bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Effects of COVID-19 Pandemic on Small- and Medium-Sized Enterprises (SMEs) in Rwanda Using Wood Firm-Level Data
Authors: Munyemana Emmanuel , Mung’atu Joseph , Ruranga Charles
Published: August 2024

This study assesses and quantifies the economic and financial impacts of the COVID-19 pandemic during the period of business operation restrictions countrywide (lockdown measures). We examine the strategies adopted by small and medium-sized enterprises (SMEs) to reopen their business operations after lockdown measures had been relaxed or lifted. Data were collected in Rwanda from nearly 244 SMEs across the country, providing firsthand and reliable information on the effects of the pandemic on business performance, with a particular emphasis on wood-based enterprises. We used Exploratory Data Analysis (EDA) and multivariate linear regression methods to measure the pandemic’s effects on employment, sales, and tax payments among SMEs. The findings reveal that firms downsized employment by 36%, with significant deviations within different SME sizes. Small businesses were particularly affected by reduced sales levels due to the pandemic. Although there was an overall reduction in tax payments during the crisis, medium-sized enterprises experienced a more significant decrease in taxes paid to the government by 74.6%. Additionally, regression findings affirm that the COVID-19 effects on SMEs were manifested in reduced sales across all categories of SMEs, reduced employment, and a reduced amount of taxes paid to the government, which further translate to reduced economic performance during COVID-19 period. Furthermore, SME owners utilised various coping mechanisms during the reopening phase, including a reliance on savings and selling assets. The analysis recommends establishing medium-term financing mechanisms and providing technical support for SMEs to ensure a steady and sustainable recovery from the pandemic’s effects, as well as enhancing their resilience to future socio-economic shocks.
Identity Development of Career-Change Secondary Teachers: A Systematic Review of Theoretical Lenses, Emerging Identities, and Implications for Supporting Transition into Teaching
Authors: Hogg Linda Mary , Elvira Quincy , Yates Anne Spiers
Published: August 2024

Career-change teachers (CCTs) are a growing group within the international secondary teacher workforce. In the context of a global teacher shortage, it is important to interrogate career-change student teachers’ (CCSTs’) experiences, so they can be effectively supported to have successful and sustainable teaching careers. This systematic literature review presents and analyzes scholarship, which focuses on the development of secondary sector CCTs’ teacher identity, with a focus on learning from CCSTs and CCTs who are recent ITE graduates. The two research questions were as follows: What theoretical frameworks are used in the literature to explore CCTs’ teacher identity development? What emerging teacher identities do CCTs take on, and what do they need to experience successful teacher identity development? Analysis of theoretical frameworks reveals different perspectives on the nature of teacher identity and identity development processes. The valuable contribution of multiple theoretical frameworks, including career engagement and development theoretical frameworks, from beyond education is highlighted. Four themes illuminate key influences on CCSTs’ teacher identity development: continuity from prior careers, self-efficacy and need for validation, CCTs’ desire for out-of-the-box teacher identities, and CCTs’ views on ITE. Because CCSTs are a distinct group, with different identities and needs, we call for further research, and we call on ITE providers and schools to use insights from research on CCTs to support CCSTs’ distinctive needs, career transition, and emerging teacher identities.
The Interplay of Self-Regulated Learning, Cognitive Load, and Performance in Learner-Controlled Environments
Authors: Gorbunova Anna , Lange Christopher , Savelyev Alexander , Adamovich Kseniia , Costley Jamie
Published: August 2024

Learner control allows for greater autonomy and is supposed to benefit learning motivation, but it might be more advantageous for students with specific learner characteristics. The current study looks into the relationships between self-regulated learning, cognitive load, and performance within learner-controlled environments. The research was conducted in an asynchronous online setting, allowing for learner control. Cognitive load and self-regulated learning were measured using self-report questionnaires. Performance was assessed through case solutions. The participants were 97 graduate law students studying the civil code. Analysis based on structural equation modeling showed that both prior knowledge and self-regulated learning skills significantly contribute to the increase in germane cognitive load and are positively correlated with performance. The implications of these findings underscore the critical role of prior knowledge and self-regulated learning skills in shaping the cognitive processes involved in learning, ultimately impacting academic achievement. These results emphasize the need for careful consideration of learner-control options in asynchronous online environments.
Expanding Models for Physics Teaching: A Framework for the Integration of Computational Modeling
Authors: Vieyra Rebecca , Megowan-Romanowicz Colleen , Fisler Kathi , Lerner Benjamin , Politz Joe , Krishnamurthi Shriram
Published: August 2024

Teaching computation in science courses can enhance science education, but doing so requires that teachers expand the vision of their discipline beyond the traditional view of science presented in most curricula. This article describes a design-based research (DBR) program that included collaboration among high school teachers and professional development leaders in physics and computer science education. Through three years of professional development and teacher-led development, field testing, and refinement of integrated curricular resources, we have combined instructional modeling practices, physical lab materials, and computer programming activities. One of the outcomes is a co-created framework for the integration of computational modeling into physics that is sensitive to teachers’ interests and expressed needs in addition to learning goals. This framework merges two evidence-based approaches to teaching: Bootstrap:Algebra, a web-based computing curriculum that emphasizes using multiple representations of functions and scaffolds that make the programming process explicit, and Modeling Instruction in physics, an approach that emphasizes the use of conceptual models, modeling practices and representational tools. In doing so, we uncover the need to balance teachers’ visions for integration opportunities with practical instructional needs and emphasize that frameworks for integration need to reflect teachers’ values and goals.
Efficient Twiddle Factor Generators for NTT
Authors: Im Nari , Yang Heehun , Eom Yujin , Park Seong-Cheon , Yoo Hoyoung
Published: August 2024

Fully Homomorphic Encryption (FHE) allows computations on encrypted data without decryption, providing strong security for sensitive information. However, computational and memory demands for FHE are significant challenges, particularly in the Number Theoretic Transform (NTT) phase. This paper presents three efficient Twiddle Factor Generators (TFGs) to address these challenges: the Half-Memory TFG, the On-the-fly Serial TFG, and the On-the-fly Parallel TFG. The Half-Memory TFG reduces memory usage by storing only half of the twiddle factors and calculating the rest as needed. The On-the-fly Serial TFG eliminates memory requirements by computing twiddle factors, while the On-the-fly Parallel TFG enhances computational speed through parallel processing. Implemented on the FPGA KCU105 board, these TFGs demonstrated significant improvements in hardware resource utilization and computational efficiency. The Half-Memory TFG effectively reduces memory footprint, the On-the-fly Serial TFG eliminates memory usage with acceptable computational overhead, and the On-the-fly Parallel TFG offers superior performance for high-throughput applications. These innovations make FHE more practical for real-world applications, contributing to the broader goal of enabling secure, privacy-preserving computations on encrypted data.
An Underwater Multi-Label Classification Algorithm Based on a Bilayer Graph Convolution Learning Network with Constrained Codec
Authors: Li Yun , Wang Su , Mo Jiawei , Wei Xin
Published: August 2024

Within the domain of multi-label classification for micro-videos, utilizing terrestrial datasets as a foundation, researchers have embarked on profound endeavors yielding extraordinary accomplishments. The research into multi-label classification based on underwater micro-video datasets is still in the preliminary stage. There are some challenges: the severe color distortion and visual blurring in underwater visual imaging due to water molecular scattering and absorption, the difficulty in acquiring underwater short video datasets, the sparsity of underwater short video modality features, and the formidable task of achieving high-precision underwater multi-label classification. To address these issues, a bilayer graph convolution learning network based on constrained codec (BGCLN) is established in this paper. Specifically, modality-common representation is constructed to complete the representation of common information and specific information based on the constrained codec network. Then, the attention-driven double-layer graph convolutional network module is designed to mine the correlation information between labels and enhance the modality representation. Finally, the combined modality representation fusion and multi-label classification module are used to obtain the category classifier prediction. In the underwater video multi-label classification dataset (UVMCD), the effectiveness and high classification accuracy of the proposed BGCLN have been proved by numerous experiments.
A Quantitative Evaluation Method Based on Single-Ended Information Protection Adaptability Considering Distributed Generator Access
Authors: Liang Weichen , Zhao Yiwei , Li Xuan , Luo Guomin , Zong Jin , Wu Mengyu , Liu Bo
Published: August 2024

A high proportion of distributed generators (DGs) connected to the distribution network causes a significant change in the normal and fault currents of the system as well as in the linearization of the characteristics. It is difficult to adapt to conventional protection. This paper theoretically analyzes the possible impact of fault current characteristics on traditional protection based on single-ended informativeness after connecting to DGs. From the perspective of protection action, the evaluation index system of DG protection is established by considering the maximum short-circuit current output from DG. Combined with the relay protection requirements, the calculation method of evaluation indexes is given concerning the protection characteristics and expert experience. An analytic hierarchy process (AHP) and a CRITIC combination assignment method based on the principle of minimum information identification are proposed. The scores of different types of protection before and after DG access are calculated using the proposed methodology employing a typical distribution network example. The proposed method can quantitatively obtain the distribution network protection adaptability boundary. In the actual calculation example selected in this paper, a DG can reasonably improve the adaptability of the three-stage current protection when it increases the current amplitude at a penetration rate of 50%; the DG needs to adjust the three-stage current protection rectification value when it decreases the current amplitude at a penetration rate of 20%; and adaptive overcurrent protection and inverse time limit current protection need to be adjusted when the penetration rate of DG is 50%. Compared with the traditional protection evaluation method, the method adopted in this paper can intuitively derive the weak link between protection handling faults after DG access as well as the appropriate capacity of DG to improve protection performance. It can provide a powerful reference for the optimization of protection schemes after the high percentage of DG access.
Navigating the Greek Energy Crisis through a Multidimensional Approach: A Review Article
Authors: Panagiotopoulos Panagiotis P. , Roukanas Spyros A.
Published: August 2024

Following the required adjustments made by the European Union (EU) to adequately absorb the negative social and economic impacts of the COVID-19 pandemic, the EU is once again confronting a crisis. The extended fiscal instability and environmental imbalance resulting from the energy crisis, primarily caused by rising energy prices owing to geopolitical upheavals (the Russian invasion in Ukraine), have been compounded by rising inflation. The main research objective of this paper is the analysis and evaluation of the effects of the current energy crisis on the Greek economy through the perspective of energy poverty, energy dependence, and climate change. Greece has been negatively impacted by the significant rise in energy costs. In 2022, the percentage of the general population that faced difficulties in paying energy bills exceeded the European average, reaching the level of 34.1%, while almost 19% of the population could not keep their homes sufficiently warm. Additionally, in 2022, Greece was one of the countries most energy-dependent on Russia. Greece achieved most of its targets regarding climate change, with the most representative example being the reduction of GHG emissions by 42% from 2000 to 2022. However, this reduction did not come from the successful green transformation of the Greek economy, but instead was due to the reduction in overall energy consumption that came from the prolonged economic crisis, combined with the restrictions of the COVID-19 pandemic. Nevertheless, the majority of Greek buildings are still not considered to be energy efficient, while the transportation industry continues to rely heavily on oil, coal, and natural gas.
Non-Industrial Solar Energy Use, Barriers, and Readiness: Case Study of Oman
Authors: Mishrif Ashraf , Khan Asharul
Published: August 2024

The depletion of fossil fuels, economic concerns over the sharp fluctuations in oil prices, and environmental concerns including global warming have renewed interest in alternative green energy solutions in the form of renewable energy technologies. Solar energy is one of the most promising and environmentally friendly forms of renewable energy for power generation. However, energy transition towards renewables has been slow in developing countries, particularly in the oil-rich Arab Gulf countries. To assess the perspective of Omani consumers in terms of solar energy use, barriers, and readiness to use solar energy for sustainable development, this study aims to determine the proportion of the Omani population who use solar energy, the barriers to solar energy consumption in Oman, people’s perceptions towards solar energy barriers, policies aimed at promoting solar energy programs, and the likelihood and willingness to use solar energy in the future. This analysis is based on quantitative data collected through a questionnaire survey distributed in Oman between 20 June 2023 to 12 August 2023. We used 113 samples for analysis using Principal Component Analysis and Krushkal–Wallis H-tests. Our results revealed that 95% of the residents and commercial units surveyed are willing to use solar PV in the future. The main barriers identified include high installation costs, high maintenance costs, and lack of awareness. The potential for growth in solar energy consumption and use depends on the capacity of the government to provide substantial incentives, financial support, improved quality, implement public-private partnership programs, as well as introduce a clear solar energy policy. While evaluating consumers’ awareness and intentions to use solar energy in the future, this study offers practical implications for policymakers to forecast the potential growth, identify effective policy instruments for promoting renewable energy, and determine the readiness of the country for transition to cleaner energy consumption.
Autarky and the Promotion of Photovoltaics for Sustainable Energy Development: Prosumer Attitudes and Choices
Authors: Jonek-Kowalska Izabela , Grebski Wieslaw
Published: August 2024

The behavior and reactions of prosumers play a key role in the development of sustainable energy and green transformation, as it is the result of their individual decisions that determines the scope of use of renewable energy sources. For these reasons, the main goal of this article is to determine whether and to what extent autarky influenced prosumers’ decisions about the use of solar energy in households, and which promotional channels play the most important role in these decisions. An assessment of the role of autarky and promotion from the prosumer perspective on the photovoltaics market is carried out on the example of Poland as a developing economy, based on the dominant share of coal in energy production. The implementation of this goal will enable recognition and better understanding of prosumers’ intentions and attitudes, and thus more effective stimulation of the green transformation. Surveys in this area were carried out on a representative sample of 754 Polish prosumers, and were analyzed using descriptive statistics and non-parametric statistical tests. The obtained results demonstrate a strong need for energy independence among prosumers (50%) and confirm the role of this motive in the green transformation process. Respondents consider the Internet (a score of 3.8793 on a 5-point suitability scale) and information from companies installing photovoltaic installations (a score of 3.6645 on a 5-point suitability scale) to be the most effective sources of promoting photovoltaics. The example and opinion of family and friends are also important to them. Government campaigns (a score of 2.8647 on a 5-point suitability scale), television and the press play a much smaller role in the popularization of solar energy. Respondents, therefore, prefer numerous and dispersed marketing sources, that allow them to confront and verify the information obtained.
Research into the Path and Mechanism by Which Intelligent Manufacturing Promotes Carbon Emission Reductions
Authors: Tang Jiahui , Wang Wan , Ding Wangwang
Published: August 2024

Utilizing a longitudinal dataset encompassing 30 Chinese provinces and municipalities (with the exception of Tibet, Hong Kong, Macao, and Taiwan) that spans the years 2011 through to 2021, this study adopts the spatial Durbin model to study the path and mechanism behind the promotion of carbon emission reductions through intelligent manufacturing. The results show the following: ① Intelligent manufacturing plays a crucial role in promoting the reduction of carbon emissions. ② Government interventions can amplify the positive influence of intelligent manufacturing in reducing carbon emissions, and intelligent manufacturing promotes carbon emission reductions by accelerating scientific and technological innovation. ③ There is temporal heterogeneity: upgrading intelligent manufacturing exerted a substantial influence in advancing the reduction of carbon emissions during the timeframe from 2011 to 2019, while it exerted a notable impeding impact on the reduction of carbon emissions during the timeframe from 2011 to 2019. ④ There is spatial heterogeneity: in the eastern region, upgrading intelligent manufacturing promoted carbon emission reductions in 2011–2015, but it inhibited carbon emission reductions in 2016–2021. Consequently, here are the insights we have distilled: ① Enhancing the overall advancement level of intelligent manufacturing can effectively promote carbon emission reductions in China; ② It can also play an important role in guiding governments in making these upgrades and actively promoting them in conjunction with technological innovations.
A Hybrid Approach for Photovoltaic Maximum Power Tracking under Partial Shading Using Honey Badger and Genetic Algorithms
Authors: Fan Zhi-Kai , Setianingrum Annisa , Lian Kuo-Lung , Suwarno Suwarno
Published: August 2024

This study presents a new approach for Maximum Power Point Tracking (MPPT) by combining the honey badger algorithm (HBA) with a Genetic Algorithm (GA). The integration aims to optimize photovoltaic (PV) system performance in partial shading conditions (PSCs). Initially, the HBA is utilized to explore extensively and identify potential solutions while avoiding local optima. If necessary, the GA is then employed to escape local optima through selection, crossover, and mutation operations. On average, this proposed method has a 40% improvement in tracking time and 0.77% in efficiency compared with the HBA. In a dynamic case, the proposed method achieves a 4.81% improvement compared to HBA.
Regional Breakthrough Innovation Change Strategies, Ecological Location Suitability of High-Tech Industry Innovation Ecosystems, and Green Energy
Authors: Bao Zemenghong , Lin Zhisen , Jin Tiantian , Lv Kun
Published: August 2024

Against the backdrop of an ongoing energy revolution, this study measured the regional green energy efficiency and ecological niche suitability of high-tech industry innovation ecosystems using the Super-SBM and entropy methods. We employed panel data from 30 mainland provinces (excluding Tibet) from 2009 to 2021 to conduct a quasi-natural experiment using spatial difference-in-differences models and double machine learning models. This was performed in order to investigate the impact mechanisms of the transformation of ecological niche suitability within the innovation ecosystems of high-tech industries driven by regional breakthrough innovation change strategies on green energy efficiency. The findings of this study revealed the following: (1) Driven by regional breakthrough innovation strategies, the transformation of the ecological niche suitability of high-tech industry innovation ecosystems has significant and positive local effects and spillover effects on green energy efficiency. (2) Regional breakthrough innovation strategies have a significant and positive mediating transmission effect on green energy efficiency through the development and optimization of internal factors within the ecological niche suitability of high-tech industry innovation ecosystems, including innovation entities, support, vitality, resources, and environment. (3) The transformation of the ecological niche suitability of high-tech industry innovation ecosystems driven by regional breakthrough innovation strategies promotes the advancement and rationalization of the industrial structure, thus indirectly enhancing regional green energy efficiency. These findings are of paramount importance for propelling the next wave of regional disruptive innovation reform strategies, ensuring that the outcomes of these reforms drive the ecological niche suitability of high-tech industry innovation ecosystems toward the advancement and realization of clean and efficient energy utilization.
Spatial–Temporal Changes in the Distribution of Populus euphratica Oliv. Forests in the Tarim Basin and Analysis of Influencing Factors from 1990 to 2020
Authors: Guo Xuefei , Zhu Lijun , Yang Zhikun , Yang Chaobin , Li Zhijun
Published: August 2024

Understanding the spatiotemporal evolution patterns of Populus euphratica Oliv. (P. euphratica) forests in the Tarim Basin (TB) and their influencing factors is crucial for regional ecological security and high-quality development. However, there is currently a lack of large-area, long-term systematic monitoring. This study utilized multi-source medium and high-resolution remote sensing images from the Landsat series and Sentinel-2, applying a Random Forest classification model to obtain distribution data of P. euphratica forests and shrublands in 14 areas of the TB from 1990 to 2020. We analyzed the effects of river distance, water transfer, and farmland on their distribution. Results indicated that both P. euphratica forests and shrublands decreased during the first 20 years and increased during the last 10 years. Within 1.5 km of river water transfer zones, P. euphratica forests more frequently converted to shrublands, while both forests and shrublands showed recovery in low-frequency water transfer areas. Farmland encroachment was most significant beyond 3 km from rivers. To effectively protect P. euphratica forests, we recommend intermittent low-frequency water transfers within 3 km of rivers and stricter management of agricultural expansion beyond 3 km. These measures will help maintain a balanced ecosystem and promote the long-term sustainability of P. euphratica forests.
Characterization of the Key Aroma Compounds of Soybean Flavor in Fermented Soybeans with Bacillus subtilis BJ3-2 by Gene Knockout, Gas Chromatography–Olfactometry–Mass Spectrometry, and Aroma Addition Experiments
Authors: Chen Zhaofeng , Wu Yongjun , Tong Shuoqiu , Jin Jing , Zhang Lincheng , Li Chen , Tan Qibo , Wen Feng , Tao Yi
Published: August 2024

Soybean flavor is considered to be essential for the aroma quality of fermented soybeans (FS) with Bacillus subtilis BJ3-2 (BJ3-2) at 37 °C. However, the key aroma compounds of the soybean flavor must be further elucidated. In this study, two candidate genes (sdaAA and katX) of BJ3-2 involved in the control of soybean flavor production were screened using prior multi-omics data. FS samples with BJ3-2, BJ3-2ΔsdaAA, BJ3-2ΔkatX, and BJ3-2ΔsdaAAΔkatX were analyzed by quantitative descriptive sensory analysis (QDA), gas chromatography–olfactometry–mass spectrometry (GC-O-MS), relative odor activity values (ROAV), and aroma addition experiments. The QDA revealed that the aroma profile of the soybean flavor in FS consisted of “sweaty”, “smoky”, “beany”, “roasted”, and “sweet” attributes. A total of 20 aroma-active compounds were detected, and 13 of them with ROAV > 1 were identified as key aroma compounds. Moreover, aroma addition experiments were conducted to further confirm the key aroma compounds of soybean flavor. Among them, 2-methylbutyric acid, 2,3,5-trimethylpyrazine, and guaiacol contributed higher aroma intensity values and ROAV, resulting in “sweaty”, “roasted”, and “smoky” attributes of soybean flavor in FS, respectively, while 1-octen-3-ol was associated with the “beany” attribute. These findings provide novel insights into the aroma attributes of soybean flavor in FS and a new strategy for revealing the key aroma compounds in fermented foods.
FIVADMI: A Framework for In-Vehicle Anomaly Detection by Monitoring and Isolation
Authors: Mahbub Khaled , Nehme Antonio , Patwary Mohammad , Lacoste Marc , Allio Sylvain
Published: August 2024

Self-driving vehicles have attracted significant attention in the automotive industry that is heavily investing to reach the level of reliability needed from these safety critical systems. Security of in-vehicle communications is mandatory to achieve this goal. Most of the existing research to detect anomalies for in-vehicle communication does not take into account the low processing power of the in-vehicle Network and ECUs (Electronic Control Units). Also, these approaches do not consider system level isolation challenges such as side-channel vulnerabilities, that may arise due to adoption of new technologies in the automotive domain. This paper introduces and discusses the design of a framework to detect anomalies in in-vehicle communications, including side channel attacks. The proposed framework supports real time monitoring of data exchanges among the components of in-vehicle communication network and ensures the isolation of the components in in-vehicle network by deploying them in Trusted Execution Environments (TEEs). The framework is designed based on the AUTOSAR open standard for automotive software architecture and framework. The paper also discusses the implementation and evaluation of the proposed framework.
Acute Hypercapnia at South African Abalone Farms and Its Physiological and Commercial Consequences
Authors: Novak Tanja , Bridges Christopher R. , Naylor Matt , Yemane Dawit , Auerswald Lutz
Published: August 2024

Abalone Haliotis midae are distributed from the cold, hypercapnic waters of the dynamic Benguela Current Large Marine Ecosystem to the relatively warm, normocapnic waters of the Agulhas Current. The species supports an important fishery as well as a thriving aquaculture industry. Due to the relatively low capacity to regulate their acid–base balance and their need to calcify shell and radula, abalone are especially vulnerable to increasing ocean acidification. Exposure to acidified seawater, i.e., hypercapnia, also occurs during the farming operation and can originate from (a) changes in influent seawater, (b) pH decrease by accumulation of waste products, and (c) intentional hypercapnia for anaesthesia using CO2-saturated seawater for size grading. Currently, these are acute exposures to hypercapnia, but increasing ocean acidification can cause chronic exposure, if not mitigated. Wild South African abalone are already exposed to periodic hypercapnia during ocean upwelling events and will be more so in the future due to progressive ocean acidification. This study investigated the acute pH effects in isolation as an initial step in studying the acute physiological response of H. midae to provide a mechanistic basis for the design of complex multifactorial studies, imitating more closely what occurs on farms and in the natural habitat. The major findings relevant to the above conditions are as follows: 1. Acute exposure to hypercapnia induces a reversible, unbuffered respiratory acidosis. 2. The impact of acute hypercapnia is size-dependent and potentially fatal. 3. Exposure to extreme, short hypercapnia during anaesthesia causes a rapid imbalance in the acid–base state but a rapid subsequent recovery. LC50 for small, medium and large abalone range from pH 6.27 to 6.03, respectively, and sub-lethal levels from pH 6.8 to 6.2. These results can be used by abalone aquaculture farms to mitigate/avoid the impact of acute (and chronic) hypercapnia but also to standardise their anaesthesia method. They are also a proxy to estimate the effects on wild populations.
Genetic and Pathogenic Characterization of an Iridovirus from the Cultured Largemouth Bass Micropterus salmoides
Authors: Zhang Yi-Fan , Li Ying , Li Peng-Tian , Jiang Jing , Zeng Wei-Hang , Ye Kun , Wang Yi-Lei , Zou Peng-Fei
Published: August 2024

The largemouth bass is a freshwater aquacultured fish species of great economic importance in China. With the rapid development of aquaculture industry and the increase in the aquaculture density of the fish, various infectious pathogens, including parasites, bacteria, and viruses, have been widely spread, which have caused huge losses to the aquaculture industry. Among them, largemouth bass iridovirus (LMBV) is one of the most harmful pathogens. In the present study, a virus strain named LMBV-GDSD was isolated from cultured largemouth bass and was successfully proliferated in FHM and EPC cells, with numerous viral particles observed in the infected cells under transmission electron microscopy analysis. The annotated complete genome of LMBV-GDSD was 99,285 bp and contained 102 ORFs. Based on genomic sequence alignment and phylogenetic analysis, the identified LMBV-GDSD belonged to the genus Ranavirus of Iridoviridae and was pathogenic to largemouth bass under regression infection experiments. In addition, the infection of LMBV-GDSD in largemouth bass could significantly up-regulate the expression of antiviral immune-related genes such as IRF3, IRF7, and Mx. It is thus providing valuable genetic data for a deeper understanding of the pathogenic mechanism of iridovirus in largemouth bass.
Structural Characterization and Abundance of Sialylated Milk Oligosaccharides in Holstein Cows during Early Lactation
Authors: Isernhagen Lisa , Galuska Christina E. , Vernunft Andreas , Galuska Sebastian P.
Published: August 2024

Among other bioactive molecules, milk contains high amounts of sialylated milk oligosaccharides (MOs) that influence numerous processes in the offspring. For instance, sialylated MOs inhibit the invasion of pathogens and positively influence the gut microbiome to support the optimal development of the offspring. For these reasons, sialylated MOs are also used in infant formula as well as food supplements and are potential therapeutic substances for humans and animals. Because of the high interest in sialylated bovine MOs (bMOs), we used several analytical approaches, such as gas and liquid chromatography in combination with mass spectrometry, to investigate in detail the profile of sialylated bMOs in the milk of Holstein Friesian cows during early lactation. Most of the 40 MOs identified in this study were sialylated, and a rapid decrease in all detected sialylated bMOs took place during the first day of lactation. Remarkably, we observed a high variance within the sialylation level during the first two days after calving. Therefore, our results suggest that the content of sialylated MOs might be an additional quality marker for the bioactivity of colostrum and transitional milk to ensure its optimized application for the production of milk replacer and food supplements.
The Impact of Selected Ingredients on the Predicted Glycemic Index and Technological Properties of Bread
Authors: Pasqualoni Ilaria , Tolve Roberta , Simonato Barbara , Bianchi Federico
Published: August 2024

Bread, a staple food consumed worldwide, plays a pivotal role in nutrition. Nevertheless, it is to be underlined that white bread is classified as a high glycemic index food, and its frequent consumption can lead to rapid increases in blood glucose, potentially causing metabolic stress and contributing to insulin resistance and type 2 diabetes. So, there is a growing interest in bread formulations with ingredients that can lower its GI. With this view, bread was formulated, substituting wheat with chickpea flour, red chicory powder, and three distinct types of resistant starch. The results showed the different resistant starches’ impacts on the glycemic index reduction. Specifically, chemically modified tapioca RS IV produced a bread formulation with a low predicted glycemic index (pGI < 55). Retrograded starch from tapioca (RS III) allows the bread to reach a pGI value of 55, the upper value for classifying a food as low pGI. The retrograded starch from corn (RS III) allows a decrease in the bread’s glycemic index, but the product is still classified as ‘high pGI’ (>70). Moreover, the addition of by-products rich in polyphenols contributes to a lowering of the pGI. Concerning the technological parameters, the outcome revealed an increase in the moisture content across all the newly formulated samples compared to the control. At the same time, the volume and specific volume showed a decrease. The newly formulated samples exhibited a higher baking loss, particularly when incorporating resistant starch, which increased the hardness and chewiness with decreased cohesiveness. In conclusion, incorporating chickpea flour, red chicory powder, and tapioca-resistant starch (RS III and IV) offers a promising strategy for producing high-fiber bread with a low glycemic index, catering to health-conscious consumers.
Effects of Wickerhamomyces anomalus Co-Fermented with Saccharomyces cerevisiae on Volatile Flavor Profiles during Steamed Bread Making Using Electronic Nose and HS-SPME-GC-MS
Authors: Ding Xialiang , Yue Meixiang , Gu Henghao , Li Suyang , Chen Shiyi , Wang Liang , Sun Ling
Published: August 2024

Steamed bread is a traditional staple food in China, and it has gradually become loved by people all over the world because of its healthy production methods. With the improvement in people’s living standards, the light flavor of steamed bread fermented by single yeast cannot meet people’s needs. Multi-strain co-fermentation is a feasible way to improve the flavor of steamed bread. Here, the dynamic change profiles of volatile substances in steamed bread co-fermented by Saccharomyces cerevisiae SQJ20 and Wickerhamomyces anomalus GZJ2 were analyzed using the electronic nose (E-nose) and headspace solid-phase microextraction combined with gas chromatography–mass spectrometry (HS-SPME-GC-MS). The five detectors of the E-nose rapidly detected the changes in volatile substances in different dough or steamed bread with the highest response value in co-fermented dough. A total of 236 volatile substances were detected in all the samples using HS-SPME-GC-MS, and alcohols were the most variable component, especially Phenylethyl alcohol. Significantly, more alcohols and esters were upregulated in co-fermented dough, and the addition of W. anomalus GZJ2 improved the key volatile aroma compounds of steamed bread using the relative odor activity value method (ROAV), especially the aldehydes and alcohols. Moreover, these key volatile aroma compounds can be quickly distinguished using the W2S detector of the E-nose, which can be used for the rapid detection of aroma components in steamed bread.
Effect of Dry Processing of Coconut Oil on the Structure and Physicochemical Properties of Coconut Isolate Proteins
Authors: Liu Xiaoyan , Yang Duwei , Liu Wantong , Kan Jintao , Zhang Yufeng
Published: August 2024

The effects of the dry processing of coconut oil on the amino acid composition, molecular weight, secondary structure, solubility, surface hydrophobicity, microstructure, total sulfhydryl and free sulfhydryl content, free amino acid content, thermal properties, and water-holding, oil-holding, foaming, and emulsifying properties of coconut isolate protein were investigated. The results showed that the dry processing altered the amino acid composition of coconut isolate proteins as well as resulted in fewer irregular structural regions and more homogeneous particle sizes, leading to an improvement in the thermal stability of the proteins. SDS-PAGE analysis showed that globular proteins located at ~34 kDa in coconut isolate proteins underwent slight degradation during the dry processing of coconut oil. The dry processing reduced the surface hydrophobicity, total and free sulfhydryl groups, solubility, and free amino acid content of coconut isolate proteins. In addition, the water-holding capacity, oil-holding capacity, and foam stability of coconut isolate proteins were improved to different degrees after the dry processing. Therefore, the development and utilization of copra meal protein is of great significance to increase its added value.
On Martínez–Kaabar Fractal–Fractional Volterra Integral Equations of the Second Kind
Authors: Martínez Francisco , Kaabar Mohammed
Published: August 2024

The extension of the theory of generalized fractal–fractional calculus, named in this article as Martínez–Kaabar Fractal–Fractional (MKFF) calculus, is addressed to the field of integral equations. Based on the classic Adomian decomposition method, by incorporating the MKFF α,γ-integral operator, we establish the so-called extended Adomian decomposition method (EADM). The convergence of this proposed technique is also discussed. Finally, some interesting Volterra Integral equations of non-integer order which possess a fractal effect are solved via our proposed approach. The results in this work provide a novel approach that can be employed in solving various problems in science and engineering, which can overcome the challenges of solving various equations, formulated via other classical fractional operators.
Molecular Manipulation of the miR160/AUXIN RESPONSE FACTOR Expression Module Impacts Root Development in Arabidopsis thaliana
Authors: Zimmerman Kim , Pegler Joseph L. , Oultram Jackson M. J. , Collings David A. , Wang Ming-Bo , Grof Christopher P. L. , Eamens Andrew L.
Published: August 2024

In Arabidopsis thaliana (Arabidopsis), microRNA160 (miR160) regulates the expression of AUXIN RESPONSE FACTOR10 (ARF10), ARF16 and ARF17 throughout development, including the development of the root system. We have previously shown that in addition to DOUBLE-STRANDED RNA BINDING1 (DRB1), DRB2 is also involved in controlling the rate of production of specific miRNA cohorts in the tissues where DRB2 is expressed in wild-type Arabidopsis plants. In this study, a miR160 overexpression transgene (MIR160B) and miR160-resistant transgene versions of ARF10 and ARF16 (mARF10 and mARF16) were introduced into wild-type Arabidopsis plants and the drb1 and drb2 single mutants to determine the degree of requirement of DRB2 to regulate the miR160 expression module as part of root development. Via this molecular modification approach, we show that in addition to DRB1, DRB2 is required to regulate the level of miR160 production from its precursor transcripts in Arabidopsis roots. Furthermore, we go on to correlate the altered abundance of miR160 or its ARF10, ARF16 and ARF17 target genes in the generated series of transformant lines with the enhanced development of the root system displayed by these plant lines. More specifically, promotion of primary root elongation likely stemmed from enhancement of miR160-directed ARF17 expression repression, while the promotion of lateral and adventitious root formation was the result of an elevated degree of miR160-directed regulation of ARF17 expression, and to a lesser degree, ARF10 and ARF16 expression. Taken together, the results presented in this study identify the requirement of the functional interplay between DRB1 and DRB2 to tightly control the rate of miR160 production, to in turn ensure the appropriate degree of miR160-directed ARF10, ARF16 and ARF17 gene expression regulation as part of normal root system development in Arabidopsis.
Analysis of the miR482 Gene Family in Plants
Authors: Kuang Wei , Qin Danfeng , Huang Ying , Liu Yihua , Cao Xue , Xu Meng
Published: August 2024

MicroRNA482 (miR482) is a conserved microRNA family in plants, playing critical regulatory roles in different biological activities. Though the members of the miR482 gene family have been identified in plants, a systematic study has not been reported yet. In the present research, 140 mature sequences generated by 106 precursors were used for molecular characterization, phylogenetic analysis, and target gene prediction, and the competing endogenous RNA (ceRNA) network mediated by miR482 was summarized. The length of mature sequences ranged from 17 nt to 25 nt, with 22 nt being the most abundant, and the start and end of the mature sequences had a preference for uracil (U). By sequence multiplex comparison, it was found that the mature sequences of 5p were clustered into one group, and others were clustered into the other group. Phylogenetic analysis revealed that the 140 mature sequences were categorized into six groups. Meanwhile, all the precursor sequences formed a stable hairpin structure, and the 106 precursors were divided into five groups. However, the expression of miR482 varied significantly between different species and tissues. In total, 149 target genes were predicted and their functions focused on single-organism process, cellular process, and cell and cell part. The ceRNA network of miR482 in tomato, cotton, and peanut was summarized based on related publications. In conclusion, this research will provide a foundation for further understanding of the miR482 gene family.
Neural Network-Based Climate Prediction for the 21st Century Using the Finnish Multi-Millennial Tree-Ring Chronology
Authors: Kasatkina Elena A. , Shumilov Oleg I. , Timonen Mauri
Published: August 2024

The sun’s activity role in climate change has become a topic of debate. According to data from the IPCC, the global average temperature has shown an increasing trend since 1850, with an average increase of 0.06 °C/decade. Our analysis of summer temperature records from five weather stations in northern Fennoscandia (65°–70.4° N) revealed an increasing trend, with a range of 0.09 °C/decade to 0.15 °C/decade. However, due to the short duration of instrumental records, it is not possible to accurately assess and predict climate changes on centennial and millennial timescales. In this study, we used the Finnish super-long (~7600 years) tree-ring chronology to create a climate prediction for the 21st century. We applied a method that combines a long short-term memory (LSTM) neural network with the continuous wavelet transform and wavelet filtering in order to make climate change predictions. This approach revealed a significant decrease in tree-ring growth over the near term (2063–2073). The predicted decrease in tree-ring growth (and regional temperature) is thought to be a result of a new grand solar minimum, which may lead to Little Ice Age-like climatic conditions. This result is significant for understanding current climate processes and assessing potential environmental and socio-economic risks on a global and regional level, including in the area of the Arctic shipping routes.
Ecosystem Barriers and Facilitators Linked to the Fear of Cancer Recurrence: An Umbrella Review
Authors: Caumeil Benjamin , Bazine Nicolas , Maugendre Axel , Calvin Sarah
Published: August 2024

The fear of cancer recurrence is an important topic in the healthcare field. In general, approximately 40% of survivors experience high levels of fear of recurrence. This study aims to fill this gap by synthesizing the findings of systematic reviews studies investigating ecosystems, correlates or predictors, and barriers and facilitators of fear of cancer recurrence among cancer survivors. An umbrella meta-synthesis was conducted using the following databases: MEDLINE, PsycINFO, PsycARTICLES, CINAHL, Business source premier, and SOCindex, ending in April 2024 with PRISMA methods. A total of 24 systematic reviews, representing 729 articles, were included in the study. In total, six ecosystems were identified, including family, work, friends, the healthcare system, caregivers, and religion. As part of this umbrella review, 55 specific ecosystemic factors were identified that may contribute to fear of cancer recurrence. Furthermore, the umbrella review identified 12 facilitators and 12 barriers related to fear of cancer recurrence. This umbrella meta-synthesis contributed significantly to our review’s strength in synthesizing the main ecosystem and its influence on fears of cancer recurrence. Understanding the interdependence of ecosystems should enable future research on intervention effectiveness or the development of interventions that could reduce the fear of cancer recurrence.