bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrating Blockchain Technology in Business Models for Sustainable Innovation
Authors: Chao Yang , Goli Alireza
Published: August 2024

This research paper investigates the role of blockchain technology in sustainable business model innovation by proposing a comprehensive framework. The study addresses the following research questions: How can blockchain technology enhance business model components? What are the specific innovations enabled by blockchain technology? To answer these questions, a hybrid approach was employed. Initially, a thorough review of existing literature identified key components of business model innovation. Subsequently, a survey was conducted among technology experts to evaluate the applications of blockchain technology in these components. The analysis revealed five categories of innovation: macro-activities of the value network, micro-activities within the organization, governance, financial aspects, as well as sustainable innovation. Next, a novel conceptual model was developed to assess the impact of digital technologies on business model performance, and then it was evaluated using Structural Equation Modeling (SEM). Key findings indicate that blockchain technology significantly enhances data transparency, security, and efficiency capabilities, leading to improved innovation and increased sales volume. Practical implications include recommendations for organizations to prioritize investments in platform technologies, insight analysis, and sensor-based data collection to achieve sustainable business model innovation. The study underscores the importance of a holistic approach to integrating blockchain technology across all business model components to maximize its potential.
New Perspectives on Lighting
Authors: Doulos Lambros T. , Peña-García Antonio
Published: August 2024

Lighting has experienced dramatic developments in the last two decades [...]
Nature-Based Secondary Resource Recovery under Climate Change Uncertainty: A Robust Multi-Objective Optimisation Methodology
Authors: Alshehri Khaled , Basirati Mohadese , Sapsford Devin , Harbottle Michael , Cleall Peter
Published: August 2024

The management of high-volume (HV) waste poses a persistent challenge in sustainable materials management and represents an untapped opportunity in circular economy models. This study proposes a conceptual decision-making framework to operationalise a novel circular economy strategy for HV waste, involving temporary storage to facilitate nature-based secondary resource recovery. Using an illustrative case study of a candidate HV waste (legacy mining waste), we apply a robust multi-objective spatial optimisation approach at a national scale, employing an exact solution approach. Our methodology integrates mixed-integer linear programming to evaluate the economic viability, social benefits, and impacts of climate change uncertainties on nature-based solutions (NbS) implementation across diverse scenarios. The results demonstrate that NbS can enhance economic feasibility by incorporating carbon sequestration and employment benefits while demonstrating resilience against climate change projections to ensure long-term sustainability. The findings suggest that although NbS can improve the circular economy of HV nationally, it is essential to assess additional ecosystem services and address multiple uncertainties for effective macro-level sustainability assessment of HV management. This study offers a robust decision-making framework for policymakers and stakeholders to plan and implement nature-based circular economy strategies for HV waste streams at a national level while effectively managing long-term planning uncertainties.
Community Group Purchasing of Next-Day Delivery: Bridging the Last Mile Delivery for Urban Residents during COVID-19
Authors: Wang Yingying , Xu Feng , Lin Zhe , Guo Jianying , Li Gang
Published: August 2024

The rapid development of new retail and the impact of COVID-19 have catalyzed the blowout growth of community group purchasing. The emergence of community group purchasing collection and delivery points (CGPCDPs) has become a new way to solve the “last mile” problem of new retail delivery. Based on the point of interest (POI) data of CGPCDPs of Nansha District, Guangzhou City, this study advances our understanding by identifying unique operational models, service targets, and spatial distribution patterns of CGPCDPs, which differ significantly from traditional pick-up points (PPs). The conclusions are as follows: (1) Most CGPCDPs depend on wholesale and retail shops, and their main service targets are urban and rural communities, followed by industrial areas. (2) The distribution of CGPCDPs has apparent spatial differentiation. At the macro scale, it shows the characteristics of “central agglomeration and peripheral dispersion”. It is distributed along the “northwest-southeast” direction and presents a “dual-core multi-center” pattern. At the meso–micro scale, different built environments in developed areas of cities, villages in the city (ChengZhongCun), and rural areas show distinct distribution patterns. (3) The main influencing factors of their spatial distribution are population density, construction land, house price, supporting place, residence density, urban community, and road proximity.
Investigating UK School-Aged Children’s Sustainable Food Packaging Disposal Knowledge and Engagement Levels in Ecologically Valid Settings
Authors: Norton Victoria , Lignou Stella
Published: August 2024

There is a growing emphasis on sustainable approaches; however, consumer-related barriers can modulate adherence. Therefore, engaging future generations from an early age in adopting sustainable food-packaging practices is fundamental. This paper investigates food-packaging-related knowledge, preferences, and engagement levels at a UK science-based event. School-aged children (n = 255; 8–18 years) completed various activities to initiate conversation encompassing food packaging disposal, symbols, issues, preferences, and behaviour, as well as educational-based discussions. Most children were able to select the correct response for disposal-related questions; however, they struggled to correctly identify the appropriate bin for used food items (e.g., pizza box). Children’s knowledge of symbols varied considerably: Mobius loop and Fairtrade symbols were easily recognisable, whereas there was no clear consensus/poor knowledge for the remaining symbols. Children’s main food packaging issues were ‘excessive packaging’ and ‘bins are full’ and key information searching locations were labels-on-pack and digital sources. Currently, 51% of the children adopt sustainable approaches; therefore, engaging more children in such practices is essential. 77% of the children were interested in changing future food-packaging behaviour. Going forward, sustainable food-packaging practices need to be incorporated into the school curriculum to promote engagement as well as improving infrastructure so that children can easily implement appropriate practices; thus, resulting in notable societal impact.
Methodology for Quantification of Technological Processes in Passenger Railway Transport Using Alternatively Powered Vehicles
Authors: Kendra Martin , Pribula Daniel , Skrúcaný Tomáš
Published: August 2024

Due to the reduction in diesel propulsion on railway networks across the world, it is essential to consider the introduction of an alternative propulsion where electrification would not be feasible. The introduction of alternative propulsions may influence the technological processes of train processing and interrupt its quantification methodology, due to their specific operational requirements. The problem of the quantification of technological processes of train processing is not sufficiently solved even in the field of conventional propulsions; therefore, the aim of this paper is to propose a unique methodological procedure for the quantification of selected processes of train processing operated by multiple units with a conventional or alternative propulsion. The new process quantification methodology enables the duration determination of a specific process, which can be simply determined for multiple units of different length and propulsion under local conditions. The duration determination is based on the final formula or its graphical representation. The function is based on data obtained by analysing the evaluated workflow of a model and multiple units using the PERT network analysis method. The proposed methodological procedure is verified by different types of propulsions through a case study using real values. The application of the methodology can prevent the risks related to non-compliance of the required technological times and at the same time increase the sustainability of the operation stability of railway passenger transport.
Capacity Optimization of Pumped–Hydro–Wind–Photovoltaic Hybrid System Based on Normal Boundary Intersection Method
Authors: Wang Hailun , Li Yang , Wu Feng , He Shengming , Ding Renshan
Published: August 2024

Introducing pumped storage to retrofit existing cascade hydropower plants into hybrid pumped storage hydropower plants (HPSPs) could increase the regulating capacity of hydropower. From this perspective, a capacity configuration optimization method for a multi-energy complementary power generation system comprising hydro, wind, and photovoltaic power is developed. Firstly, to address the uncertainty of wind and photovoltaic power outputs, the K-means clustering algorithm is applied to deal with historical data on load and photovoltaic, wind, and water inflow within a specific region over the past year. This process helps reduce the number of scenarios, resulting in 12 representative scenarios and their corresponding probabilities. Secondly, with the aim of enhancing outbound transmission channel utilization and decreasing the peak–valley difference for the receiving-end power grid’s load curve, a multi-objective optimization model based on the normal boundary intersection (NBI) algorithm is developed for the capacity optimization of the multi-energy complementary power generation system. The result shows that retrofitting cascade hydropower plants with pumped storage units to construct HPSPs enhances their ability to accommodate wind and photovoltaic power. The optimal capacity of wind and photovoltaic power is increased, the utilization rate of the system’s transmission channel is improved, and the peak-to-valley difference for the residual load of the receiving-end power grid is reduced.
Perceived Quality of Service in Tourist Transportation in the City of Baños de Agua Santa, Ecuador
Authors: Velastegui-Hernández Rommel , Melo-Fiallos Diego , Mayorga-Ases María , Hernández-Del-Salto Segundo , Manobanda-Tenelema Eduardo , Garcia Marcelo V.
Published: August 2024

This study investigates the perceived quality of tourist transportation services in Baños de Agua Santa, Ecuador, utilizing the SERVQUAL model to assess service quality. Through an examination of the gap between tourists’ expectations and their actual experiences, the research aims to evaluate service quality. A survey of 203 tourists who utilized the “Chivas” tourist ground transportation service forms the basis of the analysis. The findings reveal significant negative gaps across all dimensions of service quality, indicating a shortfall in meeting tourists’ expectations. Notably, the reliability dimension exhibits the most pronounced gap, highlighting the importance of fulfilling service commitments to cultivate trust. The study underscores the crucial role of service quality in the tourism sector and proposes targeted improvements, including enhancing facility modernity, providing staff training, and enhancing service responsiveness and reliability. Addressing these gaps has the potential to enrich the tourist experience, bolster the positive image of transportation services, and enhance the city’s appeal.
CRISP-DM-Based Data-Driven Approach for Building Energy Prediction Utilizing Indoor and Environmental Factors
Authors: Elkabalawy Moaaz , Al-Sakkaf Abobakr , Mohammed Abdelkader Eslam , Alfalah Ghasan
Published: August 2024

The significant energy consumption associated with the built environment demands comprehensive energy prediction modelling. Leveraging their ability to capture intricate patterns without extensive domain knowledge, supervised data-driven approaches present a marked advantage in adaptability over traditional physical-based building energy models. This study employs various machine learning models to predict energy consumption for an office building in Berkeley, California. To enhance the accuracy of these predictions, different feature selection techniques, including principal component analysis (PCA), decision tree regression (DTR), and Pearson correlation analysis, were adopted to identify key attributes of energy consumption and address collinearity. The analyses yielded nine influential attributes: heating, ventilation, and air conditioning (HVAC) system operating parameters, indoor and outdoor environmental parameters, and occupancy. To overcome missing occupancy data in the datasets, we investigated the possibility of occupancy-based Wi-Fi prediction using different machine learning algorithms. The results of the occupancy prediction modelling indicate that Wi-Fi can be used with acceptable accuracy in predicting occupancy count, which can be leveraged to analyze occupant comfort and enhance the accuracy of building energy models. Six machine learning models were tested for energy prediction using two different datasets: one before and one after occupancy prediction. Using a 10-fold cross-validation with an 8:2 training-to-testing ratio, the Random Forest algorithm emerged superior, exhibiting the highest R2 value of 0.92 and the lowest RMSE of 3.78 when occupancy data were included. Additionally, an error propagation analysis was conducted to assess the impact of the occupancy-based Wi-Fi prediction model’s error on the energy prediction model. The results indicated that Wi-Fi-based occupancy prediction can improve the data inputs for building energy models, leading to more accurate energy consumption predictions. The findings underscore the potential of integrating the developed energy prediction models with fault detection systems, model predictive controllers, and energy load shape analysis, ultimately enhancing energy management practices.
Model Predictive Controlled Parallel Photovoltaic-Battery Inverters Supporting Weak Grid Environment
Authors: Selim Fatma , Aly Mokhtar , Megahed Tamer F. , Shoyama Masahito , Abdelkader Sobhy M.
Published: August 2024

The hybrid photovoltaic (PV) with energy storage system (ESS) has become a highly preferred solution to replace traditional fossil-fuel sources, support weak grids, and mitigate the effects of fluctuated PV power. The control of hybrid PV-power systems as generation-storage and their injected active/reactive power for the grid side present critical challenges in optimizing their performance. Therefore, this paper introduces hybrid PV-battery parallel inverters employing a finite control set model predictive control (FCSMPC) method. The proposed FCSMPC-based controller and inverter system achieves multiple functionalities, including maximum power extraction from PV, proper charging/discharging commands for ESS, support for weak grid conditions, support during low-voltage ride-through (LVRT) by increasing reactive power injection to counteract the drop in grid voltage, and economic management based on feed-in-tariff (FiT). The controller significantly improves the performance of the PV-battery system under faulty LVRT conditions and unbalanced grid voltages, satisfying grid code requirements while continuously supplying the microgrid’s delicate local load. A real-time simulation hardware-in-the-loop (HiL) setup, utilizing the OPAL-RT platform, is employed to implement the proposed hybrid PV–ESS with its controller. The results affirm the superior ability of FCSMPC in weak-grid conditions and its capability to achieve multiple objectives simultaneously.
The Effect of Multilateral Economic Cooperation on Sustainable Natural Resource Development
Authors: Zheng Tingting , Chai Zongxuan , Zuo Pengfei , Wang Xinyu
Published: August 2024

The relationship between natural resource development and sustainable development has long been a focus in academia. In the context of a new global economic cooperation system, many scholars argue that such cooperation can lead to a “resource curse” effect in partner countries, hindering their sustainable development. This study analyzed panel data from 64 countries from 2008 to 2020, using the Belt and Road Initiative as a representative of multilateral economic cooperation (MEC) policies. The aim was to examine the actual impact of multilateral economic cooperation on the sustainable development levels of partner countries and to explore the underlying mechanisms influencing these outcomes. First, we measured and identified the sustainable development index (SDI) under natural resource development schemes and the “resource curse” effect in these countries. Then, we employed a double machine learning approach to evaluate the policy effects of MEC on sustainable resource development. We constructed an interactive double machine learning model to examine and validate the specific mechanisms of resource development effects. The results indicate that the level of sustainable resource development in MEC countries is relatively low, and a “resource curse” effect already exists. However, participating in MEC suppresses this “curse” effect. By promoting innovation cooperation, institutional improvement, structural optimization, trade openness, and pollution reduction, MEC effectively enhances the sustainable development levels of partner countries.
Evaluation of the Development Level of Green Transportation in National Central Cities
Authors: Yu Huan , Yang Qi
Published: August 2024

Green transportation is the core embodiment of ecological civilization and the concept of green development within the field of transportation, and it is an important strategic choice for sustainable urban development. National central cities represent the highest level in China’s urban system planning. This paper aims to evaluate the level of green transportation development in national central cities. It established a set of 29 specific evaluation indicators from five dimensions: basic indicators, green transportation infrastructure, traffic environmental protection, traffic travel, and traffic safety. It constructed an evaluation index system for the development level of green transportation. The entropy weight TOPSIS method was utilized to evaluate the development levels of green transportation in nine national central cities from 2020 to 2022. An obstacle degree model was constructed to identify key obstacle factors at both the criterion and indicator layers of the green transportation development level evaluation index system for national central cities. Suggestions were proposed from five aspects: establishing a comprehensive policy framework, promoting regional collaborative development, accelerating infrastructure construction, improving transportation service quality, and fostering the green upgrading of industries. The results showed that the comprehensive ranking of green transportation development levels among the national central cities from high to low for the years 2020–2022 was as follows: Shanghai, Chongqing, Chengdu, Beijing, Guangzhou, Tianjin, Wuhan, Xi’an, Zhengzhou. In terms of the regional spatial layout, the green transportation development levels of the nine national central cities generally exhibited a “high on the periphery, low in the center” distribution characteristic. The comprehensive ranking of the obstacle degree in the criterion layer was as follows: basic indicators, traffic travel, green transportation infrastructure, traffic environmental protection, traffic safety. After screening the criteria level where the obstacle degree calculation results are above 15%, traffic safety is eliminated. The nine cities, which were located in different regions, generally maintained consistent internal obstacle factors and their order. The top five indicators with the highest frequency of obstacle degrees at the indicator layer were as follows: total passenger transport volume, number of taxis, new energy vehicle production, expenditure for transportation, and total freight transport volume. The specific key obstacle factors at the indicator level were different in the nine cities.
Advancing CO2 Solubility Prediction in Brine Solutions with Explainable Artificial Intelligence for Sustainable Subsurface Storage
Authors: Shokrollahi Amin , Tatar Afshin , Zeinijahromi Abbas
Published: August 2024

Underground CO2 storage is crucial for sustainability as it reduces greenhouse gas (GHG) emissions, helping mitigate climate change and protect the environment. This research explores the use of Explainable Artificial Intelligence (XAI) to enhance the predictive modelling of CO2 solubility in brine solutions. Employing Random Forest (RF) models, the study integrates Shapley Additive exPlanations (SHAP) analysis to uncover the complex relationships between key variables, including pressure (P), temperature (T), salinity, and ionic composition. Our findings indicate that while P and T are primary factors, the contributions of salinity and specific ions, notably chloride ions (Cl−), are essential for accurate predictions. The RF model exhibited high accuracy, precision, and stability, effectively predicting CO2 solubility even for brines not included during the model training as evidenced by R2 values greater than 0.96 for the validation and testing samples. Additionally, the stability assessment showed that the Root Mean Squared Error (RMSE) spans between 8.4 and 9.0 for 100 different randomness, which shows good stability. SHAP analysis provided valuable insights into feature contributions and interactions, revealing complex dependencies, particularly between P and ionic strength. These insights offer practical guidelines for optimising CO2 storage and mitigating associated risks. By improving the accuracy and transparency of CO2 solubility predictions, this research supports more effective and sustainable CO2 storage strategies, contributing to the overall goal of reducing greenhouse gas emissions and combating climate change.
Long-Term Variation Patterns of Precipitations Driven by Climate Change in China from 1901 to 2022
Authors: Han Jing , Zhang Rui , Guo Bing , Han Baomin , Xu Tianhe , Guo Qiang
Published: August 2024

Studying long-term precipitation trends is crucial for sustainable development, as the proper utilization of water resources is essential for maintaining a sustainable water supply. The objective and novelty of this paper was to reveal the gradual mutation process of precipitation in China over a century. This study utilized monthly precipitation data from 1901 to 2022 (at a century scale) to analyze and explore the spatiotemporal variability in precipitation across different time scales and regions with a trend analysis, an abrupt change analysis, and gravity center models. The findings indicate that (1) from 1901 to 2022, the precipitation in China generally decreased from the southeast coastal areas toward the northwest inland regions. (2) There were significant differences in the migration of precipitation gravity centers among the different study regions, with the least dispersion being observed in the Liao River basin, while the Hai River basin, various river basins in the northwest, and the Pearl River basin exhibited certain regularities in gravity center movement, and other regions showed periodic variations. (3) Over the period from 1901 to 2022, there was a trend of transitioning from lower to higher precipitation levels. (4) According to continuous long-term abrupt change tests, the timing of precipitation shifts varied across different basins. Precipitation, as a crucial component of natural resources, directly impacts various aspects of socio-economic life. Research findings provide decision support for regional flood control and disaster reduction and offer scientific decisions for ecological security.
Product Characteristics and Emotions to Bridge the Intention-Behavior Gap in Green Food Purchasing
Authors: de Sio Sara , Casu Giulia , Zamagni Alessandra , Gremigni Paola
Published: August 2024

Promoting environmentally friendly behaviors is a pivotal strategy in addressing the climate crisis. The food industry’s impact on pollution and resource consumption underscores the importance of fostering eco-sustainable food consumption, which can significantly benefit the environment. However, despite the global surge in green purchase intentions, a noticeable discrepancy persists between these intentions and actual purchasing behavior. This study aimed to investigate the influence of various factors on the likelihood of purchasing green food. An online survey was administered to Italian adult consumers (n = 832, 66% female, aged 18–84 years), collecting sociodemographic data and assessing emotions related to green purchases, perceptions of green food characteristics, intention to buy green food, and frequency of green food purchases. Through cluster analysis, three distinct consumer categories emerged: Coherent Buyers (individuals willing to buy green food and actively doing so), Coherent Non-Buyers (individuals who have no intention to buy green food and do not buy it), and Non-Buyers with Favorable Intentions (individuals expressing willingness to buy green food but not following through with purchases). Results from multinomial logistic regression analysis revealed that several factors influenced the likelihood of being categorized in the other two categories, as opposed to the Coherent Buyers one. These factors included younger age, a lower sense of pride associated with purchasing green products, and considering healthiness, natural content, and eco-sustainability of food less important and familiarity of green food more important. These findings provide valuable insights for marketers and policymakers, facilitating efforts to bridge the gap between green food intentions and behaviors and promote a shift toward a more eco-sustainable dietary pattern.
How Perceived Proximity to Climate Change Threats Affects Pro-Environmental Behaviors in South Korea?
Authors: Park Jeeyoung , Chang Kiyoung
Published: August 2024

This study explores how perceived proximity to environmental threats influences pro-environmental behaviors in South Korea. We find that individuals are more likely to engage in environmentally friendly actions, such as reducing their standard of living, paying higher taxes, and purchasing higher-priced eco-friendly products when they perceive climate change as a nearby threat. Our findings highlight the importance of perceived immediacy in motivating significant lifestyle changes and financial sacrifices for environmental protection. The results also reveal that political ideology influences these behaviors, with conservative individuals showing less support for green taxes and financial sacrifices. Additionally, higher levels of education and income, along with older age, correlate with a greater willingness to adopt pro-environmental behaviors. These insights contribute to environmental psychology by highlighting the role of perceived proximity in shaping environmental attitudes and behaviors, informing the development of targeted policies aimed at fostering sustainable behaviors, and addressing local environmental threats.
Integrated Control Design for Hybrid Grid-Photovoltaic Systems in Distillation Applications: A Reference Model and Fuzzy Logic Approach
Authors: Abouobaida Hassan , Mchaouar Youssef , Ullah Safeer , Abouelmahjoub Younes , Alghamdi Hisham , Alghamdi Baheej , Kraiem Habib
Published: August 2024

This paper presents a novel hybrid structural control solution designed for distillation systems that utilize a solar source alongside an electrical grid. The power conversion architecture incorporates a reversible bridge rectifier and a quadratic boost converter. The hybrid photovoltaic grid configuration offers several benefits, including source complementarity, enhanced dependability, and energy availability aligned with power requirements. Leveraging a photovoltaic source operating at maximum power facilitates energy conservation. On the control front, an adaptive technique based on a reference model is proposed. Fuzzy logic governs the quadratic boost converter, simplifying the management of its complex nonlinear nature. The control strategy aims to maximize solar power utilization, minimize harmonic components in the grid current, synthesize an adaptive controller, and achieve a near-unit power factor on the grid. The simulation results for a steady distillation system demonstrate promising findings. Despite variations in irradiation, load power, and grid drops, the system maintains a minimal bus voltage ripple, remaining close to the intended value. Optimization of the panel-generated power leads to improved PV source utilization and enhanced system efficiency. Furthermore, the combination with an electrical grid achieves a low rate of grid current distortion and a unitary power factor.
“Curious Is as Curious Does”: Fostering Question-Asking in a Sino-Foreign Engineering School—A Case Study
Authors: Rakedzon Tzipora , Van Horne Constance
Published: August 2024

Curiosity and question-asking are at the heart of science and engineering education. However, question-asking can be difficult for students due to several factors, including fear, language barriers, and cultural norms. This is especially true among Chinese students, who represent a growing number of upcoming engineers. To address this, in this case study from a university teaching reform project, we investigate the perceptions of curiosity and question-asking among Chinese science, technology, engineering, and mathematics (STEM) undergraduate students following a newly developed semester-long project in a second-year communications course at a recently established Sino-foreign engineering school in China. In this period, students engaged in project-based learning centered around Nobel Prize-winning research, allowing them to explore the driving questions behind groundbreaking discoveries. Through a combination of qualitative analyses from students’ personal reflections as well as from a post-survey, the study examines students’ perceptions of curiosity and question-asking, the influence of gender on these skills, and the role of failure and perseverance in scientific inquiry. Findings indicate that the project increased students’ curiosity and improved their confidence in asking questions while providing insights into gender differences. Moreover, students were inspired by the curiosity of the Nobel Laureates, by the “simplicity” of the questions asked, and by the great importance of tenacity, passion, and learning from mistakes.
Sustainable Strategies for Innovative Cooperation in Human Resources Training between the Business Sector and Universities through Internship Programs from the Pre- to Post-COVID-19 Period
Authors: Yfantidou Georgia , Spyridopoulou Eleni , Papaioannou Alkistis , Koustelios Athanasios , Katsoni Vicky
Published: August 2024

Internships can foster educational alliances between industry (business environment) and academic institutions, which can facilitate both flexibility and accelerated innovation. The purpose of this research is to search for the factors that determine HRT through the implementation of the internship program among the students at the Democritus University of Thrace and reveal the correlation between the factors. Also, this paper investigated the impact of the COVID-19 Eras on human resource training (HRT) factors and, finally, investigated the correlation between the two variables “Recruitment in the specialization” and “COVID Eras”. The sample of the research consisted of 1398 students at the DUTh who implemented internships during the academic years from 2015–2016 to 2021–2022. A questionnaire with 60 variables was created for data collection. A random sampling method was applied to collect the sample. From the results of the survey, ten factors were extracted for human resource training that explained 75.512% of the total variance, and for each one, Cronbach’s Alpha reliability was tested, which was high. In detail, the factors revealed were Learning Outcomes, Efficacy, Emotional Commitment, Satisfaction, Participation, Empowerment, Role Ambiguity, Role Conflict, Supervisor, and Collaboration. From the results of the study, it was evident that HR training is a multidimensional concept and is a necessary condition for the competitiveness of the firms. Training can help to improve the flexibility of the firm, but also to motivate the staff by implementing multidisciplinary training programs. Overall, internship programs are beneficial for students to develop a wide range of skills, as the hands-on experience obtained enhances and supplements the theoretical learning from educational institutions.
Material Flow Analysis-Based Sustainability Assessment for Circular Economy Scenarios of Urban Building Stock of Vienna
Authors: Lederer Jakob , Blasenbauer Dominik
Published: August 2024

Urban buildings consume raw material and energy, and they produce waste and greenhouse gasses. Sustainable urban development strategies aim to reduce these. Using the case study of buildings in Vienna, this article evaluates the impact of a defined urban development pathway on the heating energy demand, greenhouse gas emissions, and total material requirement of buildings in Vienna for 2021–2050. Furthermore, the impact of recycling to reduce the total material requirement and to increase the circular material use rate is evaluated. The results show that the heating energy demand can be reduced to meet the targets of Vienna’s sustainable development strategy. The same does not count for greenhouse gas emissions. To meet the targets for the latter, the renovation of old buildings by thermal insulation should be expanded and heating systems substituted. With respect to the total material requirement, the recycling of demolition waste from buildings in Vienna to produce secondary raw materials for buildings in Vienna can help to achieve the reduction targets of Vienna’s sustainable development strategy so that in the year 2050, the material footprint is only 44% of the value of the year 2019. Since there is a contradiction between the total material requirement and the circular material use rate, the latter has to be discussed for its use as a circular economy indicator, since the aim of circular economy is not to produce as much recycling materials as possible, but to reduce resource consumption to a sustainable level.
Optimization Study of Outdoor Activity Space Wind Environment in Residential Areas Based on Spatial Syntax and Computational Fluid Dynamics Simulation
Authors: Cao Peng , Li Tian
Published: August 2024

In the context of increasing global energy shortages and climate change, the human living environment, as a crucial component of residents’ daily lives, has garnered growing attention from the academic community. Research on residential environments is vital for promoting the sustainable development of urban construction and constitutes an important aspect of sustainable development studies. This study focuses on the optimization strategy for the outdoor activity space wind environment in the Xihuayuan residential area in Lanzhou city, utilizing spatial syntax analysis and Computational Fluid Dynamics (CFD) simulation technology. Firstly, the outdoor activity space is analyzed for visibility and spatial accessibility using DepthmapX0.6 software. Then, the outdoor wind environment in the residential area is simulated using PHOENICS 2018 software, and the analysis is conducted on outdoor spaces with a poor wind environment in terms of high accessibility. The results indicate that residents’ outdoor comfort in these spaces is poor, highlighting the urgent need for improvement in the wind environment. This research attempts to optimize the wind environment in high-accessibility spaces within the residential area by improving building layout, orientation, and height. The simulation results after optimization demonstrate an increase in the overall average wind speed to 1.44 m/s, with the proportion of spaces with a good wind environment in high-accessibility areas during summer rising from 33.4% to 59.2%. The optimization strategy effectively improves the wind environment in high-accessibility areas of the residential area.
Study on Parking Adaptability in Urban Complexes on Top of Subways Based on Shared Parking Spaces
Authors: Feng Yuqin , Wang Fu , Chen Xinyu , Zhang Xiaona
Published: August 2024

Urban complexes on top of subways as a function of intensive building groups, including residential, office, business, and other types nature of land use where parking time differences are obvious, can implement shared parking spaces, thereby reducing the index of parking allotment. Currently, the parking space allocation index for complexes is only a simple superposition of different land uses, resulting in an over-allocation of parking allotments, leading to a waste of land resources and a low utilization rate of parking allotments. Considering the factor of shared parking spaces, this paper conducted an in-depth analysis of the parking adaptability of urban complexes on top of subways and selected five urban complexes on top of subway stations in Wuhan to conduct a parking survey to analyze the parking demand characteristics. This study also investigated the parking behavior of parkers and analyzed the characteristics of parking behavior in urban complexes on top of subways as well as the current parking demand prediction methods and models, establishing a parking demand prediction model based on shared parking spaces and conducting an adaptability analysis. Finally, using five urban complexes in Wuhan as examples, the number of parking spaces demanded by urban complexes on top of subways in 2025 was predicted, and Wuhan Golden Harvest Fashion Plaza was used as an example to verify the feasibility and implementation ability of the theoretical and applied research in this paper.
Exploring New Traveling Wave Solutions for the Spatiotemporal Evolution of a Special Reaction–Diffusion Equation by Extended Riccati Equation Method
Authors: Wu Guojiang , Guo Yong , Yu Yanlin
Published: August 2024

In this work, we aim to explore new exact traveling wave solutions for the reaction–diffusion equation, which describes complex nonlinear phenomena such as cell growth and chemical reactions in nature. Obtaining exact solutions to this equation is crucial for understanding aspects such as reaction activity and the diffusion coefficient. We solve the reaction–diffusion equation by using the Riccati equation as an auxiliary equation. By controlling the parameters in the Riccati equation, we obtained a large number of traveling wave solutions, many of which were not formerly recorded in other documents. Numerical simulations demonstrate the evolution of various traveling waves of the reaction–diffusion equation in time and space. These rich exact solutions and wave phenomena help to expand our knowledge of this equation.
Economic Scheduling Strategy for Multi-Energy-Integrated Highway Service Centers Considering Carbon Trading and Critical Peak Pricing Mechanism
Authors: Ge Xiaoxue , Liu Zhijie , Li Kejun , Guo Chenxian , Shen Gang , Wang Zichen
Published: August 2024

This study proposes an optimized economic scheduling strategy for multi-energy-integrated highway service centers (MEIHSCs) within a 24 h operational timeframe. With the imperative of carbon peaking and carbon neutrality, highway areas are increasingly incorporating renewable energy systems, such as photovoltaic arrays, to capitalize on abundant resources along highways. Considering the diverse load demands of new energy vehicles and the mismatch between energy supply and demand on the highway, MEIHSCs must adapt to these trends by establishing integrated networks for electricity, natural gas, and hydrogen refueling. However, there is a lack of coordination between equipment switching and the phases of low electricity prices and peak renewable energy periods. To address this challenge and improve economic efficiency, this study proposes an economic dispatch strategy that combines economic incentives based on carbon trading and critical peak pricing mechanisms. This strategy aims to maximize economic benefits while fully meeting the load demands of new energy vehicles. Case studies indicate that operating costs are reduced by 28.04% compared to strategies without new energy installations, and by 47.85% compared to strategies without optimization. The results demonstrate that this integrated and optimized strategy significantly reduces energy costs and enhances economic benefits in highway service centers.
The Crystal Structure of Thermal Green Protein Q66E (TGP-E) and Yellow Thermostable Protein (YTP-E) E148D
Authors: Anderson Matthew R. , Padgett Caitlin M. , Ogbeifun Victoria O. , DeVore Natasha M.
Published: August 2024

Thermal green protein Q66E (TGP-E) has previously shown increased thermal stability compared to thermal green protein (TGP), a thermal stable fluorescent protein produced through consensus and surface protein engineering. In this paper, we describe the protein crystal structure of TGP-E to 2.0 Å. This structure reveals alterations in the hydrogen bond network near the chromophore that may result in the observed increase in thermal stability. We compare the very stable TGP-E protein to the structure of a yellow mutant version of this protein YTP-E E148D. The structure of this mutant protein reveals the rationale for the observed low quantum yield and directions for future protein engineering efforts.
Synergy between Nitrogen Removal and Fermentation Bacteria Ensured Efficient Nitrogen Removal of a Mainstream Anammox System at Low Temperatures
Authors: Zhi Jiaru , Ma Guocheng , Shi Xueqing , Dong Guoqing , Yu Deshuang , Zhang Jianhua , Zhang Yu , Li Jiawen , Zhao Xinchao , Xia Haizheng , Chen Xinyu , Tian Zhuoya , Miao Yuanyuan
Published: August 2024

Simultaneous partial nitrification, anammox, denitrification, and fermentation (SNADF) is a novel process achieving simultaneous advanced sludge reduction and nitrogen removal. The influence of low temperatures on the SNADF reactor was explored to facilitate the application of mainstream anammox. When temperature decreased from 32 to 16 °C, efficient nitrogen removal was achieved, with a nitrogen removal efficiency of 81.9–94.9%. Microbial community structure analysis indicated that the abundance of Candidatus Brocadia (dominant anaerobic ammonia oxidizing bacteria (AnAOB) in the system) increased from 0.03% to 0.18%. The abundances of Nitrospira and Nitrosomonas increased from 1.6% and 0.16% to 2.5% and 1.63%, respectively, resulting in an increase in the ammonia-oxidizing bacteria (AOB) to nitrite-oxidizing bacteria (NOB) abundance ratio from 0.1 to 0.64. This ensured sufficient nitrite for AnAOB, promoting nitrogen removal. In addition, Candidatus Competibacter, which plays a role in partial denitrification, was the dominant denitrification bacteria (DNB) and provided more nitrite for AnAOB, facilitating AnAOB enrichment. Based on the findings from microbial correlation network analysis, Nitrosomonas (AOB), Thauera, and Haliangium (DNB), and A4b and Saprospiraceae (fermentation bacteria), were center nodes in the networks and therefore essential for the stability of the SNADF system. Moreover, fermentation bacteria, DNB, and AOB had close connections in substrate cooperation and resistance to adverse environments; therefore, they also played important roles in maintaining stable nitrogen removal at low temperatures. This study provided new suggestions for mainstream anammox application.
Correction: Roberg et al. A Mixed-Methods Exploration of Legal Vulnerability, Trauma, and Psychological Wellbeing in Immigrant Caregivers and Youth. Trauma Care 2024, 4, 60–74
Authors: Roberg Regina , Camargo Tamara , Marks Amy K.
Published: August 2024

In the original publication [...]
Long-Term SARS-CoV-2 Findings Related to Persisting Viral Antigen and Inflammation Resemble Those Reported for Influenza Virus and Respiratory Syncytial Virus
Authors: Roberts Norbert J.
Published: August 2024

Recent studies have documented prolonged expression of viral antigens and RNA and associated inflammation after infection with SARS-CoV-2 in a substantial proportion of infected patients. The persisting SARS-CoV-2 effects and findings, with inflammation associated with continued detection of viral antigens, especially resemble those previously reported for influenza virus, as well as respiratory syncytial virus (RSV). The reports indicate the need for improved insight into the mechanisms whereby post-SARS-CoV-2 infection-related illness is apparently more common and perhaps even more persistent after infection than observed for other respiratory viruses.
Looking Back, Moving Forward: Challenges and Opportunities for Global Cervical Cancer Prevention and Control
Authors: Castle Philip E.
Published: August 2024

Despite the introduction of Pap testing for screening to prevent cervical cancer in the mid-20th century, cervical cancer remains a common cause of cancer-related mortality and morbidity globally. This is primarily due to differences in access to screening and care between low-income and high-income resource settings, resulting in cervical cancer being one of the cancers with the greatest health disparity. The discovery of human papillomavirus (HPV) as the near-obligate viral cause of cervical cancer can revolutionize how it can be prevented: HPV vaccination against infection for prophylaxis and HPV testing-based screening for the detection and treatment of cervical pre-cancers for interception. As a result of this progress, the World Health Organization has championed the elimination of cervical cancer as a global health problem. However, unless research, investments, and actions are taken to ensure equitable global access to these highly effective preventive interventions, there is a real threat to exacerbating the current health inequities in cervical cancer. In this review, the progress to date and the challenges and opportunities for fulfilling the potential of HPV-targeted prevention for global cervical cancer control are discussed.
Adsorbents Produced from Olive Mill Waste and Modified to Perform Phenolic Compound Removal
Authors: Rocha Kleper de Oliveira , Brandão Francisco , Mazierski Pawel , Gomes João , Martins Rui C. , Domingues Eva
Published: August 2024

Olive mill waste (olive pomace, OP, and olive stone, OS) was used in this work to produce adsorbents for the removal of five phenolic acids typically found in olive mill wastewater. OP and OS were subjected to different treatments (combined or not) that were chemically modified (NaOH) or physically modified by two different methods, incipient wetness impregnation (IWI) and hydrothermal deposition (HD), and even biochar production obtaining a total of 16 materials. The materials were characterized by different analytical techniques such as N2 absorption, scanning electron microscopy, infrared spectroscopy, and pH zero-potential charge. The mixture of five phenolic acids was used to evaluate in batch conditions the adsorption capacity of the prepared materials. OS chemically modified with IWI (OSM-IWI) and OS biochar with HD (BOS-HD) presented better adsorption capacity at 157.1 and 163.6 mg/g of phenolic acids, respectively, from a total of 200 mg/g. For some materials, the surface area cannot be correlated with adsorption capacity, unlike pHzpc, where high values fit better adsorption rates. The infrared spectroscopy profile indicates the presence of O-H and N-H functional groups and, the last one, red-shifted in the IWI preparation compared to the HD one. In addition to this, the prepared material from olive mill waste can be suitably used for the mixture of phenolic compounds.