bluuebunny/crossref_metadata_2025 huggingface dataset:
A relação hierárquica de polígonos
Authors: Silva Angélica da Fontoura Garcia , Maria de Souza Oliveira Claudia
Published: February 2025

Esta pesquisa qualitativa analisa os conhecimentos profissionais sobre a relação hierárquica de figuras poligonais, demonstrados por professores dos anos iniciais que participaram de um grupo de estudos. Com base nas concepções de Shulman sobre os conhecimentos necessários ao ensino, investigou-se como a participação em sessões de estudo pode influenciar a compreensão geométrica dos professores. O grupo de estudos foi realizado em uma faculdade particular na Grande São Paulo e envolveu quatro pedagogas. Durante as sessões, foram explorados conceitos como a classificação hierárquica de quadrados, retângulos e losangos. Os resultados revelaram dificuldades iniciais das professoras em reconhecer e aplicar corretamente esses conceitos, manifestadas por surpresas ao descobrir que o quadrado pode ser classificado como retângulo e losango. Entretanto, as intervenções pedagógicas proporcionaram uma (re)significação desses conceitos, levando a uma compreensão mais profunda das propriedades geométricas. A reflexão crítica sobre a prática pedagógica também foi evidenciada, especialmente na adaptação das práticas de ensino. Conclui-se que a participação em grupos de estudos pode promover um aprimoramento significativo nos conhecimentos profissionais dos professores, destacando a importância de espaços formativos que incentivem a reflexão e a adaptação pedagógica contínua.
Mycobacterium tuberculosis infection may increase the degrees of malignancy in lung adenocarcinoma
Authors: Li Shanshan , Feng Mengru , Wang Fenghua , Liu Dongxu , Li Mingyan , Dai Jinlong , Yang Yan , Chai Yinghui , Chen Wen
Published: February 2025

Background

The early diagnosis and management of lung adenocarcinoma co-existing with tuberculosis (LAC-TB) presents significant challenges in clinical settings. This is compounded by a paucity of robust clinical evidence elucidating the interactions between these two conditions.

Methods

This study included 14 patients diagnosed with LAC-TB, with an equal distribution among those with pulmonary tuberculosis (TB) and those with peripheral lymph node TB. Controls included patients with simple TB and those with lung adenocarcinoma (LAC). Histopathologic examinations confirmed typical changes in each group. Immunohistochemistry analyzed immune markers, focusing on PD-L1, while genomic analysis identified differential mutant genes.

Results

Pathological evaluations showed that LAC-TB and LAC groups expressed TTF-1 and Napsin A in their adenocarcinoma specimens. Notably, a higher proportion of patients in the LAC-TB group had a Ki-67 proliferation index of ≥10%. Subsequent Molecular analyses revealed significant differences in RALGAPA1 gene expression, with the LAC-TB group also exhibiting a greater median count of missense mutations, single nucleotide polymorphisms, and overall mutations, suggesting a higher malignancy level than the LAC group. Additionally, the LAC-TB group showed an increased tumor mutational burden, indicating a potentially better response to immunotherapy. Immunohistochemical assessments indicated that Mycobacterium tuberculosis (MTB) infection correlated with reduced infiltration of T cells and CD4+ T cells, alongside an upregulation of PD-L1 expression in LAC. Notably, PD-L1 was strongly expressed in the TB granuloma and surrounding areas.

Conclusion

Our findings suggest that MTB infection may increase the malignancy of LAC, with the pronounced expression of PD-L1 in granuloma regions constituting a pivotal mechanism underlying this relationship.
Engaging in moral learning: veterans’ perspectives on how the moral dimensions of moral injury are addressed in one-on-one meetings with Dutch military chaplains
Authors: Mudde Laura , Schuhmann Carmen , Jacobs Gaby
Published: February 2025

Introduction

There is an increasing attention for the role of military chaplains (MCs) in supporting veterans with moral injury. However, research into how veterans experience the support of MCs remains scarce. Moreover, no studies to date have explored this question in a Dutch contex, while this is relevant as it can offer insight into what forms of care are helpful in predominantly secular societies.

Methods

This article presents a study from the Netherlands, involving 12 veterans. Using a longitudinal qualitative approach, we explored how the one-on-one conversations with MCs unfold over time.

Results

Our study shows that three types of moral questions underly experiences of moral injury. Veterans see the conversations with MCs as an opportunity to exchange thoughts and perspectives concerning these ongoing moral struggles, a process that we conceptualize as ‘moral learning’. Over time, we found 5 types of change in veterans’ experience of moral injury. The conversations with MCs helped veterans to: share their stories, thoughts and worries; grow personally; better understand and accept certain events; feel a stronger connection with others; critically engage with the Dutch Ministry of Defence.

Discussion

This study raises questions about the centrality of the morally injurious events in chaplaincy interventions that are described in the literature. It suggests that supporting veterans in dealing with questions about the good life and about the conduct of the military may be just as or even more important as reflecting on morally injurious events. Moreover, the study highlights the importance of engaging with seemingly mundane, everyday issues when addressing the moral dimensions of veterans’ struggles. This counters the focus on grand concepts like “forgiveness,” “acceptance,” “reconciliation,” “restitution” and “vindication” which are usually emphasized in the literature about chaplaincy in the context of moral injury. The study shows that it is through reflection on the everyday that these larger concepts gain relevance and meaning within veterans’ lives.
From Traits to Resilience: How Muslim Entrepreneurs Thrive in Times of Crisis
Authors: Trinanda Okki , Wardi Yunia , Evanita Susi
Published: February 2025

During the COVID-19, Muslim entrepreneurs had to adapt to remain resilient. These Muslim entrepreneurs can rely on entrepreneurial personality and skill traits to survive a crisis. This paper aims to expand the analysis of the several contributing factors to the resiliency of small- and medium-sized enterprises (SMEs) managed by Muslim entrepreneurs, as identified in various scholarly publications. Additionally, this study emphasises the significance of entrepreneurial personality and skill traits, investigates the mediating role of entrepreneurial orientation on the link between entrepreneurial traits and SME resilience, and explores the moderating effects of Muslim religiosity. Furthermore, it delves into specific Islamic principles such as “ikhtiar” (effort) and “tawakkal” (reliance on God), which contribute to the resilience of Muslim entrepreneurs. This study centres on Muslim business owners of small- and medium-sized enterprises (SMEs) in West Sumatra. The final sample obtained was 452 Muslim entrepreneurs. This research was conducted in 2021, at the peak of the COVID-19 pandemic. The findings indicate that entrepreneurial traits influence the resiliency of Muslim entrepreneurs in two distinct ways: directly and indirectly via entrepreneurial orientation. This research advances the entrepreneurial literature in three ways. First, research on entrepreneurial resilience is extended, considering the different dimensions of entrepreneurial personality and traits (negotiation skills, risk-taking, optimism, locus of control, and need for achievement). Second, this study explores the mediating role of entrepreneurial orientation on the relationship between entrepreneurial personality and skill traits toward entrepreneurial resilience. Finally, this study specifically discusses Muslim entrepreneurs as research respondents.
Influence of Vertical/Spanwise Offsets on Aerodynamic Performance of Double Serpentine Nozzles
Authors: Zhang Xuyong , Shan Yong , Zhang Jingzhou
Published: February 2025

Serpentine exhaust systems, known for their infrared and radar stealth capabilities, are becoming standard in flying wing aircraft. However, their design is constrained by the fuselage layout, causing potential offsets between the engine and nozzle exit axes. Developing a universal, high-performance serpentine nozzle design that accommodates various vertical and spanwise offsets (ΔZ, ΔY) presents a significant challenge. A series of ‘Preferred Nozzles’ and ‘Modest Nozzles’ were designed and numerically evaluated to assess the impact of these offsets on flow characteristics. Results show that the ‘Modest Nozzle’ exhibits a complex wave system and significant local losses in the constant-area extension section when subjected to ΔZ > 0.10D0 (D0 is the nozzle inlet diameter) or ΔY > 1.0D0, leading to a rapid thrust coefficient decrease. Vertical offsets significantly affect the Preferred Nozzle’s aerodynamic performance. When ΔZ = −0.50D0, a large vertical offset in the first ‘S’ section creates a recirculation zone, causing significant losses and reducing the thrust coefficient to around 0.96. When ΔZ ≥ −0.25D0, gas flow and wall shear stress distributions transition smoothly. When ΔZ ≥ 0.10D0, as the spanwise offset increases, the thrust coefficient experiences only a 0.17% loss and remains above 0.97.
Design and Analysis of a Micro–Electro-Mechanical System Thruster for Small Satellites and Low-Thrust Propulsion
Authors: Zhong Yubin , Ponti Fabrizio , Barato Francesco , Xia Guojun , Li Siyu , Zhang Xiao , Wu Tao
Published: February 2025

As a cost-effective and versatile solution, small satellites are increasingly being considered for space exploration. However, one of the major challenges in deploying small satellites for high total impulse missions, particularly deep space exploration, lies in the propulsion system. These missions face strict constraints in terms of volume, mass, and power budgets. This paper proposes a potential solution to this issue through the design of a bipropellant MEMS thruster. Simulation results indicate that this type of thruster offers superior performance compared to the monopropellant propulsion systems typically used in small satellite missions. Specifically, the bipropellant MEMS thruster demonstrates enhanced specific impulse and thrust-to-weight ratio, making it a promising alternative for small satellite propulsion in high total impulse missions.
A Study on the Management and Evolution of Land Use and Land Cover in Romania During the Period 1990–2022 in the Context of Political and Environmental Changes
Authors: Călina Jenica , Călina Aurel , Vangu Gheorghe Marian , Croitoru Alin Constantin , Miluț Marius , Băbucă Nicolae Ion , Stan Ion
Published: February 2025

Land use and land cover are the main anthropogenic factors that lead to the rapid and aggressive degradation of land and interfere with the functioning of ecosystems, especially through the expansion of urbanization and the reduction in forested areas. The purpose of this article is to identify sources of official data and to build an updated dataset upon which analysis algorithms can be applied. Basic analyses were performed on the dataset to study the evolution of land use and land cover in Romania during the period 1990–2022 and to analyze whether they align with and support national and European strategies for economic development. The study is based on the historical evolution of land use and land cover over the past 30 years, which has allowed us to identify current trends and to analyze potential future positive and negative effects, and facilitates the adoption of documented corrective measures. The methodology applied is based on the collection and analysis of historical data obtained mainly from the TEMPO database managed by the National Institute of Statistics and from the annual reports of the National Environmental Protection Agency, analyzing these data, identifying current trends, and issuing specific recommendations. Monitoring the dynamics of land use during the mentioned period allowed us to identify the most important developments with positive effects (a slight increase in forested areas and minimal variations in arable land) but mostly negative effects (a drastic reduction in areas occupied by vineyards and orchards, a decrease in areas occupied by water, and a concerning increase in unproductive land). The results highlight the importance of the immediate implementation of the national general cadastre system, as well as the importance of implementing appropriate policies, legislative provisions, and land management practices aimed at environmental protection and supporting sustainable development and biodiversity in general.
Enhancing Pear Tree Yield Estimation Accuracy by Assimilating LAI and SM into the WOFOST Model Based on Satellite Remote Sensing Data
Authors: Fan Zehua , Qin Yasen , Chi Jianan , Yan Ning
Published: February 2025

In modern agriculture, timely and accurate crop yield information is crucial for optimising agricultural production management and resource allocation. This study focused on improving the prediction accuracy of pear yields. Taking Alar City, Xinjiang, China as the research area, a variety of data including leaf area index (LAI), soil moisture (SM) and remote sensing data were collected, covering four key periods of pear growth. Three advanced algorithms, Partial Least Squares Regression (PLSR), Support Vector Regression (SVR) and Random Forest (RF), were used to construct the regression models of LAI and vegetation index in four key periods using Sentinel-2 satellite remote sensing data. The results showed that the RF algorithm provided the best results when inverting the LAI. The coefficients of determination (R2) were 0.73, 0.72, 0.76, and 0.77 for the four periods, respectively, and the root-mean-square errors (RMSE) were 0.21 m2/m2, 0.24 m2/m2, 0.18 m2/m2, and 0.16 m2/m2, respectively. Therefore, the RF algorithm was selected as the preferred method for LAI inversion in this study. Subsequently, the study further explored the potential of data assimilation techniques in enhancing the accuracy of pear yield simulation. LAI and SM were incorporated into the World Food Studies (WOFOST) crop growth model by four assimilation algorithms, namely, the Four-Dimensional Variational Approach (4D-Var), Particle Swarm Optimisation (PSO) algorithm, Ensemble Kalman Filter (EnKF), and Particle Filter (PF) in separate and joint assimilation, respectively. The experimental results showed that the assimilated model significantly improved the accuracy of yield prediction compared to the unassimilated model. In particular, the EnKF algorithm provided the highest accuracy in yield estimation with R2 of 0.82, 0.79 and RMSE of 1056 kg/ha and 1385 kg/ha when LAI alone and SM alone were assimilated, whereas 4D-Var performed the best when LAI and SM were jointly assimilated, with R2 as high as 0.88, and the RMSE reduced to 923 kg/ha. In addition, it was found that assimilating LAI outperformed assimilating SM when assimilating one variable, whereas joint assimilation of LAI and SM further enhanced the predictive performance beyond that of assimilating one variable alone. In summary, the present study demonstrated great potential to provide strong support for accurate prediction of pear yield by effectively integrating LAI and SM into crop growth models through data assimilation.
Remote Sensing Applications for Pasture Assessment in Kazakhstan
Authors: Kabzhanova Gulnara , Arystanova Ranida , Bissembayev Anuarbek , Arystanov Asset , Sagin Janay , Nasiyev Beybit , Kurmasheva Aisulu
Published: February 2025

Kazakhstan’s pasture, as a spatially extended agricultural resource for sustainable animal husbandry, requires effective monitoring with connected rational uses. Ranking number nine globally in terms of land size, Kazakhstan, with an area of about three million square km, requires proper assessment technologies for climate change and anthropogenic impact to track the pasture lands’ degradation. Remote sensing (RS)-based adaptive approaches for assessing pasture load, combined with field cross-checking of pastures, have been applied to evaluate the quality of vegetation cover, economic potential, service function, regenerative capacity, pasture productivity, and changes in plant species composition for five pilot regions in Kazakhstan. The current stages of these efforts are presented in this project report. The pasture lands in five regions, including Pavlodar (8,340,064 ha), North Kazakhstan (2,871,248 ha), Akmola (5,783,503 ha), Kostanay (11,762,318 ha), Karaganda (19,709,128 ha), and Ulytau (18,260,865 ha), were evaluated. Combined RS data were processed and the Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Fraction of Vegetation Cover (FCover), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Canopy Chlorophyll Content (CCC), and Canopy Water Content (CWC) indices were determined, in relation to the herbage of pastures and their growth and development, for field biophysical analysis. The highest values of LAI, FCOVER, and FARAR were recorded in the Akmola region, with index values of 18.5, 126.42, and 53.9, and the North Kazakhstan region, with index values of 17.89, 143.45, and 57.91, respectively. The massive 2024 spring floods, which occurred in the Akmola, North Kazakhstan, Kostanay, and Karaganda regions, caused many problems, particularly to civil constructions and buildings; however, these same floods had a very positive impact on pasture areas as they increased soil moisture. Further detailed investigations are ongoing to update the flood zones, wetlands, and swamp areas. The mapping of proper flood zones is required in Kazakhstan for pasture activities, rather than civil building construction. The related sustainable permissible grazing husbandry pasture loads are required to develop also. Recommendations for these preparation efforts are in the works.
GeNetFormer: Transformer-Based Framework for Gene Expression Prediction in Breast Cancer
Authors: Thaalbi Oumeima , Akhloufi Moulay A.
Published: February 2025

Background: Histopathological images are often used to diagnose breast cancer and have shown high accuracy in classifying cancer subtypes. Prediction of gene expression from whole-slide images and spatial transcriptomics data is important for cancer treatment in general and breast cancer in particular. This topic has been a challenge in numerous studies. Method: In this study, we present a deep learning framework called GeNetFormer. We evaluated eight advanced transformer models including EfficientFormer, FasterViT, BEiT v2, and Swin Transformer v2, and tested their performance in predicting gene expression using the STNet dataset. This dataset contains 68 H&E-stained histology images and transcriptomics data from different types of breast cancer. We followed a detailed process to prepare the data, including filtering genes and spots, normalizing stain colors, and creating smaller image patches for training. The models were trained to predict the expression of 250 genes using different image sizes and loss functions. GeNetFormer achieved the best performance using the MSELoss function and a resolution of 256 × 256 while integrating EfficientFormer. Results: It predicted nine out of the top ten genes with a higher Pearson Correlation Coefficient (PCC) compared to the retrained ST-Net method. For cancer biomarker genes such as DDX5 and XBP1, the PCC values were 0.7450 and 0.7203, respectively, outperforming ST-Net, which scored 0.6713 and 0.7320, respectively. In addition, our method gave better predictions for other genes such as FASN (0.7018 vs. 0.6968) and ERBB2 (0.6241 vs. 0.6211). Conclusions: Our results show that GeNetFormer provides improvements over other models such as ST-Net and show how transformer architectures are capable of analyzing spatial transcriptomics data to advance cancer research.
Artificial Intelligence Adoption in Public Administration: An Overview of Top-Cited Articles and Practical Applications
Authors: Babšek Matej , Ravšelj Dejan , Umek Lan , Aristovnik Aleksander
Published: February 2025

Background: The adoption of artificial intelligence (AI) in public administration (PA) has the potential to enhance transparency, efficiency, and responsiveness, ultimately creating greater public value. However, the integration of AI into PA faces challenges, including conceptual ambiguities and limited knowledge of the practical applications. This study addresses these gaps by offering an overview and categorization of AI research and applications in PA. Methods: Using a dataset of 3149 documents from the Scopus database, this study identifies the top 200 most-cited articles based on citation per year. It conducts descriptive and content analyses to identify the existing state, applications, and challenges regarding AI adoption. Additionally, selected AI use cases from the European Commission’s database are categorized, focusing on their contributions to public value. The analysis centers on three governance dimensions: internal processes, service delivery, and policymaking. Results: The findings provide a categorized understanding of AI concepts, types, and applications in PA, alongside a discussion of best practices and challenges. Conclusion: This study serves as a resource for researchers seeking a comprehensive overview of the current state of AI in PA and offers policymakers and practitioners insights into leveraging AI technologies to improve service delivery and operational efficiency.
Periprosthetic Infection of Transfibular Ankle Arthroplasties Managed with Implant Retention: Anatomical Limitations of Surgical Debridement
Authors: Hernández-Jiménez Pilar , Mancheño-Losa Mikel , Meléndez-Carmona María Ángeles , Mellado-Romero M Ángela , Brañas Patricia , Lumbreras-Bermejo Carlos , Vilá y Rico Jesús Enrique , Lora-Tamayo Jaime
Published: February 2025

Background: Prosthetic ankle infection is an infrequent and rarely explored prosthetic joint infection (PJI). In early infection, the debridement of implants inserted using the transfibular approach has certain peculiarities that pose a diagnostic and therapeutic challenge, the impact of which on infection prognosis is still unknown. Methods: This study prospectively collected all cases of transfibular prosthetic ankle infection at a tertiary hospital between 2014 and 2022, describing their demographic, clinical, microbiological, and management characteristics, along with the outcome over a long follow-up. This cohort was compared with a cohort of infected fibular plates without prostheses implanted in the same period of time. Results: Seven cases of ankle PJI were analysed, all of them implanted using a transfibular approach. They were all early prosthetic infections. The median age was 63 years (range 54–74) with a predominance of women (71.4%), three patients with diabetes (42.9%), and one patient with rheumatoid arthritis (14.3%). The aetiology was predominantly staphylococcal (4 [57.1%] methicillin-susceptible S. aureus and 1 [14.3%] S. epidermidis). All cases were managed with irrigation and debridement limited to the fibular plate, four of which failed (57%). By comparison, eleven cases of infected fibular plates without prostheses implanted were analysed. There were no differences in clinical, microbiological, or therapeutic management characteristics between the groups. Failure among infected fibular plates occurred in only two cases (18%). Conclusions: Debridement of infected transfibular ankle prostheses suggests a worse evolution than would be expected for other joint infections. This could be explained by the nature of the debridement, limited to the fibular component. Further detailed studies of the surgical possibilities in prosthetic ankle infections are necessary to improve the prognosis of these infections, given their impact on joint function.
Molecular Epidemiology of Clostridioides difficile Infections in Patients Hospitalized in 2017–2019 at the Central Teaching Hospital of Medical University of Lodz, Central Poland
Authors: Ptaszyńska Agata , Macieja Anna , Rosińska-Lewandoska Dominika , Bielec Filip , Machnicki Piotr , Brauncajs Małgorzata , Pastuszak-Lewandoska Dorota
Published: February 2025

Background/Objectives: Clostridioides difficile infection (CDI) represents a significant public health challenge globally, driven by its increasing prevalence, hypervirulent strains like ribotype 027 (RT027), and growing antibiotic resistance. This study aimed to evaluate the prevalence of RT027 and analyze molecular markers of vancomycin and metronidazole resistance in stool samples from CDI patients hospitalized in Poland between 2017 and 2019. Methods: A total of 200 stool samples from confirmed CDI cases were analyzed for the presence of RT027, vanA (vancomycin resistance), and nim (metronidazole resistance) genes. DNA was extracted, and a polymerase chain reaction (PCR) was conducted using specific primers. Statistical associations between RT027 and resistance genes were evaluated using chi-square tests and logistic regression. Results: RT027 was detected in 14% of samples. The vanA gene, indicative of vancomycin resistance, was found in 52.5% of samples, while the nim gene, associated with metronidazole resistance, was present in 1.5% of cases. Co-occurrence of RT027 with vanA was not statistically significant. The study revealed no significant association between RT027 and vanA. Also, no significant association was observed between RT027 and nim due to the latter’s low prevalence. Conclusions: This study highlights a concerning prevalence of vanA among CDI cases, indicating widespread vancomycin resistance and challenging current treatment guidelines. While RT027 prevalence was moderate, no significant associations with vancomycin or metronidazole resistance were observed. These findings emphasize the need for molecular surveillance and improved antimicrobial stewardship to manage CDI effectively.
Bioremediation of Non-Essential Toxic Elements Using Indigenous Microbes in Soil Following Irrigation with Treated Wastewater
Authors: Kekana Itumeleng Kgobokanang Jacob , Kgopa Pholosho Mmateko , Munjonji Lawrence
Published: February 2025

Treated wastewater (TWW) is recognised as an alternative irrigation source to mitigate global water scarcity for irrigation purposes. However, one of the challenges of using TWW as an irrigation source is the accumulation of non-essential toxic elements in soil post-irrigation. Thus, this study determined whether indigenous microbes that are tolerant to toxic elements would remediate non-essential toxic elements in contaminated soil following irrigation with TWW. Soil from a fallowed field at the University of Limpopo Experimental Farm was irrigated with TWW in pots for 12 weeks. After that, an incubation study was established to assess the abilities of Escherichia coli, Staphylococcus aureus, Aspergillus flavus, and Pseudomonas aeruginosa to remediate the contaminated soil over 12 weeks. Both water and soil samples (non-contaminated, contaminated, and remediated) were analysed for toxic elements: Aluminium (Al), Arsenic (As), Chromium (Cr), Cadmium (Cd), and Lead (Pb). Data were analysed using GenStat 20th edition. The results revealed that irrigation with TWW increased the concentration of non-essential toxic elements in soil by 110%, 31%, 31%, 31%, and 54% for Al, As, Cr, Cd, and Pb, respectively. The inoculation of soil with indigenous microbes led to the decline in the concentration of non-essential toxic elements in soil. Furthermore, soils inoculated with S. aureus led to a reduction in Cr to levels below those observed prior to irrigation with TWW. Overall, the findings of the study effectively convey that these indigenous microbes can be used for bioremediation.
Polycaprolactone-Based Fibrous Scaffolds Reinforced with Cellulose Nanocrystals for Anterior Cruciate Ligament Repair
Authors: Rocha Joana M. , Sousa Rui P. C. L. , Sousa Diogo , Tohidi Shafagh D. , Ribeiro Artur , Fangueiro Raul , Ferreira Diana P.
Published: February 2025

Anterior cruciate ligament (ACL) injuries pose significant challenges, driving the need for innovative repair strategies. Tissue engineering (TE) has emerged as a promising field for ACL injuries. Wet spinning is a filament production technique that enables precise control over filament alignment, diameter, and porosity, making it suitable for developing new scaffolds for ACL injuries. This study develops fibrous scaffolds using wet spinning of polycaprolactone (PCL) reinforced with cellulose nanocrystals (CNC) to enhance mechanical properties. Wet spinning was employed to fabricate fibrous scaffolds, utilizing PCL as the primary polymer due to its favorable biocompatibility and degradability. An automated collector was developed and optimized, which allowed the stretching of the PCL filaments to diameters as low as 30 µm. Several filaments were explored and characterized using SEM, TGA, and mechanical tests. The optimized PCL/CNC filaments were used to develop 3D braided structures that mimic ACL structure. The combination of wet-spun PCL/CNC filaments (with an optimized stirring method) and the braiding procedure allowed for fully biocompatible scaffolds that mimic both the structure and the mechanical properties of native ACL. Cytotoxicity and biocompatibility tests showed cell viability and proliferation values above 99% and 81%, respectively. These findings underscore the potential of CNC-reinforced PCL scaffolds as promising candidates for ACL repair, laying the groundwork for future biomedical applications.
A Novel Chipless Hybrid RFID Sensor for Metal Crack Detection
Authors: Kotriwar Yamini Devidas , Haq Mahmoodul , Deng Yiming
Published: February 2025

RFID technology has been widely researched and used for structural health applications because of its compact, wireless, and scalable nature. This technology is divided into chipped and chipless sensors. Chipped sensors are costly due to their chipped tags, have narrowband operations, and contribute to shortcomings in detection capability. Chipless tags provide real-time monitoring of cracks in harsh environments like high-temperature areas and high electromagnetic interference areas. This paper presents a design of a novel chipless hybrid circular-hexagon sensor that uses the frequency signature-based method for metal crack detection and characterization using wideband frequency. This sensor is small in size (16 mm × 16 mm × 1.4 mm) and easily mountable in hard-to-reach areas. It is a low-cost, passive chipless sensor that can wirelessly monitor the cracks in metallic structures. The radar cross-section of the chipless tag shows a shift in the resonant frequency of the tag under crack and no crack conditions. Key contributions of this work are that through simulations and experimental investigation, the tag is shown to be able to detect mm-scale cracks, validating the concept and correlating the presence and size of the cracks based on the shift in resonant frequencies in which a pair of Vivaldi antennas are used as a transmitter and receiver to connect to the VNA. The designed small sensor tag is tested in a benchtop setup with no prior calibration, imitating the real-time environment conditions for crack detection.
Multiscale Feature Modeling and Interpretability Analysis of the SHAP Method for Predicting the Lifespan of Landslide Dams
Authors: Huang Zhengze , Bai Yuqi , Liu Hengyu , Lin Yun
Published: February 2025

Landslide dams, formed by natural disasters or human activities, pose significant challenges for lifespan prediction, which is crucial for effective water conservancy management and disaster prevention. This study proposes a hybrid CNN–Transformer model optimized using the Improved Black-Winged Kite Algorithm (IBKA) aimed at improving the accuracy of landslide dam lifespan prediction by combining local feature extraction with global dependency modeling. The model integrates CNN’s local feature extraction with Transformer’s global modeling capabilities, effectively capturing the nonlinear dynamics of key parameters affecting landslide dam lifespan. The IBKA ensures optimal parameter tuning, which enhances the model’s adaptability and generalization, especially when dealing with small-sample datasets. Experiments utilizing multi-source heterogeneous datasets compare the proposed model with traditional machine learning and deep-learning approaches, including LightGBM, MLP, SVR, CNN–Transformer, and BKA–CNN–Transformer. The results show that the IBKA–CNN–Transformer achieves R2 values of 0.99 on training data and 0.98 on testing data, surpassing the baseline methods. Moreover, SHapley Additive exPlanations analysis quantifies the influence of critical features such as dam length, reservoir capacity, and upstream catchment area on lifespan prediction, improving model interpretability. This approach not only provides scientific insights for risk assessment and decision making in landslide dam management but also demonstrates the potential of deep learning and optimization algorithms in broader geological disaster management applications.
Industrialized Construction: A Systematic Review of Its Benefits and Guidelines for the Development of New Constructive Solutions Applied in Sustainable Projects
Authors: Rojas-Herrera Carlos , Martínez-Soto Aner , Avendaño-Vera Constanza , Carrasco Rodrigo Cancino , Barbato Natalia Reyes
Published: February 2025

In the scientific literature, it is highlighted that industrialized construction has significant comparative advantages over traditional construction, primarily in four indicators: (i) cost reduction, (ii) time reduction, (iii) increased energy performance, and (iv) reduced environmental impacts. However, there is no certainty about the range of variation of these indicators for these comparative advantages, creating uncertainty about the real impact of industrialized construction. In this work, through a systematic literature review based on PRISMA, 90 articles that met the selection criteria related to the four mentioned indicators were selected and analyzed. The results show that industrialized construction has comparative advantages over traditional construction but with a wide spectrum of variation in each of the indicators. In the cost indicator, reductions between 7% and 50% and increases between 26% and 72% are observed; in time, reductions between 9% and 50% and increases up to 32% are recorded, and reductions in energy demand between 20% and 90% are also reported. For the environmental indicators, data were only provided for projects in the design stage or for construction solutions on a scale, demonstrating the need to obtain indicators in the operational stage. It is concluded that although industrialized construction offers significant advantages, it is essential that new construction solutions consider contextual variations, initial investment, logistical challenges, and specialized labor to maximize their benefits.
Predictive Artificial Neural Networks as Applied Tools in the Remediation of Dyes by Adsorption—A Review
Authors: da Costa Mauro F. P. , Araújo Rinaldo dos Santos , Silva Ana R. , Pereira Luciana , Silva Glória M. M.
Published: February 2025

Environmental pollution has become one of society’s main concerns, which is why it is increasingly necessary to look for new effective remediation strategies. The applicability of artificial intelligence (AI) tools in different areas of knowledge has attracted the attention of the academic community due to their ability to process large datasets efficiently and deliver rapid, reliable predictions. Among them, artificial neural networks (ANNs) have stood out as some of the main aids in remediation and environmental control research. In this review, we systematically assess the current state of research on ANN applications in environmental remediation, particularly focusing on the remediation of dyes in water and wastewater treatment, through a comprehensive bibliographical analysis using the Methodi Ordinatio 2.0 methodology. This advanced methodology adds value compared to traditional systematic reviews by offering a structured and data-driven ranking of relevant publications based on impact, recency, and citation scores. The results demonstrate a clear trend toward adopting ANN models in water treatment processes, with the multilayer perceptron neural network emerging as the most widely used model due to its high predictability and adaptability. Key validation criteria for ANN models are discussed, and recent experimental results related to their application in adsorptive systems for wastewater treatment are highlighted. This review not only underscores the potential of ANN tools for improving environmental control but also identifies key challenges and emerging trends in this rapidly evolving field.
Abrasiveness and Bleaching Level of Toothpastes on Composite Resins: A Quantitative Analysis Using a Novel Brushing Simulator
Authors: Meseli Simge , Alkan Elif , Korkut Bora , Kanar Ozlem , Tagtekin Dilek
Published: February 2025

This study assessed the bleaching and abrasiveness levels of different kinds of toothpaste with various RDA values on nanohybrid and microhybrid composite samples using a novel Press-on Force-Guided brushing simulator. One hundred and forty disc-shaped samples were prepared using two nano-hybrid and three microhybrid composites and divided randomly into four subgroups (n = 7). The samples were immersed in a coffee solution for 144 h and then brushed using R.O.C.S. (Remineralizing Oral Care Systems) brand toothpaste with different RDA values [Sensitive Instant Relief (SIR), Sensation Whitening (SW), and their combination with PRO Polishing (PP) (once a week)] using a brushing simulator for 140, 280 and 560 strokes (140 strokes correspondence to one week of real-time brushing). The level of surface roughness and color change (ΔE) were measured before and after the simulated brushing. Color changes were evaluated in Photoshop CC software through ∆E00* values generated from before and after L, a*, b* parameters on sample photographs taken by a mobile dental photography tool. The surface structure of samples was measured before and after the brushing using a profilometer. The measurements were analyzed in SPSS V23 software by Analysis of Variance and the Bonferroni Test, and the level of significance was set at <0.05. Regarding ΔE values comparisons, there were no significant differences between the toothpastes after 2 weeks of brushing. SW (2.82 ± 1.24), SIR + PP (2.78 ± 0.98), and SW + PP (2.84 ± 1.22) values were found to be similar after one month of brushing (p < 0.007). Regarding surface roughness comparisons between the toothpastes, two-week and one-month brushing values were found to be similar and statistically rougher than the initial values. Using R.O.C.S. PRO Polishing with low-abrasive toothpaste may increase the whitening effect by enhancing color recovery.
Modeling and Estimation of Traffic Intensity in M/M/1 Queueing System with Balking: Classical and Bayesian Approaches
Authors: Kushvaha Bhaskar , Das Dhruba , Tamuli Asmita , Bora Dibyajyoti , Deka Mrinal , Choudhury Amit
Published: February 2025

This article focuses on both classical and Bayesian inference of traffic intensity in a single-server Markovian queueing model considering balking. To reflect real-world situations, the article introduces the concept of balking, where customers opt not to join the queue due to the perceived waiting time. The essence of this article involves a comprehensive analysis of different loss functions, namely, the squared error loss function (SELF) and the precautionary loss function (PLF), on the accuracy of the Bayesian estimation. To evaluate the performance of the Bayesian method with various priors such as inverted beta, gamma, and Jeffreys distributions, an assessment is performed using the Markov Chain Monte Carlo (MCMC) simulation technique. The efficacy of the Bayesian estimators is assessed by comparing the mean squared errors (MSEs).
Enhancing Air Quality in High-Density Cities: Investigating the Link Between Traffic-Related Air Pollution Distribution and Urban Ventilation
Authors: Zhou Mengge , Cao Xiaoqun , Qiu Wuyi , Guo Yanan
Published: February 2025

Urban traffic-related air pollution has emerged as a significant concern for the physical environment in densely populated urban areas. This study numerically investigates the dispersion of air pollutants and ventilation within typical urban blocks in Shanghai, considering the prevailing annual winds—northerly in winter (4.64 m/s) and easterly in summer (5.85 m/s). Multiple factors influence the dispersion of urban pollution. In this research, we examine the effects of viaducts and urban ventilation corridors, alongside the impact of urban parameters on pedestrian-level ventilation, by analyzing variations in building forms along residential streets in Shanghai. A novel approach for analyzing pollution dispersion is proposed, which involves performing a sensitivity analysis on the buffer radius and mapping various radii onto the C* parameter. The results indicate that: (1) enhancing air fluidity in regions with stagnant winds can be achieved by introducing vertical turbulence; (2) the prevailing wind direction, urban ventilation corridors, and urban permeability play a crucial role in determining the direction of pollutant dispersion at pedestrian levels in densely populated urban environments; (3) the contribution of pollutants released at ground level is significantly higher than those from viaducts at pedestrian height (248.58%). Drawing on both theoretical and experimental research, this study explores the spatial dispersion of air pollutants across various scales, including city-wide, block-level, and building-specific perspectives. The findings provide recommendations for the design of environmentally sustainable urban streets in residential areas.
Parameter Optimization, Morphological and Histological Characteristics of Accurate Bone Ablation by Femtosecond Laser: An In Vitro Study
Authors: Wang Yiyang , Liang Shanshan , Zhou Yongsheng , Yuan Fusong , Ye Hongqiang
Published: February 2025

The use of femtosecond laser for bone ablation has been demonstrated in numerous studies; however, the clinical application requires further optimization to meet safety, accuracy, and efficiency standards. This study aims to optimize the energy density parameter of a robot-controlled femtosecond laser surgical system for bone ablation by assessing temperature changes, ablation efficiency, and ablation effects. Furthermore, the morphological and histological characteristics of bone tissue were compared with those of conventional mechanical methods. The results indicated that a laser energy density of 1.05 J/cm2 was optimal for bone ablation, maintaining the bone surface temperature below 47 °C and achieving an ablation efficiency of 0.145 mm3/s. The deviations in cavity diameters were significantly smaller for the laser group (6.58 ± 18.09 μm) compared to the bur group (80.09 ± 45.45 μm, p < 0.001, N = 5 per group). Femtosecond laser ablation produced cleaner cavity margins with minimal bone debris accumulation. Additionally, the adjacent Volkmann and Haversian canals retained their normal morphology, indicating limited mechanical and thermal damage to the bone tissue. The robot-controlled femtosecond laser system demonstrated the potential for achieving safe, accurate, efficient, and clean bone ablation, offering promising prospects for clinical applications.
A Bifunctional Phosphoglucomutase/Phosphomannomutase from Thermococcus kodakarensis: Biophysical Analysis and Cryo-EM Structure
Authors: Naz Zahra , Rathore Ishan , Saleem Muhammad , Rahman Moazur , Wlodawer Alexander , Rashid Naeem
Published: February 2025

Phosphoglucomutase (EC 5.4.2.2., PGM), a key enzyme of glycogenolysis and glycogenesis, catalyzes the interconversion of glucose 1-phosphate and glucose 6-phosphate, whereas phosphomannomutase (EC 5.4.2.8., PMM) transfers the phosphate group from the 1′ to the 6′, or from the 6′ to the 1′ position in mannose phosphate. However, in the hyperthermophilic archaeon Thermococcus kodakarensis, a single gene, Tk1108, encodes a protein with both PGM and PMM activities. Here, we report biophysical analysis and the 2.45 Å resolution cryo-EM structure of this novel enzyme. Our results demonstrate a specific arrangement of the four subunits in the quaternary structure, displaying a distinct catalytic cleft required for the bifunctional activity at extremely high temperatures. To the best of our knowledge, this is the first biophysical characterization and cryo-EM structure elucidation of a thermostable, bifunctional PGM/PMM.
Thyroid Hormones in Early Pregnancy and Birth Weight: A Retrospective Study
Authors: La Verde Marco , De Franciscis Pasquale , Molitierno Rossella , Caniglia Florindo Mario , Fordellone Mario , Braca Eleonora , Carbone Carla , Varro Claudia , Cirillo Paolo , Scappaticcio Lorenzo , Bellastella Giuseppe
Published: February 2025

Background/Objectives: Various factors influence intrauterine growth and birth weight. We investigated the possible association between first-trimester pregnancy thyroid functions and birth weight. Methods: A retrospective observational study was conducted from 31 March 2021 to 30 September 2022. Ninety-eight low-risk pregnant women were evaluated. To obtain a homogeneous population, we included only patients with no maternal or fetal comorbidities. TSH, FT3, and FT4 levels in the first trimester and birth weight were recorded and analyzed. Results: The average maternal age was 33.37 years (IQR = 8.67), with a median BMI of 24.98 kg/m2 (IQR = 5.66). The average gestational week of pregnancy was 39.40 weeks (IQR = 2.10). Linear regression for birth weight according to TSH effects adjusted by sociodemographic and clinical factors did not show any associations between birth weight and TSH, age, ethnicity, BMI, smoking, or weight gain. Pregnancy duration was associated with birth weight: β = 172.027, p-value < 0.001. A negative significant correlation between FT3 and birth weight was found (beta = −118.901 95% CI: −222.942 to −14.859, p = 0.026). Age, ethnicity, BMI, smoking, and weight showed non-significant associations with birth weight. The FT3 scatterplot showed a negative correlation of FT3 levels with birth weight. Higher values of FT3 were associated with a low birth weight (R = −0.22, p = 0.029). Conclusions: Our study, focused on the first trimester, found a negative correlation between FT3 variations and birth weight.