bluuebunny/crossref_metadata_2025 huggingface dataset:
Causal Relationships Between Environmental Exposures, Iron Metabolism, Hematuria Markers, and Rheumatoid Arthritis: An Investigation Using Mendelian Randomization
Authors: Wang Chao , Xie Wenqing , Wang Chenggong , Zhu Yong , Zhong Da
Published: February 2025

Background: Rheumatoid arthritis (RA) is a globally prevalent chronic inflammatory disease. Environmental exposures, such as air pollution and smoking, are considered potential risk factors. However, the causal relationships and underlying mechanisms between these factors and RA are not fully understood. Methods: This study utilized large-scale genome-wide association studies (GWASs) from European ethnic backgrounds and employed bidirectional two-sample Mendelian randomization (MR) to investigate the relationships between air pollution, smoking, and RA. Genetic correlations were assessed using linkage disequilibrium score regression (LDSC). Furthermore, mediation analysis was conducted to evaluate the potential mediating roles of iron metabolism and urinary biomarkers in these relationships. Results: The MR analysis revealed that genetically predicted lifetime smoking intensity was associated with an 85% increased risk of RA. Subgroup analysis differentiating between seropositive RA (SPRA) and seronegative RA (SNRA) showed a causal association with SPRA, but not with SNRA. C-reactive protein was identified as a mediator in the relationship between lifetime smoking and both RA and SPRA, mediating 18.23% and 32.45% of the effects, respectively. Genetic correlation analysis further confirmed a positive genetic association between smoking and both RA and SPRA. Conclusions: This study provides significant insights into the genetic and causal connections between air pollution, smoking, and the development of RA, highlighting the mediating role of C-reactive protein. These findings not only offer new perspectives on how smoking might enhance RA risk through inflammatory pathways but also underscore the importance of reducing smoking exposure in public health strategies.
Advances and Challenges in Modeling Autosomal Dominant Polycystic Kidney Disease: A Focus on Kidney Organoids
Authors: Gu Jinglan , Liu Fei , Li Lu , Mao Jianhua
Published: February 2025

Autosomal dominant polycystic kidney disease (ADPKD) is a prevalent hereditary disorder characterized by distinct phenotypic variability that has posed challenges for advancing in-depth research. Recent advancements in kidney organoid construction technologies have enabled researchers to simulate kidney development and create simplified in vitro experimental environments, allowing for more direct observation of how genetic mutations drive pathological phenotypes and disrupt physiological functions. Emerging technologies, such as microfluidic bioreactor culture systems and single-cell transcriptomics, have further supported the development of complex ADPKD organoids, offering robust models for exploring disease mechanisms and facilitating drug discovery. Nevertheless, significant challenges remain in constructing more accurate ADPKD disease models. This review will summarize recent advances in ADPKD organoid construction, focusing on the limitations of the current techniques and the critical issues that need to be addressed for future breakthroughs. New and Noteworthy: This review presents recent advancements in ADPKD organoid construction, particularly iPSC-derived models, offering new insights into disease mechanisms and drug discovery. It focuses on challenges such as limited vascularization and maturity, proposing potential solutions through emerging technologies. The ongoing optimization of ADPKD organoid models is expected to enhance understanding of the disease and drive breakthroughs in disease mechanisms and targeted therapy development.
Plants Inspired Biomimetics Architecture in Modern Buildings: A Review of Form, Function and Energy
Authors: Bijari Maryam , Aflaki Ardalan , Esfandiari Masoud
Published: February 2025

Biomimicry architecture provides innovative solutions to contemporary environmental challenges by drawing inspiration from nature’s strategies to enhance sustainability and energy efficiency in the built environment. Plants, with their remarkable ability to adapt to changes in light, temperature, and humidity, serve as a central model for biomimetic design due to their potential to optimize energy use and improve building performance. By leveraging these natural principles, biomimetic architecture can significantly reduce carbon emissions and create eco-friendly structures that respond dynamically to environmental conditions. This approach not only addresses the urgent need for sustainable development but also fosters harmony between human-made environments and the natural world. This study offers a comprehensive review of biomimetic technologies, focusing on their role in improving energy efficiency and building performance. Also, it examines a range of global case studies that have successfully implemented biomimicry, showcasing its versatility and effectiveness across diverse environmental and architectural contexts. Based on these insights, this research proposes a novel design inspired by the moonflower plant, which adapts to its environment by responding to external stimuli. The proposed design applies these adaptive strategies to architectural solutions, enabling buildings to optimize performance by dynamically interacting with environmental conditions such as light and temperature. By analyzing biomimetic principles and their applications, this study contributes to the growing body of knowledge on sustainable architecture. It highlights the potential of biomimicry to balance environmental sustainability with economic growth, offering valuable insights for architects, designers, and policymakers seeking to create greener, more efficient built environments.
Bird Collisions with an Unmarked Extra-High Voltage Transmission Line in an Average Riverine Landscape: An Appeal to Take a Closer Look
Authors: Reinhardt Arno , Mercker Moritz , Sabel Maike , Henningsen Kristina , Bernshausen Frank
Published: February 2025

Anthropogenic structures such as overhead powerlines pose potentially high collision risks to flying animals, particularly birds, leading to millions of fatalities each year. Studies of bird collisions with powerlines to date, however, have estimated different numbers of collision per year and per kilometer in highly variable landscapes. This study aimed to clarify the risk of bird collisions with powerlines in an average landscape, to overcome the bias towards studies in collision hotspots. We conducted experiments to determine searcher efficiency, removal, and decomposition rates of collided birds as well as searching for collision victims and recording flight movements and flight reactions towards the powerlines. Annual bird-strike rates and flight phenology were analyzed using generalized additive models (GAMs). We estimated 50.1 collision victims per powerline kilometer per year and demonstrated that pigeons (especially Wood Pigeon, Columba palumbus) accounted for the largest proportion of collision victims (approximately 65%). Our study thus offers the opportunity to estimate the number of bird collisions (and the range of species) that can be expected in areas that are not particularly rich in bird life or sensitive, especially in view of the planned intensive expansion of energy structures in the context of the green energy transition.
The Value of Non-Invasive Optimal Vessel Analysis Quantitative Magnetic Resonance Angiography for Studying Flow and Collateral Patterns in Patients with Bilateral Carotid Steno-Occlusive Disease
Authors: Helg Fiona , Colombo Elisa , Inauen Corinne , Höbner Lara Maria , Sebök Martina , Schubert Tilman , Fierstra Jorn , Spinello Antonio , Wegener Susanne , Luft Andreas R. , Kulcsar Zsolt , Regli Luca , Esposito Giuseppe
Published: February 2025

Background/Objectives: Bilateral steno-occlusive disease of the internal carotid artery (ICA) carries an increased stroke risk with associated high morbidity and mortality. Management of these patients is often complex. In this study, we evaluate the value of non-invasive optimal vessel analysis quantitative magnetic resonance angiography (NOVA-qMRA) for studying flow and collateral patterns in patients with bilateral carotid steno-occlusive disease. Methods: Patients with bilateral ICA-stenosis ≥ 50% who received NOVA-qMRA were included in this study. The volume flow rates (VFRs) of the A2-segment of the anterior cerebral artery (A2-ACA), M1-segment of the middle cerebral artery (M1-MCA), and P2-segment of the posterior cerebral artery (P2-PCA) were analyzed. Demographic, clinical, and treatment data were collected. Results: Twenty-two patients (mean age ± SD: 68 ± 10 years) were included. Nineteen patients (86%) were symptomatic. Thirteen patients (59%) were revascularized; among them, M1-VFR was significantly lower (p-value = 0.01) on the side selected for revascularization (88 mL/min ± 53) compared to the contralateral one (130 mL/min ± 56). P2-VFR was significantly higher (p-value = 0.04) in the treated subgroup (108 mL/min ± 41) than in the non-treated one (83 mL/min ± 34). Conclusions: The present study supports the use of NOVA-qMRA to study flow and collateral patterns in patients with bilateral steno-occlusive carotid disease, especially M1- and P2-VFR. This information may be helpful for decision-making and to tailor revascularization treatment.
Gender Differences in Clinical and Biochemical Variables of Patients Affected by Bipolar Disorder
Authors: Piccirilli Luigi , Capuzzi Enrico , Legnani Francesca , Di Paolo Martina , Pan Anna , Ceresa Alessandro , Esposito Cecilia Maria , Cirella Luisa , Surace Teresa , Tagliabue Ilaria , Clerici Massimo , Buoli Massimiliano
Published: February 2025

Introduction: Bipolar disorder (BD) affects over 1% of the global population and significantly impacts psychosocial functioning and life expectancy. This manuscript has the objective of investigating gender differences in the clinical and biochemical parameters of patients affected by BD. Methods: This retrospective cross-sectional study examined 672 patients diagnosed with BD in psychiatric wards in Milan and Monza. Clinical data and biochemical parameters were collected on the first day of hospitalization. Independent sample t-tests, chi-square tests and binary logistic regressions were performed to identify gender differences in BD. Results: With regard to univariate analyses, women were found to be more susceptible to psychiatric comorbidities (χ2 = 12.75, p < 0.01), medical comorbidities (χ2 = 45.38, p < 0.01), obesity (χ2 = 6.75, p = 0.01) and hypercholesterolemia (χ2 = 23.54, p < 0.01), as well as to having more mood episodes in the year prior to hospitalization (t = 5.69, p < 0.01). Men were found to be more likely to develop psychotic symptoms (χ2 = 4.40, p = 0.04), to be tobacco smokers (χ2 = 15.13, p < 0.01) and to have substance abuse disorders (χ2 = 14.66, p = <0.01). Logistic regression analyses showed that women compared to men showed more psychiatric comorbidity (p < 0.01), higher Global Assessment of Functioning (GAF) scores (p = 0.05) and higher total cholesterol plasma levels (p < 0.01); however, they also had fewer red blood cells (p < 0.01) and lower creatinine plasma levels (p < 0.01). Conclusions: Female patients (compared to males) exhibited higher levels of global functioning despite the higher frequency of psychiatric comorbidity and susceptibility to metabolic complications; consistent with earlier studies, female patients also showed higher cholesterol levels. Further studies will have to confirm the present findings and identify gender-related clinical pathways for the management of BD.
Application of Resistometric Sensors in Investigation of Zinc Corrosion in Simulated Concrete Environments
Authors: Reiser Matěj , Kouřil Milan , Forcellese Pietro , Bellezze Tiziano
Published: February 2025

The aim of this paper was to investigate the corrosion behaviour of zinc in simulated concrete solutions using resistometric sensors and to describe the kinetics of zinc corrosion. The sensors provide corrosion data information in real time; thus, it is a useful technique for observing zinc corrosion behaviour in concrete environments. The replacement of carbon steel rebar by galvanized steel in concrete is a discussable topic with contradictory results in the literature presented in the introduction. In our case, zinc resistometric sensors were used, and they showed results in good agreement with other techniques, such as corrosion potential monitoring and EIS measurements. According to our results, zinc is able to passivate in a simulated concrete solution and even in a simulated carbonated solution. The corrosion rate was reduced by almost 40 times, during the active to passive transition. The zinc remains passive even in simulated concrete solutions contaminated with low levels of chloride ions up to 0.9 wt.%.
Strengthening Reinforced Concrete Walls with Externally Bonded Galvanized Steel Sheets and Near-Surface Mounted Steel Bars
Authors: Hamoda Ahmed , Bahrami Alireza , Abadel Aref A. , Ahmed Mizan , Ghalla Mohamed
Published: February 2025

Reinforced concrete (RC) walls are mainly used in RC structures to resist gravity and lateral forces. These structural elements may need to be upgraded to withstand additional forces and extend their life cycle. Therefore, it is crucial to provide effective strengthening techniques using low-cost sustainable materials under optimal conditions to rehabilitate RC walls. This study presents an experimental and numerical investigation of reinforced normal concrete (NC) walls strengthened with near-surface mounted (NSM) steel bars, confined with or without an externally bonded reinforced (EBR) galvanized steel sheets (GSSs). A total of six RC walls were constructed, loaded, and tested to failure. The examined parameters included the type of strengthening technique, materials used, and the position and configuration of the strengthening. Both EBR and NSM techniques were applied using GSSs and steel bars, respectively. The configurations were introduced in vertical and horizontal positions to resist gravity and lateral forces, respectively. The experiments revealed that these parameters significantly influenced the crack control, energy absorption, mode of collapse, and ultimate load capacity. Nonlinear three-dimensional finite element models were developed and verified against experimental results, achieving a validation accuracy of 95% on average. This was followed by a parametric study investigating the effect of confinement with or without vertical reinforcements. Both experimental and numerical results confirmed that the strengthening could increase the ultimate load capacity from 20% to 38%.
Numerical Analysis of Anti-Slide Pile Reinforcement for Slope Stability Under Rainfall Conditions
Authors: Wen Zhongyi , Xu Weiyuan , Yuan Bingxiang , Zhang Lijuan , Liang Zhu
Published: February 2025

Rainfall-induced slope instability is a critical challenge in geotechnical engineering. This study investigates the reinforcement effect of anti-slide piles on slope stability under rainfall conditions using finite element numerical simulations, based on a slope reinforcement project in Youxi County, Fujian Province. The MIDAS GTS NX 2019(v1.2) software was employed to analyze the effects of anti-slide pile arrangements on slope safety factors, pore water pressure, displacement fields, and reinforcement effectiveness. The results showed that anti-slide piles significantly enhanced slope stability by mitigating the adverse effects of rainfall, such as an increased pore water pressure and reduced soil strength. The optimal stability was achieved when anti-slide piles were positioned in the middle sections of the slope, and the horizontal displacement in the x-direction was reduced from 74.49 mm (without reinforcement) to 7.42 mm, achieving a reduction of 90.0%, effectively reducing horizontal displacement and plastic strain zones. This study provides valuable insights into the interaction mechanisms between anti-slide piles and soil, offering practical guidance for slope reinforcement design and strategies to mitigate rainfall-induced slope failures.
Machine Learning Applications in Building Energy Systems: Review and Prospects
Authors: Li Daoyang , Qi Zhenzhen , Zhou Yiming , Elchalakani Mohamed
Published: February 2025

Building energy systems (BESs) are essential for modern infrastructure but face significant challenges in equipment diagnosis, energy consumption prediction, and operational control. The complexity of BESs, coupled with the increasing integration of renewable energy sources, presents difficulties in fault detection, accurate energy forecasting, and dynamic system optimisation. Traditional control strategies struggle with low efficiency, slow response times, and limited adaptability, making it difficult to ensure reliable operation and optimal energy management. To address these issues, researchers have increasingly turned to machine learning (ML) techniques, which offer promising solutions for improving fault diagnosis, energy scheduling, and real-time control in BESs. This review provides a comprehensive analysis of ML techniques applied to fault diagnosis, energy consumption prediction, energy scheduling, and operational control. According to the results of analysis and literature review, supervised learning methods, such as support vector machines and random forest, demonstrate high classification accuracy for fault detection but require extensive labelled datasets. Unsupervised learning approaches, including principal component analysis and clustering algorithms, offer robust fault identification capabilities without labelled data but may struggle with complex nonlinear patterns. Deep learning techniques, particularly convolutional neural networks and long short-term memory models, exhibit superior accuracy in energy consumption forecasting and real-time system optimisation. Reinforcement learning further enhances energy management by dynamically adjusting system parameters to maximise efficiency and cost savings. Despite these advancements, challenges remain in terms of data availability, computational costs, and model interpretability. Future research should focus on improving hybrid ML models, integrating explainable AI techniques, and enhancing real-time adaptability to evolving energy demands. This review also highlights the transformative potential of ML in BESs and outlines future directions for sustainable and intelligent building energy management.
Activated Carbon Ammonization: Effects of the Chemical Composition of the Starting Material and the Treatment Temperature
Authors: Oliveira Silvia da C. , Dutra Romulo C. , León José J. L. , Martins Gesley A. V. , Silva Alysson M. A. , Azevedo Diana C. S. de , Santiago Rafaelle G. , Ballesteros-Plata Daniel , Rodríguez-Castellón Enrique , Prauchner Marcos J.
Published: February 2025

N-containing carbon-based materials have been employed with claimed improved performance as an adsorbent of acidic molecules, volatile organic compounds (VOC), and metallic ions; catalyst; electrocatalyst; and supercapacitor. In this context, the present work provides valuable insights into the preparation of N-doped activated carbons (ACs) by thermal treatment in NH3 atmosphere (ammonization). A commercial AC was submitted to two kinds of pretreatment: (i) reflux with dilute HNO3; (ii) thermal treatment up to 800 °C in inert atmosphere. The original and modified ACs were subjected to ammonization up to different temperatures. ACs with N content up to ~8% were achieved. Nevertheless, the amount and type of inserted nitrogen depended on ammonization temperature and surface composition of the starting material. Remarkably, oxygenated acidic groups on the surface of the starting material favored nitrogen insertion at low temperatures, with formation of mostly aliphatic (amines, imides, and lactams), pyridinic, and pyrrolic nitrogens. In turn, high temperatures provoked the decomposition of labile aliphatic functions. Therefore, the AC prepared from the sample pre-treated with HNO3, which had the highest content of oxygenated acidic groups among the materials submitted to ammonization, presented the highest N content after ammonization up to 400 °C but the lowest content after ammonization up to 800 °C.
A Look to the Future: Potential Theranostic Applications in Head and Neck Tumors
Authors: Oldan Jorge D. , Solnes Lilja B. , Chin Bennett B. , Rowe Steven P.
Published: February 2025

Theranostics, the practice of using a diagnostic radiopharmaceutical to guide radiotherapy with a chemically identical (or nearly identical) therapeutic radiopharmaceutical, is an exciting new field under development within the auspices of nuclear medicine. We aim to provide a narrative review of the areas of theranostics use and development which are occurring specifically in the head and neck, with attention to the therapeutic use of existing diagnostically used radiotracers such as agents that target prostate-specific membrane antigen (PSMA) and somatostatin receptors (e.g., DOTATATE derivatives), as well as developing classes of radiotracers such as those targeting fibrinogen-activating protein (FAP) and carbonic anhydrase IX (CAIX), as well as new meta-iodo-benzylguanidine (MIBG) derivatives. Most of those agents are still at the preclinical or early clinical stages of development, but as this is an emerging field, we aim to both outline current progress and suggest future directions.
Health-Related Quality of Life in Long-Term Survivors of Non-Hodgkin Lymphoma: A French Population-Based Study
Authors: Wasse Stephane Kroudia , Assogba Emerline , Orazio Sebastien , Atsou Kueshivi Midodji , Rossi Cédric , Guilloteau Adrien , Gauthier Sophie , Girard Stéphanie , Poncet Jean-Marc , Damaj Gandhi , Troussard Xavier , Monnereau Alain , Dabakuyo-Yonli Sandrine Tienhan , Maynadie Marc
Published: February 2025

Background/Objectives: Non-Hodgkin lymphoma (NHL) represents 63% of all hematological malignancies in France, with diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) being the two most frequent forms. With the improvement of therapeutics, the issue of health-related quality of life (HRQoL) is becoming increasingly crucial for these patients. The aim was to compare HRQoL of NHL survivors with that of the general French population and to identify factors associated with HRQoL in NHL survivors. Methods: We conducted a population-based study among living patients from three registries of hematological malignancies, using standardized questionnaires, including the SF-12, in September 2023. The data collected were compared to those of a normative general French cohort. Results: In total, 493 patients completed the study questionnaires, yielding a response rate of 36%. The median time since diagnosis was 8 years (IQR 6–10) These NHL survivors reported lower HRQoL compared to the general French population, except in terms of bodily pain (p < 0.01). Each one-year increase in the time since diagnosis was associated with an increase in social functioning (p = 0.009). Men had better general health (p = 0.01) and less bodily pain (p = 0.007) than women. Higher income was associated with better HRQoL (p < 0.01). Underweight or obesity were associated with poorer physical functioning (p = 0.008). The presence of comorbidities, socioeconomic deprivation, anxiety, and depression were associated with poorer HRQoL (p < 0.01). Conclusions: This study provides valuable information of HRQoL values for comparison in further follow-up studies and proposes measures that could be implemented to improve the HRQoL of NHL survivors.
Speciation of 3d Elements in Spinel Versus Corundum: Elucidating the Interplay Between Ligand Field, Structural Dissimilarities and Processing Conditions
Authors: Goldstein Adrian , Zandonà Alessio
Published: February 2025

The simultaneous analysis of optical and electronic paramagnetic resonance spectra of all 3d metals, doped into transparent α-Al2O3 and MgAl2O4 spinel, was effectuated with a view of establishing the speciation pattern of the dopants. The examination of these patterns enabled the revelation of certain regularities (rules) affecting the correlation between the physical factors controlling the process and speciation patterns. It was observed that structural dissimilarities between the lattices significantly affected the correlation. Thus, the spinel lattice was found to impose the accommodation of the dopants as 2+ cations replacing native Mg2+ ions located in tetrahedral sites, with the process concerning only the late 3d elements. The difference in behavior between the early and late 3d elements is mostly caused by the increase in ionization potential along the series. In alumina, the dopants are accommodated as 3+ cations in octahedral sites; 6-coordinated 2+ cation stabilization is feasible but requires extremely reductive conditions for late 3d elements.
Enhancement of Sol–Gel Coatings for Photoprotection of Rosé Wines
Authors: Moriones Jennifer , Osés Javier , Amézqueta Pablo , F. Palacio José , Fernández De Ara Jonathan , Almandoz Eluxka
Published: February 2025

Exposure to short-wavelength light, including UV-A and blue light, can degrade high-value products like rosé wine, which are usually packaged in colourless bottles. This study investigates the optimisation of sol–gel coatings enhanced with UV-absorbing additives (Tinuvin 479 and semaSORB 20109) to provide photoprotection for rosé wines. Coatings with varying additive concentrations (0.5%, 0.75%, 1%, and 1.5%) were applied to glass substrates via spin coating and cured with UV light. Then, optical and mechanical characterisation was performed. The 1.5% concentration semaSORB 20109 bilayer coating demonstrated improved photoprotective properties without compromising colour properties, leading to successful application on glass bottles by spray coating. Accelerated degradation tests confirmed that the optimised coating effectively protected against photodegradation, as indicated by the stability of polyphenol levels and colour parameters in rosé wines. The results suggest that these coatings could be a suitable option for commercial-scale applications, enhancing the light resistance of colourless-bottled products.
Ultra High Efficiency Solar Capture Device Based on InAs Nanoring Microstructure
Authors: Yi Zao , Yao Xiangchao , Song Qianju , Wu Xianwen
Published: February 2025

As a widely used clean energy source, solar energy has demonstrated significant promise across various applications due to its wide spectral range and efficient absorption performance. This study introduces a cross-structured, ultra-broadband solar absorber utilizing titanium (Ti) and titanium dioxide (TiO2) as its foundational materials. The absorber exhibits over 90% absorption within the 280–4000 nm wavelength range and surpasses 95% absorption in the broader spectrum from 542 to 3833 nm through the cavity coupling effect of incident light excitation and the subsequent initiation of the surface plasmon resonance mechanism, thus successfully achieving the goal of broadband high absorption. Through the finite difference time domain method (FDTD) simulation, the average absorption efficiency reaches 97.38% within the range from 280 nm to 4000 nm, and it is 97.75% in the range from 542 nm to 3833 nm. At the air mass of 1.5 (AM 1.5), the average absorption efficiency of solar energy is 97.46%, and the loss of solar energy is 2.54%, which has extremely high absorption efficiency. In addition, thanks to the material considerations, the absorber adopts a variety of high-temperature resistant materials, making the thermal radiation efficiency in a high-temperature environment still good; specifically, at the temperature of 900 K, its thermal radiation efficiency can reach 97.27%, and at the extreme 1800 K temperature, it can still maintain 97.52% of high efficiency thermal radiation, further highlighting its excellent thermal stability and comprehensive performance. The structure exhibits excellent optical absorption and thermal radiation properties, which give it broad applicability as an ideal absorber or thermal emitter. More importantly, the absorber is insensitive to the polarization state of the light and can effectively handle the incident light lines in the wide-angle range. In addition, its photothermal conversion efficiency (Hereafter referred to as pc efficiency) can sustain an elevated level under various temperature conditions, which enables it to flexibly adapt to diverse environmental conditions, especially suitable for the integration and application of solar photovoltaic systems, and further broaden its potential application range in the field of renewable energy.
Ester Exchange Modification for Surface-Drying Time Control and Property Enhancement of Polyaspartate Ester-Based Polyurea Coatings
Authors: Yang Xiandi , Deng Yiqing , Li Peini , Guo Kaixuan , Zhao Qiang
Published: February 2025

In recent years, polyurea (PUA) systems have drawn considerable attention in the coatings industry for their superior performance. Among these systems, polyaspartate ester-based polyurea (PAE-PUA) stands out for its excellent comprehensive properties, and the structure of the diamines used in polyaspartate ester (PAE) significantly influences key performance attributes, such as gel time, mechanical properties, and thermal stability. To investigate the influence of diamine structures on PAE-PUA properties, this study synthesized PAEs through ester exchange reactions involving diamines and monohydric alcohols with varied chain lengths and structural types (linear or cyclic). The effects of four diamines (D230, DMH, IPDA, PACM) and four monohydric alcohols (CA, DDA, OD, CHOL) on polyurea coating properties were systematically examined. The results demonstrated that adjusting the structural regularity of PAEs via ester exchange reactions effectively regulated their viscosity, maintaining it below 1500 mPa·s. These reactions also enabled simultaneous regulation of surface-drying time, mechanical properties, and thermal performance. Notably, introducing 1-octadecanol (OD) significantly improved surface-drying time and thermal stability, whereas cyclic structures in diamines or alcohols resulted in higher glass transition temperatures (Tg). Additionally, the mechanical properties and reaction rates of modified PAEs can be tailored to meet specific application requirements, offering an effective strategy for developing polyurea materials optimized for the coatings industry.
CFD-DPM Model of Gas–Solid Two-Phase Flow Erosion of Needle Throttle Valve
Authors: Zhao Zhihui , Wu Zhe , Wang Weiqiang , Wang Xingyu , Du Shengnan , Chen Xianlei , Li Panfeng , Wang Yingying
Published: February 2025

During shale gas field production, wellhead throttle valves are prone to erosion caused by solid particles carried in the gas stream, posing significant safety risks. Existing studies on erosion primarily focus on simple structure like elbows and tees, while research on gas–solid two-phase flow erosion in needle throttle valves remains limited. This paper establishes a numerical model based on the CFD-DPM approach, integrating actual shale gas field production conditions to investigate the erosion behavior of needle throttle valves under varying openings, particle sizes, inlet velocities, and particle mass flow rates. The results show that the valve spool consistently exhibits the highest erosion rate among all components, with the most severe erosion localized at its front end. At a 1/4 opening, particles colliding with the spool exhibit significantly increased frequency and energy when re-entering the upstream pipeline, raising the risk of blockages. Furthermore, when the opening exceeds 2/4, the valve chamber experiences higher erosion rates than the upstream and downstream pipelines. This study provides critical insights for optimizing valve design and maintenance strategies, thereby enhancing service life and ensuring safe shale gas production.
Current Distribution of the Nine-Banded Armadillo (Dasypus novemcinctus) in the United States
Authors: DeGregorio Brett A. , Deshwal Anant
Published: February 2025

The nine-banded armadillo (Dasypus novemcinctus: hereafter armadillo) was first recorded in the United States (U.S.) in the state of Texas in 1849 and has been expanding its range northward and eastward since then. With the widespread adoption of participatory science as well as the proliferation of nationwide wildlife game camera studies, occurrence data of armadillos can be compiled more rapidly and thoroughly than at any time in the past. Here, we use disparate data sources to update the current geographic distribution of the armadillo in the United States and use occurrence data from the leading edge of its range expansion to create a species distribution model to understand their relationship with landscape and bioclimatic factors. Since the last report on the geographic distribution of the armadillo in 2014, we show that armadillos have expanded to cover the entirety of Missouri and established in southern Iowa, expanded modestly within Kansas and Illinois, expanded northward and eastward in Indiana, expanded eastward in both Kentucky and Tennessee, established throughout the entirety of South Carolina and Georgia and established in the western third of North Carolina. Our species distribution model indicates that there is substantial opportunity for the species to continue to expand its geographic range, particularly in the Eastern United States. These results provide information to managers who are now or might soon be co-existing with the armadillo to proactively manage the species or inform the public regarding potential conflicts.
Pitfalls in Ultrasound Diagnosis of Vascular Malformations: A Retrospective Review of 14 Nonvascular Tumors Treated as Vascular Malformations
Authors: Mitamura Shintaro , Ishikawa Kosuke , Sasaki Yuki , Murao Naoki , Sasaki Satoru
Published: February 2025

Background/Objectives: Vascular malformations form masses in subcutaneous and muscular tissues throughout the body and are occasionally misdiagnosed as subcutaneous nonvascular tumors. Understanding and differentiating their clinical and imaging features are crucial due to their different treatments and prognoses. This study aimed to report cases of nonvascular tumors that were initially misdiagnosed and treated as vascular malformations. Methods: In this retrospective observational study, we enrolled 14 (1.8%) patients with pathologically diagnosed nonvascular tumors from among 536 patients with 759 lesions of clinically diagnosed vascular malformations. Results: The average age at the initial visit was 41.9 years, with a male-to-female ratio of 3:11. Tumor locations included the lower limb in seven patients, the upper limb in five patients, and the trunk and head in one patient each. Ultrasound evaluation revealed 12 lesions of low-flow vascular malformations and two lesions of high-flow vascular malformations. These findings led to an initial diagnosis of venous or lymphatic malformations in 12 patients and arteriovenous malformations in two patients. Based on the clinical diagnosis, treatments administered before tumor resection included sclerotherapy in four patients and transcatheter arterial embolization in one patient. All patients underwent tumor resection. The final histopathological diagnoses included schwannoma in six patients, epidermal cyst and angiomyoma in two patients each, and other types of tumors in four patients. The average time from initial diagnosis to final histopathological diagnosis was 370 days. Conclusions: Multimodal diagnostic strategies, especially the use of ultrasound, enhance the differentiation between vascular malformations and nonvascular tumors.
Spatiotemporal Analysis of Multi-UAV Persistent Search and Retrieval with Stochastic Target Appearance
Authors: Day Ryan , Salmon John L.
Published: February 2025

This research introduces novel analytical methods for evaluating multi-UAV persistent search and retrieval with stochastic target appearance (PSR-STA) scenarios. Traditional approaches that rely on single aggregate effectiveness measures for a scenario fail to capture the complex spatiotemporal dynamics of multi-UAV operations and provide limited insights into improving search performance. To address these limitations, we present a comprehensive analysis framework combining temporal and spatial analysis techniques. For temporal analysis, we employ a graphical comparison of line charts and discrete Fourier transform analysis to identify shared temporal patterns across scenarios. Spatial patterns are analyzed through principal components analysis and random forest surrogate modeling with profiling to understand non-linear parameter influences. Additionally, we introduce trellis charts for integrated visualization and analysis of combined spatiotemporal patterns. This research builds on a case study developed in a previous case study of multi-UAV PSR-STA. While the previous work established foundational algorithms and metrics for multi-UAV PSR-STA, this study introduces sophisticated spatiotemporal analysis techniques that reveal deep insights into system behavior and enable a nuanced understanding of UAV search performance across varied scenarios.
Variations in Multi-Agent Actor–Critic Frameworks for Joint Optimizations in UAV Swarm Networks: Recent Evolution, Challenges, and Directions
Authors: Alam Muhammad Morshed , Trina Sayma Akter , Hossain Tamim , Mahmood Shafin , Ahmed Md. Sanim , Arafat Muhammad Yeasir
Published: February 2025

Autonomous unmanned aerial vehicle (UAV) swarm networks (UAVSNs) can efficiently perform surveillance, connectivity, computing, and energy transfer services for ground users (GUs). These missions require trajectory planning, UAV-GUs association, task offloading, next-hop selection, and resource allocation, including transmit power, bandwidth, timeslots, caching, and computing resources, to enhance network performance. Owing to the highly dynamic topology, limited resources, stringent quality of service requirements, and lack of global knowledge, optimizing network performance in UAVSNs is very intricate. To address this, an adaptive joint optimization framework is required to handle both discrete and continuous decision variables, ensuring optimal performance under various dynamic constraints. A multi-agent deep reinforcement learning-based adaptive actor–critic framework offers an effective solution by leveraging its ability to extract hidden features through agent interactions, generate hybrid actions under uncertainty, and adaptively learn with scalable generalization in dynamic conditions. This paper explores the recent evolutions of actor–critic frameworks to deal with joint optimization problems in UAVSNs by proposing a novel taxonomy based on the modifications in the internal actor–critic neural network structure. Additionally, key open research challenges are identified, and potential solutions are suggested as directions for future research in UAVSNs.
Lacunary Series and Strong Approximation
Authors: Berkes István
Published: February 2025

Strong approximation, introduced by Strassen (1964), is one of the most powerful methods to prove limit theorems in probability and statistics. In this paper we use strong approximation of lacunary series with conditionally independent sequences to prove uniform and permutation-invariant limit theorems for such series.
Divergence Between New and Existing FDI in Times of Sustained Inflation Post the COVID-19 Pandemic: The Case of a Subnational Economy in the U.S.
Authors: Wright Roxana , Wu Chen
Published: February 2025

The relationship between inflation and foreign direct investment (FDI) is not clear-cut in theory. In the U.S., rising inflation coupled with increased economic recovery boosted FDI immediately after the COVID-19 pandemic but suppressed it afterwards. To shed light on the relationship between inflation and the resulting contractionary monetary policy and FDI, three key propositions were put forth for investigation. The propositions rely on relevant scientific literature showing that (1) although the connection between FDI and inflation is complex, a high and sustained inflation depresses incoming FDI due to increases in uncertainty and guarding government policies; (2) there exist significant location-based differences in how this connection manifests; and (3) high inflation and subsequent policies motivate FDI-related strategic action. Thus, we propose that new FDI is expected to be negatively affected by the rising entry cost associated with an inflationary economy that adopts anti-inflationary policies. Second, there exists heterogeneity in the effects of inflation on new FDI across subnational economies with various local characteristics. Third, existing FDI demonstrates strategic actions and expansion at the subnational location and beyond, even under inflationary pressure. We employ a positive comparative analysis based on descriptive statistics and qualitative interpretation of data to examine the status and activities of both new FDI (using subnational aggregated data) and existing foreign businesses (using firm-level data) in the state of New Hampshire during the recent inflation surge of 2022–2023. Our analysis provides empirical evidence supporting our propositions. Key implications are that, during challenging times of inflation and recovery, business leaders and economic development professionals should anticipate strategic actions to expand markets, products, operations, and partnerships. Leaders and professionals should act to take advantage of business actions outside the subnational location, as more companies look to strengthen and diversify their national and international networks.
Semantic Segmentation of Distribution Network Point Clouds Based on NF-PTV2
Authors: Han Long , Song Bin , Wu Shaocheng , Nie Deyu , Chen Zhenyang , Wang Linong
Published: February 2025

An on-site survey is the primary task of working live in distribution networks. However, the traditional manual on-site survey method is not only not very intuitive but also inefficient. The application of 3D point cloud technology has opened up new avenues for on-site surveys in life working in distribution networks. This paper focused on the application of the Point Transformer V2(PTV2) model in the segmentation of distribution network point clouds. Given its deficiencies in boundary discrimination ability and limited feature extraction ability when processing the point clouds of distribution networks, an improved Non-local Focal Loss-Point Transformer V2 (NF-PTV2) model was proposed. With PTV2 as its core, this model incorporated the Non-Local attention to capturing long-distance feature dependencies, thereby compensating for the PTV2 model’s shortcomings in extracting features of large-scale objects with complex features. Simultaneously, the Focal Loss function was introduced to address the issue of class imbalance and enhance the model’s learning ability for small complex samples. The experimental results demonstrated that the overall accuracy (OA) of this model on the distribution network dataset reached 93.28%, the mean intersection over union (mIoU) reached 81.58%, and the mean accuracy (mAcc) reached 87.21%. In summary, the NF-PTV2 model proposed in this article demonstrated good performance in the point cloud segmentation task of the distribution network and can accurately identify various objects, which, to some extent, overcomes the limitations of the PTV2 model.
Validation of a Heat Pump System Model for Energy Recycling in Grocery Stores Through On-Site Energy Monitoring
Authors: Söderholm Niklas , Gröndahl Mikko , Niemelä Tuomo , Jokisalo Juha , Kosonen Risto , Ni Long
Published: February 2025

This paper presents a validated simulation model for heat pump-based energy recycling systems, with a focus on heat recovery applications in grocery stores. Heat is recovered through heat pumps from a subcritical CO2-based refrigeration system, with exhaust air heat recovery used on demand according to the heating demand. The model is validated through a case study on a Finnish hypermarket-sized grocery store, where the heat pump system has been operational since 2020. Multi-objective energy optimization is used to validate the model by estimating critical decision variable values and providing error estimates compared to the measured data. The calibrated energy system model has a maximum mean bias error, MBE, of ±5% and a 10–15% coefficient of variation of root mean squared error, CV(RMSE), for the heat pump-related energy balance. Energy optimizations indicate that the control algorithm of the investigated heat pump system can be enhanced to reduce district heating consumption by 12%. The study emphasizes the need for numerous input parameters tailored to a system-specific layout to accurately reproduce the heat pump system’s control algorithm. Compared to a typical transcritical CO2 booster system with heat recovery, the novel heat recovery system shows superior heat recovery potential and a high total COP for both heating and cooling.
Estimating Stand Carrying Capacity for Three Common Pine Species Across Various Regions of Türkiye
Authors: Seki Mehmet , Yang Sheng-I , Duyar Ahmet , Raptis Dimitrios I. , Atar Davut , Özkal Mustafa Kağan , Sakici Oytun Emre , von Gadow Klaus
Published: February 2025

Sustainable management of forest ecosystems requires assessing forest dynamics and project stand growth and yield in order to make strategic decisions. The size–density relationship is one of the most important measures in quantifying the carrying capacity of a forest ecosystem and determining appropriate silvicultural decisions. In this study, the maximum stand density index (SDImax) was estimated for three common pine species in seven different ecological regions across Türkiye. Observations from 14,413 sample plots, including Calabrian pine (Pinus brutia Ten.; 6266 plots from five regions), Black pine (Pinus nigra J.F. Arnold; 6106 plots from five regions) and Scots pine (Pinus sylvestris L.; 2041 plots from three regions) forests were used in this study, covering the entire natural range of these three pine species. A mixed model with region as a random effect was developed for each species to estimate SDImax. Results show that the slope coefficients of the self-thinning lines vary by species and are significantly different from −1.605. The Scots pine stands exhibited the highest SDImax, followed by Black pine and Calabrian pine stands. Across seven ecological regions, the highest SDImax was observed in the Aegean region for Calabrian and Black pine and in the East Anatolia region for Scots pine. The arid Inner Anatolia region yielded the lowest SDImax for Black pine and Scots pine. The humid and semi-humid regions showed a higher SDImax compared to arid regions. The three pine species studied make up almost half of the total forest area in Türkiye. The results of the study are therefore very important in terms of quantitative assessment of the country’s forests. The differences in stand dynamics of these three pine species, which are also widely distributed outside Türkiye under different ecological conditions, may also be a relevant source of information for other regions. Moreover, considering that pine stands in dry environments have a lower carrying capacity than those in humid conditions, it seems likely that pine forests in Türkiye will be affected by increasing global warming.