bluuebunny/crossref_metadata_2025 huggingface dataset:
AdaMoR-DDMOEA: Adaptive Model Selection with a Reliable Individual-Based Model Management Framework for Offline Data-Driven Multi-Objective Optimization
Authors: Pramanik Subhadip , Alameen Abdalla , Mohapatra Hitesh , Pathak Debanjan , Goswami Adrijit
Published: January 2025

Many real-world expensive industrial and engineering multi-objective optimization problems (MOPs) are driven by historical, experimental, or simulation data. In such scenarios, due to the expensive cost and time required, we are only left with a small amount of labeled data to perform the optimization. These offline data-driven MOPs are usually solved by multi-objective evolutionary algorithms (MOEAs) with the help of surrogate models constructed from offline historical data. The key challenge in developing these data-driven MOEAs is that they have to replace multiple conflicting fitness functions by approximating these objective functions, which may produce cumulative approximation errors and misguide the search. In order to build a reliable surrogate model from a small amount of multi-output offline data and solve the DDMOPs, we have proposed an adaptive model selection method with a reliable individual-based model management-driven MOEA. The proposed algorithm dynamically selects between DNN and XGBoost by comparing their k-fold cross-validation MAE error, which can capture the true generalization ability of the surrogates on unseen data. Then, the selected surrogate is updated with a reliable individual selection strategy, where the individual who is closest, both in the decision and objective space, to the most preferred solution among labeled offline data is chosen. As a result, these two strategies guide the underlying MOEA to the Pareto optimal solutions. The empirical results of the ZDT and DTLZ benchmark test suite validate the use of the three state-of-the-art offline DDMOEAs, showing that our algorithm is able to achieve highly competitive results in terms of convergence and diversity for 2–3 objectives. Finally, our algorithm is applied to an offline data-driven multi-objective problem—transonic airfoil (RAE 2822) shape optimization—to validate its efficiency on real-world DDMOPs.
Differentiating Apical and Basal Left Ventricular Aneurysms Using Sphericity Index: A Clinical Study
Authors: Tomić Slobodan , Veljković Stefan , Šljivo Armin , Radoičić Dragana , Lončar Goran , Bojić Milovan
Published: January 2025

Background and Objectives: Left ventricular aneurysm (LVA) causes geometric changes, including reduced systolic function and a more spherical shape, which is quantified by the sphericity index (SI), the ratio of the short to long axis in the apical four-chamber view. This study aimed to assess SI’s value in A-LVA and B-LVA, identify influencing factors, and evaluate its clinical relevance. Materials and Methods: This clinical study included 54 patients with post-infarction LVA and used echocardiography to determine LVA locations (A-LVA near the apex and B-LVA in the basal segments), with SI and other echocardiographic measures assessed in both systole and diastole for the entire cohort and stratified by A-LVA and B-LVA groups. Results: Among the 54 patients, 41 had A-LVA and 13 had B-LVA. The mean SI was 0.55 in diastole and 0.47 in systole for the cohort. Patients with A-LVA had a mean SI of 0.51 in diastole and 0.44 in systole, while B-LVA patients exhibited significantly higher SI values, with 0.65 in diastole and 0.57 in systole, due to lower long-axis (L) values in both phases. The mean left ventricular ejection fraction (EF) was 23.95% in A-LVA and 30.85% in B-LVA, with no significant difference. However, apical aneurysms were larger (greater LVAV and LVAA) and more significantly reduced functional myocardium. LVEDV, LVESV, LVEDA, and LVESA did not differ significantly between A-LVA and B-LVA. In cases of severe mitral regurgitation (MR), SI was notably higher (0.75 in diastole) due to a marked reduction in the L axis. Conclusions: SI is key in differentiating A-LVA and B-LVA on echocardiography. B-LVA has lower volume and area values, but similar aneurysm and left ventricular volumes and EF. Higher SI in B-LVA is due to a reduced L-axis, and is worsened by severe mitral regurgitation (MR). Surgical ventricular reconstruction (SVR) compensates for L-axis reduction, with preservation of the L axis critical for achieving a more physiological shape. SI thus serves as a marker for left ventricular geometry and surgical outcomes.
Effect of Nb and Si Content on Phase Stability, Microstructure and Mechanical Properties of Sintered Ti–Nb–Si Alloys
Authors: Luup Carvalho Derek Manoel , Paim Deivison Daros , Schramm Deschamps Isadora , Aguilar Claudio , Klein Aloísio Nelmo , Cavilha Neto Francisco , Oliveira Neves Guilherme , Binder Cristiano
Published: January 2025

The development of beta titanium alloys with biocompatible elements to replace Al and V is a subject of significant interest in the biomedical industry. This approach aims to enhance biocompatibility and mitigate potential cytotoxic effects associated with traditional alloying elements. In this work, Ti–xNb–ySi alloys were produced using powder metallurgy, with x of 35, 40, and 45 wt.%, and y of 0.10, 0.35, and 0.60% wt.%, using a 32 experimental design. Milling was used to mix and disperse the powders, followed by cold pressing, sintering, and heat treatment. Nb was the main element used to stabilize the β phase, and Si was used to form Si precipitates, although Si also exhibits a β-stabilizing effect. It was found that an increase from 0.10 to 0.35 wt.% of Si improved relative density, with no benefits observed at 0.60 wt.% Si. Electron microscopy showed the presence of β phase grains, and grains with β + α intragranular structures and precipitates. Increasing Nb content resulted in a decrease in ultimate tensile strength while increasing Si content from 0.10% to 0.35 wt.% exhibited the opposite effect.
Development of Solid Nanosystem for Delivery of Chlorhexidine with Increased Antimicrobial Activity and Decreased Cytotoxicity: Characterization and In Vitro and In Ovo Toxicological Screening
Authors: Dănilă Alexandra-Ioana , Romînu Mihai , Munteanu Krisztina , Moacă Elena-Alina , Geamantan-Sîrbu Andreea , Olariu Iustin , Marian Diana , Olariu Teodora , Talpoş-Niculescu Ioana-Cristina , Cosoroabă Raluca Mioara , Popovici Ramona , Dinu Ştefania
Published: January 2025

The evaluation of chlorhexidine-carrier nanosystems based on iron oxide magnetic nanoparticles (IOMNPs), has gained significant attention in recent years due to the unique properties of the magnetic nanoparticles (NPSs). Chlorhexidine (CHX), a well-established antimicrobial agent, has been widely used in medical applications, including oral hygiene and surgical antisepsis. This study aims to report an in vitro and in ovo toxicological screening of the synthesized CHX-NPS nanosystem, of the carrier matrix (maghemite NPSs) and of the drug to be delivered (CHX solution), by employing two types of cell lines—HaCaT immortalized human keratinocytes and JB6 Cl 41-5a murine epidermal cells. After the characterization of the CHX-NPS nanosystem through infrared spectroscopy and electronic microscopy, the in vitro results showed that the CHX antimicrobial efficacy was enhanced when delivered through a nanoscale system, with improved bioavailability and reduced toxicity when this was tested as the newly CHX-NPS nanosystem. The in ovo screening exhibited that the CHX-NPS nanosystem did not cause any sign of irritation on the chorioallantoic membrane vasculature and was classified as a non-irritant substance. Despite this, future research should focus on optimizing this type of nanosystem and conducting comprehensive in vivo studies to validate its therapeutic efficacy and safety in clinical settings.
Antimicrobial Properties of Monomeric and Dimeric Catanionic Surfactant System
Authors: Kowalczyk Iwona , Koziróg Anna , Szulc Adrianna , Komasa Anna , Brycki Bogumił
Published: January 2025

Cationic gemini surfactants are used due to their broad spectrum of activity, especially surface, anticorrosive and antimicrobial properties. Mixtures of cationic and anionic surfactants are also increasingly described. In order to investigate the effect of anionic additive on antimicrobial activity, experimental studies were carried out to obtain MIC (minimal inhibitory concentration) against E. coli and S. aureus bacteria. Two gemini surfactants (12-6-12 and 12-O-12) and two single quaternary ammonium salts (DTAB and DDAC) were analyzed. The most commonly used commercial compounds of this class, i.e., SDS and SL, were used as anionic additives. In addition, computer quantum mechanical studies were also carried out to confirm the relationship between the structure of the mixture and the activity. The obtained results of microbiological tests and quantum mechanical calculations are in agreement with each other and show the lack of synergism in catanionic mixtures in the case of antibacterial activity.
Sustainable Valorization of Rice Straw into Biochar and Carbon Dots Using a Novel One-Pot Approach for Dual Applications in Detection and Removal of Lead Ions
Authors: Singh Jagpreet , Bhattu Monika , Verma Meenakshi , Bechelany Mikhael , Brar Satinder Kaur , Jadeja Rajendrasinh
Published: January 2025

Lead (Pb) is a highly toxic heavy metal that causes significant health hazards and environmental damage. Thus, the detection and removal of Pb2+ ions in freshwater sources are imperative for safeguarding public health and the environment. Moreover, the transformation of single resources into multiple high-value products is vital for achieving sustainable development goals (SDGs). In this regard, the present work focused on the preparation of two efficient materials, i.e., biochar (R-BC) and carbon dots (R-CDs) from a single resource (rice straw), via a novel approach by using extraction and hydrothermal process. The various microscopic and spectroscopy techniques confirmed the formation of porous structure and spherical morphology of R-BC and R-CDs, respectively. FTIR analysis confirmed the presence of hydroxyl (–OH), carboxyl (–COO) and amine (N–H) groups on the R-CDs’ surface. The obtained blue luminescent R-CDs were employed as chemosensors for the detection of Pb2+ ions. The sensor exhibited a strong linear correlation over a concentration range of 1 µM to 100 µM, with a limit of detection (LOD) of 0.11 µM. Furthermore, the BET analysis of R-BC indicated a surface area of 1.71 m2/g and a monolayer volume of 0.0081 cm3/g, supporting its adsorption potential for Pb2+. The R-BC showed excellent removal efficiency of 77.61%. The adsorption process followed the Langmuir isotherm model and second-order kinetics. Therefore, the dual use of rice straw-derived provides a cost-effective, environmentally friendly solution for Pb2+ detection and remediation to accomplish the SDGs.
Association Between Physical Fitness and Cardiovascular Health in Chilean Schoolchildren from the Metropolitan Region
Authors: Vasquez Fabian , Salazar Gabriela , Vasquez Sofia , Torres Jorge
Published: January 2025

Background: Cardiovascular diseases increasingly impact youth, with early development of risk factors such as obesity, hypertension, and inadequate nutrient intake. Proper nutrient intake and physical fitness are vital for reducing these risks, especially in pediatric populations. This study explores the connection between physical fitness, metabolic risk, and nutrient status among 1656 Chilean schoolchildren from diverse socio-economic backgrounds. Methods: Anthropometric measures included weight, height, skinfold thickness, waist circumference, and blood pressure. Physical fitness was assessed via handgrip strength, standing long jump, and a six-minute walk test. Nutrient intake was also evaluated, and a composite metabolic risk score was calculated based on waist circumference, skinfolds, and blood pressure. Results: Boys consistently outperformed girls in physical fitness tests, including grip strength and horizontal jump, with differences becoming more pronounced in higher grades and Tanner stages. Girls exhibited higher subcutaneous fat levels and obesity prevalence during later grades, highlighting gender-specific patterns in body composition. Better physical fitness was associated with lower waist circumference, skinfold thickness, and metabolic risk scores. A moderate correlation between aerobic fitness (distance/height) and blood pressure (r = 0.27, p = 0.01) was observed. Z-Score MR analysis revealed that students in the lowest fitness tertile exhibited significantly higher cardiovascular risk profiles compared to their fitter peers. Conclusions: Physical fitness plays a critical role in reducing cardiovascular risk in children. The findings underscore the importance of promoting gender- and age-specific interventions that include both aerobic and strength-based physical activities. Comprehensive school programs focusing on nutrition and physical activity are essential to mitigating cardiovascular risk and promoting long-term health outcomes. Future longitudinal studies are recommended to establish causal relationships and evaluate the impact of targeted interventions.
Dietary Disruptors in Romania: Seasonality, Traditions, and the COVID-19 Pandemic
Authors: Pană Adrian , Strilciuc Ștefan , Ileanu Bogdan-Vasile
Published: January 2025

Background: The global rise in obesity has been significantly influenced by shifts in dietary habits that have been exacerbated by external factors such as the COVID-19 pandemic. This study aims to analyze the trends in Romanian dietary habits from 2015 to 2023, focusing on the impact of the COVID-19 pandemic and the role of socio-economic factors, seasonality, and cultural practices. Methods: For dietary habits, we used nationally representative data from the Romanian Household Budget Survey provided by the Romanian National Institute of Statistics. The survey includes 30,000 households annually. From the same provider, we downloaded data about potential drivers of food consumption, such as income, the consumer price index, and the unemployment rate. The analysis mixes descriptive statistics and panel data analysis. Among the main drivers, the econometric models include seasonality and regional factors, ensuring a comprehensive understanding of the changes in dietary behavior. Results: During the COVID-19 pandemic, daily calorie consumption increased to over 3000 calories per person, representing a 20% increase compared to the pre-pandemic period. Post-pandemic, food consumption remains elevated, averaging 2500–2600 calories per person daily. The pandemic also led to a shift in dietary composition, with significant changes. Thus, we mark an increase in fat (p < 0.001) and carbohydrate intake (p < 0.01) and a decrease in protein intake (p < 0.001). Beyond the presence of health disruptors, we confirm the significant impact of income (p < 0.001) and seasonality (p < 0.001). Other factors like unemployment, the consumer price index, and hidden regional factors have a minor role. Conclusions: The COVID-19 pandemic has had a lasting impact on Romanian dietary habits, reinforcing unhealthy eating patterns that were already prevalent. The sustained increase in calorie consumption, particularly of nutrient-poor, energy-dense foods, poses a significant public health challenge. The study also highlights significant seasonal variations, with a marked increase in food intake during the last quarter of the year, driven by cultural and religious traditions. These findings underscore the need for targeted public health interventions and policies that address economic factors and cultural and regional influences to promote healthier dietary behaviors in Romania.
Pharmaceutical Humanities and Narrative Pharmacy: An Emerging New Concept in Pharmacy
Authors: Banerjee Mita , Efferth Thomas
Published: January 2025

The complexity of our life experiences and the rapid progress in science and technology clearly necessitate reflections from the humanities. The ever-growing intersection between science and society fosters the emergence of novel interdisciplinary fields of research. During the past decade, Medical Humanities arose to meet the need to unravel hidden information beyond technology-driven and fact-based medicine. In the present paper, we put forward the hypothesis that there is a similar requirement to develop Pharmaceutical Humanities as an academic discipline within pharmacy and pharmaceutical biology. Based on Thomas Kuhn’s epistemological theory on the structure of scientific revolutions, one may argue that a paradigm change for Pharmaceutical Humanities might open new levels of insight. Many complex diseases (e.g., cancer, neurological diseases, and mental disorders) remain uncurable for many patients by current pharmacotherapies, and the old beaten paths in our therapeutic thinking may at least partly have to be left behind. By taking examples from Pharmaceutical Biology, we attempt to illustrate that the transdisciplinary dialogue with the humanities is fertile ground not only for enlarging our understanding of disease-related conditions but also for exploring new ways of combatting diseases. In this context, we discuss aspects related to traditional herbal medicine, fair access and benefit sharing of indigenous knowledge about medicinal plants, post-traumatic stress syndrome, the opioid crisis, stress myocardiopathy (broken heart syndrome), and global environmental pollution with microplastics. We also explore possibilities for a narrative turn in pharmacy. The urgent need for inter- and transdisciplinary solutions to pressing health-related problems in our society may create a scholarly atmosphere for the establishment of Pharmaceutical Humanities as a fruitful terrain to respond to the current demands of both science and society.
Cutting-Edge Advances in Anticancer Therapies: Insights from the Third Edition of the Special Issue “Novel Anticancer Strategies”
Authors: Bousbaa Hassan
Published: January 2025

Cancer incidence and mortality continue to rise at an alarming rate worldwide, underscoring the urgent need for more effective therapeutic interventions [...]
Development and Application of Physiologically-Based Pharmacokinetic Model to Predict Systemic and Organ Exposure of Colorectal Cancer Drugs
Authors: Peribañez-Dominguez Sara , Parra-Guillen Zinnia , Troconiz Iñaki F.
Published: January 2025

Background/Objectives: Colorectal cancer (CRC) holds the third and second position among cancers affecting men and women, respectively. Frequently, the first-line treatment for metastatic CRC consists of the intravenous administration of 5-fluorouracil and leucovorin in combination with oxaliplatin or irinotecan. Physiologically-based pharmacokinetic models (PBPK) aim to mechanistically incorporate body physiology and drug physicochemical attributes, enabling the description of both systemic and organ drug exposure based on the treatment specificities. This bottom-up approach represents an opportunity to personalize treatment and minimize the therapeutic risk/benefit ratio through the understanding of drug distribution within colorectal tissue. This project has the goal of characterizing the systemic and tissue exposure of four anti-cancer drugs in humans using a PBPK platform fed with data from the literature. Methods: A literature search was performed to collect clinical data on systemic concentration versus time profiles. Physicochemical features were obtained from the literature, as well as parameters associated with distribution, metabolism, and excretion. The PBPK models were built using PK-Sim®. Results: The data from 51 clinical studies were extracted and combined in one single dataset. The PBPK models successfully described the exposure vs. time profiles with respect to both, with both the typical tendency and dispersion shown by the data. The percentage of observations falling within the two-fold error bounds ranged between 94 and 100%. The colon/plasma AUCinf ratios were similar for 5-FU, oxaliplatin, and leucovorin, but it was significantly higher for irinotecan. Conclusions: The PBPK models support tailored treatment approaches by linking in vitro studies to organ exposure. These models serve as the initial step towards incorporating a dedicated tumor compartment, which will further account for the variability in tumor microenvironment characteristics to improve therapeutic strategies.
Effect of Staggered vs. Simultaneous Co-Administration of Bempedoic Acid on Pharmacokinetics of Pravastatin: Randomized, Cross-Over Clinical Trial in Healthy Volunteers
Authors: Stoll Felicitas , Amato Salvatore , Sauter Max , Burhenne Jürgen , Weiss Johanna , Haefeli Walter E. , Blank Antje
Published: January 2025

Background/Objectives: Bempedoic acid (BA) is a novel cholesterol-lowering agent with proven positive effects on cardiovascular endpoints. Because it is an inhibitor of the hepatic transporters OATP1B1 and OATP1B3, two uptake transporters regulating the intrahepatic availability of statins, it increases the systemic exposure of co-administered statins. This interaction could raise the risk of myopathy. We hypothesized that the drug interaction between BA and statins could be mitigated by staggered administration. Methods: This was a single-centre, open-label, randomized, two-arm, cross-over, phase I drug interaction trial in healthy volunteers (EudraCT-No: 2022-001096-13). The primary objective was to evaluate the OATP1B1 inhibitory effect of BA on exposure to pravastatin after simultaneous administration versus different schedules of staggered administration. A secondary objective was to evaluate the impact of SLCO1B1 genotypes (*1, *5, *15, *37) on pravastatin exposure. Pravastatin was administered in single oral doses of 40 mg at six visits. After a baseline visit with pravastatin alone, BA was dosed to steady state at the approved oral dose of 180 mg. Outcome measures were the area under the plasma concentration–time curve, extrapolated to infinity (AUC∞) and Cmax of pravastatin, 3α-hydroxy-pravastatin (pravastatin 3-iso), and pravastatin lactone, and their geometric mean ratios (GMRs) of different schedules of administration. Log-transformed AUC∞ and Cmax were compared with one-way ANOVA with a 90% confidence interval (CI). Results: Fourteen participants completed all visits. At BA steady state, the GMRs of pravastatin AUC∞ and Cmax were 1.80 (90% CI 1.31–2.46) and 1.95 (90% CI 1.40–2.72), respectively, compared to baseline. There was no significant difference in pravastatin exposure between simultaneous vs. staggered administration. There was no statistically significant difference in pravastatin 3-iso or pravastatin lactone between different administration modes. For the AUC∞ of pravastatin and pravastatin 3-iso, haplotype was a significant source of variation (63% and 20%, respectively), while the type of administration (simultaneous vs. staggered) had no significant impact. Conclusions: The increase in pravastatin exposure with concomitant intake of BA was larger than expected. There was no significant difference between simultaneous vs. staggered administration of pravastatin and BA, possibly due to a population that was heterogenous in SLCO1B1 haplotypes.
Gray-Level Co-Occurrence Matrix Uniformity Correction Algorithm in Positron Emission Tomographic Image: A Phantom Study
Authors: Kim Kyuseok , Lee Youngjin
Published: January 2025

High uniformity of positron emission tomography (PET) images in the field of nuclear medicine is necessary to obtain excellent and stable data from the system. In this study, we aimed to apply and optimize a PET/magnetic resonance (MR) imaging system by approaching the gray-level co-occurrence matrix (GLCM), which is known to be efficient in the uniformity correction of images. CAIPIRINHA Dixon-VIBE was used as an MR image acquisition pulse sequence for the fast and accurate attenuation correction of PET images, and the phantom was constructed by injecting NaCl and NaCl + NiSO4 solutions. The lambda value of the GLCM algorithm for uniformity correction of the acquired PET images was optimized in terms of energy and contrast. By applying the GLCM algorithm optimized in terms of energy and contrast to the PET images of phantoms using NaCl and NaCl + NiSO4 solutions, average percent image uniformity (PIU) values of 26.01 and 83.76 were derived, respectively. Compared to the original PET image, an improved PIU value of more than 30% was derived from the PET image to which the proposed optimized GLCM algorithm was applied. In conclusion, we demonstrated that an algorithm optimized in terms of the GLCM energy and contrast can improve the uniformity of PET images.
Enhanced Phytoextraction Technologies for the Sustainable Remediation of Cadmium-Contaminated Soil Based on Hyperaccumulators—A Review
Authors: Cao Xuerui , Dong Qing , Mao Lihui , Yang Xiaoe , Wang Xiaozi , Zou Qingcheng
Published: January 2025

Heavy metal pollution in soil is a significant challenge around the world, particularly cadmium (Cd) contamination. In situ phytoextraction and remediation technology, particularly focusing on Cd hyperaccumulator plants, has proven to be an effective method for cleaning Cd-contaminated agricultural lands. However, this strategy is often hindered by a long remediation cycle and low efficiency. To address these limitations, assisted phytoextraction has been proposed as a remediation strategy based on the modification of certain traits of plants or the use of different materials to enhance plant growth and increase metal absorption or bioavailability, ultimately aiming to improve the remediation efficiency of Cd hyperaccumulators. To thoroughly understand the progress of Cd hyperaccumulators in remediating Cd-polluted soils, this review article discusses the germplasm resources and assisted phytoextraction strategies for these plants, including microbial, agronomic measure, chelate, nanotechnology, and CO2-assisted phytoextraction, as well as integrated approaches. This review paper critically evaluates and analyzes the numerous approaches and the remediation potential of Cd hyperaccumulators and highlights current challenges and future research directions in this field. The goal is to provide a theoretical framework for the further development and application of Cd pollution remediation technologies in agricultural soils.
Antifungal Activity of Genistein Against Phytopathogenic Fungi Valsa mali Through ROS-Mediated Lipid Peroxidation
Authors: Li Fangjie , Yang Chen , Li Maoye , Liu Su , Xu Kuo , Fu Xianjun
Published: January 2025

Valsa mali (V. mali) is a necrotrophic fungus responsible for apple Valsa canker, which significantly diminishes apple production yields and quality in China. Our serendipitous findings revealed that genistein significantly inhibits the mycelial growth of V. mali, with an inhibition rate reaching 42.36 ± 3.22% at a concentration of 10 µg/mL. Scanning electron microscopy analysis revealed that genistein caused significant changes in the structure of V. mali, including mycelial contraction, distortion, deformity, collapse, and irregular protrusions. Transmission electron microscopy analysis revealed leakage of cellular contents, blurred cell walls, ruptured membranes, and organelle abnormalities. Genistein has been shown to increase reactive oxygen species levels in V. mali mycelia, as demonstrated by 2′,7′-dichlorofluorescin diacetate staining. This increase was associated with a decrease in superoxide dismutase activity alongside increases in catalase and peroxidase activities. These changes collectively disrupted the oxidative equilibrium, leading to the induction of oxidative stress. The transcriptomic analysis revealed 13 genes enriched in this process, linked to unsaturated fatty acid biosynthesis (three downregulated DEGs), saturated fatty acid biosynthesis (three upregulated and six downregulated DEGs), and fatty acid metabolism (four upregulated and nine downregulated DEGs). Additionally, the downregulated DEGs VMIG_07417 and VMIG_08675, which are linked to ergosterol biosynthesis, indicate possible changes in membrane composition. In conjunction with the qRT-PCR results, it is hypothesized that genistein exerts an antifungal effect on V. mali through ROS-mediated lipid peroxidation. This finding has the potential to contribute to the development of novel biological control agents for industrial crops.
Rice Starch Chemistry, Functional Properties, and Industrial Applications: A Review
Authors: Shoukat Rizwan , Cappai Marta , Pilia Luca , Pia Giorgio
Published: January 2025

Starch is among the most abundant natural compounds in nature after cellulose. Studies have shown that the structure and functions of starch differ extensively across and among botanical types, isolation procedures, and climate factors, resulting in starch with significant variations in its chemical, physical, morphological, thermal, and functional characteristics. To enhance its beneficial properties and address inherent limitations, starch is modified through various techniques, resulting in significant alterations to its chemical and physical characteristics. These structural modifications impart considerable technological and industrial versatility. In the food sector, modified starch serves as a thickener, shelf-life extender, fat replacer, texture modifier, gelling agent, and stabilizer. In non-food applications, it functions as a sizing agent, binder, disintegrant, absorbent, and adhesive and is employed in construction as a sealant and to improve material bonding strength. The demand for modified starch has surpassed that of its native counterpart, reflecting its growing market value and the industry’s interest in products with novel functional attributes and enhanced value. This study focuses on rice starch, highlighting its structure and composition and their impact on physicochemical properties and functionality. Additionally, it examines the enhancement of its techno-functional characteristics, achieved through various modification processes.
Advancements in Carbohydrate Scaffold Synthesis: Exploring Prins Cyclization Methodology
Authors: Dubbu Sateesh , Jampani Santhi
Published: January 2025

The synthesis of natural and unconventional compounds with carbohydrate structures is of great interest to glycochemists due to their vital biological roles. In recent years, there has been significant progress in developing direct and indirect synthetic strategies for constructing sugar moieties. Among these methods, the Prins reaction, employing homoallylic alcohols and carbonyl compounds, has proven invaluable for directly creating sugar skeletons. This review discusses approaches for crafting carbohydrate frameworks using the Prins reaction, utilizing both carbohydrate and non-carbohydrate starting materials.
Recycling of Bulk Polyamide 6 by Dissolution-Precipitation in CaCl2-EtOH-H2O Mixtures
Authors: Goldhahn Ruben , Minor Ann-Joelle , Rihko-Struckmann Liisa , Ohl Siew-Wan , Pfeiffer Patricia , Ohl Claus-Dieter , Sundmacher Kai
Published: January 2025

To address the problems of virgin plastic production from fossil resources and the growing amount of plastic waste, a rapid transition to a circular economy is being pursued. The separation of mixed plastics into pure fractions is of paramount importance for promoting recycling and preventing downcycling. In this study, experimental parameters were determined for the selective bulk dissolution of polyamide 6 (PA 6) filaments (1.75 mm diameter, 1 cm length) in CaCl2-EtOH-H2O mixtures (CEW) at 75 °C. These parameters included the energy supply mode, dissolution time, CEW composition and CEW:PA mass ratio. Compared with energy supply by microwaves, energy supply by ultrasound improved the yield of dissolved and recovered PA 6 after 5 h from 31% to 52%. In total, the yield of PA 6 after 3 h of bulk dissolution increased from 18% to 69% when the energy supply mode was changed from microwave to ultrasound and the H2O:EtOH molar ratio of CEW was increased from 0.40 to 1.33 while maintaining an optimal CEW:PA mass ratio of 8.5. Additionally, master plot analysis suggested that dissolution under microwave energy supply followed a contracting cylinder model, whereas dissolution under ultrasonic energy supply aligned with a 2D diffusion or third-order kinetic model. Microscopic observations suggested that, in the case of ultrasonic energy supply, oscillating bubbles on the particle surface enhanced the dissolution rate of PA 6 filaments in CEW.
Multispectral, Thermal, and Hyperspectral Sensing Data Depict Stomatal Conductance in Grapevine
Authors: Veloo Kesevan , Zúñiga Espinoza Carlos , Salgado Alberto Espinoza , Jacoby Pete W. , Sankaran Sindhuja
Published: January 2025

Climate-driven water challenges in the Pacific Northwest necessitate precise irrigation for sustainable vineyard management. In such scenarios, conservation of water using different approaches, including subsurface irrigation, becomes critical. Detecting crop water status becomes key to evaluating and managing such approaches. This study examines how multispectral, thermal, and hyperspectral proximal sensing data depict irrigation-induced variations in stomatal conductance in Cabernet Sauvignon vineyards during 2016 and 2017. The roles of individual and combined sensing modalities were analyzed, with key contributions including the identification of indices that characterize stomatal conductance. Data were collected at the following growth stages: 80 and 44 days before harvest (DBH) in 2016; and 64, 44, and 8 DBH in 2017. The vegetation indices analyzed included the green normalized difference vegetation index (GNDVI) and leaf area index (LAI) from multispectral data, crop water stress index (CWSI) from thermal data, and normalized difference spectral indices (NDSI) from hyperspectral data. Pearson’s correlations at 80 and 44 DBH (2016) showed significant relationships between normalized stomatal conductance and multispectral indices (LAI: r = 0.59 to 0.66, GNDVI: r = 0.41 to 0.50, both p < 0.01). NDSI pairs (1380 nm with 1570 nm, 1570 nm with 1810 nm) at 80 DBH showed significant correlations (r = −0.27, 0.31, both p < 0.05). In 2017, the thermal data showed the strongest correlation with normalized stomatal conductance (r = −0.83) at 44 DBH. In the same year, NDSI pairs exhibited stronger correlations than multispectral indices as the DBH decreased (1380 nm with 1570 nm: r = −0.58 to −0.69, 1570 nm with 1810 nm: r = 0.64 to 0.48, both p < 0.05). Combining LAI with these NDSI pairs improved stomatal conductance predictions (2016: R2 = 0.37–0.50; 2017: R2 = 0.51–0.63, both p < 0.01). These results demonstrate the precision of a multimodal sensing approach, particularly integrating multispectral and hyperspectral data, to improve irrigation strategies and promote sustainable viticulture.
Retrieval of Vegetation Indices and Vegetation Fraction in Highly Compact Urban Areas: A 3D Radiative Transfer Approach
Authors: Xue Wenya , Feng Liping , Yang Jinxin , Xu Yong , Ho Hung Chak , Luo Renbo , Menenti Massimo , Wong Man Sing
Published: January 2025

Vegetation indices, especially the normalized difference vegetation index (NDVI), are widely used in urban vegetation assessments. However, estimating the vegetation abundance in urban scenes using the NDVI has constraints due to the complex spectral signature related to the urban structure, materials and other factors compared to natural ground surfaces. This paper employs the 3D discrete anisotropic radiative transfer (DART) model to simulate the spectro-directional reflectance of synthetic urban scenes with various urban geometries and building materials using a flux-tracking method under shaded and sunlit conditions. The NDVI is calculated using the spectral radiance in the red (0.6545 μm) and near-infrared bands (0.865 μm). The effects of the urban material heterogeneity and 3D structure on the NDVI, and the performance of three NDVI-based fractional vegetation cover (FVC) inversion algorithms, are evaluated. The results show that the effects of the building material heterogeneity on the NDVI are negligible under sunlit conditions but not negligible under shaded conditions. The NDVI value of building components within synthetic scenes is approximately zero. The shaded road exhibits a higher NDVI value in comparison to the illuminated road because of scattering from adjacent pixels. In order to correct the effects of scattering caused by building geometry, the reflectance of the Landsat 8/OLI image is corrected using the sky view factor (SVF) and then used to calculate the FVC. Jilin-1 satellite images with high spatial resolution (0.5 m) are used to extract the vegetation cover and then aggregated to 30 m spatial resolution to calculate the FVC for validation. The results show that the RMSE is up to 0.050 after correction, while the RMSE is 0.169 before correction. This study makes a contribution to the understanding of the effects of the urban 3D structure and material reflectance on the NDVI and provides insights into the retrieval of the FVC in different urban scenes.
KANDiff: Kolmogorov–Arnold Network and Diffusion Model-Based Network for Hyperspectral and Multispectral Image Fusion
Authors: Li Wei , Li Lu , Peng Man , Tao Ran
Published: January 2025

In recent years, the fusion of hyperspectral and multispectral images in remote sensing image processing still faces challenges, primarily due to their complexity and multimodal characteristics. Diffusion models, known for their stable training process and exceptional image generation capabilities, have shown good application potential in this field. However, when dealing with multimodal data, it may prove challenging for the models to fully capture the intricate relationships between the modalities, which may result in incomplete information integration and a small amount of remaining noise in the generated images. To address these problems, we propose a new model, KanDiff, for hyperspectral and multispectral image fusion. To address the differences in modal information between multispectral and hyperspectral images, KANDiff incorporates Kolmogorov–Arnold Networks (KAN) to guide the inputs. It helps the model understand the complex relationships between the modalities by replacing the fixed activation function in the traditional MLP with a learnable activation function. Furthermore, the image generated by the diffusion model may exhibit a small amount of the remaining noise. Convolutional Neural Networks (CNNs) effectively extract local features through their convolutional layers and achieve noise suppression via layer-by-layer feature representation. Therefore, the MergeCNN module is further introduced to enhance the fusion effect, resulting in smoother and more accurate outcomes. Experimental results on the public CAVE and Harvard datasets indicate that KanDiff has achieved improvements over current high-performance methods across several metrics, particularly showing significant enhancements in the peak signal-to-noise ratio (PSNR) and the structural similarity index measure (SSIM), thus demonstrating superior performance. Additionally, we have created an image fusion dataset of the lunar surface, and KANDiff exhibits robust performance on this dataset as well. This work introduces an effective solution for addressing the challenges posed by missing high-resolution hyperspectral images (HRHS) data, which is essential for tasks including landing site selection and resource exploration within the realm of deep space exploration.
From Spectra to Signatures: Detecting Fentanyl in Human Nails with ATR–FTIR and Machine Learning
Authors: Barney Aubrey , Trojan Václav , Hrib Radovan , Newland Ashley , Halámek Jan , Halámková Lenka
Published: January 2025

Human nails have recently become a sample of interest for toxicological purposes. Multiple studies have proven the ability to detect various analytes within the keratin matrix of the nail. The analyte of interest in this study is fentanyl, a highly dangerous and abused drug in recent decades. In this proof-of-concept study, ATR–FTIR was combined with machine learning methods, which are effective in detecting and differentiating fentanyl in samples, to explore whether nail samples are distinguishable from individuals who have used fentanyl and those who have not. PLS-DA and SVM-DA prediction models were created for this study and had an overall accuracy rate of 84.8% and 81.4%, respectively. Notably, when classification was considered at the donor level—i.e., determining whether the donor of the nail sample was using fentanyl—all donors were correctly classified. These results show that ATR–FTIR spectroscopy in combination with machine learning can effectively differentiate donors who have used fentanyl and those who have not and that human nails are a viable sample matrix for toxicology.
Seasonal Land Use and Land Cover Mapping in South American Agricultural Watersheds Using Multisource Remote Sensing: The Case of Cuenca Laguna Merín, Uruguay
Authors: Alciaturi Giancarlo , Wdowinski Shimon , García-Rodríguez María del Pilar , Fernández Virginia
Published: January 2025

Recent advancements in Earth Observation sensors, improved accessibility to imagery and the development of corresponding processing tools have significantly empowered researchers to extract insights from Multisource Remote Sensing. This study aims to use these technologies for mapping summer and winter Land Use/Land Cover features in Cuenca de la Laguna Merín, Uruguay, while comparing the performance of Random Forests, Support Vector Machines, and Gradient-Boosting Tree classifiers. The materials include Sentinel-2, Sentinel-1 and Shuttle Radar Topography Mission imagery, Google Earth Engine, training and validation datasets and quoted classifiers. The methods involve creating a multisource database, conducting feature importance analysis, developing models, supervised classification and performing accuracy assessments. Results indicate a low significance of microwave inputs relative to optical features. Short-wave infrared bands and transformations such as the Normalised Vegetation Index, Land Surface Water Index and Enhanced Vegetation Index demonstrate the highest importance. Accuracy assessments indicate that performance in mapping various classes is optimal, particularly for rice paddies, which play a vital role in the country’s economy and highlight significant environmental concerns. However, challenges persist in reducing confusion between classes, particularly regarding natural vegetation features versus seasonally flooded vegetation, as well as post-agricultural fields/bare land and herbaceous areas. Random Forests and Gradient-Boosting Trees exhibited superior performance compared to Support Vector Machines. Future research should explore approaches such as Deep Learning and pixel-based and object-based classification integration to address the identified challenges. These initiatives should consider various data combinations, including additional indices and texture metrics derived from the Grey-Level Co-Occurrence Matrix.
Temperature Dependence on Microstructure, Crystallization Orientation, and Piezoelectric Properties of ZnO Films
Authors: Deng Ke , Liu Zhonghao , Liu Hulin , Chen Yanxiang , Li Shang , Guo Shuren , Xiu Boyu , Dong Xuanpu , Cao Huatang
Published: January 2025

This study has investigated the effects of different annealing temperatures on the microstructure, chemical composition, phase structure, and piezoelectric properties of ZnO films. The analysis focuses on how annealing temperature influences the oxygen content and the preferred c-axis (002) orientation of the films. It was found that annealing significantly increases the grain size and optimizes the columnar crystal structure, though excessive high-temperature annealing leads to structural degradation. This behavior is likely related to changes in oxygen content at different annealing temperatures. High resolution transmission electron microscopy (HR-TEM) reveals that the films exhibit high-resolution lattice stripes, confirming their high crystallinity. Although the films exhibit growth in multiple orientations, the c-axis (002) orientation remains the predominant crystallographic growth. Further piezoelectric property analysis demonstrates that the ZnO films annealed at 400 °C exhibit enhanced piezoelectric performance and stable linear piezoelectric behavior. These findings offer valuable support for optimizing the piezoelectric properties of ZnO films and their applications in piezoelectric sensors.
Correction: Kulachai et al. (2023). Factors Influencing Voting Decision: A Comprehensive Literature Review. Social Sciences 12: 469
Authors: Kulachai Waiphot , Lerdtomornsakul Unisa , Homyamyen Patipol
Published: January 2025

In the original publication (Kulachai et al [...]
Development of Interface-Specific Two-Dimensional Vibrational–Electronic (i2D-VE) Spectroscopy for Vibronic Couplings at Interfaces
Authors: Qian Yuqin , Huang-Fu Zhi-Chao , Brown Jesse B. , Rao Yi
Published: January 2025

Bulk 2D electronic–vibrational (2D-EV) and 2D vibrational–electronic spectroscopies (2D-VE) were previously developed to correlate the electronic and vibrational degrees of freedom simultaneously, which allow for the study of couplings between electronic and vibrational transitions in photo-chemical systems. Such bulk-dominated methods have been used to extensively study molecular systems, providing unique information such as coherence sensitivity, molecular configurations, enhanced resolution, and correlated states and their dynamics. However, the analogy of interfacial 2D spectroscopy has fallen behind. Our recent work presented interface-specific 2D-EV spectroscopy (i2D-EV). In this work, we develop interface-specific two-dimensional vibrational–electronic spectroscopy (i2D-VE). The fourth-order spectroscopy is based on a Mach–Zehnder IR interferometer that accurately controls the time delay of an IR pump pulse pair for vibrational transitions, followed by broadband interface second-harmonic generation to probe electronic transitions. We demonstrate step-by-step how a fourth-order i2D-VE spectrum of AP3 molecules at the air/water interface was collected and analyzed. The line shape and signatures of i2D-VE peaks reveal solvent correlations and the spectral nature of vibronic couplings. Together, i2D-VE and i2D-EV spectroscopy provide coupling of different behaviors of the vibrational ground state or excited states with electronic states of molecules at interfaces and surfaces. The methodology presented here could also probe dynamic couplings of electronic and vibrational motions at interfaces and surfaces, extending the usefulness of the rich data that are obtained.
Study on Non-Metal-Induced EPFRs in PM2.5 Generated from Flue Gas of Cellulose Combustion
Authors: Zhang Lixin , An Boru , Chen Jingmin , Zhang Yuwei , Yu Guojiao
Published: January 2025

Environmental persistent free radicals (EPFRs) are a type of environmental risk substances existing in atmospheric particulate matter, which pose a challenge to human survival and sustainable development. The current understanding is that the formation mechanism of EPFRs is generally related to metallic materials. However, this study analyzed the PM2.5 generated from cellulose combustion and found that EPFRs could be generated even without the metallic materials. Therefore, this paper explores the emission characteristics of non-metal-induced EPFRs, aiming to reveal the influencing factors, distribution, and decay characteristics of non-metal-induced EPFRs generated from cellulose combustion. The results show that combustion conditions such as combustion temperature and oxygen concentration have a significant impact on the emission concentration of non-metal-induced EPFRs in PM2.5 from cellulose combustion. The emission concentrations of non-metal-induced EPFRs in PM2.5 are at the order of magnitude of 1014 spins/m3 and over 50% is distributed in the inextricable substances. Their g-factor are in the range from 2.0015 to 2.0022, indicating that these EPFRs are carbon-centered radicals. Furthermore, non-metal-induced EPFRs in PM2.5 from cellulose combustion have a half-life of several years or even longer, which exhibit distinct characteristics different from metal-induced EPFRs.