bluuebunny/crossref_metadata_2025 huggingface dataset:
The Critical Influence of Wire Diameter and Bending for Orthodontic Wire Integration—New Insights for Maxillary Movements (In Vitro Study)
Authors: Moncher Michael , Othman Ahmed , Schneider Benedikt , Fahim Fady , von See Constantin
Published: December 2024

Background: Traditional methods for palatal expansion using fixed appliances often face limitations in comfort and aesthetics. In comparison, aligner therapy has limitations, particularly regarding maxillary expansion. The aim of this study is to examine the biomechanical properties regarding the wire diameter and bending of different stainless steel wires to evaluate their potential for incorporation into maxillary aligner therapy. Materials and Methods: Three rectangular stainless steel wires (0.016″ × 0.022″, 0.017″ × 0.025″, and 0.019″ × 0.025″) were tested for mechanical expansion forces in the intermolar region, comparing non-tooth-shaped bent wires (A groups) and tooth-shaped bent wires (B groups). Using a Z010 testing machine (ZwickRoell GmbH and Co. KG, Ulm, Germany), expansion forces were measured at 1 mm intervals over a 5 mm distance, with 15 samples analyzed per group. Statistical analyses included the Shapiro–Wilk test for normal distribution, the Mann–Whitney U test, which revealed significant results (U = 225, p < 0.001), and the Kruskal–Wallis test, which indicated significance (H = 39.130; df = 2; p < 0.001). Results: Tooth-shaped bent wires exhibited significantly lower expansion forces than non-tooth-shaped bent wires for all tested wire types. This difference was most notable in wires with larger transverse profiles (0.019″ × 0.025″), where the tooth-shaped bent wires displayed a marked reduction in mechanical load capacity. Specific force measurements for non-tooth-shaped wires ranged from 760.61 ± 79.51 mN at 1 mm of deformation to 2468.46 ± 66.27 mN at 5 mm of deformation, while tooth-shaped wires ranged from 116.80 ± 3.74 mN to 1979.49 ± 23.23 mN. Conclusions: These findings suggest that non-tooth-shaped bent wires offer a more efficient and uniform expansion potential for maxillary movements due to their stable elastic properties. Clinically, integrating non-tooth-shaped stainless steel wires into aligner therapy may provide a viable method for maxillary expansion, supporting both first- and second-order movements in orthodontic treatment. Further research is needed to explore the integration of such wires for effective maxillary expansion in aligner therapy.
Production of High Specific Surface Area Activated Carbon from Tangerine Peels and Utilization of Its By-Products
Authors: Kang Da-Jung , Kim Kyung-Woo , Hong Bum-Ui , Park Jung-Eun
Published: December 2024

Biomass waste, generated globally in vast quantities, represents an underutilized yet highly valuable resource for advanced material production. This study highlights a novel valorization pathway for waste tangerine peels, sourced from Jeju Island, South Korea, by converting them into high-performance activated carbon (T-AC) with exceptional pore characteristics, specifically designed for volatile organic compound (VOC) removal. Utilizing a unique combination of hydrothermal carbonization (HTC) and dry carbonization (DC) processes, the structural properties of the biomass were optimized, significantly enhancing the fixed carbon content. Subsequent chemical activation with an alkaline agent yielded T-AC with an outstanding specific surface area (1530–3375 m2/g) and total pore volume (0.73–2.00 cm3/g), with a tailored pore distribution favoring the sub-mesopore range (2.0–4.0 nm). The T-AC demonstrated remarkable performance in removing methylene chloride (MC), a hazardous VOC, with methylene chloride activity (MA) increasing from 44.7% to 76.3% as the activation agent ratio increased, while methylene chloride working capacity (MWC) improved significantly from 17.1% to 55.9%. These results underscore the transformative potential of tangerine peel-derived AC as a sustainable solution for VOC remediation, combining environmental waste management with advanced adsorption technology. The findings not only advance the field of biomass utilization but also offer a scalable approach for tackling pressing environmental and industrial challenges.
Shortening the Payback Period of Greenhouse Gas Reduction Benefits from Photovoltaic Rooftop Systems
Authors: Rugthaicharoencheep Nattachote , Ruangsap Natchapol , Nedphokaew Supawud
Published: December 2024

This paper presents an analysis of shortening the payback period of greenhouse gas reduction benefits from photovoltaic rooftop systems. The objective was to evaluate the amount of carbon credits generated and their returns. The study includes an economic analysis and a comparison of the economic outcomes with and without the consideration of carbon credits from 149.80 kWp and 25.68 kWp photovoltaic rooftop systems. The study evaluated the amount of electrical energy produced by the photovoltaic rooftop systems, estimated using the PVsyst program version 7.3.1, at a factory in Pathum Thani Province, Thailand. The economic indices analyzed in this study include the payback period, net present value (NPV), benefit–cost ratio (B/C ratio), and internal rate of return (IRR). The analysis is divided into four case studies: Case 1 is the base case, and Cases 2, 3, and 4 consider carbon credits for 7, 14, and 25 years, respectively. The economic indices analyzed in Case 1 include the financial internal rate of return (FIRR), payback period, financial net present value (FNPV), and B/C ratio. In Cases 2, 3, and 4, the economic indices analyzed are the economic internal rate of return (EIRR), the economic net present value (ENPV), the B/C ratio, and the payback period. This paper outlines a new economic calculation approach that incorporates carbon credits produced by photovoltaic rooftop systems, which helps achieve break-even points more quickly. It also discusses the application of carbon credits in conjunction with renewable energy.
Assessing Grid Reliability for Optimal Integration of System-Integrated Modular Advanced Reactor Technology (SMART) for Kenya: A Case of the Nairobi Distribution Network
Authors: Goga Ondiegi Kapis , Chang Choong-koo
Published: December 2024

The integration of advanced nuclear technologies like the System-Integrated Modular Advanced Reactor (SMART) offers a transformative approach to enhancing grid reliability in developing countries. This study focuses on the Nairobi distribution network in Kenya, a critical region characterized by an evolving energy mix of geothermal, hydro, solar, and wind power sources, comprising 220 kV and 132 kV transmission lines feeding 66 kV, 33 kV, and 11 kV distribution lines to various load centers. Using ETAP 22 simulation software, the research evaluates the impact of SMART integration through three scenarios: baseline operation, grid compensator-only operation, and SMART-SMR integration. Key reliability indices such as the System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI), and Expected Energy Not Supplied (EENS) were analyzed. Results reveal that integrating a 100 MW SMART reactor reduces SAIDI by 2.8% (5.0433 h/customer-year) and SAIFI by 5.1% (0.0516 interruptions/customer-year), while maintaining voltage profiles within 98.21–98.91% of nominal. This analysis bridges gaps in prior research by demonstrating SMART’s ability to stabilize power grids in emerging economies, providing critical insights for policymakers aiming to achieve reliable and sustainable energy systems.
Optimal Scheduling Strategies for EV Charging and Discharging in a Coupled Power–Transportation Network with V2G Scheduling and Dynamic Pricing
Authors: Ran Yunzheng , Liao Honghua , Liang Huijun , Lu Luoping , Zhong Jianwei
Published: December 2024

With the increasing penetration of electric vehicles (EVs), the spatial–temporal coupling between the transportation network (TN) and the power distribution network (PDN) has intensified greatly. Large-scale uncoordinated charging of EVs significantly impacts both the PDN and TN. In this paper, an optimal scheduling strategy for EV charging and discharging in a coupled power–transportation network (CPTN) with Vehicle-to-Grid (V2G) scheduling and dynamic pricing is proposed. The strategy considers the influence of dynamic transportation road network (DTRN) information on EV driving patterns, as well as the unique vehicle characteristics and mobile energy storage capabilities of EVs. Firstly, a DTRN model is established. Subsequently, the dynamic Dijkstra algorithm is utilized to accurately simulate the EV driving paths and predict the spatial–temporal distribution of the EV charging load. Secondly, optimal scheduling for EV charging and discharging within the CPTN is performed, guided by a V2G model coupled with a multi-time dynamic electricity price (MTDEP) strategy to optimize the grid load curve while accommodating the charging requirements of EVs. Finally, the effectiveness and superiority of the proposed optimization scheduling model are validated by the IEEE 33-node PDN test system.
Scaling up Trickle Bed Reactor for Gas Fermentation Technology: The Effect of Temperature and Reactor Characteristics on Mass Transfer
Authors: Dutta Sambit , Gavala Hariklia N. , Skiadas Ioannis V.
Published: December 2024

The increasing demand for efficient and sustainable industrial processes has accelerated research into green alternatives. Gas fermentation in a trickle bed reactor is a promising technology; however, optimal scaling up is still challenging. A mass transfer model is crucial for identifying bottlenecks and suggesting design improvements to optimize the scale-up of TBR for gas fermentation. This study explores the effects of temperature, reactor dimensions, and packing material size on the volumetric mass transfer coefficient (kLa) in a commercial-scale trickle bed reactor (TBR). Using dynamic mass transfer modeling, the research results highlight that thermophilic conditions (60 °C) significantly enhance kLa and mass transfer rates for H2, CO, and CO2, despite reduced gas solubility at higher temperatures. Additionally, packing material of smaller particles improves kLa by increasing the surface for gas–liquid interaction, while reactor dimensions, particularly volume and diameter, are shown to critically influence kLa. This study provides valuable insights into optimizing TBR design and scale-up, emphasizing the importance of thermophilic conditions, proper packing material selection, and reactor geometry for efficient gas–liquid mass transfer in syngas (a mixture of H2, CO, and CO2) biological conversion. Overall, the findings offer practical guidelines for enhancing the performance of industrial-scale TBR systems.
Simplified Approach to Evaluate Cavitation Intensity Based on Time Information on Imposed Pressure in Liquid
Authors: Kawashima Hiroyuki , Kogawa Hiroyuki , Futakawa Masatoshi , Tanaka Nobuatsu
Published: December 2024

Cavitation damage is an important research topic in fluid–structure interactions, such as those being studied using the mercury target for the pulsed neutron source at the Materials Life Science Experimental Facility/Japan Proton Accelerator Complex. Hence, the estimation of cavitation damage (cavitation intensity) is required from the perspective of structural integrity. The results of previous studies suggest that the maximum radii of cavitation bubbles immediately prior to collapse are related to cavitation intensity. Therefore, we propose a method for estimating the maximum radius from the time information by measuring the vibrations of structure walls that are induced by collapsing cavitation bubbles in a confined liquid. In this study, we used a magnetic impact testing machine to experimentally investigate the cavitation bubble dynamics, directly observe the bubble collapsing behavior, and measure the induced vibration. We experimentally confirmed that the time information is useful in the estimation of the maximum radii of bubbles. Moreover, we theoretically derived a simple evaluation formula to estimate the maximum radius from the time responses of the imposed pressure in a confined liquid in a structure.
Prevention of Food Waste in China: Role and Impact of China’s Anti-Food Waste Law
Authors: Wang Shenghang , Liu Dongxu , Sheng Jiping
Published: December 2024

In recent years, despite global improvements in development, food scarcity and waste remain critical issues impacting food security, human health, and environmental sustainability. China’s Ministry of Agriculture and Rural Affairs reports that China’s food loss and waste rate is approximately 22.7%, amounting to 460 million tons annually, with the consumption and post-harvest processing stages facing the highest losses. To address these issues, China enacted the Anti-Food Waste Law in 2021, aiming to reduce food waste through clear responsibilities, incentives, and penalties for government agencies and relevant stakeholders. While scholars note that the law represents a significant shift from moral to legal governance in tackling food waste, some argue that its provisions lack sufficient specificity. This article assesses the effectiveness of China’s anti-food waste legislation using case studies and comparative analyses, highlighting the challenges in defining and implementing the law within China’s cultural framework, where food signifies abundance and prosperity. Additionally, the article explores successful international practices, including the 2030 Champions Program and similar efforts in Europe and Japan, to inform China’s strategy. The key recommendations for policy improvement include strengthening accountability and governance, establishing a food hierarchy for sustainable resource management, enhancing data collection on food waste, promoting food donation mechanisms, and transitioning from a solely government-led regulatory approach to a multi-dimensional co-regulation model.
Predictive Model for Listeria monocytogenes in RTE Meats Using Exclusive Food Matrix Data
Authors: Gowda N. A. Nanje , Singh Manjari , Lommerse Gijs , Kumar Saurabh , Heintz Eelco , Subbiah Jeyamkondan
Published: December 2024

Post-processing contamination of Listeria monocytogenes has remained a major concern for the safety of ready-to-eat (RTE) meat products that are not reheated before consumption. Mathematical models are rapid and cost-effective tools to predict pathogen behavior, product shelf life, and safety. The objective of this study was to develop and validate a comprehensive model to predict the Listeria growth rate in RTE meat products as a function of temperature, pH, water activity, nitrite, acetic, lactic, and propionic acids. The Listeria growth data in RTE food matrices, including RTE beef, pork, and poultry products (731 data sets), were collected from the literature and databases like ComBase. The growth parameters were estimated using the logistic-with-delay primary model. The good-quality growth rate data (n = 596, R2 > 0.9) were randomly divided into 80% training (n = 480) and 20% testing (n = 116) datasets. The training growth rates were used to develop a secondary gamma model, followed by validation in testing data. The growth model’s performance was evaluated by comparing the predicted and observed growth rates. The goodness-of-fit parameter of the secondary model includes R2 of 0.86 and RMSE of 0.06 (μmax) during the development stage. During validation, the gamma model with interaction included an RMSE of 0.074 (μmax), bias, and accuracy factor of 0.95 and 1.50, respectively. Overall, about 81.03% of the relative errors (RE) of the model’s predictions were within the acceptable simulation zone (RE ± 0.5 log CFU/h). In lag time model validation, predictions were 7% fail-dangerously biased, and the accuracy factor of 2.23 indicated that the lag time prediction is challenging. The model may be used to quantify the Listeria growth in naturally contaminated RTE meats. This model may be helpful in formulations, shelf-life assessment, and decision-making for the safety of RTE meat products.
Development of Thermosensitive Hydrogels with Tailor-Made Geometries to Modulate Cell Harvesting of Non-Flat Cell Cultures
Authors: García-Sobrino Rubén , Martínez-Campos Enrique , Marcos-Ríos Daniel , Zepeda-Rodríguez Zenen , Valentín Juan L. , Sanz-Horta Raúl , León-Calero Marina , Reinecke Helmut , Elvira Carlos , Gallardo Alberto , Rodríguez-Hernández Juan
Published: December 2024

Considering the complexity in terms of design that characterizes the different tissues of the human body, it is necessary to study and develop more precise therapies. In this sense, this article presents the possibility of fabricating photocurable thermosensitive hydrogels with free geometry and based on N-Vinyl Caprolactam (VCL) with the aim of modulating the adhesion of non-planar cell cultures. The fabrication process is based on the use as a mold of two-layer thick water-soluble polyvinyl alcohol (PVA) previously printed by Extrusion Material (MatEx). From this technology it has been possible to obtain hydrogels with different 3D geometries and different crosslinking percentages (2, 4 and 6 mol%). Studies have shown that networks reduce their thermosensitivity not only when the percentage of crosslinking in the formulation increases, but also when the thickness of the hydrogel obtained increases. Based on this reduction in thermosensitivity, the less crosslinked (2 mol%) hydrogels have been evaluated to carry out a novel direct application in which hydrogels with curved geometry have allowed cell adhesion and proliferation at 37 °C with the endothelial cell line C166-GFP; likewise, non-aggressive cell detachment was observed when the hydrogel temperature was reduced to values of 20 °C. Therefore, the present manuscript shows a novel application for the synthesis of free-form thermosensitive hydrogels that allows modulation of non-planar cell cultures.
The Navahoax
Authors: Sherbert Cedar
Published: December 2024

THE NAVAHOAX is a first-person account of ethnic fraud as told by an American Indian media professional whose tribal background was utilized by a presumed Native American author pursuing a film adaption of his work; it was later discovered the author was a white man masquerading as a Navajo citizen. A full narrative account will be given of the two-year ordeal and its aftermath as well as a contextualization within of the then-current socio-historical moment as it relates to the ongoing history of “playing Indian” as well as Native (in)visibility within the broader U.S. culture. This will be followed by an updated contextualization of this case in the wake of recent high-profile unmaskings of “pretendians” in the U.S. and Canada and the efforts of tribally-enrolled citizens in combatting such race-shifting.
Glucose Metabolism Disorders and Parkinson’s Disease: Coincidence or Indicator of Dysautonomia?
Authors: Chmiela Tomasz , Jarosz-Chobot Przemysława , Gorzkowska Agnieszka
Published: December 2024

Background: Parkinson’s disease (PD) and type 2 diabetes mellitus (T2DM) are both age-related diseases. Evidence from recent studies suggests a link between them. The existence of an interaction between autonomic nervous system dysfunction and the dysregulation of glucose metabolism is one of the proposed mechanisms to explain the complicated relationship between these diseases. The aims of this study are to assess the incidence of glycemic dysregulation in people with PD and to identify clinical factors that may predispose patients with PD to the occurrence of metabolic disturbances. Methods: In total, 35 individuals diagnosed with PD and 20 healthy control subjects matched in terms of age and gender participated in a study consisting of clinical and biometric assessments along with 14 days of continuous glucose monitoring (CGM) using the Freestyle Libre system. In the group of patients with PD, a comparative analysis was performed between patients with and without autonomic dysfunction. The severity of autonomic dysfunction was assessed using the SCOPA-AUT. Results: Participants diagnosed with PD demonstrated a trend toward lower morning glucose levels compared to the control group. PD patients with autonomic symptoms had greater glucose variability and a deeper trend toward lower glucose levels in the mornings. The presence of autonomic dysfunction, especially orthostatic hypotension and micturition disturbance, and the severity of autonomic symptoms were associated with greater glycemic variability. Conclusions: The occurrence of autonomic disorders in the course of Parkinson’s disease predisposes patients to more profound glycemic dysregulation.
Exploring Cancer Prevention Challenges for People with Intellectual Disabilities: Perspectives from Family Caregiver
Authors: Golubović Špela , Simin Dragana , Vuković Vladimir , Demirović Semra , Milutinović Dragana
Published: December 2024

Background: Cancer prevention is a crucial public health strategy, with 30–50% of cancers being preventable through early screening and lifestyle modifications. However, people with intellectual disabilities (PWID) face significant barriers to cancer prevention services, leading to delayed diagnoses and poorer outcomes. Family caregivers play a key role in bridging the healthcare access gaps for PWID, but there is limited research exploring their perspectives on cancer prevention. This study examined the needs, challenges, and strategies family caregivers employ in cancer prevention for PWID, framed within Bronfenbrenner’s ecological systems theory. Methods: A mixed methods sequential explanatory design was used. Quantitative data were collected through a structured questionnaire from 41 caregivers of PWID, followed by qualitative semi-structured interviews with 15 caregivers to explore the quantitative findings further. Data were analysed using descriptive statistics, chi-square tests, and thematic content analysis. Results: The study revealed that 75.6% of caregivers had not received information about cancer prevention for PWID, and 63.4% did not regularly coordinate cancer screenings. Barriers identified included a lack of accessible information, logistical challenges, and emotional strain. However, 80.5% of caregivers expressed a need for additional training to support their roles in cancer prevention. Qualitative findings highlighted four key themes: promoting a healthy lifestyle, access to healthcare services, health literacy, and psychosocial support. Conclusions: The findings emphasise the need for tailored cancer prevention strategies and educational resources for caregivers of PWID. Addressing these gaps requires systemic changes in healthcare practices, better coordination of services, and enhanced support for caregivers to reduce the barriers to cancer prevention for PWID.
Telehealth Adoption Among Saudi Older Adults: A Qualitative Analysis of Utilization and Barriers
Authors: Alodhialah Abdulaziz M. , Almutairi Ashwaq A. , Almutairi Mohammed
Published: December 2024

Background/Objectives: The rapid adoption of telehealth services has been significantly accelerated by the need for accessible healthcare solutions, especially among older adults. However, the utilization of telehealth remains limited in many regions, including Saudi Arabia. This study aims to identify the barriers and facilitators influencing telehealth adoption among older adults in Riyadh. Methods: A qualitative phenomenological approach was employed, involving semi-structured interviews with 25 participants aged 60 and above. Thematic analysis was utilized to analyze the data, allowing for the identification of key themes related to participants’ experiences with telehealth services. Results: Four main themes emerged from the analysis: access to technology and connectivity, attitudes toward telehealth, support systems, and institutional and policy factors. Participants reported challenges such as low digital literacy and unreliable Internet access, along with the need for trust in healthcare providers. Family support and the desire for training resources were highlighted as important facilitators of telehealth utilization. Conclusions: The findings indicate that addressing barriers such as digital literacy and connectivity is crucial for enhancing telehealth utilization among older adults. Implementing strategies that promote education, strengthen support systems, and improve policy frameworks is essential for facilitating greater engagement with telehealth services in this demographic.
Comparative Study of Water and Fertilizer Regimes on Water Potential, Phenolic Substances, and Photosynthetic Characteristics of Pistacia weinmannifolia
Authors: He Zhenmin , Sun Yongyu , Peng Lingxiao , Luo Zhifeng , Qi Jianhua , Li Xiangfei , Duan Xingwu , Ou Zhaorong
Published: December 2024

Effective water and fertilizer management is crucial for the forestry production of Pistacia weinmannifolia. This experiment employed an orthogonal design to measure the water potential, anthocyanins, chlorophyll, and photosynthetic parameters of Pistacia weinmannifolia under different water and fertilizer regimes. The effects of different water and fertilizer regimes on the water potential, phenolic compounds, and photosynthetic characteristics of Pistacia weinmannifolia were analyzed. A comprehensive analysis method was used to evaluate and establish the best water and fertilizer regimes system. The results showed that the water and fertilizer regimes increased the water potential, anthocyanins, chlorophyll content, flavonoids, and photosynthesis (p < 0.05). During the mid-growth stage and late mid-stage growth of Pistacia weinmannifolia, the fertilizers with the most significant effects on water potential, chlorophyll, and anthocyanins were nitrogen (N) and phosphorus (P). The supply of a certain amount of N and P had positive effect on water potential, chlorophyll, and anthocyanins. Increasing N content was more effective in improving carboxylation efficiency than increasing P content. The effect of N content on photosynthetic efficiency was greater than that of P content Analyses using the TOPSIS model demonstrate that Pistacia weinmannifolia exhibits superior comprehensive efficiency in water potential, chlorophyll, flavonoid, and anthocyanin content. When applying 0.54 g·plant−1 of pure P and 0.67 g·plant−1 of pure N, with the relative soil moisture content maintained at 85%, the optimal comprehensive benefit for photosynthetic indicators is achieved with 0.34 g·plant−1 of pure P and 0.77 g·plant−1 of pure N, while maintaining the relative soil moisture content at 46.66%. These findings indicate that the water–fertilizer coupling treatment group exhibited improved growth status and photosynthesis. Therefore, the cultivation of Pistacia weinmannifolia should prioritize maintaining a balanced water–fertilizer ratio to optimize resource utilization.
Evaluation of Sodium Chloride Concentrations on Growth and Phytochemical Production of Mesembryanthemum crystallinum L. in a Hydroponic System
Authors: Eoh Giju , Kim Chulhyun , Bae Jiwon , Park Jongseok
Published: December 2024

Mesembryanthemum crystallinum L., commonly known as the ice plant, is a halophyte recognized for its exceptional salinity tolerance. This study aimed to determine the optimal NaCl concentration for promoting plant growth, D-pinitol, and other phytochemicals in M. crystallinum cultivated in a hydroponics system. Seedlings of M. crystallinum were transplanted into a hydroponic system and subjected to different NaCl concentrations (0, 100, 200, 300, 400, and 500 mM) in the nutrient solution. To evaluate the plant’s response to salinity stress, measurements were conducted on growth parameters, chlorophyll and carotenoid levels, total flavonoid and polyphenol contents, and DPPH scavenging activity. The optimal NaCl concentration for growth was found to be 200 mM, at which the shoot fresh and dry weights were highest. Additionally, total chlorophyll and carotenoid contents were maximized at 200 mM NaCl, with a subsequent decrease at higher concentrations. The highest DPPH scavenging activity was observed in the 200 mM NaCl treatment, which correlated with increased levels of total flavonoids and polyphenols. These results indicated that optimizing NaCl concentration can enhance the antioxidant activity of Mesembryanthemum crystallinum L. The D-pinitol content also peaked at 200 mM NaCl treatment, further supporting its role osmotic adjustment under salinity stress. M. crystallinum exhibited enhanced antioxidant production and cellular protective functions at 200 mM NaCl, which optimized its biochemical defense mechanisms and helped maintain physiological functions under salinity stress. These findings provide valuable insights for agricultural and biological applications, particularly in cultivating M. crystallinum for its bioactive compounds.
Recurrent Neural Network for Quantitative Time Series Predictions of Bridge Condition Ratings
Authors: Sowemimo Adeyemi D. , Chorzepa Mi G. , Birgisson Bjorn
Published: December 2024

Traditional forecasting models for bridge conditions, such as ARIMA and Markov chains, often fail to adequately capture nonlinear and dynamic relationships among critical variables like age, traffic patterns, and environmental factors, leading to suboptimal maintenance decisions, increased long-term maintenance costs, and heightened safety risks. This study addresses these limitations by developing recurrent neural network (RNN) models utilizing Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) architectures with a TimeDistributed output layer. This novel approach enables accurate forecasting of the Bridge Health Index (BHI) and condition ratings for key components—deck, superstructure, and substructure—while effectively modeling temporal dependencies. Applied to bridge data from Georgia, USA, the regression models (BHI) achieved R2 values exceeding 0.84, while the classification models (components condition ratings) demonstrated accuracy between 84.78% and 87.54%. By modeling complex temporal trends in bridge deterioration, our method processes time-dependent data from multiple bridges simultaneously, revealing intricate relationships that influence bridge performance within a state’s inventory. These results provide actionable insights for maintenance planning, optimized resource allocation, and reduced risks of unexpected failures. This research establishes a robust framework for bridge performance prediction, ensuring improved infrastructure safety and resilience amid aging assets and constrained maintenance budgets.
A Molecular Dynamics Study on Auxetic Behaviors of Origami Graphene/Cu Nanocomposites
Authors: Na Bai-Wei , Zhang Hai-Ning , Fan Yin , Wang Yeqing
Published: December 2024

Graphene is considered to be one of the most promising reinforcement phases for nanocomposites due to its unique two-dimensional planar structure with excellent mechanical properties. After the design of origami, the 2D material will obtain a negative Poisson’s ratio in the in-plane direction and become a metamaterial with unusual mechanical properties. Inspired by this, an origami pattern is adopted for graphene at an atomic scale using a molecular dynamics (MD) approach, and then origami graphene is embedded into a single-crystal copper matrix to obtain origami graphene/copper nanocomposites with auxetic behaviors. In the modeling, the periodic boundary condition is chosen to exhibit the Poisson’s ratio of the whole system. Under the isothermal–isobaric ensemble, the interactions between C-C, Cu-Cu, and C-Cu atoms are, respectively, determined by three potential functions: AIREBO, EAM, and LJ. The effect of the origami graphene/copper interfacial gap on the critical strain of incremental Poisson’s ratio, critical strain of engineering Poisson’s ratio, and moduli of the origami graphene/copper nanocomposites is studied to determine the optimum distance between the two phases. The influences of the mass fraction of carbon atom and temperature on those properties are discussed in detail after the MD model is confirmed.
Investigation of the Impact of SmFeN Doping on the Anisotropic NdFeB/SmFeN Composite Magnets
Authors: Cai Wei , Zhang Xinqi , Shi Zhiping , Chen Haibo , Zhu Qiaomin , Jiang Kun , Qiao Liang , Ying Yao , Li Wangchang , Yu Jing , Li Juan , Zheng Jingwu , Che Shenglei
Published: December 2024

By incorporating various types of permanent magnetic powders, composite magnets with cost-effectiveness and a wide range of magnetic properties can be achieved. In this study, the anisotropic composite magnets were fabricated using the hot press forming method, which involved blending neodymium iron boron (NdFeB) powder and samarium iron nitrogen (SmFeN) powder. The experiment demonstrated that the magnet density reaches its maximum point when the doping level of SmFeN reaches 20 wt.%, aligning remarkably well with the corresponding theoretical value of 19.22 wt.% achieved through a cubic stacking arrangement. In the absence of an applied magnetic field or under a sufficiently high oriented magnetic field (3 T), the remanence variation pattern in composite magnets doped with different amounts of SmFeN aligns consistently with the density pattern, yielding a maximum value of 20%. However, in the actual solidification process, the orientation field is insufficient (e.g., 1.5 T), necessitating a doping amount that exceeds the value corresponding to peak density by 28% to achieve optimal remanence. This observation suggests that the incorporation of a higher proportion of small-sized and relatively low coercivity SmFeN magnetic powder can effectively facilitate the rotational alignment of neighboring large-sized NdFeB magnetic powder under weak magnetic fields, thereby inducing a synergistic effect.
State-of-the-Art Deep Learning Methods for Microscopic Image Segmentation: Applications to Cells, Nuclei, and Tissues
Authors: Krikid Fatma , Rositi Hugo , Vacavant Antoine
Published: December 2024

Microscopic image segmentation (MIS) is a fundamental task in medical imaging and biological research, essential for precise analysis of cellular structures and tissues. Despite its importance, the segmentation process encounters significant challenges, including variability in imaging conditions, complex biological structures, and artefacts (e.g., noise), which can compromise the accuracy of traditional methods. The emergence of deep learning (DL) has catalyzed substantial advancements in addressing these issues. This systematic literature review (SLR) provides a comprehensive overview of state-of-the-art DL methods developed over the past six years for the segmentation of microscopic images. We critically analyze key contributions, emphasizing how these methods specifically tackle challenges in cell, nucleus, and tissue segmentation. Additionally, we evaluate the datasets and performance metrics employed in these studies. By synthesizing current advancements and identifying gaps in existing approaches, this review not only highlights the transformative potential of DL in enhancing diagnostic accuracy and research efficiency but also suggests directions for future research. The findings of this study have significant implications for improving methodologies in medical and biological applications, ultimately fostering better patient outcomes and advancing scientific understanding.
Ship-Route Prediction Based on a Long Short-Term Memory Network Using Port-to-Port Trajectory Data
Authors: Lee Hyeong-Tak , Yang Hyun
Published: December 2024

In this study, a ship-route prediction model based on a long short-term memory network using port-to-port trajectory data is presented. Data from a traditional automatic identification system—often used for ship-route prediction—are limited by uneven sampling intervals and noise. To address these issues, equal-interval data collected every 10 s from a target ship, which is a liner container vessel, were employed. Our study focuses on predicting the entire trajectory between the Gunsan and Busan ports. The root mean square error (RMSE), mean absolute error (MAE), and average distance d¯ between two trajectories were used as the key evaluation metrics. The analysis yielded excellent predictive performance, with the values RMSE = 0.000999, MAE = 0.000672, and d¯ = 0.101 km. This study thus provides a foundation for predicting complete port-to-port routes and offers practical insights for managing vessel operations. Accurate route prediction contributes to reducing port congestion, improving fuel efficiency, and lowering carbon emissions.
Effect of Speed Linear Decrease on Internal Flow Characteristics and Pressure Pulsations of Variable-Speed Pump Turbine in Turbine Mode
Authors: Shi Guangtai , Li Binyan , Xiao Yexiang , Tang Manqi , Yang Xi
Published: December 2024

Pumped storage units often deviate from the optimal operating conditions in the process of regulating new energy fluctuations. To effectively improve the performance of the units, the variable speed of the units is one of the more feasible means at present. This paper focuses on the part-load condition of turbine operation, with an emphasis on the internal flow characteristics and pressure pulsation characteristics of the pump turbine during the linear reduction of the rated speed. It is found that the streamlines in the runner become turbulent in the process of speed reduction, forming a vortex at the inlet of the runner, and the vortex scale gradually increases with the speed reduction. The vortex rope in the draft tube undergoes three types of changes during the speed reduction: helical eccentric vortex rope, vanishing vortex rope, and columnar vortex rope. Before the speed change, the low-frequency components with high amplitude exist in each flow-passing part, but gradually disappear with the speed reduction. Except for the runner, the frequency affected by rotor–stator interference of each flow-passing part increases with the decrease of speed, and the growth is most obvious in the vaneless region. The findings of this research can serve as a valuable reference for the variable speed operation of pumped storage units.
Nondestructive Detection of Osmotic Damage in GFRP Boat Hulls Using Active Infrared Thermography Methods
Authors: Garafulić Endri , Bagavac Petra , Krstulović-Opara Lovre
Published: December 2024

This article presents the application of infrared thermography as a nondestructive testing method (NDT) for detecting osmotic damage in glass-fiber-reinforced polymer (GFRP) and glass-reinforced polymer (GRP) boat hull structures. The aim of the conducted experiments is to explore the possibilities of applying active infrared thermography to real structures and to establish a procedure capable of filtering out anomalies caused by various thermal influences, such as thermal reflections from surrounding objects, geometry effects, and heat flow variations on the observed object. The methods used for post-processing IR signals include lock-in thermography (LT), pulse thermography (PT), pulse phase thermography (PPT), and gradient pulse phase thermography (GT). The practical application and advantages and disadvantages of infrared thermography in identifying osmotic damage in GFRP and GRP boat hulls will be illustrated through three case studies. Each case study is based on specific conditions and characteristics of different types of osmotic damage, enabling a thorough analysis of the effectiveness of the method in detecting and assessing the severity of the damage. The post-processed thermal images enable a clearer distinction between damaged and undamaged zones, improving the robustness of detection under realistic field conditions.
Pilot Investigation of Socio-Spatial Relationships in an Ex Situ White Rhino (Ceratotherium simum simum) Bachelor Group
Authors: Metrione Lara C. , Roth Terri L. , Rodriguez Yaraila , Freeman Elizabeth W.
Published: December 2024

Nonbreeding white rhino bulls are traditionally housed individually in zoos, but space limitations require the exploration of alternative techniques. There are no studies of group-housed bulls, and the feasibility of managing a bachelor group is unknown. Six bulls (two bulls each of 3-, 5-, and 8-yr-olds) in a 3.1 ha enclosure were observed for 30 min each 2×/wk for 20–31 wks. The 3-yr-olds were relocated after the first 20 weeks. Rhino location, nearest neighbor, aggressive behaviors, and dominance interactions were recorded. There was no evidence of habitat spatial segregation. The 3- and 5-yr-olds grouped together by age; 8-yr-olds did not associate as much as younger rhinos. Aggressive vocalizations and physical aggression were infrequent (range 0–1.5/h/bull and 0–1/h/bull, respectively). Eight-year-olds displayed and received aggressive vocalizations the most; three-year-olds displayed and received physical aggression the most. After the 3-yr-olds were removed, the habitat usage and social proximity of the remaining bulls did not change. Aggressive behaviors increased, but vocalizations (range 0.18–3.1/h/bull) remained more frequent than physical aggression (range 0.18–0.73/h/bull). The highest-ranking 8-yr-old engaged in physical altercations the least. The bulls shared space, and the use of vocalizations more than physical aggression deterred injury. These findings indicate that bachelor group management is feasible in a large enclosure with young bulls.
Influence of the Ag Content on the Natural and Thermal Induced Oxidation of Cu Thin Films
Authors: Carrupt Maria C. , Serro Ana P. , Piedade Ana P.
Published: December 2024

In this paper, we studied the deposition and characterization of monolithic and silver-doped copper coatings using RF magnetron sputtering. The main objective was to examine the impact of different Ag contents on natural and thermally induced aging when compared with monolithic copper coatings. For this purpose, the as-deposited surfaces were left exposed to normal temperature and humidity conditions during one year (natural) and were annealed at 200 °C in a non-controlled atmosphere. To evaluate the results of these treatments, the films were characterized in terms of surface and cross-section morphology, structure, chemical composition, wettability, and surface energy. The as-deposited monolithic copper films exhibit a clear face-centered cubic structure with a very strong preferential crystallographic orientation according to the (111) diffraction plane. The presence of Ag in the as-deposited coatings decreased the ability of the films to be wetted, increasing their hydrophobicity and jeopardizing crystallographic orientation development according to the (111)-Cu diffraction plane, particularly after annealing, when compared to Cu films. Through annealing, Cu2O and Ag2O were formed, leading to a significant decrease in surface energy and reduced wettability. These results can help elucidate and estimate the life span of smart windows, batteries, and solar panels, which are some of the many applications for these coatings.
The Functionalization of Activated Polyester Fabrics with Chitosan—Changes in Zeta Potential and Moisture Management
Authors: Čorak Ivana , Tarbuk Anita , Dekanić Tihana , Sikorski Dominik , Draczyński Zbigniew
Published: December 2024

In the interests of using green and sustainable chemical innovations to create sustainable products with minimized (or no) chemical hazard potential, the polyester fabric in this work was activated and functionalized with chitosan and its durability was investigated. Chitosan is a natural biopolymer derived from chitin. As it has good biocompatibility, bio-absorption, anti-infectious, antibacterial and hemostatic properties and accelerates wound healing, it is increasingly being researched for the antimicrobial treatment of textiles. Due to the increased demands on the durability of antimicrobial properties during care, its binding to cellulose in cotton and cotton–polyester blends has been researched, but not to polyester alone. Therefore, the functionalization of polyester fabrics with chitosan by thermosol in the form of submicron particles and pad-dry-curing with homogenized gel was investigated in this work. The functionalization with chitosan was carried out on untreated polyester fabric and polyester fabric activated by alkali hydrolysis. In order to reduce the release of chemical substances during the entire life cycle of textile production, no binder was used. The effects were evaluated by electrokinetic analysis (zeta potential), and the mechanical, spectral, moisture management and antimicrobial properties were determined using standard methods. The functionalized polyester fabrics were submitted to 10 washing cycles in a solution of non-ionic surfactant for determination of its durability. It was shown that the functionalization of hydrolyzed polyester fabric with homogenized chitosan gel by pad-dry-curing results in excellent antimicrobial efficacy and moisture management properties while maintaining the mechanical properties of the fabric even after 10 washing cycles.
Application of a 3D-Printed Part with Conformal Cooling in High-Pressure Die Casting Mould and Evaluation of Stress State During Exploitation
Authors: Małysza Marcin , Żuczek Robert , Wilk-Kołodziejczyk Dorota , Jaśkowiec Krzysztof , Bitka Adam , Głowacki Mirosław , Zięba Łukasz , Pysz Stanisław
Published: December 2024

The article addresses stress formation in the structural 3D-printed elements of a high-pressure die casting die mould used for production of aluminum castings. The 3D-printed elements with conformal cooling are manufactured of 18Ni300 powder. Initial numerical calculations were performed on a test die mould made of standard steel X40CrMoV5 to determine temperature distribution and stress state, providing a baseline for comparing 3D-printed 18Ni300 parts. A database for 18Ni300 material was developed, including optimal heat treatment parameters: aged at 560 °C for 8 h. The resulting tensile strength of approximately ~1600 MPa, yield strength 1550 MPa, and elongation 6–7%, with properties temperature-dependent from 20 °C to 600 °C. Results show that conformal cooling increases stress gradients, highlighting the demands on fatigue strength at elevated temperatures. The study revealed that the heat treatment significantly influences the final properties, with tensile strengths of 1400–2000 MPa and elongation from 1 to 8%. While the heat treatment has a greater impact on the mechanical properties than the printing parameters, optimizing the printing settings remains crucial for ensuring density and quality in the die moulds under cyclic loads.
Real-Time Acoustic Measurement System for Cutting-Tool Analysis During Stainless Steel Machining
Authors: Salm Tom , Tatar Kourosh , Chilo José
Published: December 2024

This study presents a sound-based tool-wear monitoring system designed to overcome the limitations of conventional methods that focus solely on gradual and predictable wear patterns. The proposed system employs low-cost, high-frequency microphones and advanced signal processing—featuring analog/digital filtering, oversampling, signal conditioning, PLL-based synchronization, and feature extraction (ZCR, RMS)—to capture acoustic emissions during machining. Key innovations include optimized microphone placement, a custom PCB, and real-time data transfer via WiFi to MATLAB for analysis. Using the TreeBagger machine-learning algorithm, the system accurately predicts tool wear, detecting both gradual and abrupt wear patterns. Tested on EN 1.4307 (AISI/ASTM 304L) stainless steel, the system demonstrated robust performance in real-time tool-condition assessment. Its scalable and cost-effective design allows for the integration of additional sensors and features, providing a non-invasive and adaptive solution to enhance machining efficiency and reduce operational costs.