bluuebunny/crossref_metadata_2025 huggingface dataset:
FinTech Adoption in SMEs and Bank Credit Supplies: A Study on Manufacturing SMEs
Authors: Rehman Shafiq Ur , Al-Shaikh Mustafa , Washington Patrick Bernard , Lee Ernesto , Song Ziheng , Abu-AlSondos Ibrahim A. , Shehadeh Maha , Allahham Mahmoud
Published: August 2023

Bank lending to SMEs plays a vital role in economic growth, contributing significantly to employment and GDP. Access to bank lending is crucial for small- and medium-sized enterprises (SMEs), as they contribute significantly to global employment and GDP. New financial technologies promise better bank operations, fewer costs, and enhanced credit supply to SMEs. However, there is still a lack of empirical findings on how these technologies can solve demand-side bank lending problems for small- and medium-sized firms. This study gathered data from a sample of 381 respondents, comprising CEOs, managers, officers, loan managers, IT consultants, and other relevant stakeholders. The findings indicate that the adoption of blockchain technologies, as well as the adoption of Big Data technologies encompassing cloud computing, data analytics, algorithms, and programming, along with the adoption of mobile banking technologies, have had a substantial positive impact on bank credit supplies for small- and medium-sized enterprises (SMEs) in Pakistan. This novel study contributes to existing knowledge in two ways. First, it provides knowledge to SMEs looking to adopt new technologies; second, it provides knowledge to a manager looking to finance the SMEs with information asymmetries. This research also provides key findings for researchers and policymakers.
Metabolic Adverse Effects of Psychotropic Drug Therapy: A Systematic Review
Authors: Sepúlveda-Lizcano Lizeth , Arenas-Villamizar Vivian Vanessa , Jaimes-Duarte Enna Beatriz , García-Pacheco Henry , Paredes Carlos Silva , Bermúdez Valmore , Rivera-Porras Diego
Published: August 2023

This review aimed to investigate the metabolic alterations associated with psychopharmacological treatment of neuropsychiatric disorders, which can significantly impact patients’ physical health and overall quality of life. The study utilized the PRISMA methodology and included cross-sectional, retrospective studies, and randomized clinical trials from reputable databases like SCOPUS, CLARIVATE, SCIENCE DIRECT, and PUBMED. Out of the 64 selected studies, various psychotropic drug classes were analyzed, including antidepressants, anticonvulsants, and antipsychotics. Among the antidepressants, such as amitriptyline, Imipramine, and clomipramine, weight gain, constipation, and cardiovascular effects were the most commonly reported metabolic adverse effects. SSRI antidepressants like Fluoxetine, Sertraline, Citalopram, Escitalopram, and Paroxetine exhibited a high prevalence of gastrointestinal and cardiac alterations. Regarding anticonvulsants, valproic acid and Fosphenytoin were associated with adverse reactions such as weight gain and disturbances in appetite and sleep patterns. As for antipsychotics, drugs like Clozapine, Olanzapine, and Risperidone were linked to weight gain, diabetes, and deterioration of the lipid profile. The findings of this review emphasize the importance of continuous monitoring for adverse effects, particularly considering that the metabolic changes caused by psychopharmacological medications may vary depending on the age of the patients. Future research should focus on conducting field studies to further expand knowledge on the metabolic effects of other commonly prescribed psychotropic drugs. Overall, the study highlights the significance of understanding and managing metabolic alterations induced by psychopharmacological treatment to enhance patient care and well-being.
Identifying Users and Developers of Mobile Apps in Social Network Crowd
Authors: Alamer Ghadah , Alyahya Sultan , Al-Dossari Hmood
Published: August 2023

In the last fifteen years, an immense expansion has been witnessed in mobile app usage and production. The intense competition in the tech sector and also the rapidly and constantly evolving user requirements have led to increased burden on mobile app creators. Nowadays, fulfilling users’ expectations cannot be readily achieved and new and unconventional approaches are needed to permit an interested crowd of users to contribute in the introduction of creative mobile apps. Indeed, users and developers of mobile apps are the most influential candidates to engage in any of the requirements engineering activities. The place where both can best be found is on Twitter, one of the most widely used social media platforms. More interestingly, Twitter is considered as a fertile ground for textual content generated by the crowd that can assist in building robust predictive classification models using machine learning (ML) and natural language processing (NLP) techniques. Therefore, in this study, we have built two classification models that can identify mobile apps users and developers using tweets. A thorough empirical comparison of different feature extraction techniques and machine learning classification algorithms were experimented with to find the best-performing mobile app user and developer classifiers. The results revealed that for mobile app user classification, the highest accuracy achieved was ≈0.86, produced via logistic regression (LR) using Term Frequency Inverse Document Frequency (TF-IDF) with N-gram (unigram, bigram and trigram), and the highest precision was ≈0.86, produced via LR using Bag-of-Words (BOW) with N-gram (unigram and bigram). On the other hand, for mobile app developer classification, the highest accuracy achieved was ≈0.87, produced by random forest (RF) using BOW with N-gram (unigram and bigram), and the highest precision was ≈0.88, produced by multi-layer perception neural network (MLP NN) using BERTweet for feature extraction. According to the results, we believe that the developed classification models are efficient and can assist in identifying mobile app users and developers from tweets. Moreover, we envision that our models can be harnessed as a crowd selection approach for crowdsourcing requirements engineering activities to enhance and design inventive and satisfying mobile apps.
Application of Improved Butterfly Optimization Algorithm in Mobile Robot Path Planning
Authors: Zhai Rongjie , Xiao Ping , Shu Da , Sun Yongjiu , Jiang Min
Published: August 2023

An improved butterfly optimization algorithm (IBOA) is proposed to overcome the disadvantages, including slow convergence, generation of local optimum solutions, and deadlock phenomenon, of the optimization algorithm in the path planning of mobile robots. A path-planning grid model is established based on an improved obstacle model. First, the population diversity is improved by introducing kent mapping during population position renewal in the normal butterfly optimization algorithm (BOA) to enhance the global search ability of the butterfly population. Second, an adaptive weight coefficient is introduced in the renewal process of each generation to increase the convergence speed and accuracy. An opposition-based learning strategy based on convex lens imaging is introduced to help the butterfly population jump out of the local optimum. Finally, a mutation strategy is introduced to solve the path planning problem. On this basis, two path simplification strategies are proposed to make up for the shortcomings of planning paths in grid maps. The shortest path lengths solved by IBOA, BOA, and GA in the 20 × 20 map are 30.97, 31.799, and 31.799, respectively. The numbers of iterations for the shortest paths searched by IBOA, BOA, and GA are 14, 24, and 38 in that order. The shortest path lengths solved by IBOA, BOA and GA in the 40 × 40 map are 63.84, 65.60, and 65.84, respectively. The number of iterations for the shortest paths searched by IBOA, BOA and GA are 32, 40, and 46, respectively. Simulation results show that IBOA has a strong ability to solve robot path planning problems and that the proposed path simplification strategy can effectively reduce the length of the optimal path in the grid map to solve the path planning problem of mobile robots. The shortest paths solved by IBOA in 20 × 20 and 40 × 40 maps are simplified to lengths of 30.2914 and 61.03, respectively.
Hybrid Hunter–Prey Optimization with Deep Learning-Based Fintech for Predicting Financial Crises in the Economy and Society
Authors: Katib Iyad , Assiri Fatmah Y. , Althaqafi Turki , AlKubaisy Zenah Mahmoud , Hamed Diaa , Ragab Mahmoud
Published: August 2023

Financial technology (Fintech) plays a pivotal role in driving contemporary technology, society, economies, and many other fields. The new-generation Fintech is Smart Fintech, mainly empowered and inspired by data science and artificial intelligence (DSAI) technologies. Smart Fintech combines DSAI and transforms finance and economies for driving automated, intelligent, personalized financial and economic businesses, services and systems, and the whole of business. The strength and growth of the country’s economy were evaluated with the accurate prediction of how many companies will succeed and how many will fail. Financial crisis prediction (FCP) has a considerable effect on the economy. Prior research focuses mainly on deep learning (DL), machine learning (ML), and statistical approaches for forecasting the financial health of a company. Thus, this study presents a hybrid hunter–prey optimization with a deep learning-based FCP (HHPODL-FCP) technique. The objective of the HHPODL-FCP algorithm lies in the effective identification of the financial crisis in enterprises or organizations. To accomplish this, the HHPODL-FCP method makes use of the HHPO algorithm for the feature subset selection process. In addition, the HHPODL-FCP technique employs the gated attention recurrent network (GARN) model for the identification and classification of financial and non-financial crises. The HHPODL-FCP method exploits a sparrow search algorithm (SSA)-based hyperparameter tuning process to enrich the performance of the GARN model. The simulation results of the HHPODL-FCP method are tested on different financial datasets. A wide range of experiments highlighted the remarkable performance of the HHPODL-FCP method over recent techniques under various measures.
Research on Online Monitoring Method for Bond Wire Fatigue Applied to IGBT Module
Authors: Liu Hongtao , Wang Fei , Xia Weiyi , Shen Chaoyue
Published: August 2023

Bond wire fatigue is a prominent problem affecting the reliability of IGBT modules and power electronic converters, and has thus received much attention in the research community. As bond wire fatigue leads to changes in the gate circuit parameters, it affects the IGBT turn-off process. Based on this finding, this paper proposes a fatigue evaluation method for bond wire based on IGBT turn-off time. This includes constructing a turn-off time-bond wire fatigue model that considers the impact of changes in collector current, and developing a control software that utilizes the coupling relationship between the Kelvin terminal voltage VeE and turn-off time for the online extraction of IGBT turn-off time. In summary, the proposed online monitoring method of IGBT bond wire fatigue based on turn-off time can help improve the reliability of power electronic converters.
Energy-Efficient Power Allocation for Full-Duplex Device-to-Device Underlaying Cellular Networks with NOMA
Authors: Zhao Xu , Liu Fang , Zhang Yajing , Chen Songchao , Gan Jie
Published: August 2023

Full-duplex (FD), Device-to-Device (D2D) and non-orthogonal multiple access (NOMA) are promising wireless communication techniques to improve the utilization of spectrum resources. Meanwhile, introducing FD, D2D and NOMA in cellular networks is very challenging due to the complex interference problem. To deal with the complex interference of FD D2D underlaying NOMA cellular networks, power allocation (PA) is extensively studied as an efficient interference management technique. However, most of the previous research works on PA to optimize energy efficiency only consider the system framework of partially joint combining techniques of FD, D2D and NOMA, and the constraints of optimization problem are very different. In this paper, in order to further improve the energy efficiency of a system, a dual-layer iteration power allocation algorithm is proposed to eliminate the complex interference. The outer-layer iteration is to solve the non-linear fractional objective function based on Dinkelbach, and the inner-layer iteration is to solve the non-convex optimization problem based on D.C. programming. Then, the non-convex and non-linear fractional objective function is transformed into a convex function to solve the optimal power allocation. In this approach, FD D2D users reuse the spectrum with downlink NOMA cellular users. Imperfect self-interference (SI) cancellation at the FD D2D users and the successive interference cancellation (SIC) at the strong NOMA user are considered in the system framework. The optimization problem is constructed to maximize the system’s energy efficiency with the constraints of successful SIC, QoS requirements, the maximum transmit power of BS and FD D2D users. Numerical results demonstrate that the proposed algorithm outperforms the traditional orthogonal multiple access (OMA) in terms of energy efficiency with a higher system sum rate.
Joint Unmanned Aerial Vehicle Location and Beamforming and Caching Optimization for Cache-Enabled Multi-Unmanned-Aerial-Vehicle Networks
Authors: Chen Zikang , Zeng Ming , Fei Zesong
Published: August 2023

Due to the advantages such as high flexibility, low cost and easy implementation offered by unmanned aerial vehicles (UAVs), a UAV-assisted network is regard as an appealing solution to a seamless coverage, high disaster-tolerant and on-demand wireless system. In this paper, we focus on the downlink transmission in a cache-enabled UAV-assisted wireless communication network, where UAVs cache popular content from a macro base station in advance and cooperatively transfer the content to users. We aim to minimize the average transmission latency of the system and to formulate an optimization problem that jointly optimizes the UAV location, beamforming and caching strategy. However, the formulated problem is very challenging because of its non-convexity and the highly coupled optimization variables. To solve this resulting problem efficiently, we decompose it into two subproblems, namely UAV location and beamforming optimization, and UAV caching strategy optimization. The first subproblem is an NP-hard joint optimization problem, while the second one is a linear programing problem. By adopting the first-order Taylor expansion, we propose a convex optimization algorithm based on the difference-of-convex (DC) method. Specifically, we bring out a method to apply linear approximation in the DC-based algorithm, which is particularly suitable to the problems involving complicated summations. The numerical results demonstrate that the proposed DC-based iterative optimization algorithm can efficiently reduce the average transmission latency of the system.
Application of Artificial Intelligence for Predicting CO2 Emission Using Weighted Multi-Task Learning
Authors: Talaei Mohammad , Astaneh Majid , Ghiasabadi Farahani Elmira , Golzar Farzin
Published: August 2023

Carbon emissions significantly contribute to global warming, amplifying the occurrence of extreme weather events and negatively impacting the overall environmental transformation. In line with the global commitment to combat climate change through the Paris Agreement (COP21), the European Union (EU) has formulated strategies aimed at achieving climate neutrality by 2050. To achieve this goal, EU member states focus on developing long-term national strategies (NLTSs) and implementing local plans to reduce greenhouse gas (GHG) emissions in alignment with EU objectives. This study focuses on the case of Sweden and aims to introduce a comprehensive data-driven framework that predicts CO2 emissions by using a diverse range of input features. Considering the scarcity of data points, we present a refined variation of multi-task learning (MTL) called weighted multi-task learning (WMTL). The findings demonstrate the superior performance of the WMTL model in terms of accuracy, robustness, and computation cost of training compared to both the basic model and MTL model. The WMTL model achieved an average mean squared error (MSE) of 0.12 across folds, thus outperforming the MTL model’s 0.15 MSE and the basic model’s 0.21 MSE. Furthermore, the computational cost of training the new model is only 20% of the cost required by the other two models. The findings from the interpretation of the WMTL model indicate that it is a promising tool for developing data-driven decision-support tools to identify strategic actions with substantial impacts on the mitigation of CO2 emissions.
A Prognosis Method for Condenser Fouling Based on Differential Modeling
Authors: Zhang Ying , Yang Tao , Zhou Hongkuan , Lyu Dongzhen , Zheng Wei , Li Xianling
Published: August 2023

Fouling in heat exchanger tubes is a common problem in the operation of condensers. The deposition of fouling can affect the thermal efficiency and safety of the condenser. Therefore, it is necessary to predict the impact of fouling on time and carry out scientific treatment. Firstly, fault prognosis methods require a significant amount of historical fault data, which is often lacking in practical applications. This paper proposes a method based on dynamically adjusting parameters of the fouling thermal resistance empirical equation to establish a fouling thermal resistance digital twin model. It is combined with simulation tools to rapidly generate a large amount of fault data for the research of prognosis methods. Secondly, in the research of fault prognosis methods, prognosis accuracy relies on establishing a reliable and accurate model that describes the behavior of faults. The uncertainty in the modeling process significantly affects the results. Classic modeling methods do not effectively quantify uncertainty. Therefore, this paper proposes a method that applies differential modeling to predict fouling faults in condensers, automatically obtaining uncertain parameters while establishing a reliable model. By calculating the performance evaluation indicator, the accuracy error indicator of the differential modeling-based prognosis method is further reduced to 0.35. The results demonstrate that this method can provide effective reference opinions for handling fouling faults in condensers.
Blockchain-Based Microgrid for Safe and Reliable Power Generation and Distribution: A Case Study of Saudi Arabia
Authors: Khubrani Mousa , Alam Shadab
Published: August 2023

Energy demand is increasing rapidly due to rapid growth and industrialization. It is becoming more and more complex to manage generation and distribution due to the diversification of energy sources to minimize carbon emissions. Smart grids manage reliable power generation and distribution efficiently and cater to a large geographical area and population, but their centralized structure makes them vulnerable. Cybersecurity threats have become a significant concern with these systems’ increasing complexity and connectivity. Further transmission losses and its vulnerability to the single point of failure (SPOF) are also major concerns. Microgrids are becoming an alternative to large, centralized smart grids that can be managed locally with fewer user bases and are safe from SPOF. Microgrids cater to small geographical areas and populations that can be easily managed at the local level and utilized for different sources of energy, like renewable energy. A small group of consumers and producers are involved, but microgrids can also be connected with smart grids if required to exchange the excess energy. Still, these are also vulnerable to cybersecurity threats, as in the case of smart grids, and lack trust due to their decentralized nature without any trusted third party. Blockchain (BC) technology can address the trust and cybersecurity challenges in the energy sector. This article proposes a framework for implementing a BC-based microgrid system for managing all the aspects of a microgrid system, including peer-to-peer (P2P) energy trading, Renewable Energy Certificate (REC), and decentralized energy trading, that can be utilized in the case of Saudi Arabia. It can integrate cybersecurity standards and protocols, as well as the utilization of smart contracts, for more secure and reliable energy generation and distribution with transparency.
Green Transition and Electricity Sector Decarbonization: The Case of West Macedonia
Authors: Kaldellis John K. , Boulogiorgou Despoina , Kondili Emilia M. , Triantafyllou Athanasios G.
Published: August 2023

During the last 50 years, the vast majority of European countries have relied on coal and imported carbon-containing fuels to meet their growing electricity demand. Coal is the only fossil fuel in significant reserves across Europe. However, the pressing threat of radical climate change and the looming depletion of fossil fuels necessitate a structural transformation from a conventional centralized fossil fuel-based electricity generation system to an innovative decentralized system based on zero carbon (green) energy resources. In this context, one important issue for communities operating coal-based Thermal Power Stations (TPS) nearing retirement is whether the European Union (EU) policy can ensure a socially just development of the coal mining areas during the coal phase-out. The objective is to avoid a decline in living standards and mass immigration. In response to the EU’s decarbonization policy, the Greek state has recently decided to retire the lignite-based West Macedonia TPS, which has been in operation since the 1970s. Since its establishment in August 1950, the (initially State-controlled) Greek Public Power Corporation (PPC) has undertaken the responsibility to operate the quarries and the six local TPS, offering approximately 25,000 direct and indirect jobs. Over the last 50 years, the extraction of lignite and the operation of the 4500 MWe TPS of West Macedonia has been the primary economic activity, accounting for nearly 45% of the entire Region’s GDP. While both the Greek state and the EU have prepared and presented plans to financially support local communities and encourage new private and public investments, local citizens remain anxious about their future. The present study investigates the attitude of young scientists towards the forthcoming radical changes linked to the green transition in seriously affected EU Regions, with a focus on West Macedonia. The proposed analysis in West Macedonia reveals the skepticism of young people regarding the speed of the green transition and concerns about significant migration and potential brain drain. On the other hand, the implementation of EU initiatives, including the involvement of young scientists in the planned new green energy-related activities, offers a promising alternative solution. This engagement can lead to the successful integration of local communities into the sustainable and green future envisioned by the EU.
An Innovative H-Type Flux Switching Permanent Magnet Linear Generator for Thrust Force Enhancement
Authors: Farahani Ehsan Farmahini , Baker Nick J. , Mahmouditabar Farshid
Published: August 2023

In this paper, two H-type flux switching permanent magnet linear generators with outer-translator and inner-translator configurations are discussed and compared to a more conventional flux switching topology. The stators consist of H-Type modules housing circumferential coils and are surrounded by two annular permanent magnets. In conventional flux switching machines, the windings are orientated perpendicular to the direction of motion and the conductors twist around the magnets. In H-type topologies, the orientation of the windings is in the same plain as the magnets and parallel to the direction of motion, resulting in an increase in flux linkage. The proposed topologies are designed for a low operating speed and a large magnetic gap, as found in wave energy converters. All topologies are optimized using the Taguchi optimization approach with the goals of reducing force ripple and increasing the average thrust force and efficiency. The 2D finite element method (FEM) is used in the optimization stage to calculate the optimized parameters of the presented generators, after which the optimized structures are simulated using 3D FEM, and the results are extracted. The results of the optimization show that the H-type topologies deliver a 20% higher shear stress whilst offering an easier to assemble structure.
Exploring Landscape Design Intensity Effects on Visual Preferences and Eye Fixations in Urban Forests: Insights from Eye Tracking Technology
Authors: Lan Yuxiang , Liu Qunyue , Zhu Zhipeng
Published: August 2023

Individuals’ preferences for urban forest scenes are an essential factor in the design process. This study explores the connection between landscape design intensity, visual preferences, and eye fixations in urban forest scenes. Five pictures representing different urban forest scenes (plaza, lawn, garden path, pond, and rockery) were selected as stimuli, representing the original landscape design intensity. Three additional levels of design intensity (low, moderate, and high) were created by modifying the landscape elements of the original picture. A group of 50 participants was randomly assigned to observe the four levels of design intensity pictures within each type of landscape using eye-tracking technology. They also rated their preferences for each scene. In total, 250 participants took part in the study, with five groups observing five types of urban forest scenes. The results indicate that landscape design intensity has a positive impact on visual preferences, with moderate design intensity showing the strongest effect. However, the influence of design intensity and preferences also depends on the specific landscape scene. The fixation data did not show a significant relationship with design intensity but were associated with the type of landscape scene. In conclusion, this study suggests that moderate design intensity is recommended for urban forest design. However, it also highlights the importance of considering the specific landscape scene type. The research provides valuable insights into urban forest design and contributes to the understanding of eye-tracking technology in landscape perception studies.
Responses of Plant Species Diversity and Biomass to Forest Management Practices after Pine Wilt Disease
Authors: Liu Jinliang , Liu Weiyong , Wu Jianbin , Wei Boliang , Guo Jing , Zhong Lei , Yu Mingjian
Published: August 2023

Pine wilt disease (PWD), which is caused by the Bursaphelenchus xylophilus, is one of the most serious biological invasions in East Asia. Removal of infected pine trees is generally used to prevent the spread of PWD. However, how this strategy affects plant species diversity and ecosystem functions needs to be clarified. We compared alpha diversity, species composition, and biomass for all woody plant species, adults, saplings, and seedlings in infected Masson pine forests where removal of infected trees occurred (CTD) and where infected trees were retained (UTD), uninfected Masson pine forests (PMF), and evergreen broad-leaved forests (EBF). UTD had the highest alpha diversity of all species and saplings, and UTD and PMF had the lowest alpha diversity of seedlings. CTD and EBF had a similar composition of seedlings, and CTD and UTD had similar species composition of all plant species and saplings. UTD had the lowest biomass for all species and adults but had the highest saplings biomass. Soil properties were significantly related to plant biomass. The retention of infected trees likely maintained soil fertility which increased species alpha diversity and the biomass of saplings, and unchanged species composition compared to the removal of infected trees, indicating that the retention strategy could help to maintain ecosystem functions.
Spatio-Temporal Variation of Carbon Sources and Sinks in the Loess Plateau under Different Climatic Conditions and Land Use Types
Authors: Wang Mi , Hu Zhuowei , Wang Xuetong , Li Xiaojuan , Wang Yongcai , Liu Honghao , Han Chaoqi , Cai Junhao , Zhao Wenji
Published: August 2023

The carbon balance of terrestrial ecosystems is intertwined with climate and changes in land use. Over the past 30 years, the Loess Plateau (LP) has experienced temperature increases and an expansion of forest and grassland. The net ecosystem productivity (NEP) underlying these changes is worth investigating. Using three periods (i.e., 1990–2000, 2000–2010, and 2010–2019) of annual average NEP and climatic, topographic, and land use data, we analyzed changes in the spatial distribution of carbon sources and sinks of the LP. Using an optimal parameter-based geographical detector model to discuss the driving factors of carbon sources and sinks, we found that: (1) The area of carbon sinks has been increasing continuously, and that the distributions of both of these elements are zonal. The carbon sinks show a downward trend from south to north, which is mainly driven by climate and land use type. (2) Carbon sources are mainly concentrated in the middle temperate zone, and they are mainly linked to impervious land, unused land, and grassland. The carbon sinks are mainly concentrated in the south temperate zone and plateau climatic zone, and they are mainly linked to forest, grassland, and cultivated land. Additionally, the southern temperate zone has been the most green, due to its superior hydrothermal conditions that sustain carbon sinks. (3) It is not uncommon for some forests, grasslands, and cultivated land to transition between being carbon sources and carbon sinks, especially when affected by human intervention and inadequate management measures. (4) NEP was primarily influenced by CO2 concentration, temperature, and precipitation, and the interaction of these factors greatly influenced the dynamics of carbon sources and sinks, while terrain exerted insignificant impacts on the NEP. This study highlights the importance of the carbon balance in terrestrial ecosystems and can be used to guide the creation of vegetation-based carbon sequestration policies.
Modelling of Amino Acid Fermentations and Stabilization of Anaerobic Digestates by Extracting Ammonium Bicarbonate
Authors: Moure Abelenda Alejandro , Aggidis George , Aiouache Farid
Published: August 2023

With the current increase in demand for animal and agricultural products, management of agrowaste has become critical to avoid greenhouse gas emissions. The present article investigates the applicability of ammonium bicarbonate synthesis via flash distillation to valorize and stabilize several types of anaerobic digestates which are produced from individual fermentations of amino acids. The content of CO2 in the digestate was found to be responsible for the OH alkalinity (0.4 equivalents of acid/kg digestate), while the partial and total alkalinities (0.8 eq/kg digestate) were essentially derived from the content of NH3. The most suitable conditions for the flash distillation were 95 °C and 1 bar with the condensation occurring at 25 °C. However, in order to attain the precipitation of NH4HCO3 in the distillate, it was necessary to consider digestates with a moisture content of 50 wt.%, since saturation levels of inorganic nitrogen and inorganic carbon were not attained otherwise. Even under these conditions, few amino acids (i.e., arginine, glycine, and histidine) were able to provide an anaerobic digestate upon fermentation that would be suitable for NH4HCO3 stabilization. The process of stabilization with a capacity of a t of digestate per h was improved by adding hydrochloric acid or sodium hydroxide at a rate of 44 kg/h, leading to production of 34 kg NH4HCO3/h. Given the role of the volatile elements of the biogas as endogenous stripping agents, it is recommended to use a fresh and saturated digestate as feed for the flash distillation.
Effects of Fermentation Period on the Non-Volatile Metabolites of Chinese Ultra-Long-Term Solid Fermented Kohlrabi Based on Non-Targeted Metabolomic Analysis
Authors: Jia Xiaohan , Chen Hongfan , Wang Xinyi , Nie Xin , Xiang Lu , Liu Dayu , Zhao Zhiping
Published: August 2023

This study aimed to investigate the effects of ultra-long-term fermentation on the formation of non-volatile metabolites of Chinese solid-fermented kohlrabies. Liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) based non-targeted metabolomics coupled with multivariate statistical analysis were employed to respectively analyze the kohlrabies solid fermented for 5 years (5Y), 8 years (8Y), and 11 years (11Y). The results showed that 31, 169, and 123 differential metabolites were identified in the three groups of 5Y and 8Y (A1), 5Y and 11Y (A2), and 8Y and 11Y (A3), respectively (VIP > 1, p < 0.05 and |log2FC| > 1). The differential non-volatile metabolites were mainly organic acids and derivatives, organoheterocyclic compounds, benzenoids, lipids and lipid-like molecules, and organicoxygen compounds. Furthermore, 11 common differential metabolites were screened in the three groups, including diaminopimelic acid, ectoine, 9,10,13-TriHOME, and 9 others. The citrate cycle, glycine, serine and threonine metabolism, pantothenate and CoA biosynthesis, and glyoxylate and dicarboxylate metabolism were the four pathways most significantly correlated with the differential non-volatile metabolites based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis (p < 0.05). The present study describes the effects of ultra-long-term fermentation periods on the formation of non-volatile metabolites in solid fermented kohlrabies, providing a theoretical basis for cooking with the three solid fermented kohlrabies to make different Chinese dishes.
Anaerobic Digestion of Lignocellulosic Biomass: Substrate Characteristics (Challenge) and Innovation
Authors: Manyi-Loh Christy E. , Lues Ryk
Published: August 2023

Modern society is characterised by its outstanding capacity to generate waste. Lignocellulosic biomass is most abundant in nature and is biorenewable and contains energy sources formed via biological photosynthesis from the available atmospheric carbon dioxide, water, and sunlight. It is composed of cellulose, hemicellulose, and lignin, constituting a complex polymer. The traditional disposal of these types of waste is associated with several environmental and public health effects; however, they could be harnessed to produce several value-added products and clean energy. Moreover, the increase in population and industrialisation have caused current energy resources to be continuously exploited, resulting in the depletion of global fuel reservoirs. The overexploitation of resources has caused negative environmental effects such as climate change, exacerbating global greenhouse gas emissions. In the quest to meet the world’s future energy needs and adequate management of these types of waste, the anaerobic digestion of lignocellulosic biomass has remained the focus, attracting great interest as a sustainable alternative to fossil carbon resources. However, substrate characteristics offer recalcitrance to the process, which negatively impacts the methane yield. Nevertheless, the biodigestibility of these substrates can be enhanced through chemical, physical, and biological pretreatment methods, leading to improvement in biogas yields. Furthermore, the co-digestion of these substrates with other types and adding specific nutrients as trace elements or inoculum will help to adjust substrate characteristics to a level appropriate for efficient anaerobic digestion and increased biogas yield.
Effect of Microbial Reinforcement on Polyphenols in the Acetic Acid Fermentation of Shanxi-Aged Vinegar
Authors: Du Peng , Li Yingqi , Zhen Chenrui , Song Jia , Hou Jiayi , Gou Jia , Li Xinyue , Xie Sankuan , Zhou Jingli , Yan Yufeng , Zheng Yu , Wang Min
Published: August 2023

Polyphenols are important functional substances produced in the acetic acid fermentation (AAF) of Shanxi aged vinegar (SAV). Previous studies have shown that the metabolic activity of microorganisms is closely related to polyphenol production and accumulation. In this study, microorganisms in the AAF of SAV were analyzed to explore how to increase the polyphenol yield by changing the microorganisms and reveal the potential mechanism of the microbial influence on the polyphenol yield. Macrotranscriptome analysis showed that acetic and lactic acid bacteria dominated the AAF fermentation process and initially increased and decreased. Spearman correlation analysis and verification experiments showed that the co-addition of Acetobacter pasteurianus and Lactobacillus helveticus promoted the accumulation of polyphenols, and the total polyphenol content increased by 72% after strengthening.
Fire Protection Principles and Recommendations in Disturbed Forest Areas in Central Europe: A Review
Authors: Berčák Roman , Holuša Jaroslav , Kaczmarowski Jan , Tyburski Łukasz , Szczygieł Ryszard , Held Alexander , Vacik Harald , Slivinský Ján , Chromek Ivan
Published: August 2023

Forest fires are becoming a more significant problem in Central Europe, but their danger is not as high as that in Southern Europe. The exception, however, is forest fires occurring in disturbed areas (windthrow and bark beetle outbreak areas), which are comparable in severity and danger to the most serious forest fires. In this study, we describe the current situation in Central European countries in terms of fire protection for disturbed areas in managed forests and forest stands left to spontaneously develop (secondary succession). If a country has regulations and strategies in this area, they are often only published in the local language. In this review, we combine information from all Central European countries and summarize it in a unified international language, provide an opportunity for local authorities to express their own experiences, and integrate data from worldwide scientific research. Thus, this paper may be considered a universal guide for managing fire protection and preparedness in disturbed areas and can serve as a reference for the establishment of strict legislative rules at the state level. These laws must be obligatory for all stakeholders in individual countries. The motivation for this study was two large forest fires in an area left to spontaneously develop in the Bohemian Switzerland National Park in the Czech Republic and Harz Mountains in Germany in the summer of 2022. These incidents revealed that fire prevention legislation was inadequate or nonexistent in these areas. The strategy of the European Union is to increase the size of protected areas and spontaneous development areas. Therefore, we consider it necessary to provide governments with relevant information on this topic to create conditions for better management of these destructive events.
Quantifying Fire-Induced Surface Climate Changes in the Savanna and Rainforest Biomes of Brazil
Authors: De Sales Fernando , Werner Zackary , de Souza Ribeiro João Gilberto
Published: August 2023

This study uses a combined research approach based on remote-sensing and numerical modeling to quantify the effects of burned areas on the surface climate in the two Brazilian biomes most affected by fires: the tropical savanna and the Amazon rainforest. Our estimates indicate that between 2007 and 2020, approximately 6% of the savanna and 2% of the rainforest were burned on average. Non-parametric regressions based on 14-year climate model simulations indicate that latent heat flux decreases on average by approximately 0.17 W m−2 in the savanna and 0.60 W m−2 in the rainforest per each 1 km2 burned, with most of the impacts registered during the onset of the wet season. Sensible and ground heat fluxes are also impacted but at less intensity. Surface air is also warmer and drier, especially over rainforest burned sites. On average, fire reduced gross primary production in the savanna and rainforest by 12% and 10%, respectively, in our experiments.
Wildfires Risk Assessment Using Hotspot Analysis and Results Application to Wildfires Strategic Response in the Region of Tangier-Tetouan-Al Hoceima, Morocco
Authors: Boubekraoui Hamid , Maouni Yazid , Ghallab Abdelilah , Draoui Mohamed , Maouni Abdelfettah
Published: August 2023

In recent years, changes in climate, land cover, and sociodemographic dynamics have created new challenges in wildfire management. As a result, advanced and integrated approaches in wildfire science have emerged. The objective of our study is to use geospatial analysis to identify strategic responses to wildfires in the Tangier-Tetouan-Al Hoceima (TTA) region, widely reputed to exhibit the most significant incidences of wildfires in Morocco. We adopted a combined approach, using burned area products (Fire_CCI51: 2002–2020) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and active fires from the Fire Information for Resource Management System (FIRMS: 2001–2022) and processing them with spatiotemporal statistical methods: optimized hotspot analysis (OHA) and emerging hotspot analysis (EHA). The main findings indicate that the TTA region recorded an average of 39.78 km2/year of burned areas, mostly located in forests (74%), mainly cork oak and matorral stands (50%). The OHA detected hotspots covering 2081 km2, with 63% concentrated in the provinces of Chefchaouen and Larache. Meanwhile, clusters of EHA extended over 740 km2 and were composed of the oscillating coldspot (OCS) and oscillating hotspot (OHS) patterns at 50% and 30%, respectively. Additionally, an average of 149 fires/year occurred, located mostly in forests (75%), mainly cork oak and matorral stands (61%). The OHA detected active fire hotspots covering 3904 km2, with 60% located in the provinces of Chefchaouen and Larache. Clusters of EHA over 941 km2 were composed of the oscillating hotspot (OHS) and new hotspot (NHS) patterns at 57% and 25%, respectively. The prevalence of the oscillating and new models mirrors, respectively, the substantial fluctuations in wildfires within the region alternating between periods of high and low wildfire activities and the marked increase in fires in recent times, which has occasioned the emergence of novel hotspots. Additionally, we identified six homogeneous wildfire zones to which we assigned three strategic responses: “maintain” (73% of the territory), “monitor and raise awareness” (14% of the territory), and “reinforce” (13% of the territory). These strategies address current wildfire management measures, which include prevention, risk analysis, preparation, intervention, and rehabilitation. To better allocate firefighting resources, strategic responses were classified into four priorities (very high, high, medium, and low). Last, the wildfire zoning and strategic responses were validated using burned areas from 2021 to 2023, and a global scheme was suggested to assess the effectiveness of future wildfire measures.
Numerical Simulation of Soot Formation in Ethylene Laminar Diffusion Flame
Authors: Gao Xiu-Yan , Yang Fan , Zhang Chuan-Xin , Chen Qi-Xiang , Yuan Yuan
Published: August 2023

The soot produced by fossil fuel combustion affects climate and human health, and the ethylene laminar flame is a crucial research object of soot generation. After verifying the accuracy of the numerical calculation model by comparing experimental data, the impact of changes in inlet flow rate and fuel flow composition operating conditions on the generation of soot were compared and analyzed. The calculated results obtained are consistent with the experimental data in terms of distribution trend. The deviation of the calculated peak integral smoke volume fraction is only 5%. Under the operating conditions set in this study, increasing the volume flow rate of the accompanying air will increase the volume fraction of soot generated by the ethylene laminar diffusion flame. Increasing the fuel volume flow rate will first increase and then decrease the volume fraction of soot.
Fish Welfare in Aquaculture: Physiological and Immunological Activities for Diets, Social and Spatial Stress on Mediterranean Aqua Cultured Species
Authors: Dara Mariano , Carbonara Pierluigi , La Corte Claudia , Parrinello Daniela , Cammarata Matteo , Parisi Maria Giovanna
Published: August 2023

Welfare assessment currently is less well-characterized for aquatic animals and the classical methodologies used for terrestrial animals are not adequate to improve our knowledge about fish well-being. Among different approaches, the status of organism responses can be carried out using different physiological and biochemical tools. Here, we present the state of the art regarding fish welfare, methodologies, and experimental results with a particular focus on two important Mediterranean aquaculture species, Sparus aurata and Dicentrarchus labrax. We introduce an approach using physiological stress-indicators, growth performance and swimming activity to investigate the effects of the implantation of electronic tags to facilitate the application of telemetry for aquaculture purposes. The application of telemetry to research on aquatic organisms has expanded recently, and its utilization needs to be better understood. The mentioned approaches have been discussed for application in different aquaculture methodologies. Moreover, social stress and territoriality are relevant factors in the evaluation of gregarious species that may have consequences on the conditions of animals farmed in captivity. These aspects, that may impair the ability of fish to respond to various stimuli or negatively influence the flesh quality, here are analysed through behavioural observation, flanked by the physiological and immunological approach.
Sorghum (Sorghum bicolor L. Moench) Gluten-Free Bread: The Effect of Milling Conditions on the Technological Properties and In Vitro Bioaccessibility of Polyphenols and Minerals
Authors: Curti María Isabel , Palavecino Pablo Martín , Savio Marianela , Baroni María Verónica , Ribotta Pablo Daniel
Published: August 2023

The absence of gluten proteins in sorghum allows for the production of baked goods that are suitable for celiacs. Previous studies have shown that the milling process affects the performance of sorghum flour in baked products, especially those that are gluten-free (GF). This study aimed to explore the effects of mill type (impact and roller) on flour properties and GF bread quality by assessing the technological quality, antioxidant activity, and mineral content of the bread. All particle populations of flour obtained via both millings presented a bimodal distribution, and the volume mean diameter (D 4,3) ranged from 431.6 µm to 561.6 µm. The partially refined milled flour obtained via polishing and impact milling produced bread with a soft crumb, fewer but larger alveoli in the crumb, and a structure that did not collapse during baking, showing the best performance in bread quality. In the in vitro bread digestibility assay, the total polyphenol content and antioxidant activity decreased during the digestion steps. High mineral (Cu, Fe, Mn, and Zn) contents were also found in a portion of the bread (120 g) made with whole sorghum flour; however, their potential bioavailability was reduced in the presence of a higher amount of bran.