bluuebunny/crossref_metadata_2025 huggingface dataset:
A Self-Sovereign Identity Blockchain Framework for Access Control and Transparency in Financial Institutions
Authors: Ou Hsia-Hung , Chen Guan-Yu , Lin Iuon-Chang
Published: January 2025

In recent years, with the development of blockchain technology and increased awareness of personal privacy, Self-Sovereign Identity (SSI) has become a hot topic. SSI gives customers more autonomy over their personal information, allowing them to control who can access and use their personal information. This provides customers with higher levels of privacy protection, as their data are no longer controlled by centralized institutions. To address the credit assessment needs of financial institutions, this paper proposes a Customer Self-Sovereign Identity and access-control framework (CSSI) based on SSI technology. Customers can securely store assessable assets and credit data on the blockchain using this framework. These data are then linked to a digital account address. With customer authorization, financial institutions processing loan applications can comprehensively evaluate customers’ repayment capabilities and conduct risk management by accessing this credit data. CSSI assists financial institutions in optimizing complex and repetitive processes involved in customer credit assessment and loan origination through SSI and access control, thereby reducing unnecessary risks.
Workforce Trends Among Canadian Medical Oncologists and Medical Oncology Trainees over Two Decades
Authors: Fundytus Adam , Cook Sarah , Yip Steven M. , Loewen Shaun K. , Hao Desiree
Published: January 2025

Background: Understanding oncology health human resources across Canada is critical to the delivery of quality cancer care. Little has been published about the medical oncology (MO) workforce and trainees; this study sought to characterize trends in the MO workforce and explore the relationship between medical oncologists and cancer incidence as a surrogate demand marker. Materials and Methods: Publicly available databases from the Canadian Medical Association, the Canadian Institute of Health Information, and the Canadian Post MD Education Registry were utilized to estimate the number, demographics, and regional distribution of practicing MOs and MO trainees between 1994 and 2020. Cancer incidence by province was obtained from Statistics Canada. To estimate changes in demand for, and supply of, medical oncology services over time, annual cancer incidence to MO provider ratios were calculated. Results: Between 1994 and 2020, annual cancer incidence nationally rose from 120,255 to 225,800 cases, while the number of MOs increased by 298%. Incident cancer case to medical oncologist (MO) ratio dropped from 749:1 to 352:1 in the same time. However, the MO workforce is aging; in 2020, 40% of providers were ≥50 years old versus 24% in 1994. Trends in Canadian MO trainees mirror MO trends. Ontario has the largest proportion of the country’s MOs (34% in 2020) and MO trainees (49%). Conclusions: Although the Canadian MO workforce has grown, more MO providers are nearing retirement age, which may influence future workforce trends. Ongoing monitoring of human resources in oncology is essential to ensure future demands for services are met.
Beyond Soil Health: The Microbial Implications of Conservation Agriculture
Authors: Santellanez-Arreola Kassandra , Martínez-Gamiño Miguel Ángel , Constante-García Vicenta , Arreola-Ávila Jesús , García-De la Peña Cristina , Siller-Rodríguez Quetzaly Karmy , Trejo-Calzada Ricardo , Nava-Reyna Erika
Published: January 2025

Conservation agriculture (CA) is a sustainable land management approach to improve soil quality while mitigating degradation. Although extensive information regarding the effect of CA on soil properties and microbiome is available, complete studies on the cumulative effect on specific interactions between soil parameters, crop productivity, and microbial communities over time are still lacking, mainly in arid regions. Thus, this study aimed to investigate the effects of no-tillage and residue retention over long- and short-term (24 and 3 years, respectively) periods. Six treatments were established in a maize–oat–triticale system from 1995 in a semiarid region: P + H—plow + harrow; H—harrow; MP—multi-plow (short-term); NT—no-tillage; NT33—NT + 33% residue surface cover (long-term); NT66—NT + 66% residue surface cover. Results indicated that CA improved soil quality by increasing soil organic matter (SOM), total carbon, and glomalin; it also enhanced microbial abundance, particularly fungi, and β-galactosidase activity. Nevertheless, conventional tillage practices led to SOM degradation and reduced crop yields. Principal component analysis revealed distinct groupings of treatments based on soil properties and microbial communities. Furthermore, changes could be detected from the short term. These findings highlight the importance of adopting sustainable agricultural practices to maintain soil health and ensure agricultural productivity in semi-arid regions.
The Status and Spatial Patterns of Poaching, Illegal Trade, and Human–Bear Conflict of Asiatic Black Bears in China, 2010–2020
Authors: Long Shuzhi , Li Sheng
Published: January 2025

Asiatic black bears (Ursus thibetanus) are a large carnivore, widely distributed in East, South, and Southeast Asia. However, they have experienced dramatic population decline across this range due to various anthropogenic threats. The great demand for bear parts in the black market exposes this species to intense pressure of being poached and then illegally traded. Meanwhile, the continuous expansion of anthropogenic land use results in the sharpening of human–bear conflicts. In this study, we conducted a comprehensive search and collected information of the poaching, illegal trade, and human–bear conflict events related to Asiatic black bears reported in China during 2010–2020. By systematically searching judicial adjudicative documents and news reports, we identified 351 (64 poaching, 221 illegal trade, and 90 conflict) events across the country. The results showed that Southwest China was a hotspot across all categories (41, 149 and 40 events, respectively). Bear paws were the most common type of bear parts found in illegal trade (52.1%), and the most frequently reported human–bear conflict form was human injury from bear attacks (at least 52 people injured and another 7 killed). By determining the status of black bears being poached, traded, and their conflicts with humans in China, these results will provide important insights into the further research and conservation of this iconic species.
Effect of Hyaluronic Acid Compared to Platelet-Rich Plasma as Adjuvants to Bone Marrow Mesenchymal Stem Cell Treatment of Knee Osteoarthritis: Analysis from Two Clinical Trials
Authors: Lamo-Espinosa José María , Suárez-López del Amo Álvaro , Núñez-Córdoba Jorge María , Blanco Juan F. , Sánchez Mikel , Moreno Victoria , Cabrera Marta , Granero-Moltó Froilán , Muiños Emma , Mazo Manuel M. , Crespo-Cullell Íñigo , Mora Gonzalo , Delgado Diego , Pompei-Fernández Orlando , Aquerreta Jesús Dámaso , Sola María Vitoria , Valentí-Azcárate Andrés , Andreu Enrique J. , López-Parra Miriam , Villarón Eva M. , Valentí-Nin Juan Ramón , Sánchez-Guijo Fermín , Prósper Felipe
Published: January 2025

Background: Bone marrow mesenchymal stem cell (BM-MSC) therapy has emerged as a safe and feasible treatment option for patients with knee osteoarthritis (OA). However, the role of adjuvants remains unclear. Our aim was to evaluate the clinical and radiological effects of hyaluronic acid (HA) in comparison to platelet-rich plasma (PRP) as adjuvants to 100 × 106 BM-MSCs in the treatment of knee OA. Methods: We used data from two randomized, parallel-group and controlled clinical trials which tested the efficacy of BM-MSC, previously published in 2016 (Clinical Trials.gov identifier NCT02123368, Nº EudraCT: 2009-017624-72) and 2020 (Clinical Trials.gov identifier NCT02365142. Nº EudraCT: 2011-006036-23). Results: Of the 34 patients included in the study, 24 had received 100 × 106 BM-MSCs plus PRP and 10 had received 100 × 106 BM-MSCs plus HA. On average, BM-MSC plus HA showed a higher improvement in VAS for pain [β-coefficient: −1.25; 95% confidence interval (95% CI):−2.20 to −0.30) than BM-MSC plus PRP (p = 0.01). We also observed that BM-MSC plus HA showed a greater improvement in all the WOMAC subscales scores and in the WOMAC overall score, compared to BM-MSC plus PRP, although these differences were not statistically significant. The Whole-Organ Magnetic Resonance Imaging Score (WORMS) at 12 months was more beneficial with 100 × 106 BM-MSCs plus HA (β-coefficient: −12.61; 95% CI: −19.71, −5.52) than with BM-MSC plus PRP (p = 0.001). Conclusions: The clinical and radiological outcomes after BM-MSC therapy for knee OA could differ according to the adjuvant employed. HA showed greater clinical effectiveness and fewer instances of articular degeneration than PRP as an adjuvant.
Integrative Path Planning for Multi-Rotor Logistics UAVs Considering UAV Dynamics, Energy Efficiency, and Obstacle Avoidance
Authors: Wu Kunpeng , Lan Juncong , Lu Shaofeng , Wu Chaoxian , Liu Bingjian , Lu Zenghao
Published: January 2025

Due to their high flexibility, low cost, and energy-saving advantages, applying Unmanned Aerial Vehicles (UAVs) in logistics is a promising field to achieve better social and economic benefits. Since UAVs’ energy storage capacity is generally low, it is essential to reduce energy costs to improve their system’s energy efficiency. In this paper, we proposed a novel trajectory planning framework to achieve the optimal trajectory with the minimum amount of energy consumption under the constraints of obstacles in a static environment. Based on UAV dynamics, we first derived the required power functions of multi-rotor UAVs in vertical and horizontal flight. To generate a feasible trajectory, we first adopted the A* algorithm to find a path and developed a safe flight corridor for the UAV to fly across by expanding the waypoints against the environment, and then proposed a time-discretization method to formulate the trajectory generation problem and solve it by the convex optimization algorithm. The optimization results in a static environment with obstacles demonstrated that the proposed method could efficiently and effectively obtain the optimal trajectory with the minimum amount of energy consumption under different allowed mission times and payloads. The framework would promote a variety of logistics UAV applications relevant to trajectory planning.
A Compact Stepped Frequency Continuous Waveform Through-Wall Radar System Based on Dual-Channel Software-Defined Radio
Authors: Li Xinhui , Ye Shengbo , Wang Zihao , Yuan Yubing , Liu Xiaojun , Fang Guangyou , Ma Deyun
Published: January 2025

Software-defined radio (SDR) has high flexibility and low cost. It conforms to the miniaturization, lightweight, and digitization trends in through-wall radar systems. Stepped frequency continuous waveform (SFCW) is commonly used in through-wall radar, which has high resolution and strong anti-interference ability. This article develops an SFCW through-wall radar system based on a dual-channel SDR platform. Without changing hardware structure and complicated accessories, a phase compensation method of solving the phase incoherence problem in a low-cost dual-channel SDR platform is proposed. In addition, this article proposes a wall clutter mitigation approach by means of singular value decomposition (SVD) and principal component analysis (PCA) framework for through-wall applications. This approach can process the wall clutter and noise efficiently, and then extract the target subspace to obtain location information. The experimental results indicate that the proposed windowing-based SVD-PCA approach is effective for the developed radar system, which can ensure the accuracy of through-wall detection. It is also superior to the traditional methods in terms of the image quality of range profiles or signal-to-noise ratio (SNR).
A Multi-Level Location-Aware Approach for Session-Based News Recommendation
Authors: Yu Xu , Cui Shuang , Wang Xiaohan , Zhang Jiale , Cheng Zihan , Mu Xiaofei , Tang Bin
Published: January 2025

Recently, personalized news recommendation systems have been widely used, which can achieve personalized news recommendations based on people’s different preferences, optimize the reading experience, and alleviate the problem of information overload. Among them, session-based news recommendation has gradually become a research hotspot as it can recommend news without requiring users to log in or when their reading history is difficult to obtain. The key to session-based news recommendation is to use short-term interaction data to learn user preferences. Existing models often focus on mining news content information in sessions and do not fully utilize geolocation information related to news and sessions, and there is also a certain inconsistency between their training objective and model evaluation metric, leading to suboptimal model recommendation performance. In order to fully utilize geolocation information, this paper proposes a multi-level location-aware approach for session-based news recommendation (MLA4SNR). Firstly, a news-location heterogeneous graph is constructed, and a graph element-wise attention network is proposed to mine high-order relationships between news and location. Secondly, a session feature extraction network based on Transformer is proposed to extract session features. Then, a session-location heterogeneous graph is constructed, and a graph element-wise attention network is used to mine high-order relationships between sessions and locations. Finally, a loss function based on the NDCG is used to train the model. Experimental results on a real news dataset show that MLA4SNR outperforms the baselines significantly.
Regulations and Policies on the Management of the End of the Life of Lithium-Ion Batteries in Electrical Vehicles
Authors: Meegoda Jay N. , Watts Daniel , Patil Udaysinh
Published: January 2025

Electrical vehicle (EV) batteries, particularly lithium-ion batteries, pose significant environmental challenges due to their hazardous components, the effects of initial building-material fabrication, and the difficulties of recycling and disposal. Policies and legislative strategies adopted by different governments to solve these issues are investigated in this manuscript, specifically based on circularity and resource use. Important steps are end-of-life management, safe disposal and transportation, avoidance of hazardous gas emissions, circularity, resource use, fire prevention, and expanded producer accountability. As of February 2024, New Jersey is the first and only state in the United States that has adopted a thorough legislative framework for EV battery management, therefore establishing a standard for other states. California passed major laws encouraging Zero-Emission Vehicle (ZEV) battery manufacture and recycling. Other states are likewise trying to show initiative by implementing and changing laws. Globally, the European Union is leading, while Canada, Australia, China, and others have created strong rules of regulation. This paper looks at and contrasts the environmental problems of lithium-ion electric vehicles with the legislative actions made by different nations and states to solve these problems. By means of a thorough examination of these policies, this paper seeks to present a whole picture of the current scene and the best techniques for lifetime management of EV batteries that can be embraced by different governments. In this manuscript, a comparison is made between two leading legislations, specifically that of the state of New Jersey and the European Union. To achieve the most beneficial outcome, it is the responsibility of stakeholders to promote rules; emphasize battery recycling, secure disposal, and extended producer accountability; promote innovation in sustainable battery technology; and try to build a pragmatic approach to battery management to mitigate environmental impacts based on a hybrid version of the legislations from the state of New Jersey and the European Union.
Assessing Geothermal Energy Production Potential of Devonian Geothermal Complexes in Lithuania
Authors: Memon Abdul Rashid , Pal Mayur
Published: January 2025

Lithuania is a Baltic European country which shares borders with Poland, Belarus, Latvia, and Russia and has a geothermal anomaly in the southwestern region. It consists of two main geothermal complexed, i.e., Devonian and Cambrian with a temperature of up to 40 °C (at a depth of 1000 m) and 96 °C (at a depth of 2000 m), respectively. The Devonian complex is composed of an unconsolidated sandstone formation with porosity and permeability in the range of 4–31% and 200 mD–6000 mD, respectively, and these make it a favorable candidate for a low enthalpy geothermal complex because of the high water production rates. This study evaluates the geothermal potential in the Devonian complex of the selected sites for commercial development. The study utilizes the mechanistic modelling approach including uncertainty management to forecast the water production rates and estimate the power generation capacity. Lastly, the study reveals that it is feasible to produce 6 MW to 60 MW of power from the existing vertical wells for a period of 25 years. Furthermore, reactive transport modelling also proves that there is dissolution and precipitation of the minerals near and away from the wellbore, respectively, which impairs the reservoir quality and further concludes that there is an effect of time on re-injection which should be considered to enhance the reservoir quality for future operations. In addition to that, no effect of the re-injection temperature of the produced water is observed.
From Crown Detection to Boundary Segmentation: Advancing Forest Analytics with Enhanced YOLO Model and Airborne LiDAR Point Clouds
Authors: Liu Yanan , Zhang Ai , Gao Peng
Published: January 2025

Individual tree segmentation is crucial to extract forest structural parameters, which is vital for forest resource management and ecological monitoring. Airborne LiDAR (ALS), with its ability to rapidly and accurately acquire three-dimensional forest structural information, has become an essential tool for large-scale forest monitoring. However, accurately locating individual trees and mapping canopy boundaries continues to be hindered by the overlapping nature of the tree canopies, especially in dense forests. To address these issues, this study introduces CCD-YOLO, a novel deep learning-based network for individual tree segmentation from the ALS point cloud. The proposed approach introduces key architectural enhancements to the YOLO framework, including (1) the integration of cross residual transformer network extended (CReToNeXt) backbone for feature extraction and multi-scale feature fusion, (2) the application of the convolutional block attention module (CBAM) to emphasize tree crown features while suppressing noise, and (3) a dynamic head for adaptive multi-layer feature fusion, enhancing boundary delineation accuracy. The proposed network was trained using a newly generated individual tree segmentation (ITS) dataset collected from a dense forest. A comprehensive evaluation of the experimental results was conducted across varying forest densities, encompassing a variety of both internal and external consistency assessments. The model outperforms the commonly used watershed algorithm and commercial LiDAR 360 software, achieving the highest indices (precision, F1, and recall) in both tree crown detection and boundary segmentation stages. This study highlights the potential of CCD-YOLO as an efficient and scalable solution for addressing the critical challenges of accuracy segmentation in complex forests. In the future, we will focus on enhancing the model’s performance and application.
The Effects of Malting and Extrusion on the Functional and Physical Properties of Extrudates from Malted Brown Rice and Pigeon Pea Flour Blends
Authors: Azuka Chinenye , Onwuchekwa Amarachi , Nwosu Adaora , Holmes Mel , Boesch Christine , Okafor Gabriel
Published: January 2025

Malted grains subjected to extrusion technology could have better quality indices than non-malted grains. The effects of malting and extrusion on the functional and physical qualities of foods extruded from malted brown rice and pigeon pea flour blends were investigated. Malted pigeon pea and brown rice flours were processed into blends, extruded under various conditions of feed moisture levels (15–20), feed compositions (8–30%), and barrel temperatures (100–130 °C), and analyzed using Response Surface Methodology with a Box–Behnken design. The impacts of malting and extrusion were assessed on the following functional qualities: bulk density, rheology, swelling capacity, water absorption capacity, and solubility. The physical quality assessment included a 2-D photographic representation of the extrudates, a microscopic assessment of their internal structure, expansion index, color parameters (L*, a*, b*), and alterations in the color index. Increased feed moisture, malted pigeon pea, and decreased barrel temperature resulted in a higher bulk density (0.72 to 0.84 g/cm3) of the extrudates. There was a decrease in water absorption capacity (6.82–4.49%) with an increase in barrel temperature above 100 °C. All the samples showed a decrease in viscosity with increasing shear rate. At low barrel temperatures, feed compositions, and feed moistures, extrusion led to increases in the expansion index (3.5 to 12.94) and the color lightness (66.83–81.71) of the extrudates. Samples with a higher proportion of malted brown rice showed a higher expansion index, lower bulk density, and lighter color of the extrudates.
Salmon Consumption Behavior Prediction Based on Bayesian Optimization and Explainable Artificial Intelligence
Authors: Wu Zhan , Cha Sina , Wang Chunxiao , Qu Tinghong , Zou Zongfeng
Published: January 2025

Predicting seafood consumption behavior is essential for fishing companies to adjust their production plans and marketing strategies. To achieve accurate predictions, this paper introduces a model for forecasting seafood consumption behavior based on an interpretable machine learning algorithm. Additionally, the Shapley Additive exPlanation (SHAP) model and the Accumulated Local Effects (ALE) plot were integrated to provide a detailed analysis of the factors influencing Shanghai residents’ intentions to purchase salmon. In this study, we constructed nine regression prediction models, including ANN, Decision Tree, GBDT, Random Forest, AdaBoost, XGBoost, LightGBM, CatBoost, and NGBoost, to predict the consumers’ intentions to purchase salmon and to compare their predictive performance. In addition, Bayesian optimization algorithm is used to optimize the hyperparameters of the optimal regression prediction model to improve the model prediction accuracy. Finally, the SHAP model was used to analyze the key factors and interactions affecting the consumers’ willingness to purchase salmon, and the Accumulated Local Effects plot was used to show the specific prediction patterns of different influences on salmon consumption. The results of the study show that salmon farming safety and ease of cooking have significant nonlinear effects on salmon consumption; the BO-CatBoost nonlinear regression prediction model demonstrates superior performance compared to the benchmark model, with the test set exhibiting RMSE, MSE, MAE, R2 and TIC values of 0.155, 0.024, 0.097, 0.902, and 0.313, respectively. This study can provide technical support for suppliers in the salmon value chain and help their decision-making to adjust their corporate production plan and marketing activities
Fractional Mathieu Equation with Two Fractional Derivatives and Some Applications
Authors: Salem Ahmed , Malaikah Hunida , Alsobhi Naif
Published: January 2025

The importance of this research comes from the several applications of the Mathieu equation and its generalizations in many scientific fields. Two models of fractional Mathieu equations are provided using Katugampola fractional derivatives in the sense of Riemann-Liouville and Caputo. Each model contains two fractional derivatives with unique fractional orders, periodic forcing of the cosine stiffness coefficient, and many extensions and generalizations. The Banach contraction principle is used to prove that each model under consideration has a unique solution. Our results are applied to four real-life problems: the nonlinear Mathieu equation for parametric damping and the Duffing oscillator, the quadratically damped Mathieu equation, the fractional Mathieu equation’s transition curves, and the tempered fractional model of the linearly damped ion motion with an octopole.
Advances in 3D and 4D Printing of Gel-Based Foods: Mechanisms, Applications, and Future Directions
Authors: Qin Zhou , Li Zhihua , Huang Xiaowei , Du Liuzi , Li Wenlong , Gao Peipei , Chen Zhiyang , Zhang Junjun , Guo Ziang , Li Zexiang , Liu Baoze , Shen Tingting
Published: January 2025

This review examines recent advancements in gel-based 3D and 4D food-printing technologies, with a focus on their applications in personalized nutrition and functional foods. It emphasizes the critical role of tunable rheological and mechanical properties in gels such as starch, protein, and Pickering emulsions, which are essential for successful printing. The review further explores 4D food printing, highlighting stimuli-responsive mechanisms, including color changes and deformation induced by external factors like temperature and pH. These innovations enhance both the sensory and functional properties of printed foods, advancing opportunities for personalization. Key findings from recent studies are presented, demonstrating the potential of various gels to address dietary challenges, such as dysphagia, and to enable precise nutritional customization. The review integrates cutting-edge research, identifies emerging trends and challenges, and underscores the pivotal role of gel-based materials in producing high-quality 3D-printed foods. Additionally, it highlights the potential of Pickering emulsions and lipid gels for expanding functionality and structural diversity. Overall, this work provides a comprehensive foundation for advancing future research and practical applications in gel-based 3D and 4D food printing.
The Development and Psychometric Properties of Malay Language Child Oral Health Impact Profile—Short Form 19 (ML COHIP-SF 19)
Authors: Ismail Noor Rashidah , Tan Su Keng , Abu Bakar Norashikin , Hasmun Noren Nor
Published: January 2025

Background/Objectives: The Child Oral Health Impact Profile—Short Form 19 (COHIP-SF 19) is widely used to measure the oral health-related quality of life (OHRQoL) of children and adolescents. The current study aimed to validate the Malay language version of the COHIP-SF19 (ML COHIP-SF 19) and to assess its psychometric properties among Malaysian children/adolescents. Methods: Children aged from 9 to 16 years attending the Faculty of Dentistry, Universiti Teknologi MARA (UiTM) participated in this study. The original English version of the COHIP-SF 19 was translated using forward- and back-translation. The psychometric properties of the final version were tested for reliability and validity using Cronbach’s alpha, a non-parametric Spearman’s correlation test, and confirmatory factor analysis (CFA). Results: A total of 252 children aged from 9 to 16 years (mean age = 11.33 ± 1.87 years) self-completed the ML-COHIP-SF 19. The total scores of the ML COHIP-SF 19 ranged from 20 to 75 (mean = 55.67 ± 10.45) with an internal consistency (α) of 0.81. Convergent validity showed a fair correlation between self-perceived oral health rating and total ML COHIP-SF 19 scores, as well as the socio-emotional well-being subscale scores (rs = 0.38–0.42, p < 0.01). Conclusions: The ML COHIP-SF 19 demonstrated reliable psychometric properties and acceptable four-factor model fits, indicating that it is a valid tool to measure the OHRQoL of Malaysian children aged from 9 to 16 years.
Implementation of Ecological Sustainability Goals in Public Industrial Heritage Facilities in Europe
Authors: Szromek Adam R.
Published: January 2025

Industrial heritage tourism has been subject to increasing visitor interest, making Europe’s old factories, mines, and steelworks into attractive tourist installations. However, these facilities, like all other market players, impact the environment, and, therefore, their management should take into account achieving sustainable development goals. The purpose of this article is to identify key sustainability measures taken by public industrial heritage tourism facilities in Europe to protect the environment. This article discusses the results of a survey of administrators of public industrial heritage facilities in Europe. This research was carried out using the Computer Assisted Web Interview technique, sending a research questionnaire to facilities associated with the European Route of Industrial Heritage. The results indicate that these entities are taking numerous measures to implement environmental sustainability patterns, particularly in the areas of waste segregation, pollution and waste generation reduction, and low energy consumption in equipment purchases. Unfortunately, the survey shows that many of the stated actions are not being implemented, as only one in four managers has implemented a formal program related to the implementation of at least some sustainability principles or training conducted in this regard. Managers of industrial heritage sites also advocate for increased national and international cooperation between sites. The author also draws attention to the need to acquire green technologies and communicate the effects of these activities to stakeholders.
Genome-Wide Analysis of the ABCB Family and Its Expression in Adventitious Root Development of Paeonia ostii
Authors: Shang Wenqian , Cui Can , Liu Xi , Meng Weihao , Qiu Yongjie , Sun Yuke , Shen Yuxiao , Liu Weichao , Wang Zheng , He Songlin , Song Yinglong , Shi Liyun
Published: January 2025

Tree peony (Paeonia ostii T. Hong et J. X. Zhang) is an important medicinal and ornamental plant. It would be useful to propagate this plant in tissue culture, but it is difficult to induce root formation. Auxin plays a pivotal role in adventitious root formation, and ABCB transporter proteins are involved in auxin transport. To elucidate the function of the ABCB transporter family in P. ostii, we identified members of the ABCB gene family in the P. ostii genome and analyzed the functional characteristics of the putative proteins. In total, 29 ABCB genes were identified in P.ostii, distributed on five chromosomes. In a phylogenetic analysis, the PoABCBs were grouped into four subfamilies, with the largest being Subfamily I, characterized by their MDR structure. PoABCB genes in the same subfamily exhibited similar intron/exon arrangements and motif composition. The promoters of PoABCBs contained cis-acting elements associated with the photoresponse and hormone signaling. qRT-PCR analyses showed that, after treatment of tissue-cultured P. ostii seedlings with auxin, five PoABCB gene family members (PoABCB6, PoABCB10, PoABCB11, PoABCB12, and PoABCB16) were significantly upregulated during adventitious root development. These genes may play roles in the auxin response and adventitious root development of P. ostii in vitro.
Surveys of Knowledge and Awareness of Plastic Pollution and Risk Reduction Behavior in the General Population: A Systematic Review
Authors: Caminiti Caterina , Diodati Francesca , Puntoni Matteo , Balan Denisa , Maglietta Giuseppe
Published: January 2025

Individual attitudes and knowledge can predict pro-environmental behaviors. Public surveys, therefore, can provide precious information, which can guide sensitization interventions. In this systematic review, we searched Medline and Embase, with no language or date restrictions, for surveys designed to measure in the general population the level of knowledge about different types of plastics, the risks associated with plastic pollution, and awareness of actions to reduce them. Survey tools were analyzed following the guide of Burns and Kho, and study methodological quality was assessed via the Appraisal Tool for Cross-Sectional Studies. We included 17 articles published from 2019 to 2024, mostly concerning European populations. The tools comprised a median of 13 items (range 7–50), and very differently formulated questions. Overall, 13/17 (76.5%) study questionnaires received less than 50% (<3.5) of the maximum possible score. The remaining four questionnaires obtained intermediate scores (between 3.5 and 5.3) indicating moderate quality. Most studies did not employ the appropriate cross-sectional survey methodology, only two studies statistically justified sample sizes, only three reported a sampling frame, and only two described a selection process that appears to be representative. In most cases, the instruments were not validated, and the statistical significance of key variables was not provided. The many shortcomings highlighted in this review emphasize the urgent need for methodological rigor when conducting survey studies, which are essential tools for public health.
Atrial Fibrillation as a Geriatric Syndrome: Why Are Frailty and Disability Often Confused? A Geriatric Perspective from the New Guidelines
Authors: Testa Crescenzo , Salvi Marco , Zucchini Irene , Cattabiani Chiara , Giallauria Francesco , Petraglia Laura , Leosco Dario , Lauretani Fulvio , Maggio Marcello
Published: January 2025

Atrial Fibrillation can be considered a geriatric syndrome for its prevalence and incidence, its impact on patients’ quality of life, and Health Systems’ economy. The European Society of Cardiology 2024 guidelines introduce a recommendation for maintaining vitamin K antagonist therapy over switching to direct oral anticoagulants in clinically stable elderly patients with atrial fibrillation. This article explores the implications of this indication for the geriatric clinical context. The focus will also be devoted to the need for the stratification of older patients with atrial fibrillation, making an appropriate distinction between frailty and disability.
Can 12-Week Resistance Training Improve Muscle Strength, Dynamic Balance and the Metabolic Profile in Older Adults with Type 2 Diabetes Mellitus?
Authors: de Seixas Soares André Luiz , Brech Guilherme Carlos , Machado-Lima Adriana , dos Santos Joselma Rodrigues , D’ Andréa Greve Júlia Maria , Grecco Marcus Vinicius , Afonso Mara , Sousa Juliana Cristina , Rodrigues Ariana Tito , dos Santos Lino Matheus Henrique , Silva Vanderlei Carneiro , de Souza Carneiro Patricia Nemara Freitas , Evangelista Alexandre Lopes , Davis Catherine L. , Castilho Alonso Angelica
Published: January 2025

The present study aimed to evaluate the effects of 12-week resistance training (RT) on muscle strength, dynamic balance, glycemic control and the lipid profile. Methods: The Laboratory of Movement Studies in the University of São Paulo, Brazil, developed this longitudinal study between 2021 and 2023. It assessed 62 males with type 2 diabetes mellitus pre and post an RT protocol. The participants, who were 69.8 (±3.9) years old, took part in a 12-week twice-weekly RT program. Three sets of eight to twelve repetitions each were executed for eight exercises targeting the large muscle groups. The intensity was set between 7 and 8 out of 10 for perceived effort, according to the Omni Resistance Exercise Scale. All participants were evaluated pre and post in knee extensor and flexor strength by isokinetic dynamometry, handgrip strength by manual dynamometry and dynamic postural balance by a force platform, as well as blood tests to determine the lipid and glycemic profiles. For comparison, paired t or Wilcoxon tests were used at an alpha of 5%. Results: There was an improvement in muscular strength by handgrip restricted to the non-dominant side (p = 0.033) and for the bilateral knee flexors (p < 0.001) and extensors (p < 0.001), as determined by isokinetic dynamometry. There was no improvement in dynamic postural balance, glycemic control or lipid control. Conclusions: The 12-week RT promoted improved muscle strength in knee extension and flexion and non-dominant grip pressure but did not affect dynamic balance, glycemic control or the lipid profile.
Digital Transformation and Location Data Interoperability Skills for Small and Medium Enterprises
Authors: De Martino Monica , Martirano Giacomo , Quarati Alfonso , Varni Francesco , Toscano Domínguez Mayte
Published: January 2025

In the dynamic landscape of digital transformation, data interoperability—particularly for location data—is a key enabler of operational efficiency, innovation, and collaboration for Small and Medium Enterprises (SMEs). Despite their strategic importance, SMEs face significant challenges in integrating and utilizing location data, which puts them at a disadvantage in the increasingly digital global market. As part of the European DIS4SME project, this study proposes a methodology to address these challenges, characterized by the rigorous development of a training curriculum aimed at upskilling and retraining SME owners and employees. The curriculum emphasizes practical learning through real business case studies and is aligned with European policies such as the INSPIRE Directive and the European Data Strategy. Accordingly, ten courses were designed, forming a modular and hierarchical curriculum that addresses SMEs’ diverse needs. Initial feedback from the first managers’ pilot implementation suggests that the structured training program effectively equips managers with strategic decision-making skills to address location data interoperability challenges.
A Joint Analysis of RNA-DNA and DNA-DNA Interactomes Reveals Their Strong Association
Authors: Zvezdin Dmitry S. , Tyukaev Artyom A. , Zharikova Anastasia A. , Mironov Andrey A.
Published: January 2025

At the moment, many non-coding RNAs that perform a variety of functions in the regulation of chromatin processes are known. An increasing number of protocols allow researchers to study RNA-DNA interactions and shed light on new aspects of the RNA–chromatin interactome. The Hi-C protocol, which enables the study of chromatin’s three-dimensional organization, has already led to numerous discoveries in the field of genome 3D organization. We conducted a comprehensive joint analysis of the RNA-DNA interactome and chromatin structure across different human and mouse cell lines. We show that these two phenomena are closely related in many respects, with the nature of this relationship being both tissue specific and conserved across humans and mice.
Steady Moderate Exercise Confers Resilience Against Neurodegeneration and Neuroinflammation in a Mouse Model of Parkinson’s Disease
Authors: Palasz Ewelina , Gasiorowska-Bien Anna , Drapich Patrycja , Niewiadomski Wiktor , Niewiadomska Grazyna
Published: January 2025

Intensive aerobic exercise slows the progression of movement disorders in Parkinson’s disease (PD) and is therefore recommended as an important component of treatment for PD patients. Studies in animal models of PD have shown that vigorous exercise has neuroprotective effects, and emerging evidence suggests that it may be a disease-modifying treatment in humans. However, many people with PD may not be able to participate in vigorous exercise because of multiple medical conditions that severely limit their physical activity. In this study, we have shown that chronic MPTP treatment in sedentary mice resulted in loss of dopaminergic neurons in the SNpc, decreased levels of neurotrophins, BDNF and GDNF, and increased levels of inflammatory markers and pro-inflammatory changes in immunocompetent cells. Moderate exercise, initiated both before and after chronic MPTP treatment, significantly attenuated the loss of dopaminergic neurons and increased BDNF and GDNF levels even above those in sedentary control mice. No signs of inflammation were observed in MPTP-treated mice, either when training began before or after MPTP treatment. Training induced beneficial changes in the dopaminergic system, increased levels of neurotrophins and suppression of inflammation were similar for both steady moderate (present data) and intense training (our previously published data). This suggests that there is a kind of saturation when the percentage of rescued dopaminergic neurons reaches the highest possible value, and therefore further increases in exercise intensity do not enhance neuroprotection. In conclusion, our present results compared with the previous data show that increasing exercise intensity beyond the level used in this study does not increase the neuroprotective effect of aerobic training in a mouse model of Parkinson’s disease.
EquiFlowShard: A Blockchain Sharding Protocol with Optimized Account Distribution
Authors: Chen Yemin , Wu Yongdong , Li Tong
Published: January 2025

Blockchain sharding is a scalable solution for distributed ledgers, but may be hindered due to cross-shard transactions and uneven workload distribution. This paper presents EquiFlowShard, an advanced blockchain sharding protocol designed to improve robustness and enhance cross-shard efficiency. Specifically, by employing Optimized Account State Distribution Algorithm (OSADA), EquiFlowShard dynamically assigns and segments account states, so as to minimize cross-shard transaction volume and balance shard workloads. In addition, the protocol introduces the SFlow mechanism to facilitate secure and consistent state transfers and a Smooth Transition scheme to mitigate performance impacts during state reconfigurations. Evaluation results confirm that EquiFlowShard outperforms existing benchmark protocols in terms of throughput, transaction confirmation latency, and cross-shard transaction ratio, demonstrating its effectiveness in dynamic blockchain environments.
An Intelligent Model for Parametric Cognitive Assessment of E-Learning-Based Students
Authors: Javed Muhammad Saqib , Aslam Muhammad , Khurshid Syed Khaldoon
Published: January 2025

In an e-learning environment, question levels are based on Bloom’s Taxonomy (BT), which normally classifies a course’s learning objectives into diverse levels. As per the previous literature, the assessment procedure lacks accuracy and results in redundant keywords when automatically assigning Bloom’s taxonomic categories using a keyword-based approach. These assessments are considered challenging as far as e-learning-based students are concerned, as the text feed is the only instrumental testing part. Student assessments are limited to multiple-choice questions and lack an evaluation of students’ text-based input. This paper proposes a natural-language processing-based intelligent deep-learning model that relies on parametric cognitive assessments. By applying class labels to students’ descriptive responses, the proposed approach helps classify a variety of questions mapped to BT levels. The first contribution of this work is a compiled dataset of the assessment items from 300 students, who were tested on 20 questions at each level. Each level is calculated by combining the responses from all students, resulting in 6000 questions per cognitive level for a total of 36,000 records. The second contribution is the development of an intelligent model based on a recurrent neural network (RNN), which not only predicts Bloom’s question level but also learns it over further iterations. The students’ text-based answers are accessed to gauge performance using a refined question pool gathered through the RNN model. The student dataset is mapped and tested using the NLP model for further classification of the students’ cognitive levels. This assessment is related to the formulation of questions and the compilation of Episode 2 for assessment. The third contribution is the comparison and demonstration of the improvements in learning using a parametric cognitive-based assessment in an episodic manner. Improved classification accuracy was attained by adding more processing layers based on the iterative, RNN-based learning model to achieve the vital threshold difference. The cognitive based questions pool classification achieved by RNN results in 98% accuracy. The resulting student assessments, based on performance, increased to an accuracy ratio of 92.16% and a precision ratio of 92.36% at an aggregate level based on the Random Forest classifier. We claim that our work serves as an initiative for effective student evaluations in interactive and e-learning-based environments when handling other types of inputs, like mathematical, graphical, and multimodal inputs.
Genetic Polymorphism of Zinc Transporter-8 Gene (SLC30A8), Serum Zinc Concentrations, and Proteome Profiles Related to Type 2 Diabetes in Elderly
Authors: Sirivarasai Jintana , Tristitworn Pimvaree , Shantavasinkul Prapimporn Chattranukulchai , Roytrakul Sittiruk , Chansirikarnjana Sirintorn , Ruangritchankul Sirasa , Chanprasertyothin Suwannee , Charernwat Piangporn , Panpunuan Pachara , Sura Thanyachai , Sritara Piyamitr
Published: January 2025

Background and Aims: Older adults are particularly susceptible to type 2 diabetes mellitus (T2DM) due to factors such as age-related insulin resistance, decreased physical activity, and deficiency of micronutrients, especially zinc. Studies have suggested that the risk allele of the zinc transporter 8 gene (SLC30A8) single-nucleotide poly-morphism (SNP) rs13266634 may contribute to T2DM susceptibility in addition to the complex protein interactions and alterations in the protein expressions and modifications associated with T2DM. This study was implemented to study the associations between SLC30A8 polymorphism, serum zinc levels, and the profiles of proteins differentially expressed in nondiabetic (n = 116) and prediabetic/diabetic (n = 149) subjects. Methods: SNP genotyping using TaqMan® assay and proteomic analysis by LC-MS/MS were performed in each group. Results: The results showed a higher risk of diabetes in individuals with the risk genotype CC accompanied by a low serum zinc level than in those with other genotypes. Profiles of proteins differentially expressed between the groups were identified and shown to be particularly associated with zinc-related functions, zinc transporter 8, and glucose metabolism. Proteins exclusively expressed in prediabetes/diabetes were assigned to a Reactome pathway related to zinc transporter and insulin processing. Conclusions: Our findings suggest that individuals carrying at least one copy of SLC30A8 rs13266634 accompanied by a low serum zinc level might be susceptible to T2DM, which could be due to alterations in insulin signaling and zinc metabolism. Understanding this relationship deepens our understanding of the genetic and molecular mechanisms underlying T2DM risk, offering potential targets for therapeutic intervention and prevention strategies.