bluuebunny/crossref_metadata_2025 huggingface dataset:
Assistive Technology and Alternative and Augmentative Communication Options in the Language Skills Development of Students with Specific Learning Disorders
Authors: Dumitru Cristina
Published: February 2025

The use of augmented reality, assistive technology (AT), and augmentative and alternative communication (AAC) offers a promising opportunity to significantly enhance the general reading abilities of students with specific learning disorders (SLDs) by providing effective learning tools. This study aimed to assess students’ learning experiences to understand the effectiveness of AT and AAC in language skills development and identify the AT tools and devices commonly used in classroom settings, with the goal of better informing practitioners. A systematic literature review was conducted across various databases, resulting in the inclusion of 22 relevant articles, focusing on multiple implications of AT and AAC. Common factors associated with the implementation of AT in teaching students with SLDs were identified, and a thematic analysis revealed recurring patterns regarding the impact of AT solutions on students with SLDs. The findings indicate notable improvements in language skills among students with SLDs, including vocabulary, spelling, orthography, phonological awareness, and reading comprehension. However, two studies reported limited effects or no effects on language skills, self-efficacy, and self-esteem. This review shows that AT and AAC effectively support language skills development and outcomes for students with SLDs. Nevertheless, given the limited number of studies and the complexity of the factors explored, these conclusions should be interpreted with caution.
Bridging Intellectual Traditions Through a Bi/Multi-Cultural Intellectual Mind
Authors: Shen Yuting , Yang Rui
Published: February 2025

This article examines why and how scholars could bridge intellectual traditions in research by developing the notion of “a bi/multi-cultural intellectual mind”. It begins with outlining the historical emergence of Western-centric dominance in global academia and its consequential unequal worldwide knowledge flows. Drawing on elements from the model of bicultural competence, including attitudes, knowledge, skills, and behaviors, this study suggests research directions for examining individual scholars to bridge intellectual traditions. It emphasizes that individual efforts can bridge intellectual traditions in research truly effectively. This article then highlights research pathways of examining intermediaries in global intellectual history, who successfully navigate Euro-American and their own intellectual traditions. In doing so, it proposes an analytical framework for the study of a bi/multi-cultural intellectual mind. Finally, this study calls for diverse and inclusive approaches to research on bridging intellectual traditions, while encouraging an equal dialogue between Euro-American and other intellectual traditions in the global higher education landscape.
Hybrid Reaching Law of Sliding Mode Position-Sensorless Speed Control for Switched Reluctance Motors
Authors: Park Seungyun , Ban Jaepil , Doh Suyoung
Published: February 2025

This study presents a method to reduce the chattering phenomenon and the reaching time of sliding mode speed control for switched reluctance motors (SRMs). In order to simultaneously reduce the chattering phenomenon and reaching time, we propose a hybrid reaching law (HRL) for sliding mode controller (SMC). Furthermore, to address the absence of a position sensor, a sliding mode observer (SMO) is integrated into the proposed HRL-based SMC, enabling accurate estimation of rotor angle and angular speed. Comprehensive simulation results are conducted to verify the effectiveness of the proposed method in terms of the reduced chattering phenomenon and reaching time.
An Envelope-to-Cycle Difference Compensation Method for eLoran Signals in Seawater Based on a Variable Step Size Least Mean Square Algorithm
Authors: Wu Miao , Liu Liang , Li Fangneng , Zhu Bing , Li Wenkui , Jin Xianzhou
Published: February 2025

The dispersion effect of seawater can cause the envelop distortion of underwater eLoran signals, which causes the envelope-to-cycle difference (ECD) to exceed the standard range. Furthermore, it results in incorrect cycle identification and significant positioning errors. However, few studies have focused on the distortion caused by the dispersion effect. In this study, we propose an accurate underwater eLoran ECD compensation method based on a variable step size least mean square (VSS-LMS) algorithm. First, a systematic modeling approach was employed to investigate the impact of dispersion effects on Loran signals. Second, the VSS-LMS algorithm was introduced to update the filter weight vector in response to discrepancies in the input signal. Finally, the input signal was subjected to an adaptive transversal filtering process, resulting in an output signal that adhered to the specifications of the ECD standard. The efficacy and superiority of the proposed algorithm were demonstrated by experimentation and simulation. When the depth of seawater exceeds 2 m, the ECD value of the original eLoran signal exceeds the standard range, precluding the possibility of cycle identification. However, when the depth of seawater reaches 4 m, the ECD of the signal compensated by the proposed algorithm adaptively compensates for the normal range, thereby enabling the accurate recognition of cycles.
Distributed Parameter Identification Framework Based on Intelligent Algorithms for Permanent Magnet Synchronous Wind Generator
Authors: Wu Xiaoxuan , Tian De , Meng Huiwen , Su Yi
Published: February 2025

Parameter identification of a permanent magnet synchronous wind generator (PMSWG) is of great significance for condition monitoring, fault diagnosis, and robust control. However, the conventional multi-parameter identification approach for a PMSWG is plagued by deficiencies, including its sluggish identification speed, subpar accuracy, and susceptibility to local optimization. In light of these challenges, this paper proposes a distributed parameter identification framework based on intelligent algorithms. The proposed approach involves the deployment of SSA, DBO, and PSO algorithms, leveraging golden sine ratio and Gaussian variation strategies for multi-parameter optimization and performance enhancement. Second, the optimal solutions of each intelligent algorithm are aggregated to achieve overall optimization performance enhancement. The efficacy of the proposed method is substantiated by a 6 MW PMSWG parameter identification practice simulation result, which demonstrates its superiority. The proposed method was shown to identify parameters more quickly and effectively than the underlying algorithms, which is of great significance for condition monitoring, fault diagnosis, and robust control of the PMSWG.
Blessing or Curse? The Impact of the Penetration of Industrial Robots on Green Sustainable Transformation in Chinese High-Energy-Consuming Industries
Authors: Sun Yueqi , Ti Junlong , Yang Fang , Chen Hsing Hung
Published: February 2025

The rapid development and widespread application of artificial intelligence (AI) and robots have profoundly impacted the economy, society, and the environment. This article focuses on the relationship between industrial robots and green sustainable transformation in high-energy-consuming industries. Through the Poisson distribution fixed effect, the negative binomial fixed-effect model, and the two-way fixed-effect model, we found that the penetration of industrial robots in high-energy-consuming enterprises (HEEs) has a significant and positive effect on green innovation. In particular, we verified that total factor productivity and ESG, included in the zero-inflation model, have a breakthrough-accelerating role in the application of industrial robots to promote green sustainable transformation. Further analysis indicated that the adoption of industrial robots is also positively correlated with the improvement of corporate green sustainable transformation in non-state-owned enterprises, but state-owned enterprises are not sensitive. In the classification of segmented industries, only the metallurgical industry demonstrates the empowering role of green sustainable transformation. This article provides a new avenue for reshaping the low-carbon green sustainable transformation strategy of HEEs, as well as useful insights, supporting the achievement of carbon peak and carbon neutrality by promoting the application of industrial robots and further improving total factor productivity and ESG performance.
ICT-Driven Strategies for Enhancing Energy Efficiency in G20 Economies: Moderating the Role of Governance in Achieving Environmental Sustainability
Authors: Zahid Zohaib , Zhang Jijian , Gao Chongyan , Oláh Judit
Published: February 2025

Achieving environmental sustainability has become a global priority, with energy efficiency (EE) emerging as a critical pathway. This study examines the influence of information and communication technology service exports (ICT) on EE by integrating the moderating role of regulatory quality. We employ a super-slack-based measure (Super-SBM) and generalized least squares models in G20 economies throughout 2001–2023. The findings show that the average EE is 0.855, which indicates a potential for further improvement of 14.50%. The findings further show that ICT is positively related to EE, and regulatory quality delivers a conducive environment for the adoption of technologies to optimize energy usage. The findings also indicate a synergistic effect between ICT and regulatory quality, which can lead to substantial improvements in EE, emphasizing the importance of governance in facilitating technological advancements. The findings highlight the role of renewable energy and economic openness in shaping EE. Furthermore, Argentina and South Africa achieved the highest EE, reflecting their proximity to the efficient frontier. In robust tests, this study verifies its results using the generalized method of moments, panel-corrected standard error, and feasible generalized least squares models. The findings suggest that ICT and governance perspectives can provide valuable insights for policymakers aiming to enhance energy sustainability through digital transformation and institutional reforms.
Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement
Authors: Fang Jie , Li Wenwu , Chen Dunchu
Published: February 2025

With the increasing penetration of distributed generation (DG), the supply–demand imbalance and voltage overruns in the distribution network have intensified, and there is an urgent need to introduce flexibility resources for regulation. This paper proposes co-planning of electric vehicles (EVs) and soft opening points (SOPs) to improve the flexibility of the active distribution network, thereby improving the economics and flexibility of the distribution network. Firstly, this paper establishes a charging pile day-ahead dispatchable prediction model and a real-time dispatchable potential assessment model through Monte Carlo sampling simulation. It replaces the traditional energy storage model with this model and then solves the EV and SOP collaborative planning model using a second-order conical planning algorithm with the objective function of minimizing the annual integrated cost. At the same time, the flexibility of the distribution network is analyzed by two indicators: power supply and demand balance and branch load margin. Finally, the optimization method proposed in this paper is analyzed and validated on an improved IEEE 33-node distribution system. Example results show that the planning method proposed in this paper can effectively reduce the annual comprehensive operating cost of distribution networks, meet the flexibility index, and be conducive to improving the economy and flexibility of distribution network operation.
The Impact of Trade Openness on Carbon Emissions: Empirical Evidence from Emerging Countries
Authors: Zhou Rui , Guan Shu , He Bing
Published: February 2025

Emerging countries are the main source of new CO2 emissions and the major net carbon importers, and they have also become an important part of the global trade pattern. In this study, the impact of trade openness on CO2 emissions was investigated by approaches such as fully modified least squares (FMOLS), dynamic ordinary least squares (DOLS), and pooled mean group-autoregressive distributive lag (PMG-ARDL) methods. Further estimations were conducted by employing methods such as DCCEMG (dynamic common-correlated effect mean group) and Driscoll–Kray to strengthen the robustness of the results. Moreover, the Granger causality between trade openness and CO2 emissions was tested by using the Dumitrescu–Hurlin method. Conclusions can be drawn as follows: First, economic growth, energy consumption, trade openness, and CO2 emissions are all interconnected in the long term. Specifically, higher levels of economic growth and trade openness are associated with lower CO2 emissions, whereas energy consumption contributes to higher emissions. However, in the short term, economic growth and energy consumption lead to an increase in CO2 emissions, while trade openness does not have a significant impact. Moreover, there is a two-way Granger causality between trade openness and CO2 emissions. Additionally, economic growth and energy consumption have an indirect effect on CO2 emissions by influencing trade openness. Given these findings, emerging market countries should focus on enhancing their service sectors, promoting technological advancements, and fostering international collaboration in green technologies. By actively engaging in efforts to combat climate change, these countries reach a point where trade expansion and carbon reduction are achieved.
Carbon Dioxide Recycling into Fuels and Valuable Chemicals
Authors: Beschkov Venko
Published: February 2025

The present review proposes an approach for remediation of atmosphere pollution by carbon dioxide. The global economic growth nowadays requires extensive energy consumption. Energy is produced traditionally by combustion of carbon containing fuels, resulting in the release of large amounts of carbon dioxide in the atmosphere. These emissions of released CO2 lead to the greenhouse effect on the atmosphere with subsequent impact on the global climate. Remediation of this harmful effect requires reduction in CO2 emissions. In addition to improving the efficiency of energy consumption, this reduction can be also accomplished by the recycling of carbon dioxide into fuels and useful commodities. This conversion of CO2 into fuels and commercial products leads to multiple benefits such as reduction in carbon emissions and greenhouse gases, production of value-added goods, thus reducing oil consumption and associated pollutions of the environment. This review summarizes the efforts to remove, or at least to remediate, the release of carbon dioxide in the atmosphere by its conversion to value-added products prior to discharging. Some of these products are urea, methanol, formic acid, some polymers of practical importance, light hydrocarbons and methane. The recent achievements in chemical catalysis, electrochemistry, bioelectrochemistry and photocatalysis are considered. Discussion on the feasibility of the considered methods compared to the traditional technologies is made. It is concluded that although production of value-added chemicals by carbon dioxide recycling is not yet competitive, it seems promising in the future when its economic feasibility will become a reality.
Effects of Thermal and Non-Thermal Sterilization Methods on the Phytocompounds, Flavor Profile, and Antioxidant Properties of High Acidity Mulberry Vinegar
Authors: Xiong Yuqing , Yang Mozi , Ma Shengmei , Boasiako Turkson Antwi , Aregbe Afusat Yinka , Ma Yongkun
Published: February 2025

This study examined the effects of three sterilization techniques—heat, microwave, and high hydrostatic pressure (HHP)—on the phytochemicals, flavor, and antioxidant properties of high-acidity mulberry vinegar. High-acidity vinegar is valued for its unique sensory properties, preservation potential, and potential health benefits, yet its quality can be significantly impacted by processing methods. Understanding how sterilization affects high-acidity vinegar is crucial for optimizing its functional and nutritional properties while maintaining consumer appeal. Thermal processing (TP) involved heating samples at 85 °C for 15 min, while microwave heating (MH) was performed at 600 W for 40 s. HHP treatments subjected samples to pressures of 400 MPa, 500 MPa, and 600 MPa at ambient temperature (~25 °C) for 15 min. Results showed that total soluble solids (TSS) remained stable at approximately 6.90% across treatments, confirming effective sterilization, especially with HHP. pH values were consistent (3.53–3.55), while total acidity varied, with HHP treatments achieving lower acidity (5.00 g/L). Phytochemical analysis indicated the control (CK) treatment preserved the highest total anthocyanin content (TAC), but HHP500 maintained notable levels. HHP treatments also yielded the highest total phenolic (TPC) and total flavonoid content (TFC), highlighting non-thermal sterilization’s advantage in preserving health-promoting compounds. Antioxidant activity, particularly DPPH, was best retained in HHP samples. HHP500 showed minimal reductions in key phenolic acids, with decreases of 6.16% in p-hydroxybenzoic acid and 7.81% in total phenolic acid. Volatile organic compound analysis revealed increased ester production, with ethyl acetate peaking at 1775.71 μg/L in HHP600. Overall, HHP at 500 and 600 MPa proved superior for producing high-quality mulberry vinegar, supporting the demand for minimally processed, health-focused food products.
Meat-Processing Wastewater Treatment Using an Anaerobic Membrane Bioreactor (AnMBR)
Authors: Hummel Ferdinand , Bauer Lisa , Gabauer Wolfgang , Fuchs Werner
Published: February 2025

This study explores AnMBR technology as a promising method for treating wastewater from the meat-processing industry by analysing its characteristics and impact under continuous feeding. The solids were retained, utilising an ultrafiltration membrane with a pore size of 0.2 µm, and the efficacy of reducing the organic load was evaluated. Although the COD removal rate decreased from 100% at an OLR of 0.71 g/(L*d) to 73% at an OLR of 2.2 g/(L*d), maximum methane yields were achieved at the highest OLR, 292.9 Nm3/t (COD) and 397.8 Nm3/t (VS) per loaded organics and 353.1 Nm3/t (COD) and 518.7 Nm3/t (VS) per removed organics. An analysis of the microbial community was performed at the end of the experiment to assess the effects of the process and the substrate on its composition. The AnMBR system effectively converts meat-processing wastewater into biogas, maintaining high yields and reducing the loss of dissolved methane in the permeate, thanks to a temperature of 37 °C and high salt levels. AnMBR enables rapid start-up, efficient COD removal, and high biogas yields, making it suitable for treating industrial wastewater with high organic loads, enhancing biogas production, and reducing methane loss. Challenges such as high salt and phosphate levels present opportunities for a wider use in nutrient recovery and water reclamation.
Sequential Fermentation with Non-Saccharomyces Yeasts Improves the Chemical and Sensory Characteristics of Albariño and Lado Wines
Authors: García-Luque Estefanía , González Rebeca , Cao Rafael , Soto Elvira , Blanco Pilar
Published: February 2025

The application of non-Saccharomyces yeast in mixed fermentations with Saccharomyces cerevisiae is a useful tool to enhance wine quality. In this study, Metschnikowia fructicola Mf278 and Pichia kluyveri Pk1 were used in sequential fermentations with S. cerevisiae XG3 to ferment grape musts from Albariño and Lado. The development of fermentations was monitored by daily measurements of density and temperature, and sampling at the beginning, tumultuous, and final stages for microbiological control. The basic chemical parameters of wine were determined using the OIV official methodology, whereas the fermentative aroma compounds were quantified by GC–MS. M. fructicola Mf278 and P. kluyveri Pk1 were the predominant yeasts at the initial stages of sequential fermentations but, after the addition of S. cerevisiae XG3, they rapidly declined. A codominance of different S. cerevisiae strains was observed at the middle and final stages of fermentation. At the chemical level, Mf278 lowered the volatile acidity and increased the glycerol content of wines. Moreover, M. Mf278 and Pk1 increased the content of fermentative esters and fatty acids of wines. These compounds contribute fruity and floral notes to the wines that stood out over wines made only with S. cerevisiae, and were better valued at the sensory level.
Fungal Biodegradation of Procyanidin in Submerged Fermentation
Authors: Valencia-Hernández Leidy Johana , Wong-Paz Jorge E. , Ascacio-Valdés J. Alberto , Prado-Barragan Arely , Chávez-González Mónica L. , Aguilar Cristóbal N.
Published: February 2025

The coffee industry generates a large amount of waste that is difficult to treat due to its chemical composition, namely, the presence of caffeine and its derivatives, as well as recalcitrant molecules such as tannins (mainly condensed tannins or polymeric procyanidins), which make it an undervalued waste product. Procyanidins are compounds beneficial to human health and can be found in nature in fruit, grain, seeds, and beverages, among other foods. The zero-waste approach has allowed for the valorization of by-products from the food industry. Currently, coffee pulp is the target of research on extraction, purification, and alternative use. Research on the fungal degradation of procyanidins has emerged as an avenue for the efficient use of these by-products. In this study, the degradation and biotransformation of procyanidin is evaluated and comprises three steps: first, the extraction and partial purification of procyanidins from coffee pulp; second, the production of the potential procyanidin-degrading enzyme by submerged fermentation with Aspergillus niger GH1; third, enzymatic extracellular extract evaluation using a model system with commercial procyanidin C1. The biodegradation/biotransformation results reveal the formation of new compounds, including a final compound with an m/z of 289, possibly a monomeric molecule such as catechin or epicatechin. Identification of the compounds by HPLC-MS confirmed procyanidin C1 depletion under the described assay conditions, which could be used to understand biodegradation pathways proposed for future study. Furthermore, these results confirm that A. niger GH1 is able to degrade and biotransform procyanidin C1.
Body Shape Variation in Atlantic Salmon (Salmo salar, L.) Fed Fishmeal and Fish Oil-Free Diets
Authors: Chollet-Villalpando Jorge G. , Barrows Frederic T. , McLean Ewen
Published: February 2025

Post-smolt Atlantic salmon were fed control (C), plant protein- (PP), and animal protein (AP)-based diets over a 90-day period. At trial start, the outline shape variation in the salmon body was recorded using two-dimensional Cartesian coordinates of a combination of 12 landmarks (LM) and three semi-landmarks from each of the 48 fish. The identical landmarks were then assessed at trial end for the differing dietary treatments. These datasets were used to determine whether diet exerted a measurable effect on body shape to enable authentication of fishmeal/fish oil-free status. Most differences in shape at trial end were visualized at the base of the dorsal and pelvic fins and caudal peduncle. The greatest shape variation between PP and AP groups was found at the base of the pectoral and pelvic fins. While PP and AP groups were more similar in shape than control fish, the recorded differences were not significant enough to verify dietary origins. The number of animals employed and the length of the trial period were likely insufficient to distinguish alterations in body shape with any certainty. Future trials should employ larger numbers of animals and be of longer length to verify whether PP-based feeds cause changes in body shape.
Enhancing Food Image Recognition by Multi-Level Fusion and the Attention Mechanism
Authors: Chen Zengzheng , Wang Jianxin , Wang Yeru
Published: February 2025

As a pivotal area of research in the field of computer vision, the technology for food identification has become indispensable across diverse domains including dietary nutrition monitoring, intelligent service provision in restaurants, and ensuring quality control within the food industry. However, recognizing food images falls within the domain of Fine-Grained Visual Classification (FGVC), which presents challenges such as inter-class similarity, intra-class variability, and the complexity of capturing intricate local features. Researchers have primarily focused on deep information in deep convolutional neural networks for fine-grained visual classification, often neglecting shallow and detailed information. Taking these factors into account, we propose a Multi-level Attention Feature Fusion Network (MAF-Net). Specifically, we use feature maps generated by the Convolutional Neural Networks (CNNs) backbone network at different stages as inputs. We apply a self-attention mechanism to identify local features on these feature maps and then stack them together. The feature vectors obtained through the attention mechanism are then integrated with the original input to enhance data augmentation. Simultaneously, to capture as many local features as possible, we encourage multi-scale features to concentrate on distinct local regions at each stage by maximizing the Kullback-Leibler Divergence (KL-divergence) between the different stages. Additionally, we present a novel approach called subclass center loss (SCloss) to implement label smoothing, minimize intra-class feature distribution differences, and enhance the model’s generalization capability. Experiments conducted on three food image datasets—CETH Food-101, Vireo Food-172, and UEC Food-100—demonstrated the superiority of the proposed model. The model achieved Top-1 accuracies of 90.22%, 89.86%, and 90.61% on CETH Food-101, Vireo Food-172, and UEC Food-100, respectively. Notably, our method not only outperformed other methods in terms of the Top-5 accuracy of Vireo Food-172 but also achieved the highest performance in the Top-1 accuracies of UEC Food-100.
Influence of the β-Casein Genotype of Cow’s Milk (A1, A2) on the Quality and β-Casomorphin-7 (BCM-7) Content of a Semi-Hard Cheese During Production
Authors: Zinßius Louisa , Keuter Lucas , Krischek Carsten , Jessberger Nadja , Cramer Benedikt , Plötz Madeleine
Published: February 2025

Cow’s milk contains A1- and A2-β-caseins. The breakdown of A1-β-casein produces β-casomorphin-7 (BCM-7), a peptide with opioid-like properties that is associated with health aspects. In addition, A1- and A2-β-casein have different technological properties. The aim of the present study was to investigate whether cheese produced from the milk of homozygous A1A1 and A2A2 cows varies in terms of its physicochemical parameters and BCM-7 concentration. These parameters were analyzed during initial cheese processing, six weeks of ripening and 84 days of storage, including additional microbiological analyses during the storage period. The pH values of the A1A1 cheeses were higher than those of the A2A2 cheeses from the beginning of production until the starter culture bacteria were added. The yellowness values of the A1A1 cheeses were lower until the salt bath treatment. Water activity, lightness, hardness, fat, protein, NaCl and dry matter content, as well as color and microbiological parameters, were not affected by the β-casein genotype. BCM-7 concentrations were higher in the A1A1 cheeses after pressing and during ripening. We found mainly comparable quality characteristics and slightly different BCM-7 levels in the A1A1 and A2A2 cheeses. From this point of view, both varieties are equally suitable for cheese production.
Microbial Ecology and Nutritional Features in Liquid Sourdough Containing Hemp Flour Fermented by Lactic Acid Bacterial Strains
Authors: Di Biase Mariaelena , Scicchitano Daniel , Valerio Francesca , Lonigro Stella Lisa , Cifarelli Valentina , Ostante Giorgia , D’Antuono Isabella , Candela Marco , Ferrara Massimo
Published: February 2025

Hemp seed flour (Cannabis sativa) is a non-traditional matrix alternative to wheat for baked goods production. The aim of this study was to investigate the microbiota of two liquid sourdoughs (SLs) based on hemp or a wheat–hemp mixture, before and after spontaneous or piloted fermentation (Lactiplantibacillus plantarum ITM21B or Weissella cibaria C43-11 used as starters). Culture-dependent and -independent (high-throughput sequencing of bacterial phylogenetic V3-V4 regions of the 16S rRNA gene) methods, were used to evaluate the microbial community. The effect of fermentation on the content of bioactive molecules (polyphenols, organic acids, proteins, and amino acids) was also investigated. Results indicated that the microbial community of all SLs was mainly (99.7 ÷ 100%) composed of Firmicutes and Proteobacteria, and the latter was the unique phylum before fermentation in formulations produced exclusively with hemp flour. Two PCoA plots (Test adonis with pseudo-F ratio, p > 0.05) showed no significance difference between the microbial communities of the formulations. However, the relative abundance variation at the family level in the wheat–hemp-based mixture SLs showed a significant enrichment of the Lactobacillaceae family (Kruskal–Wallis test, p = 0.04). Moreover, results confirmed hemp seed flour as a suitable fermentation substrate to obtain microbial consortia allowing for an increase in organic acids, especially lactic acid (9.12 ± 1.22 and 7.45 ± 0.75 mmol/kg with Lpb. plantarum and W. cibaria, respectively), in both piloted fermentations, and in polyphenols by 21% and amino acids by 158% in SL fermented by the C43-11 strain.
Cost-Benefit Analysis of Enzymatic Hydrolysis Alternatives for Food Waste Management
Authors: Ghinea Cristina , Ungureanu-Comăniță Elena-Diana , Țâbuleac Raluca Maria , Oprea Paula Sânziana , Coșbuc Ersilia Daniela , Gavrilescu Maria
Published: February 2025

In this study, we aimed to evaluate the economic, environmental, and social viability of the enzymatic hydrolysis process for food waste valorization by applying cost-benefit analysi (CBA). Our research was based on the investigation of three scenarios/alternatives for the final product of the enzymatic hydrolysis process and the production of bioethanol, bioactive peptides, and organic acids. Key economic indicators, such as cost/benefit ratios, net present value (NPV), and internal rate of return (IRR), were used to evaluate financial performance. At the end of the CBA, a sensitivity analysis was conducted to highlight the performance of each scenario under varying conditions, including fluctuating costs, benefits, and discount rates. These results indicate that enzymatic hydrolysis offers a significant opportunity for reducing food waste and its environmental impacts and promotes sustainability. Bioactive peptide production was found to be the most environmentally viable option, offering the highest cost-benefit efficiency. In both the optimistic and pessimistic scenarios of the sensitivity analysis, the results revealed that bioactive peptide production is economically viable, while the other alternatives, such as bioethanol and organic acid production, are more sensitive to economic and operational changes. This study revealed that enzymatic hydrolysis, as evaluated through CBA, offers a viable and impactful method for food waste management. It reduces environmental impacts, enhances sustainability, and aligns with the principles of a circular economy. The adoption of such innovative waste management strategies is considered essential for building a more sustainable and resource-efficient food system.
Nitrites in Meat Products in Serbia: Harmful or Safe?
Authors: Kureljušić Jasna , Maletić Jelena , Stanojević Slavoljub , Kureljušić Branislav , Petković Jelena , Vasić Ana , Bijelić Tanja
Published: February 2025

Nitrate and nitrite, commonly added to meat products as sodium or potassium salts, serve multiple functions such as developing characteristic flavor, inhibiting microbial growth, and controlling rancidity by preventing lipid oxidation. Nitrites are recognized for their potential health risks to humans. The present research aimed to determine the amount of nitrite in four meat product categories in Serbia over a period from 2015 to 2021. A total of 923 samples were analyzed, including 293 finely chopped sausages, 203 coarsely chopped sausages, 160 canned meats, and 267 smoked meats. The smoked meat category consisted of eight distinct products, such as smoked pork ribs, sirloin, and chicken drumsticks. An ISO 2918 method was used to measure the nitrite content. The average nitrite content, expressed as sodium nitrite (NaNO2), was found to be 61.5 mg/kg in finely chopped sausages, 57.6 mg/kg in coarsely chopped sausages, 48.4 mg/kg in canned meat, and 41.8 mg/kg in smoked meat. The results collectively demonstrate nitrite concentrations within regulatory limits. In conclusion, the nitrite concentrations in all tested products were below the maximum allowable limits as per national and European regulations, ensuring compliance with safety standards while highlighting the importance of continuous monitoring to mitigate public health risks.
Kinematics of the Milky Way from the Statistical Analysis of the Gaia Data Release 3
Authors: Zavada Petr , Píška Karel
Published: February 2025

The aim of the analysis of data from the Gaia Space Observatory is to obtain kinematic parameters of the collective motion of stars in a part of our galaxy. This research is based on a statistical analysis of the motion of 55,038,539 stars selected in different directions from the Sun up to a distance of 3–6 kpc. We developed statistical methods for the analysis working with input data represented by the full astrometric solution (five parameters). Using the proposed statistical methods, we obtained the local velocity of the Sun U⊙,V⊙,W⊙=(9.58,16.25,7.33)±(0.05,0.04,0.02)stat±(0.7,0.9,0.1)syst km/s and the rotation velocity of the galaxy at different radii. For the Sun’s orbit radius, we obtained the velocity of the galaxy rotationVc≈234±4 km/s. Collective rotation slows down in the region under study linearly with distance from the disk plane: ΔV/ΔZ≅33.5kms−1kpc−1. We showed that the different kinematic characteristics and distributions, which depend on the position in the galaxy, can be well described in the studied 3D region by a simple Monte Carlo simulation model, representing an axisymmetric approximation of the galaxy kinematics. The optimal values of the six free parameters were tuned by comparison with the data.
Characterization and Expression Analysis of the bHLH Gene Family During Developmental Stages and Under Various Abiotic Stresses in Sanghuangporus baumii
Authors: Liu Ruipeng , Sun Tingting , Du Pengyu , Liu Zengcai , Li Yawei , Tong Xinyu , Zou Li
Published: February 2025

Background: Basic helix–loop–helix (bHLH) transcription factors (TFs) widely exist in eukaryotic organisms and play a key role in plant growth and development in response to environmental stresses. Sanghuangporus baumii, an important medicinal mushroom known for its anticancer properties, has limited research on the bHLH gene family. Methods: This research utilized the genomic data from S. baumii to identify bHLH family members, and their gene structure, conserved motifs, and phylogenetic relationship were characterized. Additionally, we conducted an analysis of promoter cis-elements and predicted protein interaction networks. We also examined the expression profiles of bHLH genes during different developmental stages and in response to four abiotic stresses: heat, cold, oxidative stress, and heavy metal exposure. Finally, we overexpressed the candidate gene SbbHLH3 in yeast to assess its tolerance to these different stress conditions. Results: A total of 12 SbbHLH genes were identified in S. baumii, and the members of the bHLH gene family displayed a variety of physicochemical characteristics, reflecting their diverse array of functions. Based on homology, the SbbHLH proteins are more closely related to those found in Lentinula edodes and Pleurotus ostreatus. The analysis of promoter cis-elements showed that SbbHLHs contain several elements associated with abiotic stress response, and a network prediction identified 28 bHLH-interacting proteins. Expression pattern analysis revealed that most SbbHLH genes exhibited a positive response to different developmental stages and abiotic stresses. Notably, the overexpression of SbbHLH3 significantly enhanced stress tolerance in yeast. Conclusions: This study provides a comprehensive assessment of the bHLH family in S. baumii, delivering new genetic resources for breeding resistant varieties.
Passive Multichannel Analysis of Surface Waves: A Two-Dimensional Seismic Dataset Acquired with Geophones and Distributed Acoustic Sensing at a Mineral Exploration Site in the Pilbara Region of Western Australia
Authors: Al-Hemyari Emad , Isaenkov Roman , Shashkin Pavel , Pevzner Roman , Tertyshnikov Konstantin
Published: February 2025

Passive seismic surveys have attracted interest for use in many geological and geotechnical applications in the past few decades, mainly in reconstructing models of near-surface properties. They are also of interest in the mineral exploration of shallow deposits where targets lay on or within the bedrock and are covered by loose sediments above. The goal of this article was to test the effectiveness of cheap methods to understand the cover thickness and its lateral variations, which is essential to map the top of the bedrock. We investigated the use of passive seismic surveys to retrieve Rayleigh surface waves and invert them by analyzing their dispersion to reconstruct near-surface shear-wave velocity profiles. Using readily available passive seismic sources is advantageous compared to using costly active sources. Passive seismic data acquired by geophones and DAS showed the potential and challenges of using different sensing technologies. We demonstrated an approach combining passive seismic interferometry and multichannel analysis of surface waves (MASW). Computed dispersion images from both geophone and DAS data provided an improved understanding of their usability for subsurface model building and factors affecting their quality. Some of these factors are related to the surrounding environment, present noise sources, acquisition setup, and the methods used in reconstructing the dispersion images and inverting them. Successful demonstration of MASW was achieved with a relatively short period of continuous recording using a 2D array of geophones at a mineral exploration site in the Pilbara region of Western Australia.
The Implementation of Infant Anoesis and Adult Autonoesis in the Retrogenesis and Staging System of the Neurocognitive Disorders: A Proposal for a Multidimensional Person-Centered Model
Authors: Pirani Alessandro
Published: February 2025

Background: Retrogenesis is the process by which the degenerative and vascular mechanisms of dementia reverse the order of acquisition in the normal development. Objective: The development of memory/knowledge after birth may help to know the biopsychosocial and functional characteristics (biosphere) of the retrogenesis. Methods: A literature review was performed in the PubMed, Google Scholar, and Scopus databases using 43 keywords related to retrogenesis: 234 eligible records were selected. Results: The infantile amnesia, characterized from anoesis, was described along the infant/child’s biosphere in which the limbic system progressively develops the acquisition of the body knowledge (Anoetic Body Consciousness, AnBC). Anoesis is the infant memory state characterized by the absence of long-term memories of the many stressful/painful experiences that accompany the acquisition under the long-life voluntary control of the long-term memories fundamental for the body growth and survival (mainly chewing/swallowing and walking). At the age of 3–4 years, usually, the AnBC evolves, as a continuum, into the adulthood autonoesis with the emergence, in the child/adolescent, of the consciousness of “self” trough the development of the Episodic Autobiographic Memory (EAM) and the Autonoetic Mind Consciousness (AuMC). The development of cognition and knowledge is due to the progressive maturation of the whole limbic system and not only of the hippocampus. In the biopsychosocial retrogenesis, the EAM/AuMC vanishes progressively along the mild, moderate, and severe stages of dementia when the infant AnBC resurfaces, losing progressively the basic activities of daily living in a retrogenetic order of acquisition where the last functions to disappear are chewing/swallowing. Conclusion: The transition from the adult EAM-AuMC to the infant AnBC, as a continuum in the individual biosphere, adds a contribution to the assessment of the retrogenesis in dementia from a multidimensional person-centered model.
Environment Disaster: A Cross-Sectional Study of the Determinants for the Preparation of Azorean Nurses
Authors: Pires Eunice Gatinho , Nogueira Paulo , Henriques Maria Adriana , Arriaga Miguel , Costa Andreia Silva
Published: February 2025

Background/Objectives: Climate change increases the vulnerability of regions, communities, and individuals, stressing the urgent requirement to prepare health professionals in alignment with the Sustainable Development Goals. To foster sustainable and resilient communities, it is essential to integrate disaster preparedness into health education and practice. By equipping nurses with essential knowledge and skills, healthcare systems can be better prepared to respond to the challenges of climate change and disasters, contributing to safer and more resilient urban environments. This study aims to identify the factors that determine nurses’ preparedness for disaster situations. Methods: A cross-sectional online survey was conducted through digital platforms among 230 nurses across the Azores to assess their preparedness for disaster management. A structured questionnaire, adapted from the validated Disaster Preparedness Evaluation Tool (DPET©), was administered to registered nurses affiliated with the Nursing Council. The sample was chosen for convenience, and data were analyzed using IBM® SPSS Statistics, employing descriptive statistics, Cronbach’s alpha for measuring internal consistency, independent samples t-tests, and one-way ANOVA for comparative analysis. Ethical oversight was obtained from the Ethics Committee of the Azores, ensuring confidentiality and the voluntary nature of participation. Results: The findings revealed concerns about nurses’ disaster response, with 70% of participants indicating low ability. While knowledge was relatively strong (M = 5.50, SD = 1.07), practical competence showed a moderate score (3.51, SD = 1.797). Additional education is necessary in areas such as family preparation (M = 2.58, SD = 1.569), patient management during responses (M = 3.43, SD = 1.312), disaster-specific knowledge (M = 2.95, SD = 1.45), and recovery management (M = 2.53, SD = 1.363). Conclusions: Despite increased knowledge and awareness of climate change and its global impact, there is a need for more meaningful nursing interventions to minimize the impact of climate change on the community. This study highlights that nurses have an in-depth knowledge of communities’ needs, which puts them in a unique position to influence disaster preparation and response. By developing these strategies, nurses contribute significantly to communities’ resilience in climate change, improving society’s ability to respond and adapt to these challenges.
Personal and Organizational Factors as Predictors of Life Satisfaction Among Older Adults in Long-Term Care Settings
Authors: Li Xiaoli , Yin Cheng , Abude-Aribo Juliana O. , Conklin Reagen , Mpofu Elias
Published: February 2025

Background and Aims: Resident satisfaction is a critical indicator of the quality of care in long-term care facilities (LTCFs). Yet, the relative importance quality of care factors in predicting resident satisfaction remains unclear for guiding resident support initiatives. This study aims to identify the relative contribution of personal and facility care service factors as predictors of satisfaction LTCF residents. Methods: This cross-sectional study enrolled a convenience sample of 399 older adult residents from LTCFs in Shanghai, Nanjing, and Changsha, China, from June to December 2023. The inclusion criteria were age 65 or older, fluency in speaking and reading simplified Chinese Mandarin, having resided in long-term care facilities for at least one month, and cognitive competence to comprehend the questionnaires. Hierarchical multiple regressions were utilized to examine self-report survey data on ten resident personal variables, and seven care facility service domains were examined for their relative contribution to resident care satisfaction. Moreover, the analysis included the interaction between personal factors and care service attributes. Results: The combined personal and care service factors explained 26.1% of the variance in overall resident satisfaction. Personal factors that predicted resident satisfaction included age, level of independence, and length of stay (ΔR2 = 0.11). Of the care facility factors, the significant predictors of higher resident satisfaction were spending time (β = 0.60, p < 0.01, ΔR2 = 0.09) and environment domains (β = 0.62, p < 0.01, ΔR2 = 0.03). Age moderated the relationship between the spending time domain and overall satisfaction, with a positive effect for residents aged 70–79 compared to those aged 60–69 (β = −1.26, p < 0.05). Conclusions: This study provides evidence to suggest the importance of personal and care facility characteristics to LTFC resident satisfaction. Based on these findings, improved resident satisfaction is likely with LTCF care services that provide tailored care plans using resident characteristics.
Validation of a Questionnaire of Motivations for Moderated and Severe Alcohol Consumption Among College Students
Authors: Lerma Abel , Soto-Huerta Jorge Alberto , González-Flores Cristina J. , Guzmán-Saldaña Rebeca María Elena , Aguirre-Villegas Diego , Lerma Claudia
Published: February 2025

Objective: This work aimed to develop and validate a scale to assess motivations for alcohol drinking among Mexican college students. Methods: The scale design consisted of applying a stimulus phrase to assess motivations for moderate alcohol drinking (up to three drinks per occasion) and severe alcohol consumption (four or more drinks) in 130 college students. The semantic network technique was applied to identify 15 defining motivations (with more considerable semantic weight) for each drinking level, constituting the pilot scale. The pilot scale was validated on 307 students from a public university in Mexico (255 with moderate drinking and 82 with severe consumption). Results: The final number of items per level of drinking was 10 (moderate drinking) and 13 (severe consumption). Internal reliability (Cronbach’s alpha) for the first one was 0.886 with three factors that explain 57.5% of the total variance; the second had an alpha of 0.884 with four factors that explain 70.5% of the total variance. All the factors had positive correlations with the risk perception for alcohol drinking, and there was a positive correlation between severe consumption motivation and the risk perception for consumption of other substances. The confirmatory factor analysis showed that the proposed theoretical models adjust to the data with an error of approximately zero (i.e., RMSEA of 0.088 for moderate consumption and 0.074 for severe consumption), which also carefully measures the motivation for moderate and severe alcohol consumption among college students. Conclusions: The new scale is valid and reliable for assessing motivations for moderate and severe alcohol consumption in Mexican college students. This may be a valuable tool to design and evaluate interventions for the prevention of alcohol use among college students.