bluuebunny/crossref_metadata_2025 huggingface dataset:
Reviving Smallholder Hill Farming by Involving Rural Youth in Food System Transformation and Promoting Community-Based Agri-Ecotourism: A Case of Uttarakhand State in North-Western India
Authors: Rana Jai Chand , Bisht Ishwari Singh
Published: May 2023

Until recent decades, labour-intensive subsistence farming was a way of life and livelihood in the hill communities of Uttarakhand, India. However, the nature of agriculture falls far short of the expectations of the main labour force, the rural youth, leading to their mass migration to non-agricultural occupations. The large-scale youth migration has left many hill farming landscapes depopulated and farmlands abandoned. As youth have special stakes in food systems, they must be included in the sustainable transformation of food systems. By doing so, the migration-prone hill region may be transformed into a place where rural youth have more options for work and income. Therefore, the agriculture sector needs to change and develop into a more engaging and youthful workplace. There are opportunities to explore and barriers to be removed. Besides identifying priority research areas on local food systems, in this exploratory research, we investigate opportunities to involve rural young people in the transformation of the food system. We document information by conducting focus group discussion (FGD) meetings in about 100 villages in the Uttarakhand hills, representing all major farming landscapes. This study mainly focuses on improving the production and consumption aspects of local food, which not only benefits the health and wellbeing of local communities but also has many positive economic, social, and environmental effects. In addition, we explore opportunities for reviving mountain agriculture through agri-ecotourism, which is a symbiotic relationship between tourism and agriculture. Making home- or farm stays in agri-ecotourism a subsistence strategy for local youth will contribute to a more prosperous rural economy. Recognising Uttarakhand’s rich culture and heritage while exploring the culinary travel opportunities in homestays will provide opportunities to focus more on traditional food systems, exposing various tangible and intangible aspects of the host region’s food culture to tourists. The findings of this study will aid in identifying specific policy issues for consideration by planners and policymakers at the local and state levels. Additionally, this exploratory study will assist young, motivated researchers in conducting follow-up, in-depth investigations and producing empirical data in their specialised fields.
More Government Subsidies, More Innovation of New Energy Firms? Evidence from China
Authors: Feng Mei , Wang Ye
Published: May 2023

This paper evaluates the causal relationship between government subsidy and the innovation performance of new energy firms through count models using 2007–2021 data from China’s listed new energy companies. By looking at the subsidy for listed new energy firms and the number of granted patents, we find government subsidy policies significantly boost firms’ innovation performance. We estimate that a tenfold increase in government subsidy would lead to an increase of 7.11 in the total number of granted patents for new energy firms. Furthermore, a heterogeneity analysis shows such an effect varies depending on the nature of property rights, subsidy scale, and region for new energy firms. To be specific, state-owned firms are more dependent on government subsidy, the effect on innovation is generally higher in the high-subsidy group than in the low-subsidy group while being higher in the low-subsidy group when it comes to low-tech design patents, and firms in the eastern region are most sensitive to government subsidy. This paper also assesses the role of R&D investment in how government subsidy policies boost firms’ innovation performance; that is, by increasing their R&D funding investment rather than R&D manpower investment. These findings illustrate that in developing countries, government subsidy is effective in boosting new energy firms’ innovation performance.
Model of Key Factors in the Sustainable Growth of Small and Medium-Sized Enterprises Belonging to the First Nations
Authors: Melillanca Eric , Ramírez Milton , Forcael Eric
Published: May 2023

The search for better living conditions, hand in hand with economic development, is a desire shared by all peoples; the First Nations are no exception. In this sense, entrepreneurship is one of the ways to improve incomes and quality of life, both in industrialized and developing societies, which is considered a potential strategy for economic development. This exploratory research presents a model that explains, through causal relationships, the growth of Small and Medium-sized Enterprises (SMEs) belonging to the First Nations, based on the results coming from the analysis conducted within one of the most important First Nations in the Americas, the Mapuche people, located in South America (mainly Argentina and Chile). The framework was developed from interviews with entrepreneurs and owners of Mapuche SMEs, along with an exhaustive analysis carried out through the use of Partial Least Squares (PLS). The owners were consulted about their attitude towards variables that generate accelerated growth in entrepreneurship in different contexts around the world. Subsequently, a model of inter-relationships was generated that sought to explain which variables are determining factors in the growth of SMEs belonging to the First Nations. Through a process of evaluation and depuration, the model proposed here was arrived at, concluding that Constant Training and Commitment to Growth are the most relevant factors in the growth of these companies. Both of these factors are supported by Long-Term Customer Relationships, Differentiation by Quality, Business Skills, and Business Structure, with a special focus on sustainable development.
Communities in Transitions: Reflection on the Impact of the Outbreak of COVID-19 on Urban China
Authors: Du Shengchen , Tan Hongze
Published: May 2023

“Community”, as a basic category of urban socio-space, has undergone evolution within academic, policy, and day-to-day life contexts in China. Through years of transitions, a kind of dual community emerged in Chinese cities before the epidemic. It encompassed a “conceptual community” based on the concept of (social) co-governance and an “experiential community” based on citizens’ daily living. The disparity between the two had given rise to a paradoxical situation in local community governance practices. The outbreak of COVID-19 brought fundamental changes to the transition process. Through the analysis of 21 recording reports during the outbreak period, we found that to contain the pandemic, the community epidemic prevention measures necessitated both these communities to overlap within a brief time frame. This led to reinforced community boundaries, the coexistence of multiple actors, the reconstruction of a sense of security-based belongingness, and the reformulation of the governance symbolic system that temporarily resolved the paradoxical governance practices. What happened under the preface of co-governance logic during the outbreak period was the coverage and shaping of the conceptual community over the experiential community, which may continue during the post-epidemic era. This study offers a relatively new approach and valuable insights into examining the long-lasting impact of the epidemic on urban social space and sustainable development in the post-epidemic era.
Managing and Governing Integrated Research Programmes: Lessons from Theory and Practice
Authors: Wever Mark , Romera Alvaro , Shah Munir , Wognum Nel
Published: May 2023

Researchers are increasingly working in large, integrated science programmes. This is supposed to lead to several benefits, including creating and enhancing synergies amongst projects, improving collaboration and knowledge exchanges amongst researchers from different disciplines, and generating a higher return on investments in R&D. In practice, though, these benefits are often not fully realised, and large-scale integrated programmes can become frustrating for researchers. Additionally, they can result in insufficient integration and collaboration, and incur high overhead costs. In the present paper, the authors share their experience and insights on how to structure, manage and govern integrated programmes more competently. They do so by reflecting on their own practical experience in designing an integrated programme, and by drawing valuable insights from the literature on governance, management studies and organisational economics. The authors suggest that many problems can be linked to the implementation of programme management systems and coordination mechanisms that are poorly aligned with the unique characteristics of integrated programmes. They provide guidelines for programme managers to use systems that are a better fit, which can help researchers collaborate in a more engaging and productive manner while reducing the overhead costs associated with programme administration.
Optimization of Crop Recommendations Using Novel Machine Learning Techniques
Authors: Lahza Husam , Naveen Kumar K. R. , Sreenivasa B. R. , Shawly Tawfeeq , Alsheikhy Ahmed A. , Hiremath Arun Kumar , Lahza Hassan Fareed M.
Published: May 2023

A farmer can use machine learning to make decisions about what crops to sow, how to care for those crops throughout the growing season, and how to predict crop yields. According to the World Health Organization, agriculture is essential to the nation’s quick economic development. Food security, access, and adoption are the three cornerstones of the organization. Without a doubt, the main priority is to ensure that there is enough food for everyone. Increasing agricultural yield can help ensure a sufficient supply. The country-wide variation in crop yields is substantial. As a result, this will be the foundation for research into whether cluster analysis can be used to identify crop yield patterns in a field. Previous study investigations were only marginally successful in accomplishing their primary intended objectives because of unstable conditions and imprecise methodology. The vast majority of farmers base their predictions of crop yield on prior observations of crop growth in their farms, which can be deceptive. Standard preprocessing methods and random cluster value selection are not always reliable, according to the literature. The proposed study overcomes the shortcomings of conventional methodology by highlighting the significance of machine learning-based classification/partitioning and hierarchical approaches in offering a trained analysis of yield prediction in the state of Karnataka. The dataset used for the study was collected from the ICAR-Taralabalu Krishi Vigyan Kendra, Davangere, Karnataka. In the two dataset analysis techniques employed in the study to find anomalies, crop area, and crop production are significant variables. Crop area and crop yield are important variables in the two dataset analysis methods used in the study to detect anomalies. The study emphasizes the importance of a mathematical model and algorithm for identifying yield trends, which can assist farmers in selecting crops that have a large seasonal impact on yield productivity.
Discussion on Adjustment Method of the Characteristic Period of Site Response Spectrum with Soft Soil Layer
Authors: Li Yuandong , Hao Bing , Chen Zhen , Zhou Zhenghua , Bian Zhu , Han Yi , Peng Cheng
Published: May 2023

Twelve site models were established based on the analysis of the influence of site conditions on earthquake damage and the influence of the soft soil layer on-site seismic response. The equivalent linearization site seismic response analysis is carried out at different input ground motion levels to discuss the influence of soft soil layer thickness and buried depth. The results show that the characteristic period of the response spectrum exhibits a gradual increase as the buried depth or thickness of the soft soil layer increases. Furthermore, the characteristic period of the response spectrum also increases with the rise in the input ground motion peak. Moreover, according to the influence characteristics of soft soil thickness, buried depth, and input ground motion intensity on the characteristic period of the site acceleration response spectrum, a method for adjusting the characteristic period of the site acceleration response spectrum with a soft soil layer is put forward.
Segmentation of Hungarian Consumers Based on Circular Economy Values and Awareness of Food Waste
Authors: Pércsi Kinga Nagyné , Ujj Apolka , Jancsovszka Paulina
Published: May 2023

This study aims to detect those segments among the Hungarian food consumers who are aware of the climate risks of their food consumption. In order to achieve this goal, a survey was conducted with the participation of Hungarian university students. Data from 1184 households were collected and used in Factor (Principal Component) and Cluster Analysis. Two very conscious clusters were found; both are highly qualified. One favored waste utilization, asserting that and encouraging most of its members to follow a zero-waste lifestyle. The latter mentioned that cluster members are young, and they are in a good financial situation. The findings of this study may be of interest to policy makers for environmentally responsible food consumption guidance and training for planning consumer awareness programs. Even though several previous studies have addressed the concept of consumer awareness concerning food purchase decisions, only few of them dealt with consumer awareness in the environment and climate domain in food consumption in Hungary, so this research could be considered as filling a gap.
The Relationship between Air Travel Service Quality and Factors of Theory of Planned Behavior: Evidence from Low-Cost Airlines in Thailand
Authors: Thongkruer Peeraya , Wanarat Sawat
Published: May 2023

Despite an increased emphasis on improvement in airline service quality concerning consumer behavior, such as passenger repurchasing as a result of their behavioral intention over the last several decades, there is still much less concern with the nature of airline service quality than should exist in the so-called “logistics service quality” and less concern with examining the specific behavioral intention preceding repurchasing behavior together with the theory of planned behavior. As such, this study aims to explore these issues, along with the psychological factors of the theory of planned behavior, that can lead to repurchasing behavior via word-of-mouth intention (WOMI). With an online survey of 383 respondents experienced with flying, the results reveal that the logistics service quality and each determinant in the theory positively influence a passenger’s repurchasing behavior through WOMI. Accordingly, service marketers can implement service design and apply integrated marketing communication by learning from repurchasing behavior that was formed by the given factors to retain their existing customers. Moreover, this study is the first to empirically and explicitly validate dimensions of airline services through the lens of logistics that are deemed fit with the nature of the airlines. It advances the understanding of theory approaching and connects what has hampered its advancement in a body of knowledge, simultaneously in a context of airline context where it should not be relegated to transportation and consumer and service orientation.
Assessment of Building Materials in the European Residential Building Stock: An Analysis at EU27 Level
Authors: Zandonella Callegher Claudio , Grazieschi Gianluca , Wilczynski  Eric , Oberegger Ulrich Filippi , Pezzutto Simon
Published: May 2023

Reducing greenhouse gas (GHG) emissions and energy consumption in the building sector requires not only improving the energy efficiency of buildings but also minimising material requirements, embodied emissions, and waste generation. Circular Economy (CE) principles can be applied to minimize resource extraction and waste generation in the building industry. However, to implement effective CE strategies, quantification and evaluation of materials accumulated in buildings are required. This study aims to provide accurate data and a detailed analysis of the materials available in the EU27 residential building sector. By elaborating the data provided by the H2020 European projects Hotmaps and AmBIENCe, the different materials used for floors, roofs, walls, windows, and insulation layers in single-family houses, multifamily houses, and apartment blocks in the different construction periods were quantified for each EU27 country. Considering results at the EU27 level, concrete and brick characterize the largest part of the European residential building stock, whereas materials such as wood and different types of rock are used in much more limited amounts. These results form the basis for policymakers to monitor the status of the residential building sector, evaluate the potential of CE policies at a national level, and assess the environmental impact of building practices through lifecycle assessment.
Application of Synthesized Biomass Bamboo Charcoal–Iron Oxide “BC/Fe” Nanocomposite Adsorbents in the Removal of Cationic Methylene Blue Dye Contaminants from Wastewater by Adsorption
Authors: Sen Tushar Kanti
Published: May 2023

In this work, synthesized, raw-bamboo-biomass-based magnetic “BC/Fe” bamboo charcoal–iron oxide nanocomposite adsorbents were characterized and tested for their effects on the removal of aqueous-phase cationic methylene blue (MB) dye pollutants from synthetic wastewater through a laboratory batch adsorption study. This batch adsorption study aimed to identify various physico-chemical process parameters such as initial dye concentration, solution pH, adsorbent dose, temperature, and their effects on the adsorption kinetics and adsorption isotherm characteristics. From the kinetic studies, it was found that the amount of MB dye adsorption by synthesized adsorbents qe (mg/g) increased from 9.50 mg/g to 15.30 mg/g with the increase in the initial dye concentration range of 10 to 30 ppm, as per contact time, but decreased with the increase in the temperature range from 30 to 60 °C and the adsorbent doses from 20 to 40 mg, respectively, under specified experimental process conditions. From the kinetic study, it was also found that equilibrium was reached within 120 min, the adsorption kinetics followed three mechanistic steps, and the pseudo-second-order (PSO) kinetic model was applicable to explain the data of the batch adsorption kinetics. The various kinetic model parameters were determined from a fitted model equation. Furthermore, there was an increase in the amount of the MB dye adsorption qe (mg/g) from 9.87 mg/g to 17.62 mg/g with the increase in the solution pH from 3 to 7, and a reduction in the amount of dye adsorption qe (mg/g) was found at the solution pH of 10 for a 20 ppm MB dye solution at 30 °C. Both the Freundlich and Langmuir isotherm models were applicable to the equilibrium data, and the maximum adsorption capacity from the Langmuir isotherm fitting was 111.11 mg/g, which was comparative to or even better than many other magnetic adsorbents for methylene blue dye adsorption. Finally, the regeneration and reusability of the magnetic “BC/Fe” bamboo charcoal–iron oxide nanocomposite materials as well as the limitations of these batch adsorption studies are also discussed here.
Research on Optimization Method of Integrated Energy System Network Planning
Authors: Yang Chun , You Shijun , Han Yingzhu , Wang Xuan , Li Ji , Wang Lu
Published: May 2023

The development of an integrated energy system (IES) is conducive to promoting the transformation of the energy system and helping to achieve the ‘double carbon’ goal in China. The IES integrates cooling, heating, electricity, gas, and other energy resources, which is significantly more difficult than single energy network planning. This paper systematically sorts out the process of IES network planning and proposes an improved methodology. Firstly, the bottom-up dynamic multiple-load forecasting method of 8760 h a year is proposed as the basis of system configuration and capacity selection. Subsequently, a planning method for energy station location and route optimization using the Dijkstra algorithm is constructed by applying the P-median optimization model. Finally, when optimizing the capacity allocation of the IES, the complementary characteristics of natural gas, electricity and heat, as well as the corresponding energy demand characteristic, have been fully considered, so that the optimization objectives can be reasonably determined. Through the actual calculation, it is found that the optimization method proposed in this paper can reduce the construction cost of the network by 41%. The work combines the process of energy network planning and capacity configuration of IES, which provides a simple, easy and economical solution for IES planning in new areas.
Sustainable Development Assessment of Organizations through Quantitative Modelling
Authors: Bouras Dimitrios , Sofianopoulou Styliani (Stella)
Published: May 2023

The “United Nations (UN) 2030 Agenda for Sustainable Development” is calling on businesses to apply their creativity and innovation initiatives to tackle sustainable development challenges. In this respect, this study intends to propose a sustainability model for business use. The proposed model will facilitate businesses in selecting the appropriate Sustainable Development Goal (SDG) indicators, highlight potential sustainability “gaps” and emphasize the related best practices. For the development of the sustainability model, we used some basic economic principles (e.g., cost minimization, risk theory, etc.), a sustainability survey and a statistical study based on EU data. As a result, a quantitative model for the sustainable development assessment of organizations to formulate appropriate decision-making policies is proposed. The model was tested in a real-world context as a case study that was carried out at the Greek Atomic Energy Commission.
Stakeholders’ Involvement, Organizational Learning and Social Innovation: Factors for Strengthening the Resilience of Moroccan Cooperatives in the Post-COVID-19 Era
Authors: Rhouiri Mouhcine , Meyabe Mohamed-Habiboullah , Yousfi Fatima-Zahra , Saidi Hicham , Marghich Abdellatif , Aiboud-Benchekroun Bouchra , Madhat Fatima-Zahra
Published: May 2023

The Moroccan cooperative sector is increasingly important, not only in the social and economic fabric of Morocco, but also in the sustainable development of the Kingdom. With the advent of COVID, the cooperative sector offers more inclusive and sustainable economic alternatives than ever before. In this context, organizational resilience is essential to preserve the sustainability of cooperatives and anticipate potential crises. This study addresses the following issue: What are the organizational factors necessary to strengthen the organizational resilience of the Moroccan cooperative in the Fez-Meknes region in times of COVID-19 crisis? The purpose of this paper was to test the hypothesized relationships between a set of latent constructs (actor involvement and mobilization, organizational learning in times of a crisis and social innovation) and the organizational resilience of cooperatives in times of a COVID-19 crisis. The methodology adopted is structural equation modeling based on the PLS-SEM method under the “SmartPLS Version 3” used on data collected through a printed questionnaire administered to 160 cooperatives in the Fez-Meknes region. The results show the significant and positive influence between the exogenous constructs on the strengthening of organizational resilience of cooperatives as an endogenous construct. The novelty of the study lies in the identification of the organizational resources needed to strengthen the organizational resilience of cooperatives in the Moroccan context. The results show that organizational resilience depends on three selected organizational factors: stakeholder involvement and mobilization, organizational learning in the times of a crisis and social innovation.
Corporate Social Responsibility and Entrepreneurial Ventures: A Conceptual Framework and Research Agenda
Authors: Chenavaz Régis Y. , Couston Alexandra , Heichelbech Stéphanie , Pignatel Isabelle , Dimitrov Stanko
Published: May 2023

Corporate social responsibility (CSR) and entrepreneurship are two essential topics in the current business landscape. However, despite the growing literature on these topics, there needs to be more comprehensive understanding of how they are related. In this conceptual article, we explore the linkages between CSR and entrepreneurship. First, we provide a definition and scope of entrepreneurship and then discuss the literature on CSR, highlighting different ways that businesses can engage in CSR. We argue that CSR and entrepreneurship are closely related, and propose a conceptual framework to understand how CSR can be integrated into the entrepreneurial process. Additionally, we identify three key areas of research in this emerging field: (1) the motivations for entrepreneurs to engage in CSR; (2) the impact of CSR on entrepreneurial ventures; and (3) the role of CSR in social entrepreneurship. We conclude with a discussion of our conceptual framework’s theoretical and practical implications, as well as future research directions for scholars and practitioners interested in CSR and Entrepreneurship.
Design for Well-Being and Sustainability: A Conceptual Framework of the Peer-to-Peer Sharing and Reuse Platform in the Circular Economy
Authors: Ho Meng-Xun , Yanagisawa Hideyoshi
Published: May 2023

To regain overall well-being in the post-pandemic era, the priorities should not be only economic growth but also human physical and mental health. This study investigates how to incorporate the concept of well-being into the circular economy to facilitate the pursuit of individual/personal and social growth, and sustainable consumption. We begin with a systematic search of the literature on well-being and sustainable product–service systems, model the well-being components in peer-to-peer (P2P) sharing and reuse platforms, and propose design guidelines for platform development. According to our findings, (1) allocentric well-being components (such as gratitude, contribution, and altruism) serve as the antecedents of sharing behaviors, while egocentric components (such as pleasure and attachment) serve as the consequences, and (2) information sharing is crucial to initiating the flow of well-being perceptions and sustainable sharing and reuse behaviors. Based on the findings, we suggest a data-driven approach and active inference theory to facilitate related studies. This study sheds light on the potential to develop well-being within the circular economy and facilitate the sustainable working of the sharing and reuse ecosystem.
Lessons Learnt and Policy Implications from Implementing the POWERPOOR Approach to Alleviate Energy Poverty
Authors: Kanellou Eleni , Hinsch Arthur , Vorkapić Veljko , Torres Alis-Daniela , Konstantopoulos Georgios , Matsagkos Nektarios , Doukas Haris
Published: May 2023

Energy poverty is a multifaceted phenomenon that affects many Europeans. Alleviating energy poverty is high in the EU, national, and local policy agendas. Despite the attention the phenomenon has been gaining from a policy perspective, especially after the current energy crisis, there are still some gaps due to the complexity of the issue and its vastly different manifestations across Europe. This manuscript presents the policy implications stemming from the implementation of the POWEPROOR approach in alleviating energy poverty in eight European countries, as co-created with relevant stakeholders in each country. The knowledge gained from empowering energy-poor citizens by promoting behavioural changes and small-scale energy efficiency interventions, as well as by encouraging the uptake of renewable energy sources in the form of collective energy initiatives while leveraging innovative financing schemes, resulted in policy recommendations for national and sub-national governments and lessons for civil society and the private sector.
Insights for Pro-Sustainable Tourist Behavior: The Role of Sustainable Destination Information and Pro-Sustainable Tourist Habits
Authors: Gomes Sofia , Lopes João M.
Published: May 2023

In recent decades, the impositions of environmental sustainability have resulted in severe challenges for the tourism sector. It is not enough to make tourist destinations greener and more circular. It is necessary to encourage pro-sustainable behavior among tourists. This research aims to explore the role of available reliable information on the sustainability of destinations in relation to the pro-sustainable habits of tourists and to investigate changes in tourist behavior related to travel and tourism. In addition, it aims to assess the influence of tourists’ pro-sustainable habits on changes in their behavior regarding travel and tourism. For this, a sample of 25,711 residents in Europe-27 were considered, collected through the Flash Eurobarometer 499 database (attitudes of Europeans against tourism, autumn 2021) by GESIS—Leibniz Institute for Social Sciences. A quantitative analysis was performed using the Partial Least Square method. The results reveal that the available reliable information on the sustainability of destinations positively influences the adoption of pro-sustainable travel and tourism habits and changes in tourist behavior, guiding them towards pro-sustainable travel and tourism preferences. Furthermore, pro-sustainable travel and tourism habits positively influence pro-sustainable changes in tourist behavior. This study provides accurate and accessible information on the sustainability of destinations, promoting pro-sustainable travel and tourism habits and encouraging the adoption of conscious behavior during travel to work towards a more sustainable tourism industry, which is responsible in regard to the environment and to local communities.
Contribution of Social Media Analytics to Disaster Response Effectiveness: A Systematic Review of the Literature
Authors: Acikara Turgut , Xia Bo , Yigitcanlar Tan , Hon Carol
Published: May 2023

Disasters are sudden and catastrophic events with fatal consequences. Time-sensitive information collection from disaster zones is crucial for improved and data-driven disaster response. However, information collection from disaster zones in a prompt way is not easy or even possible. Human-centric information provided by citizen sensors through social media platforms create an opportunity for prompt information collection from disaster zones. There is, nevertheless, limited scholarly work that provides a comprehensive review on the potential of social media analytics for disaster response. This study utilizes a systematic literature review with PRISMA protocol to investigate the potential of social media analytics for enhanced disaster response. The findings of the systematic review of the literature pieces (n = 102) disclosed that (a) social media analytics in the disaster management research domain is an emerging field of research and practice; (b) the central focus on the research domain is on the utilization of social media data for disaster response to natural hazards, but the social media data-driven disaster response to human-made disasters is an increasing research focus; (c) human-centric information intelligence provided by social media analytics in disaster response mainly concentrates on collective intelligence, location awareness, and situation awareness, and (d) there is limited scholarly research investigating near-real-time transport network management aftermath disasters. The findings inform authorities’ decision-making processes as near-real time disaster response management depending on social media analytics is a critical element of securing sustainable cities and communities.
Myrtenal and Myrtanal as Auxiliaries in the Synthesis of Some C,P-Stereogenic Hydroxyphosphine Oxides and Hydroxyphosphine-Boranes Possessing up to Four Contiguous Centers of Chirality
Authors: Pietrusiewicz K. Michał , Kozioł Anna E. , Małuszyńska Hanna , Sowa Sylwia
Published: May 2023

1,4- and 1,2-additons of secondary phosphine oxides to (1R)-myrtenal and (1S)-myrtanal were evaluated as potential routes to P,C-stereogenic phosphine oxides bearing additional hydroxyl or aldehyde functions. 1,4-Additions of racemic secondary phosphine oxides to (1R)-myrtenal were found to offer moderate to good stereoselectivity which shows some promise for utility in kinetic resolution processes, especially at lower conversions. In case of 1,2-additions making the process doubly asymmetric by using an enantiomerically pure secondary phosphine oxide as substrate turned out to be practical. The stereochemical course of the addition reactions under study is presented. The P-resolved 1,2-addition products were demonstrated to undergo facile reduction by BH3 at room temperature leading to the formation of the corresponding α-hydroxyphosphine-boranes with clean inversion of configuration at the P-centre. All P,C-stereogenic phosphine oxides and boranes that were isolated in the form of a single diastereoisomer were assigned their absolute configurations by means of X-ray crystallography and/or 2D NMR spectral techniques.
Mental Pressure Recognition Method Based on CNN Model and EEG Signal under Cross Session
Authors: Zhou Song , Gao Tianhan , Xu Jun
Published: May 2023

There is an important application value in assessing an operator’s mental pressure (MP) level in human–computer cooperative tasks through continuous asymmetric electroencephalogram (EEG) signals, which can help predict hidden risks. Due to the different distributions of EEG features in different periods, it is particularly challenging to accurately identify brain states by training and testing asymmetric EEG signals with static pattern classifiers. Due to the limitations of non-stationary neurophysiological data capture technology, cross-session MP recognition schemes can only be used as an auxiliary means in practical applications. Deep learning methods can achieve stable feature extraction at a high level. Based on this advantage, this paper proposes a triplet loss (TL)-based CNN model that can automatically update the weights of shallow hidden neurons in cross-session MP classification tasks. Firstly, the generalization ability of the CNN model under both intra-session and cross-session conditions is evaluated. Moreover, the proposed model is compared with the existing MP classifier under different feature selection and noise destruction modes. According to the results, our TL-based CNN model has high performance in processing cross-session EEG features.
An Input-Series-Output-Parallel Cascaded Converter System Applied to DC Microgrids
Authors: Lv Menghan , Wang Peng , Wei Yaoquan , Wen Chunxue , Li Jianlin , Jia Pengyu , Wei Qingxuan
Published: May 2023

Direct current transformer (DCT) is a key piece of equipment in direct current (DC) microgrids, and the mainstream topologies mainly include LLC resonant converter (LLC) and dual active bridge (DAB). In this paper, a novel bi-directional buck/boost + CLLLC cascade topology is proposed for the input-series-output-parallel cascade converter system of a DC microgrid. To solve the problem that frequency variation causes the converter to deviate from the optimal operating point, resulting in low efficiency, and the inability to achieve a soft switching function. The CLLLC converter operates near the resonant frequency point as a DCT, only providing electrical isolation and voltage matching, while the buck/boost converter controls the output voltage and the voltage and current sharing of each module. Compared to other cascaded converter systems, the cascaded converter proposed in this paper has high efficiency, simplifies the parameter design, and is suitable for wide input and wide output operating conditions. The system adopts a three-loop control strategy, establishes the small-signal modeling of the system, and its stability is verified by theoretical analysis and simulation. The simulation and experimental results verify the correctness of the proposed cascaded converter based on buck/boost + CLLLC and the effectiveness of the control strategy.
Improved Upper Bounds of the Third-Order Hankel Determinant for Ozaki Close-to-Convex Functions
Authors: Guo Dong , Tang Huo , Zhang Jun , Li Zongtao , Xu Qingbing , Ao En
Published: May 2023

LetN be the class of functions that convex in one direction and M denote the class of functions zf′(z), where f∈N. In the paper, the third-order Hankel determinants for these classes are estimated. The estimates of H3,1(f) obtained in the paper are improved.
The Influence of Emotion and Emotion Regulation on Complex Problem-Solving Performance
Authors: Güss C. Dominik , Starker Ulrike
Published: May 2023

Complex problem solving (CPS) research has focused on cognitive variables, but in recent years, the influential role of emotions and motivation during the CPS process has been highlighted. In the current study, we focus on emotion regulation during CPS. Eighty-three university students worked on a simulated chocolate-producing company. Initially, they completed a survey on emotion regulation and demographics. Then, they were randomly assigned to four conditions where emotions were induced with short video clips: anger, fear, happiness, and trust. A manipulation check assessed the successful priming of emotions. While working individually on the microworld, CPS behavior and performance were saved in log files. We hypothesized that happiness and trust would lead to better performance than fear and anger. We also hypothesized that emotion regulation would be positively related to performance. There were no differences in performance at the beginning and at the end of the simulation among the four emotion groups. Regression analyses showed that emotion-regulation strategies significantly predicted CPS performance. Aggression was positively related to performance. Results show that it is more the regulation of emotions than the emotion per se that influences CPS performance.
Analysis of Patulin in Apple Products Marketed in Belgium: Intra-Laboratory Validation Study and Occurrence
Authors: Tangni Emmanuel K. , Masquelier Julien , Van Hoeck Els
Published: May 2023

Apple and apple derivatives (e.g., juices, puree) are the most important foodstuffs contaminated with patulin (PAT) in the human diet. To routinely monitor these foodstuffs and ensure that the PAT levels are below the maximum permitted levels, a method using liquid chromatography combined with tandem mass spectrometry (LC-MS/MS) has been developed. Afterwards, the method was successfully validated, reaching quantification limits of 1.2 μg/L for apple juice and cider, and 2.1 μg/kg for puree. Recovery experiments were performed with samples fortified with PAT in the range of 25–75 μg/L for juice/cider and 25–75 μg/kg for puree. The results show overall average recovery rates of 85% (RSDr = 13.1%) and 86% (RSDr = 2.6%) with maximum extended uncertainty (Umax, k = 2) of 34 and 35% for apple juice/cider and puree, respectively. Next, the validated method was applied to 103 juices, 42 purees and 10 ciders purchased on the Belgian market in 2021. PAT was not found in the cider samples, but it was present in 54.4% of the tested apple juices (up to 191.1 μg/L) and 7.1% of the puree samples (up to 35.9 μg/kg). When comparing the results to the maximum levels set by Regulation EC n° 1881/2006 (i.e., 50 μg/L for juices and 25 μg/kg for puree for adults, and 10 μg/kg for infants and young children), exceedances were observed in five apple juices and one puree sample, for infants and young children. Using these data, a potential risk assessment for consumers can be suggested, and it is found that the quality of apple juices and purees sold in Belgium needs further regular surveillance.
Reduced Binding between Omicron B.1.1.529 and the Human ACE2 Receptor in a Surrogate Virus Neutralization Test for SARS-CoV-2
Authors: Hoffman Tove , Kolstad Linda , Akaberi Dario , Järhult Josef D. , Rönnberg Bengt , Lundkvist Åke
Published: May 2023

The current gold standard assay for detecting neutralizing antibodies (NAbs) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the conventional virus neutralization test (cVNT), which requires infectious virus and a biosafety level 3 laboratory. Here, we report the development of a SARS-CoV-2 surrogate virus neutralization test (sVNT) that, with Luminex technology, detects NAbs. The assay was designed to mimic the virus–host interaction and is based on antibody blockage between the human angiotensin-converting enzyme 2 (hACE2) receptor and the spike (S) protein of the Wuhan, Delta, and Omicron (B.1.1.529) variants of SARS-CoV-2. The sVNT proved to have a 100% correlation with a SARS-CoV-2 cVNT regarding qualitative results. Binding between the hACE2 receptor and the S1 domain of the B.1.1.529 lineage of the Omicron variant was not observed in the assay but between the receptor and an S1 + S2 trimer and the receptor binding domain (RBD) in a reduced manner, suggesting less efficient receptor binding for the B.1.1.529 Omicron variant. The results indicate that the SARS-CoV-2 sVNT is a suitable tool for both the research community and the public health service, as it may serve as an efficient diagnostic alternative to the cVNT.
Mass-Spectrometric Evaluation of the African Swine Fever Virus-Induced Host Shutoff Using Dynamic Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC)
Authors: Wöhnke Elisabeth , Klupp Barbara G. , Blome Sandra , Mettenleiter Thomas C. , Karger Axel
Published: May 2023

African swine fever is a viral disease of swine caused by the African swine fever virus (ASFV). Currently, ASFV is spreading over the Eurasian continent and threatening global pig husbandry. One viral strategy to undermine an efficient host cell response is to establish a global shutoff of host protein synthesis. This shutoff has been observed in ASFV-infected cultured cells using two-dimensional electrophoresis combined with metabolic radioactive labeling. However, it remained unclear if this shutoff was selective for certain host proteins. Here, we characterized ASFV-induced shutoff in porcine macrophages by measurement of relative protein synthesis rates using a mass spectrometric approach based on stable isotope labeling with amino acids in cell culture (SILAC). The impact of ASFV infection on the synthesis of >2000 individual host proteins showed a high degree of variability, ranging from complete shutoff to a strong induction of proteins that are absent from naïve cells. GO-term enrichment analysis revealed that the most effective shutoff was observed for proteins related to RNA metabolism, while typical representatives of the innate immune system were strongly induced after infection. This experimental setup is suitable to quantify a virion-induced host shutoff (vhs) after infection with different viruses.
Genetic Variants Associated with Drug Resistance of Cytomegalovirus in Hematopoietic Cell Transplantation Recipients
Authors: Chae Seungwan , Kim Hoon Seok , Cho Sung-Yeon , Nho Dukhee , Lee Raeseok , Lee Dong-Gun , Kim Myungshin , Kim Yonggoo
Published: May 2023

Cytomegalovirus (CMV) infection is a serious complication in hematopoietic cell transplantation (HCT) recipients. Drug-resistant strains make it more challenging to treat CMV infection. This study aimed to identify variants associated with CMV drug resistance in HCT recipients and assess their clinical significance. A total of 123 patients with refractory CMV DNAemia out of 2271 HCT patients at the Catholic Hematology Hospital between April 2016 and November 2021 were analyzed, which accounted for 8.6% of the 1428 patients who received pre-emptive therapy. Real-time PCR was used to monitor CMV infection. Direct sequencing was performed to identify drug-resistant variants in UL97 and UL54. Resistance variants were found in 10 (8.1%) patients, and variants of uncertain significance (VUS) were found in 48 (39.0%) patients. Patients with resistance variants had a significantly higher peak CMV viral load than those without (p = 0.015). Patients with any variants had a higher risk of severe graft-versus-host disease and lower one-year survival rates than those without (p = 0.003 and p = 0.044, respectively). Interestingly, the presence of variants reduced the rate of CMV clearance, particularly in patients who did not modify their initial antiviral regimen. However, it had no apparent impact on individuals whose antiviral regimens were changed due to refractoriness. This study highlights the importance of identifying genetic variants associated with CMV drug resistance in HCT recipients for providing appropriate antiviral treatment and predicting patient outcomes.
Does Intra-Uterine Exposure to the Zika Virus Increase Risks of Cognitive Delay at Preschool Ages? Findings from a Zika-Exposed Cohort from Grenada, West Indies
Authors: Fernandes Michelle , Evans Roberta , Cheng Mira , Landon Barbara , Noël Trevor , Macpherson Calum , Cudjoe Nikita , Burgen Kemi S. , Waechter Randall , LaBeaud A. Desiree , Blackmon Karen
Published: May 2023

Maternal infection with Zika virus (ZIKV) is associated with a distinct pattern of birth defects, known as congenital Zika syndrome (CZS). In ZIKV-exposed children without CZS, it is often unclear whether they were protected from in utero infection and neurotropism. Early neurodevelopmental assessment is essential for detecting neurodevelopmental delays (NDDs) and prioritizing at-risk children for early intervention. We compared neurodevelopmental outcomes between ZIKV-exposed and unexposed children at 1, 3 and 4 years to assess exposure-associated NDD risk. A total of 384 mother–child dyads were enrolled during a period of active ZIKV transmission (2016–2017) in Grenada, West Indies. Exposure status was based on laboratory assessment of prenatal and postnatal maternal serum. Neurodevelopment was assessed using the Oxford Neurodevelopment Assessment, the NEPSY® Second Edition and Cardiff Vision Tests, at 12 (n = 66), 36 (n = 58) and 48 (n = 59) months, respectively. There were no differences in NDD rates or vision scores between ZIKV-exposed and unexposed children. Rates of microcephaly at birth (0.88% vs. 0.83%, p = 0.81), and childhood stunting and wasting did not differ between groups. Our results show that Grenadian ZIKV-exposed children, the majority of whom were without microcephaly, had similar neurodevelopmental outcomes to unexposed controls up to at least an age of 4 years.