alternative method was sought for those laboratories that prefer a PCR-based method for logistic and/or operational reasons. In this study, we developed two triplex Real-Time PCR reactions that targeted conserved and specific mutations and, therefore, enabled the reliable differentiation of field and vaccine strains. To validate the effectiveness of both assays, we extensively tested them on a dataset consisting of 405 bacterial strains. The results demonstrated a 100% sensitivity and specificity for distinguishing both Salmonella enterica ser. Typhimurium and Enteritidis, although a confirmed culture is required.
Numerical Analysis of Water–Sediment Flow Fields within the Intake Structure of Pumping Station under Different Hydraulic Conditions
Authors: Xu Cundong , Tian Junjiao , Wang Guoxia , Lian Haidong , Wang Rongrong , Hu Xiaomeng
Published: March 2024

The vortices, backflow, and siltation caused by sediment-laden flow are detrimental to the safe and efficient operation of pumping stations. To explore the effects of water–sediment two-phase flow on the velocity field, vorticity field, and sediment distribution within intake structures, field tests and numerical simulations were conducted in this study with consideration for the sediment concentration, flow rate, and start-up combination. We applied a non-contact laser scanner and ultrasonic Doppler velocimetry to obtain the field data and reverse modeling of the three-dimensional model of the intake structure under siltation. A multiphase flow model based on the Euler–Euler approach combined with the k-ε turbulence model was adopted for numerical simulation under 10 working conditions, and the reliability was verified with field data. The results indicate that sediment promotes the evolution of coaxial vortices into larger-scale spiral vortices along the water depth, and the process of sediment deposition is controlled by the range, intensity, and flow velocity of the backflow zone. Furthermore, the maximum volume fraction of the near-bottom sediment increased by 202.01% compared to the initial state. The increase in flow rate exacerbates the turbulence of the flow field. Although the increase in sediment concentration benefits the flow diffusion, it further promotes sediment deposition. This study provides a new idea for modeling complex surfaces and considers different operating conditions. It can serve as a scientific reference for the structural optimization and anti-siltation design of similar water-conservancy projects.
Geospatial Analysis of Transmissivity and Uncertainty in a Semi-Arid Karst Region
Authors: Gonçalves Thiago dos Santos , Klammler Harald , Bastos Leal Luíz Rogério
Published: March 2024

Aquifer properties, such as hydraulic transmissivity T and its spatial variability, are fundamental for sustainable groundwater exploitation in arid regions. Especially in karst aquifers, spatial variability can be considerable, and the application of geostatistical methods allows for spatial interpolation and mapping based on observations combined with the quantification of uncertainties. Moreover, direct measurements of T are typically scarce, while those of specific capacity Sc are more frequent. In this study, we establish the linear regression relationship between the logarithms of T and Sc measured in 51 wells in a semi-arid karst region in Northeastern Brazil. This relationship is used to estimate empirical values logTemp based on measurements of logSc at 269 wells. LogTemp values are found to be normally distributed with an isotropic variogram of a significant nugget effect (attributed to local-scale karst features) and approximately 10 km range (attributed to larger-scale gradual changes in karst feature density). Ordinary kriging cross-validation indicates an optimum number of 25 neighboring wells for interpolation, which is used in a conditional sequential Gaussian simulation (SGSIM) to generate 500 realizations of logTemp with respective maps of standard deviations and probabilities of (not) exceeding threshold values. High-transmissivity areas mostly coincide with karstified river valleys, while low-transmissivity areas occur toward the edges where aquifer thickness decreases. The resulting transmissivity maps are relevant for optimizing regional water management strategies, which includes stochastic approaches where transmissivity realizations can be used to parameterize multiple runs of numerical groundwater models.
Simulating Aquifer for Nitrate Ion Migration Processes in Soil
Authors: Orbuleţ Oanamari Daniela , Modrogan Cristina , Covaliu-Mierla Cristina-Ileana
Published: March 2024

The objective of this study was to explore the removal of nitrate ions from groundwater by employing dynamic permeable reactive barriers (PRBs) with A400-nZVI. This research aimed to determine the parameters of the barrier and evaluate its overall capacity to retain nitrate ions during percolation with a potassium nitrate solution. The process involves obtaining zerovalent iron (nZVI) nanoparticles, which were synthesized and incorporated onto an anionic resin support material (A400) through the reduction reaction of ferrous ions with sodium borohydride (NaBH4). This is achieved by preparing a ferrous sulfate solution, contacting it with the ion exchange resin at various solid–liquid mass ratios and gradually adding sodium borohydride under continuous stirring in an oxygen-free environment to create the A400-nZVI barrier. The results of the study, focusing on the development of permeable reactive barriers composed of nano zero-valent iron and ion exchangers, highlight the significant potential of water treatment processes when appropriately sized. The research specifically assesses the effectiveness of NO3− removal by using the A400-nZVI permeable reactive barrier, conducting laboratory tests that simulate a naturally stratified aquifer with high nitrate contamination.
Nitrite Degradation by a Novel Marine Bacterial Strain Pseudomonas aeruginosa DM6: Characterization and Metabolic Pathway Analysis
Authors: Chen Zhe , Yu Wenying , Zhan Yingjian , Chen Zheng , Han Tengda , Song Weiwei , Zhou Yueyue
Published: March 2024

High concentrations of nitrite in marine aquaculture wastewater not only pose a threat to the survival and immune systems of aquatic organisms but also contribute to eutrophication, thereby impacting the balance of coastal ecosystems. Compared to traditional physical and chemical methods, utilizing microorganism-mediated biological denitrification is a cost-effective and efficient solution. However, the osmotic pressure changes and salt-induced enzyme precipitation in high-salinity seawater aquaculture environments may inhibit the growth and metabolism of freshwater bacterial strains, making it more suitable to select salt-tolerant marine microorganisms for treating nitrite in marine aquaculture wastewater. In this study, a salt-tolerant nitrite-degrading bacterium, designated as DM6, was isolated from the seawater (salinity of 25–30‰) of Portunus trituberculatus cultivation. The molecular identification of strain DM6 was conducted using 16S rRNA gene sequencing technology. The impacts of various environmental factors on the nitrite degradation performance of strain DM6 were investigated through single-factor and orthogonal experiments, with the selected conditions considered to be the key factors affecting the denitrification efficiency of microorganisms in actual wastewater treatment. PCR amplification of key genes involved in the nitrite metabolism pathway of strain DM6 was conducted, including denitrification pathway-related genes narG, narH, narI, nirS, and norB, as well as assimilation pathway-related genes nasC, nasD, nasE, glnA, gltB, gltD, gdhB, and gdhA. The findings indicated that strain DM6 is classified as Pseudomonas aeruginosa and exhibits efficient nitrite degradation even under a salinity of 35‰. The optimal nitrite degradation efficiency of DM6 was observed when using sodium citrate as the carbon source, a C/N ratio of 20, a salinity of 13‰, pH 8.0, and a temperature of 35 °C. Under these conditions, DM6 could completely degrade an initial nitrite concentration of 156.33 ± 1.17 mg/L within 36 h. Additionally, the successful amplification of key genes involved in the nitrite denitrification and assimilation pathways suggests that strain DM6 may possess both denitrification and assimilation pathways for nitrite degradation simultaneously. Compared to freshwater strains, strain DM6 demonstrates higher salt tolerance and exhibits strong nitrite degradation capability even at high concentrations. However, it may be more suitable for application in the treatment of wastewater from marine aquaculture systems during summer, high-temperature, or moderately alkaline conditions.
Many-Objective Hierarchical Pre-Release Flood Operation Rule Considering Forecast Uncertainty
Authors: Liu Yongqi , Hou Guibing , Wang Baohua , Xu Yang , Tian Rui , Wang Tao , Qin Hui
Published: March 2024

Flood control operation of cascade reservoirs is an important technology to reduce flood disasters and increase economic benefits. Flood forecast information can help reservoir managers make better use of flood resources and reduce flood risks. In this paper, a hierarchical pre-release flood operation rule considering the flood forecast and its uncertainty information is proposed for real-time flood control. A many-objective optimization model considering the cascade reservoir’s power generation objective, flood control objective, and navigation objective is established. Then, a region search evolutionary algorithm is applied to optimize the many-objective optimization model in a real-world case study upstream of the Yangtze River basin. The optimization experimental results show that the region search evolutionary algorithm can balance convergence and diversity well, and the HV value is 40% higher than the MOEA/D algorithm. The simulation flood control results of cascade reservoirs upstream of the Yangtze River demonstrate that the optimized flood control rule can increase the average multi-year power generation of cascade reservoirs by a maximum of 27.72 × 108 kWh under the condition of flood control safety. The rules proposed in this paper utilize flood resources by identifying runoff forecast information, and pre-release to the flood limit level 145 m before the big flood occurs, so as to ensure the safety downstream and the dam’s own flood control and provide reliable decision support for reservoir managers.
Evaluating the Effectiveness of Rainwater Storage Tanks Based on Different Enabling Rules
Authors: Gong Yongwei , Meng Ge , Tian Kun , Li Zhuolun
Published: March 2024

A proposed method for analyzing the effectiveness of rainwater storage tanks (RWSTs) based on various enabling rule scenarios has been proposed to address the issue of incomplete strategies and measures for controlling excessive rainwater runoff. Three enabling rules for RWSTs have been proposed, as follows: enabling rule I, which involves activation upon rainfall; enabling rule II, which requires the rainfall intensity to reach a predetermined threshold; and enabling rule III, which necessitates the cumulative rainfall to reach a set threshold. In order to assess the effectiveness of these enabling rules when reducing the total volume of rainwater outflow (TVRO), peak flow rate (PFR), and peak flow velocity (PFV), a comparative analysis was conducted to determine which enabling rule yielded the most optimal control effect. The findings indicate that the enabling rule I is responsible for determining the optimal unit catchment’s rainfall capture volume (UCRCV), which is measured at 300 m3·ha−1. Additionally, the control effect of the TVRO of the RWSTs remains largely unaffected by the peak proportion coefficient. Enabling rule II establishes the optimal activation threshold at a rainfall intensity of 1 mm·min−1; under this enabling rule, RWSTs demonstrate the most effective control over PFR and PFV. Enabling rule III enables the determination of the optimal activation threshold, which is set at a cumulative rainfall of 20 mm; under this enabling rule, the implementation of the RWST technique yields the most effective control over the TVRO. Consequently, the optimal rainwater runoff reduction plan for the study area has been successfully determined, providing valuable guidance for the implementation of scientific and reasonable optimal runoff management.
Calibration of Hybrid-Maize Model for Simulation of Soil Moisture and Yield in Production Corn Fields
Authors: Amori Anthony A. , Abimbola Olufemi P. , Franz Trenton E. , Rudnick Daran , Iqbal Javed , Yang Haishun
Published: March 2024

Model calibration is essential for acceptable model performance and applications. The Hybrid-Maize model, developed at the University of Nebraska-Lincoln, is a process-based crop simulation model that simulates maize growth as a function of crop and field management and environmental conditions. In this study, we calibrated and validated the Hybrid-Maize model using soil moisture and yield data from eight commercial production fields in two years. We used a new method for the calibration and multi-parameter optimization (MPO) based on kriging with modified criteria for selecting the parameter combinations. The soil moisture-related parameter combination (SM-PC3) improved simulations of soil water dynamics, but improvement in model performance is still required. The grain yield-related parameter combination significantly improved the yield simulation. We concluded that the calibrated model is good enough for irrigation water management at the field scale. Future studies should focus on improving the model performance in simulating total soil water (TSW) dynamics at different soil depths by including more soil water processes in a more dynamic manner.