bluuebunny/crossref_metadata_2025 huggingface dataset:
Correction: Toikka et al. Some Remarks on the Boundary of Thermodynamic Stability. Entropy 2023, 25, 969
Authors: Toikka Alexander , Misikov Georgii , Toikka Maria
Published: June 2024

The authors would like to make a tiny but important correction to the published paper [...]
Early Warning of Systemic Risk in Commodity Markets Based on Transfer Entropy Networks: Evidence from China
Authors: Zhao Yiran , Gao Xiangyun , Wei Hongyu , Sun Xiaotian , An Sufang
Published: June 2024

This study aims to employ a causal network model based on transfer entropy for the early warning of systemic risk in commodity markets. We analyzed the dynamic causal relationships of prices for 25 commodities related to China (including futures and spot prices of energy, industrial metals, precious metals, and agricultural products), validating the effect of the causal network structure among commodity markets on systemic risk. Our research results identified commodities and categories playing significant roles, revealing that industry and precious metal markets possess stronger market information transmission capabilities, with price fluctuations impacting a broader range and with greater force on other commodity markets. Under the influence of different types of crisis events, such as economic crises and the Russia–Ukraine conflict, the causal network structure among commodity markets exhibited distinct characteristics. The results of the effect of external shocks to the causal network structure of commodity markets on the entropy of systemic risk suggest that network structure indicators can warn of systemic risk. This article can assist investors and policymakers in managing systemic risk to avoid unexpected losses.
Avionics Module Fault Diagnosis Algorithm Based on Hybrid Attention Adaptive Multi-Scale Temporal Convolution Network
Authors: Du Qiliang , Sheng Mingde , Yu Lubin , Zhou Zhenwei , Tian Lianfang , He Shilie
Published: June 2024

Since the reliability of the avionics module is crucial for aircraft safety, the fault diagnosis and health management of this module are particularly significant. While deep learning-based prognostics and health management (PHM) methods exhibit highly accurate fault diagnosis, they have disadvantages such as inefficient data feature extraction and insufficient generalization capability, as well as a lack of avionics module fault data. Consequently, this study first employs fault injection to simulate various fault types of the avionics module and performs data enhancement to construct the P2020 communications processor fault dataset. Subsequently, a multichannel fault diagnosis method, the Hybrid Attention Adaptive Multi-scale Temporal Convolution Network (HAAMTCN) for the integrated functional circuit module of the avionics module, is proposed, which adaptively constructs the optimal size of the convolutional kernel to efficiently extract features of avionics module fault signals with large information entropy. Further, the combined use of the Interaction Channel Attention (ICA) module and the Hierarchical Block Temporal Attention (HBTA) module results in the HAAMTCN to pay more attention to the critical information in the channel dimension and time step dimension. The experimental results show that the HAAMTCN achieves an accuracy of 99.64% in the avionics module fault classification task which proves our method achieves better performance in comparison with existing methods.
The Effect of Self-Regulated Learning and Community of Inquiry on the Online Learning Engagement of Chinese as Foreign Language Learners
Authors: Lyu Boning
Published: June 2024

This study aimed to understand how different dimensions of online learning engagement were influenced by learners’ self-regulated learning (SRL) and their perceptions of teaching, cognitive, and social presence in the community of inquiry (CoI) framework. A structural equation modelling analysis of survey responses from 154 online Chinese-as-a-foreign-language learners showed that the level of learners’ SRL positively influenced their perceptions of teaching, cognitive, and social presence and consistently directly impacted all dimensions of students’ learning engagement. Regarding the different dimensions of engagement, learner’ perceived CoI had different mediating effects. Affective engagement was influenced by learners’ perceptions of cognitive and social presence, while social engagement was influenced by learners’ perceptions of social presence. Cognitive and behavioural engagements were influenced by learners’ perceptions of teaching presence. The results highlight the importance of SRL in the CoI framework for enhancing learning engagement, suggesting integrating SRL training into instructional design in the online learning environment. In addition, the effects of various dimensions of the CoI framework on learning engagement inform pedagogical implications to enhance online learning engagement, such as building an online learning community to strengthen affective and social engagement while strengthening teaching presence to improve cognitive and behavioural engagement.
Investigating Language and Culture Awareness of Pre-Service Science Teachers in Ireland
Authors: Eren Ebru , Martin Catherine
Published: June 2024

Irish classrooms are becoming increasingly diverse across all levels of education due to the sustained inward migration of non-nationals to Ireland. These demographic changes have enriched the linguistic and cultural fabric of Irish society, including the educational landscape of Ireland. However, in addition to the value such diversity brings to Irish classrooms, there exist many challenges as the Irish education system needs to continue to adapt to develop more inclusive and language- and culture-sensitive pedagogical approaches. One of the ways in which the Irish educational system can respond to this challenge is through the adaptation of its pre-service science teacher education programmes to prepare teachers to teach in linguistically and culturally diverse classrooms. Therefore, it is important to investigate the needs of pre-service science teachers to inform updates to existing teacher education programmes to prepare future science teachers to meet this challenge. Consequently, this study has attempted to capture the perceptions, knowledge and attitudes of current pre-service teachers regarding the role of language and culture in science teaching, awareness of the needs of students whose first language is not English or Irish and teachers’ knowledge of pedagogical strategies to develop language- and culture-sensitive science teaching approaches. Here, we report data from a survey of pre-service science teachers undertaking science teacher training at Irish universities at the undergraduate and postgraduate levels. The data highlight gaps in trainee teachers’ language awareness and their lack of pedagogical knowledge in dealing with language and cultural diversity in science classrooms. Implications for the future development of pre-service science teacher education programmes are discussed.
Effectiveness of Problem-Based Learning in the Unplugged Computational Thinking of University Students
Authors: Moreno-Palma Natalia , Hinojo-Lucena Francisco-Javier , Romero-Rodríguez José-María , Cáceres-Reche María-Pilar
Published: June 2024

Computational thinking is recognized as a critical competency in contemporary education, preparing individuals to tackle complex challenges in a digitally pervasive world. In this quasi-experimental design study with pretest and post-test measures, the possibility of developing computational thinking from the field of didactics of mathematics in higher education students was investigated. This was performed via a problem-based learning (PBL) methodology using problem solving in the experimental group or, alternatively, focused on the analysis of solved problems in the control group. After the intervention, the control group experienced a statistically significant improvement in the scores obtained in the post-test measure. Thus, PBL and problem solving did not lead to an improvement in the students’ computational thinking, whereas the analysis of solved problems approach did. Therefore, the results suggested the potential benefits of this latter methodology for teaching computational thinking.
Analysis of Factors Influencing the Generation of a Higher-Order Hermite–Gaussian Mode Based on Cascaded Spatial Light Modulators
Authors: Ma Long , Yan Manjun
Published: June 2024

Due to its complex spatial distribution, the higher-order Hermite–Gaussian mode possesses significant application in fields such as precision measurement and optical communication. The spatial light modulator, with its capability to modulate the complex amplitude distribution of the incident light field, finds extensive applications in optical information processing and adaptive optics, thus making it an indispensable tool in these fields. Using cascaded spatial light modulators can efficiently and superbly generate a higher-order Hermite–Gaussian mode; however, the experimental system is challenging, and there are many influencing factors, such as the misalignment between the optical field on the plane of the second spatial light modulator and the hologram loaded onto it, as well as the spot size of the optical field on the plane of the second spatial light modulator. In this paper, we analyzed the influence of the above factors on the quality of generating a higher-order Hermite–Gaussian mode, providing a reference for the efficient and high-quality generation of the higher-order Hermite–Gaussian mode.
Boundary Segmentation of Vascular Images in Fourier Domain Doppler Optical Coherence Tomography Based on Deep Learning
Authors: Wu Chuanchao , Wang Zhibin , Xue Peng , Liu Wenyan
Published: June 2024

Microscopic and ultramicroscopic vascular sutures are indispensable in surgical procedures such as arm transplantation and finger reattachment. The state of the blood vessels after suturing, which may feature vascular patency, narrowness, and blockage, determines the success rate of the operation. If we can take advantage of the golden window of opportunity after blood vessel suture and before muscle tissue suture to achieve an accurate and objective assessment of blood vessel status, this will not only reduce medical costs but will also offer social benefits. Doppler optical coherence tomography enables the high-speed, high-resolution imaging of biological tissues, especially microscopic and ultramicroscopic blood vessels. By using Doppler optical coherence tomography to image the sutured blood vessels, a three-dimensional structure of the blood vessels and blood flow information can be obtained. By extracting the contour of the blood vessel wall and the contour of the blood flow area, the three-dimensional shape of the blood vessel can be reconstructed in three dimensions, providing parameter support for the assessment of blood vessel status. In this work, we propose a neural network-based multi-classification deep learning model that can automatically and simultaneously extract blood vessel boundaries from Doppler OCT vessel intensity images and the contours of blood flow regions from corresponding Doppler OCT vessel phase images. Compared to the traditional random walk segmentation algorithm and cascade neural network method, the proposed model can produce the vessel boundary from the intensity image and the lumen area boundary from the corresponding phase image simultaneously, achieving an average testing segmentation accuracy of 0.967 and taking, on average, 0.63 s. This method can realize system integration more easily and has great potential for clinical evaluations. It is expected to be applied to the evaluation of microscopic and ultramicroscopic vascular status in microvascular anastomosis.
Real-Time RGBT Target Tracking Based on Attention Mechanism
Authors: Zhao Qian , Liu Jun , Wang Junjia , Xiong Xingzhong
Published: June 2024

The fusion tracking of RGB and thermal infrared image (RGBT) has attracted widespread interest within target tracking by leveraging the complementing benefits of information from both visible and thermal infrared modalities, but achieving robustness while operating in real time remains a challenge. Aimed at this problem, this paper proposes a real-time tracking network based on the attention mechanism, which can improve the tracking speed with a smaller model, and at the same time, introduce the attention mechanism in the module to strengthen the attention to the important features, which can guarantee a certain tracking accuracy. Specifically, the modal features of visible and thermal infrared are extracted separately by using the backbone of the dual-stream structure; then, the important features in the two modes are selected and enhanced by using the channel attention mechanism in the feature selection enhancement module (FSEM) and the Transformer, while noise is reduced by using gating circuits. Finally, the final enhancement fusion is performed by using the spatial channel adaptive adjustment fusion module (SCAAM) in both the spatial and channel dimensions. The PR/SR of the proposed algorithm tested on the GTOT, RGBT234 and LasHeR datasets are 90.0%/73.0%, 84.4%/60.2%, and 46.8%/34.3%, respectively, and generally good tracking accuracy has been achieved, with a speed of up to 32.3067 fps, meeting the model’s real-time requirement.
The Implementation and Comparison of Conventional and Enhanced Borehole Thermal Response Tests: A Case Study
Authors: de Sousa Figueira João , Nachbaur Stefan , Wehinger Stefan , Bourne-Webb Peter
Published: June 2024

Ground source heat pump (GSHP) systems depend on the capacity for heat transfer between the system and the ground, and it is good practice to carry out an in situ thermal response test (TRT) to determine the undisturbed ground temperature, the thermal conductivity of the ground, and the thermal resistance of the borehole. Conventionally, a TRT is undertaken in a replica borehole heat exchanger (BHE); however, alternative methods have been developed that can provide continuous depth-resolved temperature recordings. The enhanced TRT (ETRT) uses a hybrid cable system which incorporates a resistance heating wire to provide a linear heat source and a fibre optic cable to measure the temperature along the length of the borehole. In this paper, a case study is presented in which a TRT and ETRT were carried out in the same BHE to evaluate its thermal response and estimate the thermal characteristics of the ground. After a brief introduction of both methods and their interpretation, a comparison between them is presented regarding their advantages and disadvantages using the results of the performed tests, which revealed an 8% difference in the soil thermal conductivity values, averaged over the length of the BHE.
Artificial Neural Networks as a Tool to Understand Complex Energy Poverty Relationships: The Case of Greece
Authors: Papada Lefkothea , Kaliampakos Dimitris
Published: June 2024

The present paper provides an innovative approach in the existing methods of studying energy poverty, i.e., a crucial socio-economic challenge of the past decade in Europe. Since the literature has shown that conventional statistical models lack effectiveness in handling unconventional relationships between variables and present limitations in terms of accurate classification and prediction, the paper explores the ability of Artificial Intelligence and, particularly, of Artificial Neural Networks (ANNs), to successfully predict energy poverty in Greece. The analysis included the prediction of seven energy poverty indicators (output indicators) based on certain socio-economic/geographical factors (input variables), via training an ANN, i.e., the Multilayer Perceptron. Three models (Model A, Model B and Model C) of different combinations of the input variables were tested for each one of the seven indicators. The analysis showed that ANNs managed to predict energy poverty at a remarkably good level of accuracy, ranging from 61.71% (lowest value) up to 82.72% (highest accuracy score). The strong relationships that came up on the examined cases confirmed that ANNs are a promising tool towards a deeper understanding of the energy poverty roots, which in turn can lead to more targeted policies.
Accuracy Verification of Multiple Floating LiDARs at the Mutsu-Ogawara Site
Authors: Uchiyama Shogo , Ohsawa Teruo , Asou Hiroshi , Konagaya Mizuki , Misaki Takeshi , Araki Ryuzo , Hamada Kohei
Published: June 2024

Floating LiDAR systems (FLSs) may replace conventional offshore met masts, and they have been developed well in Europe. However, before using them in Japan, we must determine whether they demonstrate the same performance under the unique East-Asian meteorological and oceanographic conditions. Therefore, herein, we investigate the performance of FLSs by focusing on the differences among models. Four independent wind datasets from three FLSs were simultaneously verified against a reference met mast and vertical LiDAR at a Japanese site. The data availability was confirmed to vary from 62.7 to 98.0% over the period at 63 m. This was strongly affected by the system availability of the buoy and LiDAR, suggesting that buoy system robustness is key to better campaigns with higher data availability. The 10 min averaged wind speed and direction largely satisfied the Carbon Trust’s key performance indicators, with a low sensitivity to wave conditions depending on the buoy shape. The standard deviation of the wind speed and turbulence intensity had poorer accuracy than that of the 10 min averaged statistics because of the wave-induced buoy motion, especially for small buoys. In short, this paper provides an overview of a measurement by FLS in Japan. Also, the unique verification with multiple units suggests the need for a low-motion buoy or motion compensation to improve the measurement accuracy of the turbulence component.
Strategic Assessment of the Environmental Impact of Ski Resorts as Part of the Polish Energy Policy Project
Authors: Lewicki Wojciech , Niekurzak Mariusz
Published: June 2024

The dilemma of choosing between conventional energy and renewable energy sources is a topic of discussion in various economic and social sectors. This problem is not only a matter of the country’s energy security but is also an important element of sustainable development that affects the functioning of future generations. The analysis of this process must cover all aspects of operation, with particular emphasis on tourism, including ski resorts. The aim of the work is to assess the current state of ski infrastructure in terms of the possibility of using green energy to power these types of devices, with an indication of the profitability of implementing this project. This analysis will cover the types of renewable energy sources and how they are used in winter sports resorts around the world, whilst additionally focusing on the energy structure of Poland and the European Union, as well as on energy transformation plans in Poland. An important aspect of this analysis is to understand the barriers to the development of the unconventional energy sector and the ski resorts themselves. The impact of ski resorts on the natural environment was also examined. When analyzing the profitability of introducing green energy to power ski slopes, the costs of traditional energy sources in a Polish ski resort were analyzed. The benefits of introducing green energy were indicated by comparing SWOT analyses of the Polish coal sector with renewable energy sources. In the economic context, the profitability of the proposed renewable energy installation was presented, using the NPV, IRR and payback period methods. The analysis of the cost structure of traditional energy sources allowed for the identification of a potential investment in renewable energy technologies, showing the share of electricity costs in the structure of energy carriers used on the ski slope. As a result, the profitability of the installation project was indicated as photovoltaic with specific power and parameters. Although the presented considerations refer to the realities and legal regulations applicable in one of the selected European Union countries—Poland, a country where energy from photovoltaic panels is developing the fastest among all renewable energy sectors in Europe—these considerations can be used in practice to indicate further directions and development prospects for other regions of the world. At the same time, the content of the considerations creates the basis for further development of research on these processes in order to popularize Poland’s energy policy.
An Intelligent Power Transformers Diagnostic System Based on Hierarchical Radial Basis Functions Improved by Linde Buzo Gray and Single-Layer Perceptron Algorithms
Authors: Hendel Mounia , Bousmaha Imen Souhila , Meghnefi Fethi , Fofana Issouf , Brahami Mostefa
Published: June 2024

Transformers are fundamental and among the most expensive electrical devices in any power transmission and distribution system. Therefore, it is essential to implement powerful maintenance methods to monitor and predict their condition. Due to its many advantages—such as early detection, accurate diagnosis, cost reduction, and rapid response time—dissolved gas analysis (DGA) is regarded as one of the most effective ways to assess a transformer’s condition. In this contribution, we propose a new probabilistic hierarchical intelligent system consisting of five subnetworks of the radial basis functions (RBF) type. Indeed, hierarchical classification minimizes the complexity of the discrimination task by employing a divide-and-conquer strategy, effectively addressing the issue of unbalanced data (a significant disparity between the categories to be predicted). This approach contributes to a more precise and sophisticated diagnosis of transformers. The first subnetwork detects the presence or absence of defects, separating defective samples from healthy ones. The second subnetwork further classifies the defective samples into three categories: electrical, thermal, and cellulosic decomposition. The samples in these categories are then precisely assigned to their respective subcategories by the third, fourth, and fifth subnetworks. To optimize the hyperparameters of the five models, the Linde–Buzo–Gray algorithm is implemented to reduce the number of centers (radial functions) in each subnetwork. Subsequently, a single-layer perceptron is trained to determine the optimal synaptic weights, which connect the intermediate layer to the output layer. The results obtained with our proposed system surpass those achieved with another implemented alternative (a single RBF), with an average sensitivity percentage as high as 96.85%. This superiority is validated by a Student’s t-test, showing a significant difference greater than 5% (p-value < 0.001). These findings demonstrate and highlight the relevance of the proposed hierarchical configuration.
Understanding the Competition Mechanism between Na2O and CaO for the Formation of the Initial Layer of Zhundong Coal Ash
Authors: Abudoureheman Maierhaba , He Lanzhen , Liu Kunpeng , Wei Bo , Lv Jia , Wang Jianjiang , Zhu Quan
Published: June 2024

The contents of alkali and alkaline earth metals are higher in Zhundong coal, and there are serious problems of slagging and fouling during the combustion process. Therefore, it is of great significance to reveal the mechanism of slagging and fouling in the boiler of Zhundong coal. In this paper, first-principle calculations based on density functional theory are used to study the competition mechanism of alkaline metal oxides during the combustion process in Zhundong coal by establishing the Na2O(110)/CaO(100)-SiO2(100) double-layer interface model. The results show that the bond lengths of the surface of Na2O(110) and CaO(100) with SiO2(100) after adsorption were generally lengthened and the value of bond population became smaller, which formed a stable binding energy during the reaction. The electron loss of Na is 0.05 e, the electron loss of Ca is 0.03 e, and the electron loss of Na2O is greater than that of CaO. The charge transfer on the surface of Na2O with SiO2 is obviously higher than that of CaO and the orbital hybridization on the surface of CaO with SiO2 is weaker than that on the surfaces of Na2O with SiO2. Na2O is easier to react with SiO2 than CaO. The adsorption energies on the surface of Na2O and CaO with SiO2 are −5.56 eV and −0.72 eV, respectively. The adsorption energy of Na2O is higher than that of CaO, indicating that Na2O is more prone to adsorption reactions and formation of Na-containing minerals and other minerals, resulting in more serious slagging. In addition, the XRD analyses at different temperatures showed that Na-containing compounds appeared before Ca-containing ones, and the reaction activity of Na2O is stronger than that of CaO in the reaction process. The experimental results have good agreement with the calculation results. This provides strong evidence to reveal the slagging and fouling of Zhundong coal.
Multi-Functional Device Based on Superconducting Magnetic Energy Storage
Authors: Guo Wenyong , Hong Yun , Lan Jianyu , Yang Yahong
Published: June 2024

Presently, there exists a multitude of applications reliant on superconducting magnetic energy storage (SMES), categorized into two groups. The first pertains to power quality enhancement, while the second focuses on improving power system stability. Nonetheless, the integration of these dual functionalities into a singular apparatus poses a persistent challenge. Considering this, this paper proposes a multi-functional device based on SMES, encompassing both power quality enhancement and power system stability improvement capabilities. It incorporates power quality enhancement features such as current harmonic filtering, active power smoothing, reactive power compensation, and critical load protection, while also furnishing virtual inertia to bolster grid frequency. Simulation results validate the effectiveness of the proposed methodologies.
Three-Dimensional Physics-Informed Neural Network Simulation in Coronary Artery Trees
Authors: Alzhanov Nursultan , Ng Eddie Y. K. , Zhao Yong
Published: June 2024

This study introduces a novel approach using 3D Physics-Informed Neural Networks (PINNs) for simulating blood flow in coronary arteries, integrating deep learning with fundamental physics principles. By merging physics-driven models with clinical datasets, our methodology accurately predicts fractional flow reserve (FFR), addressing challenges in noninvasive measurements. Validation against CFD simulations and invasive FFR methods demonstrates the model’s accuracy and efficiency. The mean value error compared to invasive FFR was approximately 1.2% for CT209, 2.3% for CHN13, and 2.8% for artery CHN03. Compared to traditional 3D methods that struggle with boundary conditions, our 3D PINN approach provides a flexible, efficient, and physiologically sound solution. These results suggest that the 3D PINN approach yields reasonably accurate outcomes, positioning it as a reliable tool for diagnosing coronary artery conditions and advancing cardiovascular simulations.
Valorization of Yellowfin Tuna Tails: From Proteolytic Enzyme Production to Gelatin and Antioxidant Hydrolysate Extraction
Authors: Sisa Alisson , Martínez-Álvarez Oscar , Gómez-Estaca Joaquín , Mosquera Mauricio
Published: June 2024

This study investigates the valorization potential of yellowfin tuna (Thunnus albacares) tails to produce high-value commercial products. Firstly, the tuna tails were placed in a perforated stainless-steel cylinder, and hydraulic pressure was applied to separate the skin from the muscle in the tails. The extracted muscle was then utilized as a nitrogen source for the growth of the proteolytic enzyme producer Bacillus subtilis, while the skins were employed for gelatin extraction. The proteases from B. subtilis were partially purified and used to produce antioxidant peptides from the obtained gelatin. The gelatin formed a gel upon cooling, with gelling and melting temperatures of 16 °C and 22 °C, respectively, and a Bloom strength of approximately 160. Response Surface Methodology (RSM) was employed to determine the optimal hydrolysis conditions to achieve the highest antioxidant activity (35.96% measured as DPPH radical scavenging activity), which were 50 °C and 6.5 IU of enzyme. The findings emphasize the importance of an integrated approach to maximize the value of tuna by-products, promoting sustainability within the framework of a circular bioeconomy. Overall, these results contribute to the efficient utilization of tuna by-products, waste reduction, and enhanced economic viability of the tuna industry.
The Use of Carrot Fiber and Some Gums in the Production of Block-Type Melting Cheese
Authors: Cankurt Hasan , Cavus Mustafa , Guner Osman
Published: June 2024

In this study, the effect of carrot fiber and certain gums on the physicochemical, textural, microbiological, and sensory properties of block-type melting cheese, which holds a significant place in our daily food consumption, was investigated. The study also aimed to determine the impact of carrot fiber and other gums on cheese properties, as well as on yield and meltability. Carrot fiber was used at levels of 2.5% and 5.0% by weight, while carrageenan and xanthan gum were each used at levels of 0.25% and 0.50%. The cheeses were analyzed on days 1, 15, and 30. At the end of the study, it was determined that the highest total dry matter, fat, and protein values were found in the control sample due to the addition of water when preparing the cheeses with fiber and gum. The highest dry matter, fat, salt, and protein ratios were 59.65%, 29.40%, 1.48%, and 24.48%, respectively, in the control sample. The lowest fat, salt, and protein ratios were 25.00%, 1.31%, and 22.07%, respectively, in the 5.0% carrot fiber sample. The lowest dry matter value was found in the 0.5% xanthan sample, namely 53.62%. The highest L* value was measured in the control sample at 86.89, while the lowest was measured in the 5.0% carrot fiber sample at 81.86. The lowest a* and b* values were 2.82 and 29.42, respectively, in the control sample, while the highest values were 6.20 and 37.37, respectively, in the 5.0% carrot fiber sample. It was observed that the use of carrot fiber imparted an orangish color to the cheese. It was observed that the pH values of the samples were similar. According to the sensory evaluation results, the most liked sample was the control sample with 8.5 points, followed by the 0.25% xanthan sample with 8.0 points. The 5.0% carrot fiber sample received the lowest sensory appreciation with 6.1 points. It was understood that the use of carrot fiber gave the cheese an orangish color. Although the meltability varied according to the amount of gum and fiber used, it was measured at 6.92 cm in the 0.25% carrageenan sample on the first day and at 6.79 cm in the control sample on the last day of storage. It was observed that the use of fiber decreased the total bacterial count, while the use of gum increased it.
Effects of Heterologous Expression of Genes Related L–Malic acid Metabolism in Saccharomyces uvarum on Flavor Substances Production in Wine
Authors: Li Ping , Song Wenjun , Wang Yumeng , Li Xin , Wu Shankai , Li Bingjuan , Zhang Cuiying
Published: June 2024

During malolactic fermentation (MLF) of vinification, the harsh L–malic acid undergoes transformation into the milder L–lactic acid, and via decarboxylation reactions it is catalyzed by malolactic enzymes in LAB. The use of bacterial malolactic starter cultures, which usually present challenges in the industry as the suboptimal conditions after alcoholic fermentation (AF), including nutrient limitations, low temperatures, acidic pH levels, elevated alcohol, and sulfur dioxide concentrations after AF, lead to “stuck” or “sluggish” MLF and spoilage of wines. Saccharomyces uvarum has interesting oenological properties and provides a stronger aromatic intensity than Saccharomyces cerevisiae in AF. In the study, the biological pathways of deacidification were constructed in S. uvarum, which made the S. uvarum carry out the AF and MLF simultaneously, as different genes encoding malolactic enzyme (mleS or mleA), malic enzyme (MAE2), and malate permease (melP or MAE1) from Schizosaccharomyces pombe, Lactococcus lactis, Oenococcus oeni, and Lactobacillus plantarum were heterologously expressed. For further inquiry, the effect of L–malic acid metabolism on the flavor balance in wine, the related flavor substances, higher alcohols, and esters production, were detected. Of all the recombinants, the strains WYm1SN with coexpression of malate permease gene MAE1 from S. pombe and malolactic enzyme gene mleS from L. lactis and WYm1m2 with coexpression of gene MAE1 and malate permease gene MAE2 from S. pombe could reduce the L–malic acid contents to about 1 g/L, and in which the mutant WYm1SN exhibited the best effect on the flavor quality improvement.
Tunable Physical Properties of Electro-Blown Spinning Dextran/Zein Nanofibers Cross-Linked by Maillard Reaction
Authors: Ren Yupeng , An Jianhui , Tian Cheng , Shang Longchen , Tao Yexing , Deng Lingli
Published: June 2024

Electrospinning biopolymer nanofibers have emerged as promising candidates for food packaging applications. In this study, dextran/zein nanofibers were fabricated using electro-blown spinning and subsequently cross-linked via the Maillard reaction (MR) at 60 °C and 50% relative humidity. Compared to traditional electrospinning, the introduction of air-blowing improved the sample preparation speed by 10 times. SEM analysis revealed that the nanofiber morphology remained stable upon MR treatment for 24 h. FTIR spectroscopy confirmed that the MR led to a deformation in the protein conformation and an increase in hydrophilicity and elasticity in the nanofibers cross-linked for 6 h. MR treatment for 18 h considerably enhanced the hydrophobicity and elastic modulus owing to covalent bond formation. Thermal analysis indicated an improved thermal stability with increasing MR duration. Mechanical property analysis revealed an increase in elastic modulus and a decrease in elongation at break for the nanofibers cross-linked for more than 6 h, indicating a trade-off between rigidity and flexibility. Notably, the water vapor permeability of the nanofibers cross-linked for 6 and 18 h was remarkably higher, which can be ascribed to the fiber morphology retention upon water evaporation. Overall, MR-cross-linked dextran/zein/xylose nanofibers showed tunable properties, making them a suitable encapsulation system for bioactive compounds.
Integration of Postbiotics in Food Products through Attenuated Probiotics: A Case Study with Lactic Acid Bacteria in Bread
Authors: Morán Javier , Kilasoniya Alina
Published: June 2024

The study examines the integration of postbiotics in food products through the use of attenuated probiotics, specifically lactic acid bacteria (LAB) in bread. Postbiotics, non-viable microorganisms or their metabolites, offer health benefits similar to probiotics without the risks associated with live bacteria. This research evaluates the regulatory aspects and safety of LAB in sourdough bread production, highlighting their historical and significant use in Europe before 1997. The study includes microbial quantification and Next-Generation Sequencing (NGS) to identify LAB in traditional sourdough, comparing them with historical and current EFSA Qualified Presumption of Safety (QPS) lists. Findings show that the LAB present in sourdough have been extensively and safely used in bread making, supporting their classification as non-novel foods under EU regulations. The stability and consistency of LAB metabolites in sourdough bread are also confirmed, ensuring quality and safety in each batch. The study concludes that LAB in sourdough, when inactivated through bread-making processes, are not considered novel foods, aligning with historical, scientific, and regulatory evidence.
Effect of Oat Beta-Glucan on Physicochemical Properties and Digestibility of Fava Bean Starch
Authors: Shi Miaomiao , Song Xing , Chen Jin , Ji Xiaolong , Yan Yizhe
Published: June 2024

The current research examined the impact of different concentrations of oat beta-glucan (OG) on the in vitro digestibility of fava bean starch (FS). Our pasting analysis demonstrated that OG effectively decreased the viscosity and regrowth of FS, suppressing its in situ regrowth while enhancing the in vitro pasting temperature. Moreover, OG markedly diminished amylose leaching and minimized the particle size of the pasted starch. Rheological and textural evaluations demonstrated that OG markedly diminished the viscoelasticity of the starch and softened the gel strength of the composite system. Structural analysis revealed that hydrogen bonding is the primary interaction in the FS-OG system, indicating that OG interacts with amylose through hydrogen bonding, thereby delaying starch pasting and enhancing the gelatinization characteristics of FS gels. Notably, the incorporation of OG resulted in a reduction in the levels of rapidly digestible starch (RDS) and slowly digestible starch (SDS) in FS, accompanied by a notable increase in resistant starch (RS) content, from 21.30% to 31.82%. This study offers crucial insights for the application of OG in starch-based functional foods.
Licuri Kernel (Syagrus coronata (Martius) Beccari): A Promising Matrix for the Development of Fermented Plant-Based Kefir Beverages
Authors: de Carvalho Alves Janaína , de Souza Carolina Oliveira , de Matos Santos Livia , Viana Suelen Neris Almeida , de Jesus Assis Denilson , Tavares Pedro Paulo Lordelo Guimarães , Requião Elis dos Reis , Ferro Jéssica Maria Rio Branco dos Santos , Roselino Mariana Nougalli
Published: June 2024

New licuri-based kefir beverages were obtained using water kefir grains as fermentation inoculum (1, 2.5, and 5%) under different fermentation times (24 and 48 h). Metagenomic sequencing of the kefir grains adapted to the aqueous licuri extract revealed Lactobacillus hilgardii and Brettanomyces bruxellensis to be predominant in this inoculum. The excellent adaptation of the kefir grains to the licuri extract raised the possibility of prebiotic action of these almonds. The beverages showed acidity values between 0.33 ± 0.00 and 0.88 ± 0.00 mg lactic acid/100 mL and pH between 3.52 ± 0.01 and 4.29 ± 0.04. The viability of lactic acid bacteria in the fermented beverages was equal to or greater than 108 CFU/mL, while yeasts were between 104 and 105 CFU/mL. There were significant differences (p < 0.05) in the proximate composition of the formulations, especially in the protein (1.37 ± 0.33–2.16 ± 0.84) and carbohydrate (5.86 ± 0.19–11.51 ± 1.26) contents. In addition, all the samples showed good stability in terms of acidity, pH, and viability for LAB and yeasts during 28 days of storage (4 °C). Overall, the beverages showed a dominant yellow-green color, non-Newtonian pseudoplastic behavior, and high mean scores in the sensory evaluation. This study provided evidence of the emerging potential of licuri in the plant-based beverage industry.
A ‘Usable Past’?: Irish Affiliation in CANZUS Settler States
Authors: Broman Patrick
Published: June 2024

In a 2023 article in this journal, Esther and Michael Fitzpatrick wrote that “complicated are those diaspora people who yearn to claim ‘Irishness’ in their places as something distinct from colonial settlers”. An Irish identity seems to offer something unique in these contexts, having been embraced by Joe Biden, for example, as a keystone of his political identity. In this article, I utilise census data from the four primary Anglo-settler polities of Canada, Australia, New Zealand, and the United States to demonstrate the comparatively greater extent that Irish ethnic antecedents are remembered by local-born Whites. While acknowledging that drivers of ethnic affiliation are personal and multifaceted, and not directly discernible from answers on a questionnaire, I consider the nature of Irishness as a political identity in settler-colonial contexts.
A Preliminary Scoping Review of the Impact of e-Prescribing on Pharmacists in Community Pharmacies
Authors: Farghali Amr A. , Borycki Elizabeth M.
Published: June 2024

Objective: This scoping review aims to map the available literature and provide an overview of the published articles discussing the impact of electronic prescribing on medication errors and pharmacy workflow. Methods: The literature search was conducted using PubMed®, Web of Science®, and the Cochrane Database of Systematic Reviews®, as well as grey literature reports, using the search terms and related components of “pharmacists”, “electronic prescribing”, “medication errors”, and “efficiency”. The search included all articles that were published from January 2011 to September 2023. Twenty-two relevant articles were identified and fully reviewed, ten of which were included in this review. Results: Electronic prescribing (e-prescribing) provides a solution for some of the challenges that are associated with handwritten and paper prescriptions. However, the implementation of e-prescribing systems has been recognized as a source of new unforeseen medication errors in all the reviewed articles. Productivity in community pharmacies has been affected with receiving electronic prescriptions (e-prescriptions) and having to deal with the issues that arise from them. The pharmacists’ interventions were not eliminated with e-prescriptions compared to other prescription formats. The most frequently reported reason for intervention was related to incomplete instructions in the field of directions of use. Other common challenges with e-prescriptions were related to missing information, quantity, inappropriate dose, dosage form, and drug. Discussion: This review demonstrates the scarcity of research about the impact of electronic prescribing on medication error and efficiency in community pharmacies. In the literature, most of the studies had mainly focused on hospital pharmacies. The literature search demonstrated that there are still some barriers to overcome with e-prescribing systems and that medication errors were not fully eliminated with e-prescriptions. New errors have been identified with e-prescriptions, all of which caused delays in processing, which affected the productivity of the pharmacy staff, and could have negatively impacted patients’ safety if not properly resolved. Conclusion: e-Prescribing solved some of the challenges associated with illegibility of handwritten prescriptions. However, more time is required to allow e-prescribing systems to mature. Further training for prescribers and pharmacists is also recommended before and after the implementation.
The Development and Content Validation of a Clinical Screening Scale to Identify Attention-Deficit Hyperactivity Disorder Cases Based on the Gender Perspective: An e-Delphi Study
Authors: Perez-Beltran Meritxell , Roldán-Merino Juan , Russi Maria Eugenia , Rolandi Maria Garau , Colome Roura Roser , Sampaio Francisco , Del Campo Marta Domínguez , Farres-Tarafa Mariona , Pardos Barbara Hurtado , Alda Díez José Ángel
Published: June 2024

Background: Although many studies analyse gender differences in the clinical expression of Attention-Deficit Hyperactivity Disorder (ADHD) and prevalence studies show that girls with ADHD are underdiagnosed, there are no instruments that are sensitive to the detection of girls with ADHD. Objective: The objective of this study is to develop a self-report early detection instrument for boys and girls with ADHD aged 7 to 16, which includes the gender perspective and is sensitive to the detection of girls with ADHD. Methods: The scale was developed and the items that comprised it were created from the thematic analysis of ADHD and its evaluation in children based on the diagnostic criteria of the DSM-5-TR. A modified e-Delphi method involving a three-round web survey was used to establish a consensus on the content of the scale. Ten experts were recruited to form a professional panel. The panel members were asked to assess the differential symptomatology of ADHD in boys and girls, the dimensions to be evaluated, and the importance of scale items to evaluate the content. Results: A consensus was reached regarding 13 total items distributed in three dimensions: inattention; hyperactivity/impulsivity; and, a third dimension, internalisation, which includes symptoms most present in the expression of ADHD in girls. Conclusions: To the best of our knowledge, the development of this scale using the Delphi method is the first specific scale used for identifying ADHD that also addresses the gender perspective and the differential symptomatology between boys and girls. However, we must proceed to the analysis of psychometric properties, as the scale requires an exhaustive study of its reliability and validity. We can anticipate that this scale will provide relevant and reliable information that can be used for the identification of ADHD in both boys and girls.
Assessing the Dependence and Perceptions of the Harm and Addictiveness of Electronic Cigarettes among Saudi University Students: A Cross-Sectional Study
Authors: Aqeeli Abdulwahab , Alsabaani Abdullah A. , Alshaiban Hassan , Alqassim Ahmad Y. , Alahmar Anwar S. , Sabai Abdullah , Alwadani Saud
Published: June 2024

(1) Background: The rising prevalence of e-cigarette use among university students necessitates a comprehensive understanding of dependence levels and associated factors. This study investigates e-cigarette dependence among Jazan University students in Saudi Arabia. (2) Methods: With the use of a cross-sectional design, data were collected from 1187 students through an online survey from January to April 2024. Dependence levels were assessed using the Penn State Electronic Cigarette Dependence Index (PS-ECDI), and the Arabic version of the questionnaire was validated through pilot testing. Multivariable logistic regression analysis was employed to identify factors associated with e-cigarette dependence. (3) Results: The results indicated that among current e-cigarette users, 37.4% had low dependence, 34.4% had medium dependence, and 13.8% had high dependence. A significant proportion of current and ever users regarded e-cigarettes to be less harmful (50.6% and 44.4%, respectively) and less addictive (37.9% and 32.3%, respectively) than cigarettes. Significant factors influencing dependence included gender, with males showing higher odds of medium (AOR = 12.8, 95% CI: 3.4–47.6) and low dependence (AOR = 9.7, 95% CI: 2.5–37.3) compared to females. Longer duration of e-cigarette use (>2 years) was strongly associated with high dependence (AOR = 50, 95% CI: 7.7–324). Daily use and multiple quit attempts were also significant predictors of higher dependence levels. (4) Conclusions: These findings highlight the substantial e-cigarette dependence among university students and underscore the need for targeted interventions to address this growing public health concern.
Financial Development and Economic Growth: Evidence from Low-Income Nations in the SADC Region
Authors: Mlambo Courage
Published: June 2024

The study sought to examine the relationship between financial development and economic growth in low-income nations in the SADC region. Motivated by the observation that numerous states in the SADC region lack adequately developed financial systems, this investigation was undertaken. Many SADC states are low-income countries, and they remain financially underdeveloped, which could compromise their growth prospects. The analysis was quantitative in nature, and used panel data to achieve its objectives. The data period spanned from 2000 to 2022. The dynamic common correlated effects (DCCE) technique was used for estimation purposes. Results showed that there is a positive relationship between financial development and economic growth. The relationship was also found to be causal: financial development is not only a result of economic growth; it also influences growth. The evidence from the findings supports the notion that financial development is needed to increase the effectiveness of resource allocation and consequently promote growth. This calls on the governments in the countries under investigation to create environments that foster financial development.