bluuebunny/crossref_metadata_2025 huggingface dataset:
The Challenge of Integrating Seismic and Energy Retrofitting of Buildings: An Opportunity for Sustainable Materials?
Authors: Penazzato Luca , Illampas Rogiros , Oliveira Daniel V.
Published: April 2024

Recent earthquakes and escalating energy demands are exposing building stock deficiencies, particularly in terms of seismic resilience and energy efficiency. Many aged constructions do not fulfil current regulations both in terms of seismic and thermal design principles, thus requiring suitable retrofitting solutions. Integrated approaches for concurrent seismic and energy renovation have emerged as promising strategies in recent years, offering holistic solutions that optimize interventions and maximize benefits. While these combined methods hold significant potential for practical applications, there remain opportunities for further research to enhance their advantages. Furthermore, addressing climate concerns requires concentrated effort within the construction sector, where synergetic refurbishments can serve a dual purpose by reducing emissions and promoting the use of more sustainable materials. This study discusses strategies proposed in the literature for integrated retrofitting, considering their environmental impact, both in terms of energy performance and embodied carbon. The overview shows the innovation potential for the development of materials and systems combining acceptable performance with eco-friendly attributes. Yet, their application in integrated retrofitting systems, either as structural components or insulators, is still limited, underscoring the need for continued investigation and advancement. This paper concludes with recommendations to inspire further research and advancements in this critical field.
By-Product Valorization as a Means for the Brewing Industry to Move toward a Circular Bioeconomy
Authors: Pasquet Paul-Loup , Villain-Gambier Maud , Trébouet Dominique
Published: April 2024

Beer production consumes significant amounts of water, energy, and raw materials, and results in the production of various by-products, including wastewater, brewers’ spent grain, yeast and hop. To lower its environmental footprint, by-products may be reclaimed or valorized in agro-food, cosmetic, material, chemical industries, etc. According to most recent research, breweries have the potential to become biorefineries, as they can extract diverse valuable plant-based compounds such as carbohydrates, proteins, lipids, phenolic compounds, platform chemicals, and biopolymers. These biomolecules possess bioactive and physicochemical properties, which can be enhanced through recovery processes. Brewery by-products may be utilized in various industries within the bioeconomy frame. In agro-food systems, extracts can increase final products’ techno-functionalities. Such additives can also help in creating marketing labels such as clean-label healthy, which can further attract potential customers. Businesses can gain economic and socio-environmental benefits by implementing sustainable practices, which can also improve their corporate image. This article outlines recent advancements in the processing and valorization of brewery by-products, ultimately defining an up-to-date, sustainable strategy for clean beer production.
A Time Series Prediction Model for Wind Power Based on the Empirical Mode Decomposition–Convolutional Neural Network–Three-Dimensional Gated Neural Network
Authors: Guo Zhiyong , Wei Fangzheng , Qi Wenkai , Han Qiaoli , Liu Huiyuan , Feng Xiaomei , Zhang Minghui
Published: April 2024

In response to the global challenge of climate change and the shift away from fossil fuels, the accurate prediction of wind power generation is crucial for optimizing grid operations and managing energy storage. This study introduces a novel approach by integrating the proportional–integral–derivative (PID) control theory into wind power forecasting, employing a three-dimensional gated neural (TGN) unit designed to enhance error feedback mechanisms. The proposed empirical mode decomposition (EMD)–convolutional neural network (CNN)–three-dimensional gated neural network (TGNN) framework starts with the pre-processing of wind data using EMD, followed by feature extraction via a CNN, and time series forecasting using the TGN unit. This setup leverages proportional, integral, and differential control within its architecture to improve adaptability and response to dynamic wind patterns. The experimental results show significant improvements in forecasting accuracy; the EMD–CNN–TGNN model outperforms both traditional models like autoregressive integrated moving average (ARIMA) and support vector regression (SVR), and similar neural network approaches, such as EMD–CNN–GRU and EMD–CNN–LSTM, across several metrics including mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and coefficient of determination (R2). These advancements substantiate the model’s effectiveness in enhancing the precision of wind power predictions, offering substantial implications for future renewable energy management and storage solutions.
Impacts of Technological Innovation on Product and Service Quality and Sustainable Financial, Environmental and Social Results in the Aeronautics Sector: A Brazilian Case Study
Authors: Santos Manoela Pastor , Berssaneti Fernando Tobal
Published: April 2024

As a result of technological advances and the increase in the quantity and diversity of companies operating in the market, an increasingly competitive scenario emerges in which innovative approaches have become important for the survival and visibility of companies in the market. Furthermore, technological innovation can be considered a source of creation of positive or negative financial results and environmental and social impacts, which requires verification. Thus, in this article, results are presented on the impacts of innovation on quality; results are also given in relation to aspects related to financial, environmental and social impacts. The research is a qualitative analysis based on a case study methodology: the focus comprises different companies and areas of a large Brazilian group in the aeronautical industry, which operates in different countries around the world. Professionals involved with technological innovations in these companies were interviewed and the results obtained were utilized to validate and corroborate the research. After conducting the survey, it can be seen that innovation can help in adaptation, meeting the new demands and opportunities of the market, while impacting aspects of quality: conformity to the requirements of the market where the company operates; product, service and/or process performance; customer satisfaction and loyalty. The meaning of quality may vary according to the business objectives of a given company.
How Does Digital Transformation Improve Corporate Carbon Emission Reduction Performance? An Empirical Study on Data from Listed Companies in China
Authors: Guo Li , Tang Min
Published: April 2024

Against the backdrop of global carbon reduction, China, as the country with the highest carbon emissions, must implement carbon reduction actions more efficiently to promote the sustainable development of the global environment. Balancing their economic and environmental benefits has become an important issue for corporations, as they are crucial entities in the final implementation of carbon reduction efforts. This study selects the data of listed companies in China from 2012 to 2022 and develops a two-way fixed-effects model to verify the effect of digital transformation on corporate carbon reduction performance. The study found that digital transformation can positively promote corporate carbon reduction performance and shows heterogeneity under different conditions. Green technology innovation plays a mediating role in the relationship between digital transformation and corporate carbon reduction performance. Furthermore, environmental subsidies play a positive moderating role in the relationship between digital transformation and green technology innovation, constituting a moderated mediation model. Meanwhile, tax reduction incentives play a positive moderating role in the relationship between digital transformation and promoting corporate carbon reduction performance. This study provides empirical suggestions for balancing economic and environmental benefits for 5323 Chinese listed companies and global corporations from both internal and external perspectives, emphasizing the potential for digital transformation to drive both commercial success and environmental stewardship in the pursuit of sustainable development goals.
Social and Spatial Inequalities during COVID-19: Evidence from France and the Need for a New Sustainable Urban and Regional Development Paradigm
Authors: Maya Roula
Published: April 2024

This study examines the impact of social and spatial inequalities on the spread of COVID-19 and the efficacy of lockdown measures in French regions during the third wave (22 March and 3 May 2021), with a focus on population density and poverty. It based on data from French government websites, adopting quantitative methods including the Pearson Coefficient and One-Way ANOVA. The results indicate a significant correlation between population density and COVID-19 deaths in 92 departments (R = 0.695), which is stronger than the correlation between density and infection rates (R = 0.633, p < 0.001). In the 25 most affected departments, this pattern shifts, with a weaker correlation between density and deaths (R = 0.644) compared to density/infections (R = 0.716, p < 0.001). Although insightful, these statistics do not capture regional disparities. A minor correlation between poverty and death rates was recorded in French regions. Spatial observations showed that areas exceeding the national poverty average experienced higher infection/death rates. The lockdowns were effective, leading to a reduction (51.7%) in infections. The present results showed that there is a significant need for a new social contract based on a new urban and regional paradigm focused on socio-spatial equality and Sustainable Development Goals locally and globally, a vital task for policymakers, planners, and researchers.
The Mathematical Modeling, Diffusivity, Energy, and Enviro-Economic Analysis (MD3E) of an Automatic Solar Dryer for Drying Date Fruits
Authors: Metwally Khaled A. , Oraiath Awad Ali Tayoush , Elzein I. M. , El-Messery Tamer M. , Nyambe Claude , Mahmoud Mohamed Metwally , Abdeen Mohamed Anwer , Telba Ahmad A. , Khaled Usama , Beroual Abderrahmane , Elwakeel Abdallah Elshawadfy
Published: April 2024

Date fruit drying is a process that consumes a significant amount of energy due to the long duration required for drying. To better understand how moisture flows through the fruit during drying and to speed up this process, drying studies must be conducted in conjunction with mathematical modeling, energy analysis, and environmental economic analysis. In this study, twelve thin-layer mathematical models were designed utilizing experimental data for three different date fruit varieties (Sakkoti, Malkabii, and Gondaila) and two solar drying systems (automated solar dryer and open-air dryer). These models were then validated using statistical analysis. The drying period for the date fruit varieties varied between 9 and 10 days for the automated solar dryer and 14 to 15 days for open-air drying. The moisture diffusivity coefficient values, determined using Fick’s second law of diffusion model, ranged from 7.14 × 10−12 m2/s to 2.17 × 10−11 m2/s. Among the twelve thin-layer mathematical models, we chose the best thin drying model based on a higher R2 and lower χ2 and RMSE. The Two-term and Modified Page III models delivered the best moisture ratio projections for date fruit dried in an open-air dryer. For date fruit dried in an automated solar dryer, the Two-term Exponential, Newton (Lewis), Approximation diffusion or Diffusion Method, and Two-term Exponential modeling provided the best moisture ratio projections. The energy and environmental study found that the particular amount of energy used varied from 17.936 to 22.746 kWh/kg, the energy payback time was 7.54 to 7.71 years, and the net CO2 mitigation throughout the lifespan ranged from 8.55 to 8.80 tons. Furthermore, economic research showed that the automated solar dryer’s payback period would be 2.476 years.
Symmetrical and Asymmetrical Sampling Audit Evidence Using a Naive Bayes Classifier
Authors: Sheu Guang-Yih , Liu Nai-Ru
Published: April 2024

Taiwan’s auditors have suffered from processing excessive audit data, including drawing audit evidence. This study advances sampling techniques by integrating machine learning with sampling. This machine learning integration helps avoid sampling bias, keep randomness and variability, and target risker samples. We first classify data using a Naive Bayes classifier into some classes. Next, a user-based, item-based, or hybrid approach is employed to draw audit evidence. The representativeness index is the primary metric for measuring its representativeness. The user-based approach samples data symmetrically around the median of a class as audit evidence. It may be equivalent to a combination of monetary and variable samplings. The item-based approach represents asymmetric sampling based on posterior probabilities for obtaining risky samples as audit evidence. It may be identical to a combination of non-statistical and monetary samplings. Auditors can hybridize those user-based and item-based approaches to balance representativeness and riskiness in selecting audit evidence. Three experiments show that sampling using machine learning integration has the benefits of drawing unbiased samples; handling complex patterns, correlations, and unstructured data; and improving efficiency in sampling big data. However, the limitations are the classification accuracy output by machine learning algorithms and the range of prior probabilities.
The Additional Role of F18-FDG PET/CT in Characterizing MRI-Diagnosed Tumor Deposits in Locally Advanced Rectal Cancer
Authors: Roef Mark J. , van den Berg Kim , Rutten Harm J. T. , Burger Jacobus , Nederend Joost
Published: April 2024

Rationale: F18-FDG PET/CT may be helpful in baseline staging of patients with high-risk LARC presenting with vascular tumor deposits (TDs), in addition to standard pelvic MRI and CT staging. Methods: All patients with locally advanced rectal cancer that had TDs on their baseline MRI of the pelvis and had a baseline F18-FDG PET/CT between May 2016 and December 2020 were included in this retrospective study. TDs as well as lymph nodes identified on pelvic MRI were correlated to the corresponding nodular structures on a standard F18-FDG PET/CT, including measurements of nodular SUVmax and SUVmean. In addition, the effects of partial volume and spill-in on SUV measurements were studied. Results: A total number of 62 patients were included, in which 198 TDs were identified as well as 106 lymph nodes (both normal and metastatic). After ruling out partial volume effects and spill-in, 23 nodular structures remained that allowed for reliable measurement of SUVmax: 19 TDs and 4 LNs. The median SUVmax between TDs and LNs was not significantly different (p = 0.096): 4.6 (range 0.8 to 11.3) versus 2.8 (range 1.9 to 3.9). For the median SUVmean, there was a trend towards a significant difference (p = 0.08): 3.9 (range 0.7 to 7.8) versus 2.3 (range 1.5 to 3.4). Most nodular structures showing either an SUVmax or SUVmean ≥ 4 were characterized as TDs on MRI, while only two were characterized as LNs. Conclusions: SUV measurements may help in separating TDs from lymph node metastases or normal lymph nodes in patients with high-risk LARC.
Spatiotemporal Analysis of Malaria Transmission in the Autonomous Indigenous Regions of Panama, Central America, 2015–2022
Authors: Cumbrera Alberto , Calzada José Eduardo , Chaves Luis Fernando , Hurtado Lisbeth Amarilis
Published: April 2024

Despite ongoing efforts for elimination, malaria continues to be a major public health problem in the Republic of Panama. For effective elimination, it is key that malaria foci and areas of high transmission are identified in a timely manner. Here, we study malaria transmission records for the 2015–2022 period, a time when cases have increased by a factor of ten. Using several methods to study spatial and spatiotemporal malaria confirmed case clusters at the level of localities, including LISA and scan, we found that cases are clustered across indigenous villages located within the autonomous indigenous regions of Ngäbe–Buglé, Guna Yala, and Embera, with the latter on the eastern border of Panama (with Colombia). We discuss the different factors that might be shaping the marked increase in malaria transmission associated with these clusters, which include an inflow of malaria-exposed migrating populations hoping to reach the USA, insufficient health services, and the lack of culturally sensitive actionable tools to reduce malaria exposure among the ethnically diverse and impoverished indigenous populations of Panama.
Comparative Study of Colorimetric In Situ Hybridization and Quantitative Real-Time Polymerase Chain Reaction for Diagnosis of Infection by Leishmania infantum in Dogs in Formalin-Fixed and Paraffin-Embedded Skin
Authors: Silva Ricardo Gonçalves , Kiupel Matti , Langohr Ingeborg Maria , Wise Annabel , Pereira Sandro Antonio , Gonçalves Natália Pedra , da Conceição Greice Maria Silva , Ferreira Luiz Cláudio , de Campos Monique Paiva , Miranda Luciana de Freitas Campos , Figueiredo Fabiano Borges , de Oliveira Raquel de Vasconcellos Carvalhaes , Keidel Lucas , Menezes Rodrigo Caldas
Published: April 2024

The zoonotic visceral leishmaniasis is caused by the protozoan Leishmania infantum and dogs are reservoirs for this parasite. For the diagnosis of Leishmania at the species level in dogs in formalin-fixed, paraffin-embedded skin (FFPES) samples, colorimetric in situ hybridization (CISH) and quantitative real-time polymerase chain reaction (qPCR) are options, but their sensitivities are not well established. Therefore, the aim of this study was to determine the sensitivity of these two techniques in FFPES for the diagnosis of the L. infantum infection in dogs using culture as the reference standard. The FFPES of 48 dogs with cutaneous infection by L. infantum confirmed by culture and by multilocus enzyme electrophoresis were examined by CISH and qPCR using specific probes for L. infantum. The sensitivities of qPCR, CISH and their combination were, respectively, 77.0%, 58.0% and 83.3%. The sensitivities of qPCR in dogs with and without clinical signs were, respectively, 74.2% and 82.4%. The sensitivities of CISH in dogs with and without clinical signs were, respectively, 61.3% and 52.9%. The CISH and qPCR showed satisfactory sensitivities for the diagnosis of L. infantum in the FFPES of dogs, even in dogs without clinical signs, and their combination increases the sensitivity for this diagnosis.
The Ontology of Urban Governance: A Framework for Pathways to Sustainable Urban Transition
Authors: Ghosh Mitra Susanna , Chandra Ajay , Ramaprasad Arkalgud
Published: April 2024

Evidence on urban governance has expanded but is fragmented and inadequate. It fails to articulate the complexity of urban governance in a way that would facilitate effective urban transitions. Using a conceptual-cognitive lens, this article describes a method to move away from governance solutions based on functional silos to those based on multidimensional, sustainable systems. Based on a combination of concepts from public policy, governance, public administration, and urban service management, it frames the problem of urban governance as a comprehensive conceptual-cognitive map of the domain. The study validates the framework through expert feedback and the mapping of the literature on urban governance in India between 2018 and 2020. The monad map and theme map emphasise the ontology’s applicability as a methodological tool for evidence generation. The analysis reveals a need to reconfigure urban governance pathways to work towards a sustainable future. The article concludes by offering new conceptual constructs of governance pathways to enhance the policies and practices that shape such transitions.
PCV2 Induced Endothelial Derived IL-8 Affects MoDCs Maturation Mainly via NF-κB Signaling Pathway
Authors: Zhang Mengyu , Xu Weicheng , Yang Ning , Li Zhuowei , Zhou Shuanghai , Liu Xuewei , Wang Jianfang , Li Huanrong
Published: April 2024

Porcine circovirus type 2 (PCV2) infection can cause immunosuppressive diseases in pigs. Vascular endothelial cells (VECs), as the target cells for PCV2, play an important role in the immune response and inflammatory regulation. Endothelial IL-8, which is produced by porcine hip artery endothelial cells (PIECs) infected with PCV2, can inhibit the maturation of monocyte-derived dendritic cells (MoDCs). Here, we established a co-culture system of MoDCs and different groups of PIECs to further investigate the PCV2-induced endothelial IL-8 signaling pathway that drives the inhibition of MoDC maturation. The differentially expressed genes related to MoDC maturation were mainly enriched in the NF-κB and JAK2-STAT3 signaling pathways. Both the NF-κB related factor RELA and JAK2-STAT3 signaling pathway related factors (IL2RA, JAK, STAT2, STAT5, IL23A, IL7, etc.) decreased significantly in the IL-8 up-regulated group, and increased significantly in the down-regulated group. The expression of NF-κB p65 in the IL-8 up-regulated group was reduced significantly, and the expression of IκBα was increased significantly. Nuclear translocation of NF-κB p65 was inhibited, while the nuclear translocation of p-STAT3 was increased in MoDCs in the PCV2-induced endothelial IL-8 group. The results of treatment with NF-κB signaling pathway inhibitors showed that the maturation of MoDCs was inhibited and the expression of IL-12 and GM-CSF at mRNA level were lower. Inhibition of the JAK2-STAT3 signaling pathway had no significant effect on maturation, and the expression of IL-12 and GM-CSF at mRNA level produced no significant change. In summary, the NF-κB signaling pathway is the main signaling pathway of MoDC maturation, and is inhibited by the PCV2-induced up-regulation of endothelial-derived IL-8.
Characterizing Infections in Two Epidemic Waves of SARS-CoV-2 Omicron Variants: A Cohort Study in Guangzhou, China
Authors: Qu Lin , Xie Chunyan , Qiu Ming , Yi Lina , Liu Zhe , Zou Lirong , Hu Pei , Jiang Huimin , Lian Huimin , Yang Mingda , Yang Haiyi , Zeng Huiling , Chen Huimin , Zhao Jianguo , Xiao Jianpeng , He Jianfeng , Yang Ying , Chen Liang , Li Baisheng , Sun Jiufeng , Lu Jing
Published: April 2024

Background: After the adjustment of COVID-19 epidemic policy, mainland China experienced two consecutive waves of Omicron variants within a seven-month period. In Guangzhou city, as one of the most populous regions, the viral infection characteristics, molecular epidemiology, and the dynamic of population immunity are still elusive. Methods: We launched a prospective cohort study in the Guangdong Provincial CDC from December 2022 to July 2023. Fifty participants who received the same vaccination regimen and had no previous infection were recruited. Results: 90% of individuals were infected with Omicron BA.5* variants within three weeks in the first wave. Thirteen cases (28.26%) experienced infection with XBB.1* variants, occurring from 14 weeks to 21 weeks after the first wave. BA.5* infections exhibited higher viral loads in nasopharyngeal sites compared to oropharyngeal sites. Compared to BA.5* infections, the XBB.1* infections had significantly milder clinical symptoms, lower viral loads, and shorter durations of virus positivity. The infection with the BA.5* variant elicited varying levels of neutralizing antibodies against XBB.1* among different individuals, even with similar levels of BA.5* antibodies. The level of neutralizing antibodies specific to XBB.1* determined the risk of reinfection. Conclusions: The rapid large-scale infections of the Omicron variants have quickly established herd immunity among the population in mainland China. In the future of the COVID-19 epidemic, a lower infection rate but a longer duration can be expected. Given the large population size and ongoing diversified herd immunity, it remains crucial to closely monitor the molecular epidemiology of SARS-CoV-2 for the emergence of new variants of concern in this region. Additionally, the timely evaluation of the immune status across different age groups is essential for informing future vaccination strategies and intervention policies.
Addressing Combative Behaviour in Spanish Bulls by Measuring Hormonal Indicators
Authors: Illera Juan Carlos , Jimenez-Blanco Francisco , Centenera Luis , Gil-Cabrera Fernando , Crespo Belen , Lopez Paula Rocio , Silvan Gema , Caceres Sara
Published: April 2024

The fighting bull is characterised by its natural aggressiveness, but the physiological mechanisms that underlie its aggressive behaviour are poorly studied. This study determines the hormonal component of aggressiveness in fighting bulls by analysing their behaviour during a fight and correlating it to their serotonin, dopamine and testosterone levels. We also determine whether aggressive behaviour can be estimated in calves. Using 195 animals, samples were obtained when the animals were calves and after 5 years. Aggressiveness scores were obtained by an observational method during bullfights, and serotonin, dopamine and testosterone levels were determined in all animals using validated enzyme immunoassay kits. The results revealed a strong correlation of serotonin and dopamine levels with aggressiveness scores in bulls during fights, but no correlation was found with respect to testosterone. These correlations led to established cut-off point and linear regression curves to obtain expected aggressiveness scores for calves at shoeing. There were no significant differences between the expected scores obtained in calves and the observed scores in bulls. Therefore, this study demonstrates that hormone determination in calves may be a great indicator of combativeness in bulls and can reliably be used in the selection of fighting bulls.
Unveiling the Dynamics and Influence of Water Footprints in Arid Areas: A Case Study of Xinjiang, China
Authors: Ren Cai , Zhang Pei , Deng Xiaoya , Zhang Ji , Wang Yanyun , Wang Shuhong , Yu Jiawen , Lai Xiaoying , Long Aihua
Published: April 2024

A prerequisite for the rational development and utilization of regional water resources is the measurement of water stress. In this study, from the perspective of water footprints, we took the proportion of the agricultural water footprint within the total water resource usage of Xinjiang (hereafter referred to as XJ) as an example to measure its water stress index and explore the state of water stress in the region and its corresponding driving factors. The ESDA method was applied to characterize the spatial patterns of and correlations with water stress. The effects of different factors on the spatial differentiation between the water footprint and water stress were quantified using the LMDI and geoprobes, respectively. The results showed that (1) both the agricultural water footprint and the water stress index in XJ showed an upward trend, the spatial distribution of water stress was uneven, and the regional pressure difference between the east and the west was greater than that between the north and the south; (2) the water stress index has an obvious negative spatial correlation, fluctuations in its discrete nature have been enhanced, and the number of spatially correlated prefectures is decreasing; (3) water consumption of CNY 10,000 GDP, GDP per capita, and total CO2 emissions have the most significant impact on the evolution of the agricultural water footprint in XJ. Meanwhile, spatial variations in water stress are mainly determined by the area of cultivation, the area of natural oasis, and the proportion of water used in agriculture. Analysis of the characteristics of and factors influencing water stress in XJ from the perspective of its agricultural water footprint provides a new perspective for further analyzing the actual state of the water footprint and water stress in XJ and supplies a reference basis for the decision-makers of the XJ government.
Ecotoxicological Assays with the Calanoid Copepod Acartia tonsa: A Comparison between Mediterranean and Baltic Strains
Authors: Vitiello Valentina , Oliva Matteo , Renzi Monia , Cuccaro Alessia , Fumagalli Giorgia , Anselmi Serena , Bentivoglio Tecla , Matarazzi Iliana , Sanna Valeria , Pellegrini David , Pretti Carlo , Buttino Isabella
Published: April 2024

The use of marine invertebrates in ecotoxicology is important for an integrated approach which takes into consideration physiological responses and chemical levels in environmental matrices. Standard protocols have been developed and organisms belonging to different trophic levels are needed as model organisms to evaluate toxicant bioavailability and assess their impact on marine biota. The calanoid copepod Acartia tonsa is commonly used in ecotoxicology due to its widespread distribution and well-studied biology. However, different strains coming from various geographical areas are available, and possible variations in physiological characteristics raise concerns about the comparability of ecotoxicological results. This study compares the life cycle assessment and sensitivity of Adriatic and Baltic strains of A. tonsa exposed to nickel (Ni2+) in standardized acute and semi-chronic tests. Life cycle assessments revealed differences in egg production, egg-hatching success, and naupliar viability between the strains. The acute toxicity test demonstrated the significantly higher sensitivity of Adriatic strain nauplii to Ni2+ compared to the Baltic strain, whereas the semi-chronic test showed no significant difference in sensitivity between the strains. These findings suggest that while strain-specific differences exist in different geographical populations, responses to toxicants are not significantly different. Particularly, the semi-chronic assessments with both A. tonsa strains emphasized the robustness of this species as a model organism in ecotoxicology.
Spatio-Temporal Variations in Nitrate Sources and Transformations in the Midstream of the Yellow River Determined Based on Nitrate Isotopes and Hydrochemical Compositions
Authors: Su Caili , Su Yuxuan , Zhang Rongkai , Xu Xiaohang , Li Junhua
Published: April 2024

Nitrate pollution is a major environmental problem threatening rivers, and nitrogen and oxygen isotopes have proved to be an effective means of analyzing the sources and transformations of nitrate in rivers. However, a low monitoring frequency cannot accurately reflect the changes in nitrate. In this study, the sources and transformations of nitrate in the middle reaches of the Yellow River and its tributaries during the dry season and the wet season were analyzed based on water quality parameters and nitrate isotopes. Stable isotope analysis conducted using the R (SIAR) model was used to estimate the proportions of different nitrate sources. The results showed that the main nitrate sources in the main stream were soil nitrogen (40.95–45.83%) and domestic sewage and manure (30.93–32.60%), respectively, with little variation between the dry season and wet season because of the large flow of the Yellow River. During the dry season, the nitrate sources of the two tributaries were mainly domestic sewage and manure (45.23–47.40%), followed by soil nitrogen (31.35–34.00%). However, the primary nitrate source of T2 (Qin River) became soil nitrogen (40.05%) during the wet season, a phenomenon that was mainly caused by the significant increase in river discharge and in soil erosion in the basin. During the wet season, the concentrations of total nitrogen (TN) and nitrate (NO3−) significantly decreased in the main stream and tributaries, and nitrification and denitrification processes occurred in both the main stream and tributaries of the Yellow River. In addition, the T2 tributary (Qin River) was also significantly affected by mixed dilution. High-frequency sampling can reflect the isotopic information of nitrate in the river more comprehensively, which helps us to understand the conversion process of nitrate more accurately.
Evolution and Effectiveness of Salt Marsh Restoration: A Bibliometric Analysis
Authors: Gonçalves Carlos , Fernandes João , Neto João M. , Veríssimo Helena , Caçador Isabel , Verdelhos Tiago
Published: April 2024

Salt marshes play a critical role in supporting water quality, erosion control, flood protection, and carbon sequestration. Threats from climate change and human activities have prompted global restoration initiatives. We analyzed restoration efforts worldwide from 1978 to 2022, using the Web of Science database and SciMAT mapping tool. After a PRISMA screening to identify methodologies, success rates, and key indicators, a total of 62 publications underwent detailed analysis, to increase knowledge on the best practices to employ in future restoration interventions and evaluation of their effectiveness. The research reveals a growing interest in ecosystem dynamics, biodiversity, anthropogenic impacts, and ecosystem services. Assisted interventions emerged as the predominant restoration method, employing 15 indicators across vegetation, sediment, fauna, and water, each one using different metrics for the intervention evaluation based on how good the outcome of the interventions described in the reviewed studies met the desired result. Our analysis suggests that combining natural interventions such as managed realignment with reconnection to tidal waters, along with long-term monitoring of vegetation, fauna, and water indicators such as sedimentation and erosion rates, plant cover and biomass, as well as fauna diversity and density, leads to the most successful outcomes. We provide valuable insights into best practices for future restoration interventions, offering guidance to future practitioners and policymakers based on a comprehensive review of the scientific literature, contributing to the resilience of these vital ecosystems, and ensuring effective restoration actions in the coming years.
Water Level Inversion Detection Method for Water Level Images without a Scale in Complex Environments
Authors: Sun Chuanmeng , Wei Yu , Wang Wenbo , Wu Zhibo , Li Yong
Published: April 2024

Accurately perceiving changes in water level information is key to achieving the fine control of water and flooding; however, the existing technology cannot achieve water level recognition in complex and harsh environments, such as at night; in haze, rain, or snow; or during obscuration by floating objects or shadows. Therefore, on the basis of a deep analysis of the characteristics of water level images in complex and harsh environments, in this study, we took full advantage of a deep learning network’s ability to characterise semantic features and carried out exploratory research on water level detection in no-water-ruler scenarios based on the two technical means of target detection and semantic segmentation. The related experiments illustrate that all the methods proposed in this study can effectively adapt to complex and harsh environments. The results of this study are valuable for applications in solving the difficulties of accurate water level detection and flood disaster early warnings in poor-visibility scenarios.
Research on the Prediction of Infiltration Depth of Xiashu Loess Slopes Based on Particle Swarm Optimized Back Propagation (PSO-BP) Neural Network
Authors: Xiao Pan , Guo Bingyue , Wang Yi , Xian Yujian , Zhang Faming
Published: April 2024

The Xiashu loess exhibits expansion when in contact with water and contraction when water is lost, making it highly susceptible to the influence of rainfall. Therefore, it is essential to investigate the infiltration behavior of rainwater in Xiashu loess slopes under various conditions. The depth of infiltration in slopes directly affects the depth of landslide failure and serves as an important indicator for studying slope infiltration characteristics; only a handful of academics have delved into its study. This article is based on on-site rainfall experiments on Xiashu loess slopes, using three main factors, rainfall intensity, rainfall duration, and slope angle, as discrimination indicators for the infiltration depth of Xiashu loess slopes. The particle swarm optimization algorithm is employed to optimize the BP neural network and establish a PSO-BP neural network prediction model. The experimental data are accurately predicted and compared with the multivariate nonlinear regression model and traditional BP neural network models. The results demonstrate that the PSO-BP neural network model exhibits a better fit and higher prediction accuracy than the other two models. This model provides a novel approach for rapidly determining the infiltration depth of Xiashu loess slopes under different rainfall conditions. The results of this study lay the foundation for the prediction of the landslide damage depth and infiltration of Xiashu loess slopes.
Bill It Right: Evaluating Public Charging Station Usage Behavior under the Presence of Different Pricing Policies
Authors: Fischer Markus , Michalk Wibke , Hardt Cornelius , Bogenberger Klaus
Published: April 2024

This study investigates for the first time how public charging infrastructure usage differs under the presence of diverse pricing models. About 3 million charging events from different European countries were classified according to five different pricing models (cost-free, flat-rate, time-based, energy-based, and mixed) and evaluated using various performance indicators such as connection duration; transferred energy volumes; average power; achievable revenue; and the share of charging and idle time for AC, DC, and HPC charging infrastructure. The study results show that the performance indicators differed for the classified pricing models. In addition to the quantitative comparison of the performance indicators, a Kruskal–Wallis one-way analysis of variance and a pairwise comparison using the Mann–Whitney-U test were used to show that the data distributions of the defined pricing models were statistically significantly different. The results are discussed from various perspectives on the efficient design of public charging infrastructure. The results show that time-based pricing models can improve the availability of public charging infrastructure, as the connection duration per charging event can be roughly halved compared to other pricing models. Flat-rate pricing models and AC charging infrastructure can support the temporal shift of charging events, such as shifting demand peaks, as charging events usually have several hours of idle time per charging process. By quantifying various performance indicators for different charging technologies and pricing models, the study is relevant for stakeholders involved in the development and operation of public charging infrastructure.
Patient Safety Trends in 2023: An Analysis of 287,997 Serious Events and Incidents From the Nation’s Largest Event Reporting Database
Authors: Kepner Shawn , Jones Rebecca
Published: April 2024

Background

The Pennsylvania Patient Safety Reporting System (PA-PSRS) is the largest repository of patient safety data in the United States and one of the largest in the world, with over 4.7 million acute care event reports dating back to 2004. In this article, we analyze the patient safety event reports submitted to PA-PSRS in 2023.

Methods

We extracted data from PA-PSRS and obtained data from the Pennsylvania Health Care Cost Containment Council (PHC4). Report counts are based on report submission date, and rates are based on event occurrence date and calculated per 1,000 patient days for hospitals or 1,000 surgical encounters for ambulatory surgical facilities (ASFs).

Results

In 2023, 287,997 reports were submitted to PA-PSRS, which is a considerable increase from 2022 but very close to the 2021 total. Reports of serious and high harm events increased by 20.6% and 25.0%, respectively, representing the largest annual increases historically. Of the 287,997 reports, 96.0% were from hospitals, 3.8% were from ambulatory surgical facilities, and 0.2% were from birthing centers and abortion facilities. The vast majority (95.9%) of the 2023 reports were incidents, with the remaining 4.1% classified as serious events. The reporting rate based on event occurrence date for hospitals in the first half of 2023 was 30.0 reports per 1,000 patient days; for ASFs, the rate was 9.9 reports per 1,000 surgical encounters. For each of the past five years, the most frequently reported event type was Error Related to Procedure/Treatment/Test, which accounted for 33.1% of acute care event reports submitted in 2023. From a distribution perspective, the greatest increase in percent of total reports in 2023 occurred with event type Medication Error, and the greatest increase for serious events was with event type Complication of Procedure/Treatment/Test (P/T/T). Almost half of the increase in Complication of P/T/T was with subtype Complication following surgery or invasive procedure (48.2%; 968 of 2,009), and 54.6% (529 of 968) of reports in this subtype were due to unplanned returns to the operating room.

Conclusion

The number of total reports, serious events, and high harm events, as well as preliminary reporting rates for hospitals and ASFs, all increased in 2023. Patient Safety Authority will continue working with Pennsylvania healthcare facilities to support high-quality reporting and patient safety practices.
Voltammetry of Constant Phase Elements: Analyzing Scan Rate Effects
Authors: Je Hyeonsu , Chow Kwok-Fan , Chang Byoung-Yong
Published: April 2024

Here we introduce a new method for characterizing the constant phase element (CPE) in electrochemical systems using cyclic voltammetry (CV), presenting an alternative to the conventional electrochemical impedance spectroscopy (EIS) approach. While CV is recognized for its diagnostic capabilities in electrochemical analysis, it traditionally encounters difficulties in accurately measuring CPE systems due to a lack of clear linearity with scan rates, unlike capacitors. Our research demonstrates a linear relationship between current and scan rate on a log–log plot, enabling the calculation of n and Y0 values for CPE from the slopes of these linear relationships. For validation of our method, it is applied to two kinds of capacitors and the results agree with those measured by EIS. Although EIS is known to be accurate in measuring CPE systems, our alternative approach offers a timely and reasonably precise diagnostic tool, balancing between ease of use and accuracy, especially beneficial for preliminary assessments before conducting further in-depth analysis.
Impact of research activity on performance of general practices: a qualitative study
Authors: Kenning Cassandra , Usher-Smith Juliet A , Jamison James , Jones Jennifer , Boaz Annette , Little Paul , Mallen Christian , Bower Peter , Park Sophie
Published: April 2024

Background

There is evidence that engaging in research is directly associated with better performance. If this relationship is to be strengthened, it is necessary to understand the mechanisms that might underlie that relationship.

Aim

To explore the perspectives of staff and wider stakeholders about mechanisms by which research activity may impact on the performance of general practices.

Design & setting

Qualitative study using semi-structured interviews with general practice professionals and wider stakeholders in England.

Method

Individual interviews with 41 purposively sampled staff in ‘research-ready’ or ‘research-active’ general practices, and 21 other stakeholders. Interviews were independently coded by three researchers using a framework approach.

Results

Participants described potential ‘direct’ and ‘indirect’ impacts on their work. ‘Direct’ impacts included improved knowledge and skills that could change practice work (for example, additional records searches for particular conditions); bringing in additional resources (for example, access to investigations or staff); and improving relationships with patients. ‘Indirect’ impacts included job satisfaction (for example, perception of practice as a centre of excellence and innovation, and the variety afforded by research activity reducing burnout); and staff recruitment (increasing the attractiveness of the practice as a place to work). Responders identified few negative impacts.

Conclusion

Staff and stakeholders identified a range of potential impacts of research activity on practice performance, with impacts on their working lives most salient. Negative impacts were not generally raised. Nevertheless, responders generally discussed potential impacts rather than providing specific examples of those impacts. This may reflect the type of research activity conducted in general practice, often led by external collaborators.
Pemberdayaan Kelompok Wanita Tani Sebagai Implementasi SDGs Desa Untuk Meningkatkan Ekonomi Keluarga
Authors: Lestari Rohmini Indah , Budiati Yuli , Indarto Indarto , Larasati Dewi
Published: April 2024

The Women Farmers Group Karya Bersemi in Rejosari Village, Karangawen District, Demak Regency. They recently received assistance with a Manual Oven using gas power from the government, but they have not been able to operate it. The Community Service Team from the Postgraduate Master Management (MM) Study Program at the University of Semarang (USM) is to provide training on how to process agricultural products into ready-to-eat food. Its purpose is to create food diversification. Second, capacity building and innovation to make processed agricultural products. Third, introduce marketing through social media. The last is to provide simple bookkeeping and counseling to separate family finances and business results. The activities' purpose can be implemented to achieve the Sustainable Development Goals (SDGs) for Villages 5 by 2030. SDG 5 is to create conditions that place all villagers in have the same position, without discrimination against women. The indicator for achieving the goal of SDG Desa 5 is the availability of space and opportunities for the involvement of women in the planning and implementation of village development like the KWT Karya Bersemi.Kelompok Wanita Tani (KWT) Karya Bersemi di Desa Rejosari Kecamatan Karangawen Kabupaten Demak baru-baru ini memperoleh bantuan Oven Gas menggunakan tenaga gas dari pemerintah, akan tetapi mereka belum bisa mengoperasikannya. Tujuan dari kegiatan Tim Pengabdian kepada Masyarakat (PKM) dari Program Studi Magister Manajemen (MM) Pascasarjana Universitas Semarang (USM) ini adalah memberikan pelatihan cara mengolah hasil pertanian menjadi olahan pangan siap makan sebagai salah satu upaya untuk menciptakan diversifikasi pangan. Kedua, peningkatan kemampuan dan inovasi membuat produk olahan hasil pertanian. Ketiga, mengenalkan pemasaran melalui media sosial Instagram dan Whatsapp. Terakhir adalah memberikan pelatihan pembukuan sederhana serta penyuluhan untuk memisah keuangan keluarga dan hasil usaha. Harapannya dengan kegiatan dapat mengimplementasi tercapainya Sustainable Development Goals (SDGs) Desa 5 pada tahun 2030. Tujuan SDGs 5 adalah terciptanya kondisi yang menempatkan semua warga desa dalam posisi adil, tanpa diskriminasi terhadap perempuan. Indikator tercapainya tujuan SDGs Desa 5 ini adalah tersedianya ruang dan kesempatan bagi keterlibatan perempuan dalam perencanaan dan pelaksanaan pembangunan desa seperti adanya KWT Karya Bersemi ini.