bluuebunny/crossref_metadata_2025 huggingface dataset:
Current Methods and Technologies for Storage Tank Condition Assessment: A Comprehensive Review
Authors: Stoicescu Alexandru-Adrian , Ripeanu Razvan George , Tănase Maria , Toader Liviu
Published: February 2025

This study investigates the current industry practices for storage tank assessment and the possibilities for improving inspection methods using the latest technologies on the market. This article presents the main methods and technologies for non-destructive testing (NDT), along with new methods that make them more efficient and economical. To further analyze the state of a tank and determine its lifetime expectancy, analysis methods are presented based on NDT results. The key aspects that can be improved and made more efficient are NDT procedures using robots/drones and autonomous devices; automated inspection procedures, like remote video inspection combined with local thickness measurement or 3D scanning of the tank elements for deformations; advanced analysis methods using the input from the NDT and inspection data collected using analytical calculations according to applicable standards; Finite Element Analysis (FEA); and digitalized models of equipment (Digital Twin) accompanied by artificial intelligence for data processing. The best way to make the process more efficient is to develop and use dedicated standardized software for tank condition assessment.
Effect of Different Substituents on the Properties of 4-R-1,5-Diaminotetrazolium Pentazolate Salts
Authors: Yuan Xiaofeng , Xu Ze , Lu Ming , Xu Yuangang
Published: February 2025

To explore the impact of different substituents (R) in 4-R-1,5-diaminotetrazolium cations on the performance of their pentazolate salts, five types of pentazolate salts with different groups were designed: -H, -OH, -NH2, -NH-NH2, and -N3. Quantum chemical methods were employed to deeply study the interionic interactions and detonation properties of these 4-R-1,5-diaminotetrazolium pentazolate salts. Among these five ionic compounds, the 1,5-diamino-4-hydroxytetrazolium pentazolate ([DAT-OH+] [N5−]) system exhibited the lowest interaction energy and highest stability, while the 1,5-diamino-1H-1,2,3,4-tetrazolium pentazolate ([DAT-H+] [N5−]) system was the least stable. Symmetry-adapted perturbation theory (SAPT) analysis indicated that electrostatic and dispersion effects predominantly contributed to these interactions. An independent gradient model based on Hirshfeld partition (IGMH) analysis further highlighted the interionic interaction regions, revealing extensive van der Waals interactions and the formation of N-H…N type hydrogen bonds. The hydrogen bond formed by the cyclo-N5− and hydroxyl groups was relatively strong, while other hydrogen bonds were weaker. Benefiting from a higher enthalpy of formation, the 1,5-diamino-4-azidotetrazolium pentazolate ([DAT-N3+] [N5−]) compound exhibited the highest detonation performance (D: 9295.77 m·s−1; P: 32.13 GPa), while [DAT-OH+] [N5−] also demonstrated good performance and stability (D: 8924.96 m·s−1; P: 28.85 GPa).
Fluorescence Output Enhancement of Ce3+:YAG Transparent Ceramics by Eutectic Soldering Packaging
Authors: Yi Xuezhuan , Sai Qinglin , Tian Yanna , Jiang Renjie , Li Mingqin
Published: February 2025

This paper demonstrates the application of eutectic welding to Ce3+:YAG transparent ceramics for reliable detection and imaging of UV emission, particularly focusing on demanding conditions, such as high repetition rate, high energy, and high vacuum. A series of Ce3+:YAG transparent ceramics with different Ce3+ doping concentrations (0.1 at%, 0.3 at%, 0.5 at%, and 1.0 at%) were prepared via vacuum sintering. Their crystal microstructure, luminescence properties, transmittance, and fluorescence lifetime were studied. It was found that the optimal Ce3+ doping concentration is 0.3 at%. The measured ultraviolet-to-visible energy conversion efficiency of the 0.3 at% Ce3+:YAG transparent ceramics with a thickness of 1.0 mm is 3.9%. Compared with silicone encapsulated Ce3+:YAG transparent ceramic samples, the eutectic-soldered samples exhibited excellent resistance to temperature quenching of the luminescence, which indicates that eutectic welding can effectively improve the fluorescence performance of Ce3+:YAG transparent ceramics for the application of deep ultraviolet light detection.
Static Behavior of Post-Installed High-Strength Large-Bolt Shear Connector with Fabricated Hybrid Fiber-Reinforced Concrete/Ordinary Concrete Deck
Authors: He Yuliang , Li Junjie , He Wujian , Wu Qiangqiang , Xiang Yiqiang , Yang Ying
Published: February 2025

Recent research indicates that high-strength bolts could be more effectively and efficiently used to connect steel girders and fabricated decks or retrofit existing composite girders than headed studs. To reduce the number of bolt shear connectors and, thus, further accelerate the construction of composite girders, high-strength large bolts could be an excellent alternative, resulting in greater concrete stress below the bolt. Also, hybrid fiber-reinforced concrete (HFRC) has better tensile ductility and strength than that of ordinary concrete (OC). Therefore, this study tried to design eighteen push-out test specimens, including different configurations of bolt shear connectors, to investigate the static properties of post-installed, high-strength, large-bolt shear connectors with fabricated HFRC/OC slabs. The experimental results indicated that the capacity and initial stiffness of a high-strength large through-bolt shear connector was the smallest. The fiber might enhance the capacity and initial stiffness of bolt shear connectors. Increasing the bolt diameter can significantly enhance the initial stiffness and load-bearing capacity, while the clearance of the bolt hole had a great influence on the capacity, initial stiffness, and slippage of the post-installed high-strength large-bolt shear connector. Finally, the capacity equation and slip behavior of post-installed, high-strength, large-bolt shear connector with fabricated HFRC deck were obtained using the regression method, which could provide the reference for their design.
Thin Cells of Polymer-Modified Liquid Crystals Described by Voronoi Diagrams
Authors: Woolhouse Felicity , Dierking Ingo
Published: February 2025

We investigated patterns formed during the polymerization process of bifunctional monomers in a liquid crystal for both large polymer concentrations (polymer-dispersed liquid crystals, PDLC) and small concentrations (polymer-stabilized liquid crystals, PSLC). The resulting experimental patterns are reminiscent of Voronoi diagrams, so a reverse Voronoi algorithm was developed that provides the seed locations of cells, thus allowing a computational reproduction of the experimental patterns. Several metrics were developed to quantify the commonality between the faithful experimental patterns and the idealized and generated ones. This led to descriptions of the experimental patterns with accuracies better than 90% and showed that the curvature or concavity of the cell edges was below 2%. Possible reasons for the discrepancies between the original and generated Voronoi diagrams are discussed. The introduced algorithm and quantification of the patterns could be transferred to many other experimental problems, for example, melting of thin polymer films, ultra-thin metal films, or bio-membranes. The discrepancies between the experimental and ideal Voronoi diagrams are quantified, which may be useful in the quality control of privacy windows, reflective displays, or smart glass.
Transformer-Based Models for Probabilistic Time Series Forecasting with Explanatory Variables
Authors: Caetano Ricardo , Oliveira José Manuel , Ramos Patrícia
Published: February 2025

Accurate demand forecasting is essential for retail operations as it directly impacts supply chain efficiency, inventory management, and financial performance. However, forecasting retail time series presents significant challenges due to their irregular patterns, hierarchical structures, and strong dependence on external factors such as promotions, pricing strategies, and socio-economic conditions. This study evaluates the effectiveness of Transformer-based architectures, specifically Vanilla Transformer, Informer, Autoformer, ETSformer, NSTransformer, and Reformer, for probabilistic time series forecasting in retail. A key focus is the integration of explanatory variables, such as calendar-related indicators, selling prices, and socio-economic factors, which play a crucial role in capturing demand fluctuations. This study assesses how incorporating these variables enhances forecast accuracy, addressing a research gap in the comprehensive evaluation of explanatory variables within multiple Transformer-based models. Empirical results, based on the M5 dataset, show that incorporating explanatory variables generally improves forecasting performance. Models leveraging these variables achieve up to 12.4% reduction in Normalized Root Mean Squared Error (NRMSE) and 2.9% improvement in Mean Absolute Scaled Error (MASE) compared to models that rely solely on past sales. Furthermore, probabilistic forecasting enhances decision making by quantifying uncertainty, providing more reliable demand predictions for risk management. These findings underscore the effectiveness of Transformer-based models in retail forecasting and emphasize the importance of integrating domain-specific explanatory variables to achieve more accurate, context-aware predictions in dynamic retail environments.
A Deep Learning Method of Credit Card Fraud Detection Based on Continuous-Coupled Neural Networks
Authors: Wu Yanxi , Wang Liping , Li Hongyu , Liu Jizhao
Published: February 2025

With the widespread use of credit cards in online and offline transactions, credit card fraud has become a significant challenge in the financial sector. The rapid advancement of payment technologies has led to increasingly sophisticated fraud techniques, necessitating more effective detection methods. While machine learning has been extensively applied in fraud detection, the application of deep learning methods remains relatively limited. Inspired by brain-like computing, this work employs the Continuous-Coupled Neural Network (CCNN) for credit card fraud detection. Unlike traditional neural networks, the CCNN enhances the representation of complex temporal and spatial patterns through continuous neuron activation and dynamic coupling mechanisms. Using the Kaggle Credit Card Fraud Detection (CCFD) dataset, we mitigate data imbalance via the Synthetic Minority Oversampling Technique (SMOTE) and transform sample feature vectors into matrices for training. Experimental results show that our method achieves an accuracy of 0.9998, precision of 0.9996, recall of 1.0000, and an F1-score of 0.9998, surpassing traditional machine learning models, which highlight CCNN’s potential to enhance the security and efficiency of fraud detection in the financial industry.
Impact of Physiological and Psychological Stress on Glaucoma Development and Progression: A Narrative Review
Authors: Isserow Lauren J. , Harris Danielle , Schanzer Nathan , Siesky Brent , Verticchio Vercellin Alice , Wood Keren , Segev Fani , Harris Alon
Published: February 2025

Glaucoma is a leading cause of irreversible blindness worldwide. Presently, elevated intraocular pressure (IOP) is the only approved modifiable risk factor. A consensus of the current literature suggests that both physiological and psychological stress may also impact the lifelong course of glaucoma. Specifically, stress is known to influence sympathetic nervous system activity. An increase in sympathetic nervous system activity may elevate a person’s blood pressure (BP) and IOP, and both are strongly associated with glaucomatous disease. Anxiety and depression have more conflicting evidence in relation to glaucoma. Socioeconomic and environmental stress may worsen adherence to therapy and disease outcomes due to a lack of financial resources and related access to healthcare. Neighborhood quality and environmental conditions, particularly urban environments, have been associated with glaucoma risk factors, higher glaucoma prevalence, and delayed surgical interventions. Racial differences have also been identified, with Black patients being more stressed and likely to present with increased glaucoma severity and faster disease progression than White patients. Mindfulness, meditation, and other forms of psychological relaxation have been shown to reduce IOP and stress biomarkers and result in improved quality of life (QOL). Larger studies in more diverse populations are needed to clarify risk and identify the best therapeutic approaches to reduce stress as a method to improve clinical outcomes and QOL for glaucoma patients.
Vitamin D Deficiency in Kazakhstani Children: Insights from a Systematic Review and Meta-Analysis
Authors: Karibayeva Indira , Bilibayeva Galiya , Iglikova Assiya , Yerzhanova Aya , Alekesheva Roza , Maxudova Makhigul , Ussebayeva Neilya
Published: February 2025

Background and Objectives: Kazakhstan’s unique geographic, dietary, and cultural factors contribute to the widespread occurrence of vitamin D deficiency across the entire country population, particularly among children. This study aims to assess the mean prevalence of vitamin D deficiency in children in Kazakhstan and determine whether it differs between healthy and non-healthy children, as well as between infants and older age groups. Materials and Methods: A comprehensive literature search was performed across five databases by two researchers. Studies were eligible if they were observational and provided the number of children with serum 25-hydroxyvitamin D levels below 20 ng/mL out of the total number of children assessed in Kazakhstan. Results: Eleven studies were included in the analysis, assessing 1396 children, of whom 714 had the outcome of interest. The pooled mean estimate of vitamin D deficiency among children was 56% (95% CI, 46–65%), with particularly concerning rates among infants at 65% (95% CI, 44–82%). No substantial differences were observed between healthy and non-healthy children. Conclusions: The prevalence of vitamin D deficiency among children is alarmingly high. These results highlight the urgent necessity of tackling vitamin D deficiency as a public health priority. Incorporating vitamin D deficiency prevention into Kazakhstan’s national healthcare program is vital for improving child health outcomes and reducing the long-term burden of associated complications.
Next-Generation Cognitive-Behavioral Therapy for Depression: Integrating Digital Tools, Teletherapy, and Personalization for Enhanced Mental Health Outcomes
Authors: Gkintoni Evgenia , Vassilopoulos Stephanos P. , Nikolaou Georgios
Published: February 2025

Background and Objectives: This systematic review aims to present the latest developments in next-generation CBT interventions of digital support tools, teletherapies, and personalized treatment modules in enhancing accessibility, improving treatment adherence, and optimizing therapeutic outcomes for depression. Materials and Methods: This review analyzed 81 PRISMA-guided studies on the efficacy, feasibility, and applicability of NG-CBT approaches. Other important innovations include web-based interventions, AI-operated chatbots, and teletherapy platforms, each of which serves as a critical challenge in delivering mental health care. Key messages have emerged regarding technological readiness, patient engagement, and the changing role of therapists within the digital context of care. Results: Findings indicate that NG-CBT interventions improve treatment accessibility and engagement while maintaining clinical effectiveness. Personalized digital tools enhance adherence, and teletherapy platforms provide scalable and cost-effective alternatives to traditional therapy. Conclusions: Such developments promise great avenues for decreasing the global burden of depression and enhancing the quality of life through novel, accessible, and high-quality therapeutic approaches.
Comparison of Incisional Hernia Rates Between General and Gynecological Surgery Procedures
Authors: Spear Krista , Davenport Daniel L. , Butler Lance , Plymale Margaret , Roth John Scott
Published: February 2025

Background and Objectives: Incisional hernias are a common and costly complication of surgery, occurring in up to 20% of midline incisions within 3 years of initial operation. Risk factors for incisional hernia include incision site, fascial closure technique, body mass index (BMI), surgical site infections, and gastrointestinal surgery. Limited studies have compared procedural type as a risk factor for hernia formation. The goal of this study was to examine incisional hernia rates among general surgical and gynecologic procedures. Materials and Methods: We queried our Research Data Warehouse for inpatients who had undergone common open abdominal surgeries between January 2012 and December 2022. Patients’ index operations were identified based upon Current Procedural Terminology (CPT) codes and presence of a postoperative incisional hernia was determined by occurrence of an incisional hernia ICD10 diagnosis code more than 2 weeks postoperatively. The main study outcome was time to incisional hernia diagnosis. Results: A total of 4447 patients were identified. Postoperatively, 241 (5.4%) patients were diagnosed with incisional hernias. Hernia rates at 1, 3 and 5 years were 3% (SE 0.003), 6% (0.004) and 8% (0.005), respectively. Patients undergoing exploratory laparotomy (hazard ratio 3.9, p < 0.001), bowel resection (HR 5.5, p < 0.001), and primary hernia repair (HR 13.0, p < 0.001) were found to have significantly increased risk for incisional hernia development compared to those undergoing hysterectomy, following adjustment for comorbid risks, age, sex, and BMI. Conclusions: Exploratory laparotomy, bowel resection, and primary ventral hernia repair are associated with a higher incidence of incisional hernia relative to gynecologic procedures. This relatively unstudied comparison warrants further investigation.
Bioconversion of Alpha-Cembratriene-4,6-diol into High-Value Compound Farnesal Through Employment of a Novel Stenotrophomonas maltophilia H3-1 Strain
Authors: Huang Shen , Cheng Jiaming , Hu Huibo , Rasool Aamir , Manzoor Robina , Mao Duobin
Published: February 2025

Alpha-cembratriene-4,6-diol (α-CBT-diol) is a complex diterpenoid primarily found in Solanaceae (i.e., tobacco leaves), Pinaceae, and marine corals. Due to its intricate chemical structure, it serves as a precursor for several aroma compounds, including farnesal. Farnesal and its derivatives have applications across various fields, such as the fragrance and flavor industry, pharmaceuticals, agriculture, and cosmetics. In this study, Stenotrophomonas maltophilia H3-1, a strain capable of efficiently biodegrading α-CBT-diol into farnesal, was isolated from soil and identified through 16S rDNA sequence analysis. S. maltophilia H3-1 biodegraded 93.3% of α-CBT-diol (300 mg/L) within 36 h when grown under optimized culture conditions, including a temperature of 40 °C, pH of 8, 2 g/L maltose, and 2 g/L ammonium sulfate. Theoretically, this strain can produce 201 mg/L of farnesal during the biotransformation of α-CBT-diol. The putative α-CBT-diol bioconversion pathway expressed in S. maltophilia H3-1 is also proposed. This is the first study to report the bioconversion of α-CBT-diol into the high-value compound farnesal using a novel S. maltophilia H3-1 strain. It highlights that other compounds found in tobacco can also be bioconverted into valuable products.
Electron Scattering Cross Sections from Thiazole for Impact Energies Ranging from 1 to 1000 eV
Authors: García-Abenza Adrián , Lozano Ana I. , Oller Juan C. , Rosado Jaime , Blanco Francisco , Limão-Vieira Paulo , García Gustavo
Published: February 2025

Total electron scattering cross sections (TCSs), in the energy range of 1–100 eV, have been measured with a high-resolution magnetically confined electron transmission apparatus, with total uncertainty limits estimated to be within ±5%. No previous experimental TCS data have been found for comparison. Electron attachment resonances, corresponding to transient negative ion formation, have been identified for energies below 20 eV by analyzing their contribution to the measured local maxima of the TCSs. Most of these resonances were observed for the first time. By means of our screening-corrected additivity rule (including interference effects) calculation method (IAM-SCAR + I), we extended TCS values to up to 1000 eV. This method also provides integral elastic, electronic excitation, and ionization cross sections for impact energies above 20 eV with total uncertainties of about ±10%. Comparisons, where possible, of the present electron scattering values with other values available in the literature are given.
Structural Evolution Leading to the Thermosalient Phase Transition of Oxitropium Bromide
Authors: Klaser Teodoro , Popović Jasminka , Lončarić Ivor , Skoko Željko
Published: February 2025

This study investigates the thermosalient effect in oxitropium bromide, with a focus on the role of anisotropic thermal expansion, elastic properties, and sound propagation in driving this phenomenon. Variable-temperature X-ray powder diffraction (VTXRPD) revealed significant anisotropic thermal expansion, including negative thermal expansion (NTE) along the c-axis in the low-temperature Form A. Density functional theory (DFT) calculations were used to analyze elastic properties of oxitropium bromide and confirmed that it does not exhibit negative compressibility, emphasizing thermal anisotropy as the primary factor in the phase transition. Studies of elastic constants and sound propagation demonstrated a preferred pathway for energy transfer along the z-direction, enabling rapid strain release during the phase transition. These findings confirmed that the thermosalient effect arises from cooperative molecular motion, resulting in an abrupt and energetic transformation driven by the interplay of structural anisotropy and elastic properties.
Advanced TiO2-Based Photocatalytic Systems for Water Splitting: Comprehensive Review from Fundamentals to Manufacturing
Authors: Ahasan Tarek , Edirisooriya E. M. N. Thiloka , Senanayake Punhasa S. , Xu Pei , Wang Huiyao
Published: February 2025

The global imperative for clean energy solutions has positioned photocatalytic water splitting as a promising pathway for sustainable hydrogen production. This review comprehensively analyzes recent advances in TiO2-based photocatalytic systems, focusing on materials engineering, water source effects, and scale-up strategies. We recognize the advancements in nanoscale architectural design, the engineered heterojunction of catalysts, and cocatalyst integration, which have significantly enhanced photocatalytic efficiency. Particular emphasis is placed on the crucial role of water chemistry in photocatalytic system performance, analyzing how different water sources—from wastewater to seawater—impact hydrogen evolution rates and system stability. Additionally, the review addresses key challenges in scaling up these systems, including the optimization of reactor design, light distribution, and mass transfer. Recent developments in artificial intelligence-driven materials discovery and process optimization are discussed, along with emerging opportunities in bio-hybrid systems and CO2 reduction coupling. Through critical analysis, we identify the fundamental challenges and propose strategic research directions for advancing TiO2-based photocatalytic technology toward practical implementation. This work will provide a comprehensive framework for exploring advanced TiO2-based composite materials and developing efficient and scalable photocatalytic systems for multifunctional simultaneous hydrogen production.
Anserine, Balenine, and Ergothioneine: Impact of Histidine-Containing Compounds on Exercise Performance—A Narrative Review
Authors: Jędrejko Maciej , Kała Katarzyna , Muszyńska Bożena
Published: February 2025

Histidine is an amino acid which plays a critical role in protein synthesis, muscle buffering during anaerobic exercise, and antioxidation. It also acts as a precursor to carnosine, a dipeptide that enhances physical performance by being present in fast-contracting muscle fibers and contributing to buffering capacity. Recent studies have examined other histidine-containing compounds, such as anserine, balenine, and ergothioneine, to assess their potential benefits for physical activity. This narrative review focuses on the literature about the effects of dietary supplementation with these histidine-containing compounds on exercise capacity in animals and humans. The findings indicate that anserine may improve physical performance and reduce fatigue, particularly in quick, repetitive activities. Although balenine has been less extensively studied, it has shown promise in enhancing muscle regeneration and antioxidative defense in animal models. Ergothioneine, a sulfur-containing histidine derivative, displayed antioxidant and anti-inflammatory properties in both animal and human studies, suggesting its potential role in reducing exercise-induced oxidative stress and aiding recovery. The diversity of the presented studies and their limitations do not provide an opportunity to confirm the ergogenic properties of the histidine-containing compounds studied. Nevertheless, supplementation with anserine and ergothioneine shows promise for enhancing physical performance and recovery, though further research is required to better understand their mechanisms and optimize their use in sports and exercise.
Cannabis: Zone Aspects of Raw Plant Components in Sport—A Narrative Review
Authors: Flangea Corina , Vlad Daliborca , Popescu Roxana , Dumitrascu Victor , Rata Andreea Luciana , Tryfon Maria Erika , Balasoiu Bogdan , Vlad Cristian Sebastian
Published: February 2025

Objectives/Background: The Cannabis genus contain a mixture of cannabinoids and other minor components which have been studied so far. In this narrative review, we highlight the main aspects of the polarized discussion between abuse and toxicity versus the benefits of the compounds found in the Cannabis sativa plant. Methods: We investigated databases such as PubMed, Google Scholar, Web of Science and World Anti-doping Agency (WADA) documents for scientific publications that can elucidate the heated discussion related to the negative aspects of addiction, organ damage and improved sports performance and the medical benefits, particularly in athletes, of some compounds that are promising as nutrients. Results: Scientific arguments bring forward the harmful effects of cannabinoids, ethical and legislative aspects of their usage as doping substances in sports. We present the synthesis and metabolism of the main cannabis compounds along with identification methods for routine anti-doping tests. Numerous other studies attest to the beneficial effects, which could bring a therapeutic advantage to athletes in case of injuries. These benefits recommend Cannabis sativa compounds as nutrients, as well as potential pharmacological agents. Conclusions and future perspectives: From the perspective of both athletes and illegal use investigators in sport, there are many interpretations, presented and discussed in this review. Despite many recent studies on cannabis species, there is very little research on the beneficial effects in active athletes, especially on large groups compared to placebo. These studies may complete the current vision of this topic and clarify the hypotheses launched as discussions in this review.
Simulation of Coherent Beam Propagation in Laboratory and Numerical Experiments: A Comparison of Results
Authors: Kanev Feodor , Rukosuev Alexey , Galaktionov Ilya , Sheldakova Julia , Veretekhin Igor
Published: February 2025

This paper presents the results of processing and systematizing data from laboratory and numerical experiments to correct the distortions of laser radiation propagating through a randomly inhomogeneous medium. The information obtained allows for an accurate estimation of the effectiveness of compensating for turbulent fluctuations in the refractive index along the beam propagation path. Experimentally derived radiation parameters were compared with corresponding values calculated using an optical system model. Limitations of the numerical simulation, stemming from inherent model constraints, were identified, as were discrepancies between experimental and theoretical results, and a reason for these discrepancies was provided.
Flat Emission Silicon Nitride Grating Couplers for Lidar Optical Antennas
Authors: Prousalidi Thenia , Syriopoulos Georgios , Kyriazi Evrydiki , Botter Roel , Zervos Charalampos , Poulopoulos Giannis , Apostolopoulos Dimitrios
Published: February 2025

Light detection and ranging (Lidar) is a key enabling technology for autonomous vehicles and drones. Its emerging implementations are based on photonic integrated circuits (PICs) and optical phased arrays (OPAs). In this work, we introduce a novel approach to the design of OPA Lidar antennas based on Si3N4 grating couplers. The well-established TriPleX platform and the asymmetric double stripe waveguide geometry with full etching are employed, ensuring low complexity and simple fabrication combined with the low-loss advantages of the platform. The design study aims to optimize the performance of the grating coupler-based radiators as well as the OPA, thus enhancing the overall capabilities of Si3N4-based Lidar. Uniform and non-uniform grating structures are considered, achieving θ and φ angle divergences of 0.9° and 32° and 0.54° and 25.41°, respectively. Also, wavelength sensitivity of 7°/100 nm is achieved. Lastly, the fundamental OPA parameters are investigated, and 35 dBi of peak directivity is achieved for an eight-element OPA.
Functionalization of Phenolic Aldehydes for the Preparation of Sustainable Polyesters and Polyurethanes
Authors: Carafa Rachele N. , Fernandes Brigida V. , Repiquet Clara , Rana Sidrah , Foucher Daniel A. , Sacripante Guerino G.
Published: February 2025

Biobased organic diols derived from the phenolic aldehyde by-products in the depolymerization of lignin (4-hydroxybenzaldehyde, vanillin, and syringaldehyde) for the synthesis of polyesters and polyurethanes is described. Methods to prepare lignin-based diols involved a two-step synthetic route using either a hydroxy alkylation and aldehyde reduction or an aldehyde reduction and Williamson–Ether substitution. The preparation of five polyesters (PEs) and ten polyurethanes (PUs) from lignin-based diols was also performed and their physical and thermal properties were analyzed. DSC analysis confirmed the amorphous nature of all synthesized polymers, and GPC analysis revealed broad dispersities and high molecular weights. Two PE polyols were also derived from a vanillin-based diol at concentrations of 10 and 25 wt% for their usage in sustainable PU foams. PU foams were prepared from these polyols, where it was found that only the foam containing the 10 wt% formulation was suitable for mechanical testing. The PU foam samples were found to have good hardness and tensile strengths compared to both control foams, showing potential for the incorporation of biobased polyols for PU foam formation.
Investigation of the Influence of Manufacturing on Filament Production and Its Impact on Additive Manufactured Structures
Authors: Refat Mohamed , Maertens Robert , Weiss Patrick , Henning Frank , Schulze Volker , Liebig Wilfried V.
Published: February 2025

In this study, the effect of various parameters of a single screw extruder on the rheology and mechanical properties of a polylactic acid (PLA) filament with a 1.75 mm diameter was investigated. The barrel temperature, nozzle and cooling bath temperature, screw speed, nozzle diameter, water bath length, and distance to the nozzle were the process variables. A Taguchi experimental design was implemented using an L8 orthogonal matrix with seven factors and two levels, and their influence on roundness and diameter were evaluated. Among the various processing parameters, the temperature of the cooling bath affected the roundness the most. The mechanical properties and surface roughness of the PLA filament were examined using a tensile test and nanofocus optical system, respectively. Moreover, to assess the filament’s reliability and investigate its behavior further, the filament was used to print 0° plates, and then dog-bone samples were cut from them to evaluate the mechanical properties of the printed specimens. Finally, the results indicate that improved-roundness filaments of 0.004 mm can lead to enhanced mechanical properties in 3D-printed samples with 3.54 MPa.
Cationized Hemp Fiber to Improve the Interfacial Adhesion in PLA Composite
Authors: Valin Fernández Meylí , Monsalves Rodríguez Matías Angelo , Medina Muñoz Carlos Andrés , Palacio Daniel A. , Soto Angelo Giovanni Oñate , Valin Rivera José Luis , Valenzuela Diaz Francisco Rolando
Published: February 2025

3D printing with biodegradable polymers such as polylactic acid (PLA) is a sustainable alternative to conventional petroleum-derived plastics. However, improving the mechanical properties of PLA remains a challenge. This study explores the incorporation of chemically treated hemp fibers to improve the interfacial adhesion and mechanical strength of PLA filaments. Samples with PLA and hemp were prepared by subjecting the fibers to cationization treatment with (3-chloro-hydroxypropyl) tri-methylammonium (EPTA) and functionalization with glycidyl methacrylate (GMA). EPTA improves adhesion mainly through surface modification, increasing reactive functional groups in cellulose, while GMA improves interfacial adhesion by forming covalent bonds with both the fiber and PLA and improves the dispersion of the fiber in the matrix. Mechanical properties were evaluated by tensile testing, as well as fracture morphology by scanning electron microscopy (SEM) and X-ray energy dispersive analysis (EDS). The results showed that the addition of untreated hemp significantly reduced the strength of PLA, but cationization with EPTA improved interfacial adhesion and increased tensile strength by 615%. The combination of treated fibers and GMA further optimized the mechanical properties, reaching values similar to pure PLA. These findings indicate that the chemical modification of natural fibers facilitates their integration into PLA filaments for 3D printing, promoting sustainable materials without compromising mechanical performance.
Isothermal Equation of State of Polyether Ether Ketone (PEEK) by Optical Imaging Method in Diamond Anvil Cell
Authors: Chen Ying , Yang Ning , Zhang Yi , Liu Lei
Published: February 2025

Polymers serve as important functional materials in various environments, including high-pressure conditions. However, the behavior of polymers under high pressure is currently less understood. In this study, the isothermal equation of state of polyether ether ketone (PEEK), an important polymer, was measured using the diamond anvil cell technique at up to 8 GPa. The isotropic compression behavior of PEEK samples was investigated by monitoring the area change in PEEK disks during the compression process using the optical imaging method. The present results shed light on the mechanical properties of PEEK under extreme conditions, which will guide the applications of PEEK at high pressures.
Enhancing Integrated Circuit Quality Control: A CNN-Based Approach for Defect Detection in Scanning Acoustic Tomography Images
Authors: Jou Yung-Tsan , Putra Vicky Pratama , Silitonga Riana Magdalena , Sukwadi Ronald , Inderawati Maria Magdalena Wahyuni
Published: February 2025

The demand for integrated circuit (IC) chips has risen markedly across various industries in conjunction with advancements in global technology. Prior to packaging, IC elements undergo several processes, including wafer dicing, wire bonding, and encapsulation. Scanning Acoustic Tomography (SAT) effectively analyzes the internal structures of integrated circuit products, thereby preventing the supply of defective components, including chip fractures, delamination, voids, and adhesion issues. The study aims to reduce operator eye strain, enhance productivity, and minimize employee turnover rates by proposing the use of convolutional neural networks (CNN) to develop a predictive model for automating defect detection in integrated circuit (IC) products within SAT images, replacing traditional visual inspections. To enhance the accuracy of the CNN model, we implement the flood-fill algorithm as the primary augmentation strategy and create an image augmentation model in Python. This method produces a training set that accurately reflects the true characteristics of defects, thereby mitigating the problem of limited defect data and ensuring the model is trained on reliable information. The incorporation of various rates and scaling factors into SAT defect images, along with the manipulation of the original defect, contributes to the development of a robust dataset suitable for real-world testing. The CNN model is trained using various batch sizes, resulting in customized training datasets and predictive models to improve accuracy. Key findings indicate that employing 40× augmentation alongside a batch size of 32 enhances the model’s performance, yielding a missed detection rate below 0.4% and a false alarm rate of 0.1%. This model offers an improved solution to the issue of manual inspections on assemblies, thereby alleviating operator stress and establishing a robust framework for automated integrated circuit quality management.
Cyber, Geopolitical, and Financial Risks in Rare Earth Markets: Drivers of Market Volatility
Authors: Calefariu Giol Emilia , Panazan Oana , Gheorghe Catalin
Published: February 2025

This study examines the integrated impacts of cyberattacks, geopolitical, and financial market volatility on rare earth markets during the 2014–2024 period, using Time-Varying Parameter Vector Autoregression and wavelet analysis. By bridging critical gaps in the literature, this research provides a comprehensive framework for understanding the compounded effects of emerging risks on market dynamics. The analysis includes key market indices (SOLLIT, PICK, SPGSIN, GSPTXGM, MVREMXTR, and XME), alongside green energy prices, to capture cross-market dependencies. The findings reveal that financial volatility exerts the most persistent long-term influence, while geopolitical events, such as the US-China trade tensions and the Ukraine conflict, trigger significant market disruptions. Cyberattacks, although episodic, exacerbate short-term volatility, especially during global crises. Rising green energy prices further amplify vulnerabilities in supply chains, underscoring the interconnectedness of rare earth markets and the sustainable energy transition. This research provides actionable insights for integrated risk management strategies, emphasizing supply chain diversification, enhanced cybersecurity, and international cooperation to ensure market stability and resilience in the energy transition.
Calibration of Short-Wave Infrared Spectrometer for Atmosphere Methane Monitoring
Authors: Li Haoran , Si Fuqi , Xi Liang , Lin Fang , Jiang Yu , Liu Fenglei , Zeng Yi , Han Yunkun , Wu Kaili
Published: February 2025

The short-wave infrared (SWIR) grating imaging spectrometer based on indium gallium arsenide (InGaAs) material inverts the atmospheric methane concentration by measuring the scattered light signals in the sky. This study proposes spectral and radiometric calibration methods for the characteristics of the spectrometer, such as the small-area array, high signal-to-noise ratio, and high spectral resolution. Four spectral response function models, namely, the Gauss, Lorentz, Voigt and super-Gaussian models, were compared during spectral calibration. With a fitting residual of 0.032, the Gauss model was found to be the most suitable spectral response function for the spectrometer. Based on the spectral response function, the spectral range and spectral resolution of the spectrometer were determined to be 1592.4–1677.2 and 0.1867 nm, respectively. In addition, radiometric calibration of the spectrometer was achieved by combining an integrating sphere and linear measuring instrument. Moreover, absolute and relative radiometric calibrations of the spectrometer were performed. The low signal response problem caused by the quantum efficiency of the detector at long wavelength was corrected, and the uncertainty and non-stability uncertainty of absolute radiometric calibration were calculated to be less than 0.2%. Finally, the calibrated spectrometer was used to accurately measure the solar scattering spectrum in the SWIR band, and the solar spectrum was simulated by the radiative transfer model for verification; the measurement error was found to be 5%. Concurrently, a methane sample gas experiment was performed using the integrating-sphere light source, and the measurement error was less than 4%. This fully proves the effectiveness of the spectral and radiometric calibrations of the SWIR spectrometer and strongly guarantees a subsequent, rapid and accurate inversion of atmospheric methane concentration.
Ecosystem Service Trade-Offs and Synergies in a Temperate Agricultural Region in Northeast China
Authors: Li Yuhong , Cong Yu , Zhang Jin , Wang Lei , Fei Long
Published: February 2025

Ecosystem services (ESs) are essential for balancing environmental sustainability and socio-economic development. However, the sustainability of ESs and their relationships are increasingly threatened by global climate change and intensifying human activities, particularly in ecologically sensitive and agriculturally-intensive regions. The Songnen Plain, a crucial agricultural region in Northeast China, faces considerable challenges in sustaining its ESs due to the overexploitation of agricultural land, environmental degradation, and climate variability. This study assessed five key ESs in the Songnen Plain from 2000 to 2020 across multiple scales: habitat quality (HQ), soil conservation (SC), water yield (WY), food production (FP), and windbreaking and sand fixing (WS). We evaluated the trade-offs and synergies between these ESs, as well as the driving factors of the main ES trade-offs. Our findings indicate that provisioning services (WY and FP) and regulating services (SC and WS) improved over time, with FP exhibiting the most significant increase at 203.90%, while supporting services (HQ) declined by 32.61%. The primary ecosystem service multifunctionality areas were those that provided FP, SC, and WY, accounting for 58% of the total. ES trade-offs and synergies varied across spatial scales, with stronger synergies being observed at the pixel scale and more pronounced trade-offs at the county scale. Climate factors, particularly precipitation and temperature, played a more significant role in shaping ES trade-offs than anthropogenic factors. Our study provides valuable insights into the restoration and sustainable management of ESs in temperate agriculturally-intensive regions, with significant implications for the protection of the northeastern black soil region and safeguarding national food security.
Optimizing Stacked Ensemble Machine Learning Models for Accurate Wildfire Severity Mapping
Authors: Nguyen Van Linh , Lee Giha
Published: February 2025

Wildfires are increasingly frequent and severe, posing substantial risks to ecosystems, communities, and infrastructure. Accurately mapping wildfire severity (WSM) using remote sensing and machine learning (ML) is critical for evaluating damages, informing recovery efforts, and guiding long-term mitigation strategies. Stacking ensemble ML (SEML) enhances predictive accuracy and robustness by combining multiple diverse models into a single meta-learned predictor. This approach leverages the complementary strengths of individual base learners while reducing variance, ultimately improving model reliability. This study aims to optimize a SEML framework to (1) identify the most effective ML models for use as base learners and meta-learners, and (2) determine the optimal number of base models needed for robust and accurate wildfire severity predictions. The study utilizes six ML models—Random Forests (RF), Support Vector Machines (SVM), k-Nearest Neighbors (KNN), Linear Regression (LR), Adaptive Boosting (AB), and Multilayer Perceptron (MLP)—to construct an SEML. To quantify wildfire impacts, we extracted 118 spectral indices from post-fire Landsat-8 data and incorporated four additional predictors (land cover, elevation, slope, and aspect). A dataset of 911 CBI observations from 18 wildfire events was used for training, and models were validated through cross-validation and bootstrapping to ensure robustness. To address multicollinearity and reduce computational complexity, we applied Linear Discriminant Analysis (LDA) and condensed the dataset into three primary components. Our results indicated that simpler models, notably LR and KNN, performed well as meta-learners, with LR achieving the highest predictive accuracy. Moreover, using only two base learners (RF and SVM) was sufficient to realize optimal SEML performance, with an overall accuracy and precision of 0.661, recall of 0.662, and F1-score of 0.656. These findings demonstrate that SEML can enhance wildfire severity mapping by improving prediction accuracy and supporting more informed resource allocation and management decisions. Future research should explore additional meta-learning approaches and incorporate emerging remote sensing data sources such as hyperspectral and LiDAR.
Development and Testing of a Compact Remote Time-Gated Raman Spectrometer for In Situ Lunar Exploration
Authors: Zhao Haiting , Liu Xiangfeng , Xu Weiming , Wen Daoyuantian , Xie Jianan , Zhang Zhenqiang , Jiang Ziqing , Ling Zongcheng , He Zhiping , Shu Rong , Wang Jianyu
Published: February 2025

Raman spectroscopy is capable of precisely identifying and analyzing the composition and properties of samples collected from the lunar surface, providing crucial data support for lunar scientific research. However, in situ Raman spectroscopy on the lunar surface faces challenges such as weak Raman scattering from targets, alongside requirements for lightweight and long-distance detection. To address these challenges, time-gated Raman spectroscopy (TG-LRS) based on a passively Q-switched pulsed laser and a linear intensified charge-coupled device (ICCD), which enable simultaneous signal amplification and background suppression, has been developed to evaluate the impact of key operational parameters on Raman signal detection and to explore miniaturization optimization. The TG-LRS system includes a 40 mm zoom telescope, a passively Q-switched 532 nm pulsed laser, a fiber optic delay line, a miniature spectrometer, and a linear ICCD detector. It achieves an electronic gating width under 20 ns. Within a detection range of 1.1–3.0 m, the optimal delay time varies linearly from 20 to 33 ns. Raman signal intensity increases with image intensifier gain, while the signal-to-noise ratio peaks at a gain range of 800–900 V before declining. Furthermore, the effects of focal depth, telescope aperture, laser energy, and integration time were studied. The Raman spectra of lunar minerals were successfully obtained in the lab, confirming the system’s ability to suppress solar background light. This demonstrates the feasibility of in situ Raman spectroscopy on the lunar surface and offers strong technical support for future missions.