bluuebunny/crossref_metadata_2025 huggingface dataset:
Transvaginal Ultrasound Findings Predicting Prolonged Pregnancy in Cases of Prolapsed Fetal Membrane: A Retrospective Study
Authors: Kondo Tomohiro , Tsuda Hiroyuki , Tsugeno Eri , Nakamura Yumi , Ito Yumiko , Tezuka Atsuko , Ando Tomoko
Published: February 2025

Background/Objectives: Fetal membrane prolapse can occur due to advanced cervical insufficiency. We investigated the yet unclear predictors of prolonged pregnancy in women with prolapsed fetal membranes. Methods: This retrospective observational study included 100 pregnant women with prolapsed fetal membranes between November 2017 and March 2023. We examined the correlation between transvaginal ultrasound findings at the time of admission and the duration of prolonged pregnancy, which was defined as the period from admission to delivery. We defined five transvaginal ultrasound indices: (1) width of the external os, (2) maximum width of the prolapsed fetal membrane, (3) distance from the external os to the presenting part of the fetus, (4) thickness of the posterior uterine lip, and (5) morphology of the prolapsed fetal membrane. Results: Women who underwent cervical cerclage comprised the cerclage group (n = 17), while those who underwent conservative management comprised the non-cerclage group (n = 83). The pregnancy period was significantly longer in the cerclage group than in the non-cerclage group (81.4 days vs. 9.1 days, p < 0.001). Multiple regression analysis revealed that type A morphology was a significant factor for prolonged pregnancy in the non-cerclage group (p < 0.05), which was significantly associated with a prolonged pregnancy period of over 7 days (p = 0.037). Conclusions: In cases of prolapsed fetal membranes, cerclage is challenging because of the high risk of iatrogenic preterm rupture of the membrane; however, if successful, a significant prolongation of the pregnancy period can be obtained. Morphological evaluation using ultrasonography is simple and easy to understand and correlates well with pregnancy outcomes, making it very useful.
Toughening of Composite Interfaces for Damage Resistance with Nanoparticle Interleaves
Authors: Subramanian Nithya , Bisagni Chiara
Published: February 2025

Composite interfaces, particularly in joints, play a critical role in the damage resistance and durability of structures for aeronautics applications. This study investigates the use of carbon nanotube (CNT) interleaves for the co-cured joining of composite parts and its effects on fracture toughness and damage progression at the co-cured interface. CNT dispersed in a thermoset resin and partially cured into thin film interleaves at three weight concentrations (0.5% wt., 1% wt., and 2% wt.) of two discrete thicknesses (200 µ and 500 µ) were investigated. The fracture toughness of the co-cured interface with CNT interleaves in mode I and mode II loading conditions was determined through double cantilever beam and end-notched flexure tests, respectively. The results reveal that despite the occurrence of a stick–slip damage progression in mode I, the crack arrest mechanisms and forces are surprisingly predictable based on interleaf thickness. At CNT concentrations above 1% wt., there was no significant enhancement of toughening, and interleaf thickness controlled the crack arrest loads. Damage delay also occurred at the interface due to the activation of multiscale toughening mechanisms. Toughening in mode II was dominated by CNT pullout resistance and, therefore, yielded up to six-fold improvement in critical fracture toughness. These insights offer significant potential for designing joints with nanocomposites for aerospace applications, incorporating inherent toughening and damage delay mechanisms.
Reduced Capacity for Parafoveal Processing (ReCaPP) Leads to Differences in Prediction Between First and Second Language Readers of English
Authors: Fernandez Leigh B. , Allen Shanley E. M.
Published: February 2025

Research has shown that first (L1) and second language (L2) speakers actively make predictions about upcoming linguistic information, though L2 speakers are less efficient. While prediction mechanisms are assumed to be qualitatively the same, quantitative prediction-driven processing differences may be modulated by individual differences We tested whether L2 proficiency and quality of lexical representation (QLR) impact the capacity of L2 readers to extract parafoveal information while reading, leading to quantitative differences in prediction. Using the same items as Slattery and Yates, we investigated the impact of predictability and length of a critical word on bottom-up parafoveal processing, measured by skipping rates, and top-down predictability processing, measured by reading times. Comparing our L2 English to their L1 English data, we found that L2 speakers skipped less and had longer gaze duration. However, both groups showed increased skipping rate and decreased gaze duration for predictable relative to unpredictable words and for shorter relative to longer words. We argue that L1 and L2 predictability mechanisms are qualitatively the same and quantitative differences stem from L2 speakers’ Reduced Capacity for Parafoveal Processing, the ReCaPP hypothesis.
Coupled Ship Simulation in Hydrodynamics and Structural Dynamics Induced by Wave Loads: A Systematic Literature Review
Authors: Mursid Ocid , Oterkus Erkan , Oterkus Selda
Published: February 2025

Coupled ship simulation in hydrodynamics and structural dynamics provides a comprehensive approach to understanding the dynamic behavior of ships under wave-induced loads. Improvements in computer power have made it much easier to create coupled simulation methods that combine structural and hydrodynamics analyses. A literature review based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 is used to look at future trends in this literature review. We have filtered 1440 articles in PRISMA 2020, including 93 articles for analysis. The bibliographic analysis reveals that China emerged as the first according to the first authors due to significant industrial and funding support. Based on 93 articles, computational methods can be grouped by the coupling method (one-way and two-way), the hydrodynamic analysis approach (potential flow and CFD), the structural analysis approach (FEM, TMM, and DMB), the hydrodynamics element type (2D and 3D), and the structural element type (1D and 3D). As an outcome of the review, it can be concluded that the most common approach is a two-way connection of the potential flow and FEM methods, which both use 3D elements for structural and hydrodynamic analyses. Future trends of this research should be explored based on the application of variables, reducing computational resources, and using artificial intelligence.
Culturable Plastisphere from the 75° N Subarctic Transect as a Potential Vector of Pathogens and Antibiotic-Resistant Bacteria
Authors: Caruso Gabriella , Papale Maria , Rappazzo Alessandro Ciro , Azzaro Maurizio
Published: February 2025

Plastic pollution is a global emerging concern, but in the Arctic Ocean, the role of the plastisphere as a potential carrier of pathogens and antibiotic-resistant bacteria is unknown yet. An initial assessment of the spread of these target bacteria through their colonization of plastic particles, attributed to the micro-sized fraction (less than 5 mm, named microplastics, MPs), was carried out across the 75° N transect (Greenland Sea). To fill the knowledge gaps regarding the bacterial community associated withmicroplastics (MPs)—belonging to the so-called “plastisphere”—and the potential risks related to their spread, our study focused on the abundance and taxonomic composition of the plastisphere, including potential pathogenic and antibiotic-resistant bacteria, using a culture-dependent approach. MPs particles were collected through a Manta net, and decimal dilutions were cultured on Marine agar plates to estimate the abundance of culturable heterotrophic bacteria. For the search of target pathogenic bacterial species (Escherichia coli, Enterococcus spp., Salmonella spp., potentially pathogenic Vibrio spp., and Staphylococcus aureus), small volumes were inoculated into selective culture media using aspread plate directly or after enrichment. Screening of the antibiotic susceptibility profiles of the bacterial isolates was performed to assess the presence of antibiotic-resistant bacteria. The culturable heterotrophic bacterial community was dominated by members of the phyla Gammaproteobacteria and Actinobacteria, with bacterial isolates assigned to the genera Psychrobacter, Pseudoalteromonas, Shewanella, and Arthrobacter. Selective enrichments resulted in the detection of target bacterial pathogens, mostly identified as potentially pathogenic Vibrios spp., in the examined samples. The antibiotic susceptibility profiles pointed out that multiple antibiotic-resistant bacteria were also isolated, suggesting the need to shed light on the potential risks to human and animal health deriving from the plastisphere in remote cold regions as well.
Does Farmland Transfer Promote Digital Agriculture?—Based on Panel Data from 30 Provinces in China
Authors: Zhou Xinxin , Cheng Guanghua , Zhang Bangbang
Published: February 2025

To achieve agricultural modernization, agricultural land must be operated on a large scale. The primary means of encouraging massive operations is through the conveyance of farmland. This is crucial for advancing China’s digital farming. In this article, the degree of digital farming growth is evaluated via the entropy value approach, the impact of farmland transfer on digital agricultural development is analyzed via fixed effects and mediating effects, and the mediating role of resource allocation in farming land transfer to advance digital agriculture growth is investigated. It has been found that agrarian land transfer can effectively stimulate the growth of digital farming. From the mediating effect, farmland transfer fosters the advancement of digital agriculture by transferring farm labor and increasing the input of digital capital. According to heterogeneity analysis, the impact of agricultural land transfer on advancing digital agriculture is more pronounced in eastern and central China. Relevant countermeasures are proposed to enhance the farmland transfer system to promote the large-scale operation of digital agriculture, to increase the input of digital capital to support the growth and construction of digital agriculture, and to improve the regional talent flow mechanism and technological innovation environment to attract from and retain technical talent in digital agriculture.
Assessing the Impact of Amazonian Fires on Atmospheric NO2 Using Satellite Data
Authors: Barbosa Humberto Alves , Buriti Catarina de Oliveira
Published: February 2025

In the Amazon region, the impact of fire on the region’s biogeochemical processes remains poorly understood. In this study, we examined the relationship of seasonal fire on greenhouse gas (GHG) emissions over the study region during the last two decades of the 21st century by integrating calibrated and validated satellite-derived products of estimations of burned biomass area, land cover, vegetation greenness, rainfall, carbon monoxide (CO), and nitrogen dioxide (NO2) through geospatial techniques. Results revealed a strong impact of fire activity on GHG emissions, with abrupt changes in CO and NO2 emission factors between early- and middle-dry-season fires (July–September). We found a strong positive correlation (r2 = 0.71) between NO2 and burned biomass when a small percentage of burned biomass (around ≤ 0.5%) is released during a fire. However, in the event of a large percentage of burned biomass (>0.8%), the correlation coefficient between NO2 and burned biomass was weak (r2 = 0.41). New models need to be developed that incorporate the substantial existing knowledge on the seasonal dynamics of fire-derived GHG emissions. This information should be utilized to make effective decisions about how to manage fire in the Amazon ecosystems and to drive further data collection campaigns and modelling initiatives.
A Data-Synthesis-Driven Approach to Recognize Urban Functional Zones by Integrating Dynamic Semantic Features
Authors: Liu Xingyu , Sheng Yehua , Yu Lei
Published: February 2025

Urban functional zones (UFZs) are related to people’s daily activities. Accurate recognition of UFZs is of great significance for an in-depth understanding of the complex urban system and optimizing the urban spatial structure. Emerging geospatial big data provide new ideas for humans to recognize urban functional zones. Point-of-interest (POI) data have achieved good results in the recognition of UFZs. However, since humans are the actual users of urban functions, and POI data only reflect static socioeconomic characteristics without considering the semantic and temporal features of dynamic human activities, it leads to an incomplete and insufficient representation of complex UFZs. To solve these problems, we proposed a data-synthesis-driven approach to quantify and analyze the distribution and mixing of urban functional zones. Firstly, representation learning is used to mine the spatial semantic features, activity temporal features, and activity semantic features that are embedded in POI data and social media check-in data from spatial, temporal, and semantic aspects. Secondly, a weighted Stacking ensemble model is used to fully integrate the advantages between different features and classifiers to infer the proportions of urban functions and dominant functions of each urban functional zone. A case study within the 5th Ring Road of Beijing, China, is used to evaluate the proposed method. The results show that the approach combining dynamic and static features of POI data and social media data effectively represents the semantic information of UFZs, thereby further improving the accuracy of UFZ recognition. This work can provide a reference for uncovering the hidden linkages between human activity characteristics and urban functions.
Enhancing Mechanical and Thermal Performance of Recycled PA6/PP Blends: Chain Extension and Carbon Fiber Reinforcement Synergy
Authors: Ergun Neslihan , Oksuz Mustafa , Ekinci Aysun
Published: February 2025

To develop novel materials through the recycling of waste polymers and to enhance their mechanical and thermal properties, composites were synthesized using chain extenders (CEs), compatibilizers (PP-g-MA), and short carbon fiber (CF) reinforcements within recycled polyamide 6 (rPA6) and polypropylene (rPP) blends. The recycling of waste polymers holds paramount importance in the context of environmental sustainability. This study investigates the role of additives in effectively improving the properties of recycled polymers. The composites were fabricated using the twin-screw extrusion method and subjected to a comprehensive range of characterizations, including Fourier Transform Infrared Spectroscopy (FTIR), differential scanning calorimetry (DSC), molecular weight analysis, melt flow index (MFI), heat deflection temperature (HDT), tensile testing, impact testing, and Scanning Electron Microscopy (SEM). Additionally, ANOVA statistical methods were applied to analyze HDT, tensile, and impact test results. The findings of this research demonstrate that chain extenders and compatibilizers significantly enhance the mechanical properties of rPA6/rPP blends, while carbon fiber reinforcements markedly improve both tensile strength and impact resistance. Furthermore, the incorporation of rPP led to an approximately 4% reduction in hardness values; however, this loss was effectively compensated by the addition of chain extenders and CF reinforcements, resulting in an overall increase in hardness. It was observed that chain extenders enhanced the elastic modulus and tensile strength by reinforcing interphase bonding, whereas CF reinforcements strengthened the polymer matrix, leading to improved impact resistance. These findings emphasize the synergistic role of chain extenders, compatibilizers, and CF reinforcements in enhancing the mechanical properties of rPA6/rPP blends. The study underscores recycling as both an environmentally beneficial and effective strategy for developing durable, high-performance composites for industrial use. Consequently, the utilization of recycled polymers contributes substantially to the circular and sustainable materials economy, demonstrating the potential for the widespread industrial adoption of such composites.
Influence of Pavement Material and Structure on Low-Temperature Crack Resistance for Double-Layer Asphalt Surface One-Time Paving
Authors: Wu Bingyang , Han Zhanchuang , Mao Yunbo , Wang Shuai , Zhao Hui , Zhang Shuo , Li Mingchen
Published: February 2025

The double-layer one-time-paving technology for asphalt mixtures enhances the interlayer adhesion and stability of pavement by simultaneously laying and compacting two layers of asphalt mixture, demonstrating improvements over traditional layer-by-layer paving and compaction methods. Based on this technology, the effects of paving techniques, mixture types, and structural layer thickness on the low-temperature crack resistance of pavement at −10 °C were investigated. Results indicated that, compared to traditional paving methods, the maximum tensile strain and bending strain energy density of pavement using the double-layer one-time-paving technique increased by at least 14% and 20%, respectively, under a 95% confidence level. Compared to the AC-13 + AC-25 mixture combination, the AC-16 + AC-20, AC-16 + AC-25, and AC-13 + AC-20 combinations showed increases in maximum tensile strain by at least 25%, 15%, and 15%, and in bending strain energy density by at least 57%, 38%, and 31%, respectively. Compared to the 5 cm + 5 cm thickness combination, the 4 cm + 6 cm and 3 cm + 7 cm combinations exhibited increases in maximum tensile strain by at least 14% and 22%, and in bending strain energy density by at least 16% and 29%, respectively. To effectively improve the low-temperature crack resistance of asphalt pavement at −10 °C, it is recommended to adopt a double-layer one-time-paving structure with a 3 cm AC-16 upper layer and a 7 cm AC-20 lower layer, providing insights for more durable asphalt pavements in cold climates.
On the Prediction and Optimisation of Processing Parameters in Directed Energy Deposition of SS316L via Finite Element Simulation and Machine Learning
Authors: Ghasempour-Mouziraji Mehran , Afonso Daniel , Alves de Sousa Ricardo
Published: February 2025

In the current study, the integration of finite element simulation and machine learning is used to find the optimal combination of processing parameters in the directed energy deposition of SS316L. To achieve this, the FE simulation was validated against previously implemented research, and a series of simulations were conducted. Three inputs, namely laser power, scanning speed, and laser beam radius, and two outputs, namely residual stress and displacement, were considered. To run the machine learning model, artificial neural networks and a non-dominated sorting genetic algorithm were applied to determine the optimal combination of processing parameters. In addition, the current study underscores the novelty of combining FE simulation and machine learning methods, which provides enhanced precision and efficiency in controlling residual stress and displacement (geometrical deviation) in the Directed Energy Deposition (DED) process. Then, the results obtained via machine learning were validated with confirmatory tests and reported. The findings offer a practical solution for process parameter optimization, contributing to the progression of additive manufacturing technologies.
A Resolution Under Interval Uncertainty
Authors: Hwang Yan-An , Liao Yu-Hsien
Published: February 2025

Traditional transferable utility (TU) games assume precise real-valued utilities for coalition outcomes, but real-world situations often involve uncertainty or imprecision. Interval TU games extend the classical framework by representing utilities and payoffs as closed intervals, leveraging interval arithmetic to address inherent ambiguities in data. This paper reviews the theoretical foundations of interval TU games and explores allocating solutions under uncertainty. Central to this study is the adaptation of consistency, a fundamental property in game-theoretical resolutions, to the interval framework. Drawing on concepts such as the pseudo equal allocations of non-separable costs and the pseudo weighted allocations of non-separable costs, we characterize these allocation resolutions through a specific reduction and related consistency. By bridging classical TU games with interval generalizations, this study offers a robust foundation for analyzing allocations under uncertainty and outlines avenues for future research in theoretical and applied game theory.
On Concatenations of Regular Circular Word Languages
Authors: Abdallah Bilal , Nagy Benedek
Published: February 2025

In this paper, one-wheel and two-wheel concatenations of circular words and their languages are investigated. One-wheel concatenation is an operation that is commutative but not associative, while two-wheel concatenation is associative but not commutative. Moreover, two-wheel concatenation may produce languages that are not languages of circular words. We define two classes of regular languages of circular words based on finite automata: in a weakly accepted circular word language, at least one conjugate of each word is accepted by the automaton; in contrast, a strongly accepted language consists of words for which all conjugates are accepted. Weakly accepted circular word languages REGw, in fact, are regular languages that are the same as their cyclic permutations. Strongly accepted circular word languages, REGs, having words with the property that all their conjugates are also in the language, are also regular. We prove that REGw and REGs coincide. We also provide regular-like expressions for these languages. Closure properties of this class are also investigated.
A Narrative Review of RAS Mutations in Early-Stage Colorectal Cancer: Mechanisms and Clinical Implications
Authors: Yildirim Hasan Cagri , Gunenc Damla , Almuradova Elvina , Sutcuoglu Osman , Yalcin Suayib
Published: February 2025

Colorectal cancer (CRC) is the third-most common cancer globally and a leading cause of cancer-related deaths. While the prognostic and predictive roles of RAS mutations in advanced CRC are well-established, their significance in early-stage CRC remains a topic of debate. Studies have been conducted for many years on clinical and pathological parameters that may be associated with RAS mutation, and there are inconsistent results in this regard. Currently, the only biomarker used in early-stage CRC is microsatellite status. KRAS mutations are detected in 40–50% of patients with colorectal cancer. RAS activating mutations cause loss of EGFR regulation by acting on the RAS/RAF/MAPK signaling pathways. In advanced colorectal cancer, these mechanisms cause a decrease in the effectiveness of EGFR inhibitors. However, studies on patients with early-stage colorectal cancer have inconsistent results. This review highlights the prognostic and clinical significance of KRAS mutations in early-stage CRC, particularly in MSS tumors. In the MSS group, KRAS mutations were associated with shorter TTR and OS compared to DWT patients. In contrast, in the MSI-H group, KRAS mutations showed no prognostic effect in TTR and OS. However. KRAS mutations were associated with shorter SAR in both MSI-H and MSS groups of patients. The findings underscore the need for routine molecular profiling, including KRAS and MSI status, to refine risk stratification and guide adjuvant therapy decisions. Further studies are warranted to explore targeted therapeutic approaches for KRAS-mutant CRC in the adjuvant setting.
Microstructure and Mechanical Properties of Inconel 718 Alloy Fabricated Using Wire Feeding Oscillated Double-Pulsed GTA-AM
Authors: Zhang Gang , Zhang Cheng , Shi Yu , Fan Ding
Published: February 2025

To address anisotropy challenges in electric arc-based additive manufacturing of Inconel 718 alloy, this study develops a novel wire feeding oscillated double-pulsed gas tungsten arc welding additive manufacturing method (DP-GTA-AM) enabling precise thermal-mass transfer control. Series of crack-free thin-walled Inconel 718 alloy parts were successfully obtained by this proposed approach, and the microstructure and mechanical properties of the parts were thoroughly studied. The results indicate that the microstructure changes from dendrites and cellular crystals in the bottom to equiaxed grains in the midsection and entirely equiaxed crystals in the top, resulting in notable grain refinement. With an average grain size of 61.76 μm and an average length of 83.31 μm of large angle grain boundaries, the density of the <001> direction reaches 19.45. The difference in tensile strength and ductility between the horizontal and the vertical directions decreases to 6.3 MPa and 0.38%, which significantly diminishes anisotropy. Fractographic analysis confirms quasi-cleavage failure with homogeneous dimple distribution, demonstrating effective anisotropy mitigation through controlled solidification dynamics.
Transient Gel Diffusiophoresis of a Spherical Colloidal Particle
Authors: Ohshima Hiroyuki
Published: February 2025

A general theory is presented to analyze the time-dependent, transient diffusiophoresis of a charged spherical colloidal particle in an uncharged gel medium containing a symmetrical electrolyte when an electrolyte concentration gradient is suddenly applied. We derive the inverse Laplace transform of an approximate expression for the relaxation function R(t), which describes the time-course of the ratio of the diffusiophoretic mobility of a weakly charged spherical colloidal particle, possessing a thin electrical double layer, to its steady-state diffusiophoretic mobility. The relaxation function depends on the mass density ratio of the particle to the electrolyte solution, the particle radius, the Brinkman screening length, and the kinematic viscosity. However, it does not depend on the type of electrolyte (e.g., KCl or NaCl), which affects only the steady-state gel diffusiophoretic mobility. It is also found that the expression for the relaxation function in transient gel diffusiophoresis of a weakly charged spherical colloidal particle with a thin electrical double layer takes the same form as that for its transient gel electrophoresis.
Holobiome Harmony: Linking Environmental Sustainability, Agriculture, and Human Health for a Thriving Planet and One Health
Authors: García Gissel , Carlin Martha , Cano Raul de Jesus
Published: February 2025

The holobiome is an interconnected network of microbial ecosystems spanning soil, plants, animals, humans, and the environment. Microbial interactions drive nutrient cycling, pathogen suppression, and climate regulation. Soil microbiomes facilitate carbon sequestration and enhance soil fertility, while marine microbiomes contribute to carbon capture and climate stability. However, industrial agriculture, extensive herbicide use, antibiotic overuse, and climate change threaten microbial diversity, leading to ecosystem and health disruptions. Probiotic interventions help to restore microbial balance. In human health, probiotics support gut microbiota diversity, reduce inflammation, and regulate metabolism. In agriculture, soil probiotics enhance microbial diversity, improve nutrient cycling, and degrade contaminants, increasing crop yields and soil health. Case studies show that microbial inoculants effectively remediate degraded soils and enhance nutrient uptake. Artificial intelligence is transforming microbiome research by enabling predictive modeling, precision probiotic design, and microbial consortia optimization. Interdisciplinary collaboration and supportive policies are essential for restoring microbial equilibria, ensuring ecosystem resilience, and promoting long-term sustainability. The integration of artificial intelligence, clinical research, and sustainable practices is crucial for advancing holobiome science. The holobiome framework underscores the need for interdisciplinary collaboration to address global challenges, bridging environmental sustainability, agriculture, and public health for a resilient future.
Prediction of Lithofacies in Heterogeneous Shale Reservoirs Based on a Robust Stacking Machine Learning Model
Authors: Peng Sizhong , Feng Congjun , Qiu Zhen , Zhang Qin , Liu Wen , Feng Jun , Hu Zhi
Published: February 2025

The lithofacies of a reservoir contain key information such as rock lithology, sedimentary structures, and mineral composition. Accurate prediction of shale reservoir lithofacies is crucial for identifying sweet spots for oil and gas development. However, obtaining shale lithofacies through core sampling during drilling is challenging, and the accuracy of traditional logging curve intersection methods is insufficient. To efficiently and accurately predict shale lithofacies, this study proposes a hybrid model called Stacking, which combines four classifiers: Random Forest, HistGradient Boosting, Extreme Gradient Boosting, and Categorical Boosting. The model employs the Grid Search Method to automatically search for optimal hyperparameters, using the four classifiers as base learners. The predictions from these base learners are then used as new features, and a Logistic Regression model serves as the final meta-classifier for prediction. A total of 3323 data points were collected from six wells to train and test the model, with the final performance evaluated on two blind wells that were not involved in the training process. The results indicate that the stacking model accurately predicts shale lithofacies, achieving an Accuracy, Recall, Precision, and F1 Score of 0.9587, 0.959, 0.9587, and 0.9587, respectively, on the training set. This achievement provides technical support for reservoir evaluation and sweet spot prediction in oil and gas exploration.
Flavonoids and Saponins from Two Chenopodium Species (C. foliosum Asch. and C. bonus-henricus L.)—Preliminary Evaluation for hMAO-A/B, Neuroprotective Activity, and Validated UHPLC-HRMS Quantification of Ethanolic Extract from C. foliosum
Authors: Kondeva-Burdina Magdalena , Panayotova Dona , Nedialkov Paraskev T. , Kokanova-Nedialkova Zlatina
Published: February 2025

The development of more effective treatments for neurodegenerative disorders presents a significant challenge in modern medicine. Currently, scientists are focusing on discovering bioactive compounds from plant sources to prevent and treat neurodegenerative diseases. Fifteen flavonoids and saponins from C. foliosum Asch. and C. bonus-henricus L. were tested for their inhibitory activity on hMAO-A and hMAO-B. Five compounds (1 μM) exhibit a weak inhibitory effect on hMAO-A and show good inhibitory activity against the hMAO-B enzyme (30–35%), compared to the positive control selegiline (55%). These active compounds were examined on rat brain synaptosomes and mitochondria obtained by multiple differential centrifugations using a Percoll gradient. Their effects were also monitored on rat brain microsomes obtained by double differential centrifugation. The main parameters characterizing the functional–metabolic status of subcellular fractions are synaptosomal viability, GSH level, and MDA production. All tested compounds (50 μM) demonstrated significant neuroprotective and antioxidant activities across models of induced oxidative stress, including 6-OHDA, t-BuOOH, and Fe2+/AA-induced lipid peroxidation. The plausible mechanisms of neuroprotection rely on MAO-B inhibition, the scavenging of ROS, stabilizing the cell membrane by reducing MDA production, and neutralizing free radicals by maintaining GSH levels. In addition, we developed and validated a UHPLC-HRMS method for identifying and simultaneously quantificatying flavonoids and saponins in the aerial parts of C. foliosum. Compounds 30-normedicagenic acid- HexA-Hex-TA 22f and medicagenic acid-HexA-Hex-TA 25f were considered new natural compounds.
Type II ZnO-MoS2 Heterostructure-Based Self-Powered UV-MIR Ultra-Broadband p-n Photodetectors
Authors: Zhou Badi , Peng Xiaoyan , Chu Jin , Malca Carlos , Diaz Liz , Zhou Andrew F. , Feng Peter X.
Published: February 2025

This study presents the fabrication and characterization of ZnO-MoS2 heterostructure-based ultra-broadband photodetectors capable of operating across the ultraviolet (UV) to mid-infrared (MIR) spectral range (365 nm–10 μm). The p-n heterojunction was synthesized via RF magnetron sputtering and spin coating, followed by annealing. Structural and optical analyses confirmed their enhanced light absorption, efficient charge separation, and strong built-in electric field. The photodetectors exhibited light-controlled hysteresis in their I-V characteristics, attributed to charge trapping and interfacial effects, which could enable applications in optical memory and neuromorphic computing. The devices operated self-powered, with a peak responsivity at 940 nm, which increased significantly under an applied bias. The response and recovery times were measured at approximately 100 ms, demonstrating their fast operation. Density functional theory (DFT) simulations confirmed the type II band alignment, with a tunable bandgap that was reduced to 0.20 eV with Mo vacancies, extending the detection range. The ZnO-MoS2 heterostructure’s broad spectral response, fast operation, and defect-engineered bandgap tunability highlight its potential for imaging, environmental monitoring, and IoT sensing. This work provides a cost-effective strategy for developing high-performance, ultra-broadband, flexible photodetectors, paving the way for advancements in optoelectronics and sensing technologies.
Evaluation of Model and Process Optimization for the Treatment of Drilling Wastewater Using Electrocoagulation
Authors: Öden Muhammed Kamil
Published: February 2025

The extraction of underground resources has accelerated globally, in response to the demands of advancing technology and the rapidly growing population. The increase in drilling activities has caused an increase in environmental pollution problems caused by waste generated during drilling activities, namely drilling sludge and drilling wastewater. In this study, the treatability of wastewater generated during drilling operations in a basin, where an underground gas storage area was created, was investigated using an electrocoagulation (EC) process, using different electrode pairs. The removal efficiencies of the pollution parameters were determined using the response surface method. The wastewater parameters included different organic and inorganic pollutants, such as sodium, chloride, magnesium, and chemical oxygen demand (COD). The concentrations of sodium, chloride, and COD in drilling industry wastewater were found to be very high, at 128,567, 185,292, and 7500 mg/L, respectively. The data obtained in this study yielded a removal efficiency of approximately 65% and above. Sodium achieved the highest pollutant removal efficiency of 85% and above. The statistical values were interpreted for all the pollutants and the suitability of second-degree regression was observed.
MOF-Derived N-Doped Carbon Nanotube-Confined Ni Nanoparticles for the Simultaneous Electrochemical Detection of Cu²⁺ and Hg²⁺ with High Sensitivity and Stability
Authors: Li Jiapeng , Chen Lili , Qiao Yiming , Li Li , Li Xin , Deng Linbo , Duan Xuemin , Chen Hui , Gao Yansha
Published: February 2025

Heavy metal pollution has posed a serious threat to the ecological environment and human health. Thus, the development of accurate and effective methods for their detection is crucial. In this study, a novel electrochemical sensor was fabricated to detect Cu2+ and Hg2+, based on N-doped carbon nanotube-wrapped Ni nanoparticle (Ni@N-CNT) sensing material, which was derived from the pyrolysis of Ni2+ doped ZIF-8. For electrode material design, the packaging structure not only protected the encapsulated Ni nanoparticles from electrochemical corrosion in the acid electrolyte but also provided excellent electro-catalytic activity and electrical conductivity by controlling their size. Thanks to the overall performance of the Ni@N-CNT composite, the proposed sensor exhibited excellent analytical performance for Cu2+ and Hg2+ detection, with ultra-low detection limits of 33.3 ng⋅L−1 and 33.3 ng⋅L−1, respectively. The sensor also demonstrated good repeatability, reproducibility and selectivity. In addition, the method was successfully applied to the electrochemical analysis of Cu2+ and Hg2+ in actual Chinese cabbage samples with satisfactory recovery, confirming its practical applicability.
Sunlight-Induced Photocatalytic Removal of Paracetamol Using Au-TiO2 Nanoparticles
Authors: Aoudjit Lamine , Queirós Joana M. , Castro A. S. , Zioui Djamila , González-Ballesteros Noelia , Lanceros-Mendez S. , Martins Pedro M.
Published: February 2025

Using sunlight as the driving force for photocatalytic processes holds great promise for sustainability. As a starting point for developing a material capable of degrading aquatic pollutants using solar energy as a stimulus, this work focuses on synthesizing Au-TiO2 nanocomposites using the deposition–precipitation method. Characterization of Au-TiO2 nanoparticles was performed by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Transmission Electron Microscopy (TEM). A model pollutant, paracetamol, was used to test the synergetic effect of Au (0.05 wt%) nanoparticles (NPs) with TiO2 on photocatalytic activity. The influence of the parameters pH, loading (0.4, 0.8, and 1 g/L), pollutant concentration (20, 30, 40 ppm), and contact time (30, 60, 90, 120, 150, and 180 min) was studied by exposing the NPs to solar radiation. The photocatalytic degradation was most effective at a contact time of 3 h, an initial concentration of 20 ppm, and a pH of 6.8. Under these conditions, paracetamol in 1 g/L of Au-TiO2 nanocomposites can be degraded by more than 99.17% under solar irradiation. As a result of the Au-TiO2 composite’s ability to successfully serve as a photocatalyst using sun radiation, water purification processes can be more widespread, cost-effective, and environmentally friendly.
Picolinamide Functionalization on Carbon Nitride Edges for Enhanced Charge Separation and Photocatalytic Hydrogen Evolution
Authors: Li Peiru , Guo Siyuan , Liu Yunan , Lin Yanhong , Xie Tengfeng
Published: February 2025

The periodical distribution of N and C atoms in carbon nitride (CN) not only results in localized electrons in each tri-s-triazine unit, but oxidation and reduction sites are in close contact spatially, resulting in severe carrier recombination. Herein, the hydrothermal method was first employed to synthesize carbon nitride (HCN), and then picolinamide (Pic) molecules were introduced at the edge of the carbon nitride so that the photo-generated electrons of the whole structure of the carbon nitride system were transferred from the center to the edge, which effectively promoted the separation of photo-generated carriers and inhibited the recombination of carriers in the structure. The introduced picolinamide not only changed the π-conjugated structure of the entire system but also acted as an electron-withdrawing group to promote charge transfer. The photocatalytic hydrogen evolution rate (HER) of the optimized HCN-Pic-1:1 sample could reach 918.03 μmolg−1 h−1, which was 11.8 times higher than that of the HCN, and the performance also improved.
Assessing the Quality of Life of Pregnant Women in Romania: Socioeconomic, Health, and Obstetric Factors and the Validation of the WHOQOL-BREF Instrument
Authors: Radu Mihaela Corina , Armean Sebastian Mihai , Chivu Laura Ioana , Aurelian Justin , Medar Cosmin , Manolescu Loredana Sabina Cornelia
Published: February 2025

Pregnancy is a transformative stage in a woman’s life, marked by significant physical, emotional, and social changes. This study had three main objectives: (1) to assess the quality of life (QoL) of pregnant women in Romania, (2) to identify the sociodemographic, health, and obstetric factors influencing their QoL and (3) to examine the psychometric properties of the WHOQOL-BREF questionnaire within the Romanian context, determining its effectiveness in evaluating QoL during pregnancy. Methods: A cross-sectional analytical survey was conducted between January and July 2023 among pregnant women in Romania, targeting a geographically diverse sample from urban and rural areas. Eligible participants were Romanian citizens aged 18 or older. Data were collected through an online self-administered questionnaire using Google Forms, with informed consent obtained electronically. The survey included demographic, obstetric, and health-related variables alongside the WHOQOL-BREF tool, which evaluates QoL across four dimensions: Physical, Psychological, Social Relationships, and Environment. Statistical analysis involved confirmatory factor analysis, reliability testing (Cronbach’s α and McDonald’s ω), and comparisons using Welch’s t-tests and ANOVA. Results: A total of 1550 valid responses were analyzed. The WHOQOL-BREF demonstrated excellent internal consistency (Cronbach’s α > 0.9 across all dimensions). Women with higher education and stable employment reported significantly higher QoL scores in physical and psychological dimensions. No significant differences were found based on pregnancy trimester, previous births, or participation in prenatal classes, although trends suggested slight advantages for participants in prenatal education. Women delivering in private hospitals or non-hospital settings reported better psychological and physical QoL than those delivering in public hospitals. Support from partners and urban residency positively influenced perceived QoL. Conclusions: The WHOQOL-BREF is a reliable tool for assessing QoL in pregnant women in Romania. The study highlights the role of education, employment, and delivery location in influencing QoL, emphasizing the need for targeted support for vulnerable groups during pregnancy.
Ion Currents Mediated by TRPA1 Channels in Freshly Dissociated Rat Articular Chondrocytes: Biophysical Properties and Regulation by Inflammatory Processes
Authors: Ponce Arturo , Jimenez Lidia , Roldan Maria Luisa , Shoshani Liora
Published: February 2025

Background: Articular chondrocytes are specialized cells in synovial joint cartilage, responsible for maintaining and regenerating the extracellular matrix. Inflammation disrupts the balance between matrix synthesis and degradation, leading to cartilage breakdown. This process, commonly observed in conditions such as osteoarthritis, results in chondrocyte dysfunction and accelerates joint degeneration. Since TRPA1 channels are implicated in inflammatory processes, this study investigates the expression of TRPA1 channels in freshly dissociated rat articular chondrocytes and their modulation by anti-inflammatory agents. Methods: We used the whole-cell patch-clamp method to assess TRPA1 channel expression and modulation. Results: Freshly dissociated chondrocytes exhibit ion currents attributable to TRPA1 channel expression, with higher magnitudes observed in medium-sized cells. These currents decrease over time in primary culture. Treatment with pro-inflammatory agents (IL-1α, IL-1β, and LPS) increases TRPA1′s current magnitude. IL-1β treatment directly induces transient TRPA1 currents. Several signaling components activated during inflammation contribute to the IL-1β-induced enhancement of TRPA1 current density, including IL-1 R1, the adaptor protein MyD88, and the downstream kinases IRAK1 and IRAK4. Conclusions: Our findings demonstrate that healthy rat chondrocytes express functional TRPA1 channels and that inflammatory processes modulate their expression.
Anticancer Nanoparticle Carriers of the Proapoptotic Protein Cytochrome c
Authors: Zhivkov Alexandar M. , Hristova Svetlana H. , Popov Trifon T.
Published: February 2025

This review discusses the literature data on the synthesis, physicochemical properties, and cytotoxicity of composite nanoparticles bearing the mitochondrial protein cytochrome c (cytC), which can act as a proapoptotic mediator in addition to its main function as an electron carrier in the electron transport chain. The introduction of exogenous cytC via absorption of carrier particles, the phagocytosis of colloid particles of submicrometric size, or the receptor-mediated endocytosis of nanoparticles in cancer cells, initiates the process of apoptosis—a multistage cascade of biochemical reactions leading to complete destruction of the cells. CytC–carrier composite particles have the potential for use in the treatment of neoplasms with superficial localization: skin, mouth, stomach, colon, etc. This approach can solve the two main problems of anticancer therapy: selectivity and non-toxicity. Selectivity is based on the incapability of the normal cell to absorb (nano)particles, except for the cells of the immune system. The use of cytC as a protein that normally functions in mitochondria is harmless for the macroorganism. In this review, the factors limiting cytotoxicity and the ways to increase it are discussed from the point of view of the physicochemical properties of the cytC–carrier particles. The different techniques used for the preparation of cytC-bearing colloids and nanoparticles are discussed. Articles reporting the achievement of high cytotoxicity with each of the techniques are critically analyzed.
Controllable Burst-Mode Nd3+:YAG/Cr4+:YAG Laser Pumped by 808 nm Polarization-Combined Laser Diodes
Authors: Dang Xincheng , Zhang Nihui , Wang Hai , Xin Di , Li Tongtong , Zhang Weiqiao , Zhou Xuyan , Zheng Wanhua , Zhang Hongbo
Published: February 2025

This paper presents a time-shared pumping technology for semiconductor lasers based on polarization-combined technology, which enables a compact passively Q-switched Nd3+:YAG/Cr4+:YAG laser to generate tunable pulse sequence output. Two 808 nm laser diodes (LDs) with high polarization were integrated into a casing system measuring 61.5 mm × 32 mm × 12.5 mm through the implementation of fast and slow axis collimation, polarization-combined, and beam-shaping techniques. The study introduces a temporal modulation function to the electrical driving signals, allowing for synchronous and delayed control of the two laser pump sources. By adjusting the pumping delays (200 μs, 240 μs, 280 μs, and 320 μs), two types of pulse sequences combined by “1 + 1” and “2 + 2” at 1064 nm were successfully generated. Experimental results demonstrated that the energy and intensity of each sub-pulse within the burst-mode remain stable throughout the entire sequence, with adjustable sub-pulse interval. Furthermore, the laser system exhibited good beam quality with near-diffraction-limited output characteristics (M2 < 1.5). In general, the tunable pulse sequence laser source offers significant potential for applications in high-precision laser processing, laser ranging and precision measurement, demonstrating its broad application potential.
Utilization of Antagonistic Interactions Between Micronutrients and Cadmium (Cd) to Alleviate Cd Toxicity and Accumulation in Crops
Authors: Shahzad Muhammad , Bibi Ayesha , Khan Ameer , Shahzad Ali , Xu Zhengyuan , Maruza Tagarika Munyaradzi , Zhang Guoping
Published: February 2025

The presence of cadmium (Cd) in agricultural soils poses a serious risk to crop growth and food safety. Cadmium uptake and transport in plants occur through the various transporters of nutrient ions that have similar physical and chemical properties to Cd, indicating that the genetic manipulation of these transporters and agronomic improvement in the Cd-antagonistic nutrients could be a good approach for reducing Cd uptake and accumulation in crops. In this review, we discuss the interactions between Cd and some micronutrients, including zinc (Zn) and manganese (Mn), focusing on their influence on the expression of genes encoding Cd-related transporters, including ZIP7, NRAMP3, and NRAMP4. Genetic improvements in enhancing the specificity and efficiency of transporters and agronomic improvements in optimizing micronutrient nutrition can inhibit the Cd uptake and transport by these transporters. This comprehensive review provides a deep insight into genetic and agronomic improvement for fighting against Cd contamination and enhancing sustainable agricultural production.