Artiles
Open Access
Article
01 December 2025Preparation, Characterization and Performance Assessment of Metal Complexes of Curcuma longa Extract as Sensitizers for Dye-Sensitized Solar Cells
The dye extract of Curcuma longa (turmeric), which is very rich in curcumin, was chemically modified by complexation reaction with Zn2+, Cu2+, and Fe3+ ions to enhance its stability, electron transfer and photovoltaic performance. The dye and complexes were characterized by Ultraviolet-Visible (UV-Vis) absorption and Fourier Transform Infra-Red (FTIR) spectroscopy of potential chromophores and functional groups. The spectral data obtained indicated that the curcuminoid ligands were successfully coordinated with the metal centers, resulting in red-shifted absorption bands from beyond 460 nm and C=O vibrational frequency decreasing below 1650 cm−1. Complexation reaction resulted in improved photochemical response and enhanced light-harvesting potential. When compared, the solar cells fabricated with titanium dioxide (TiO2) photoanodes sensitized by the complexes afforded improvement in the magnitude of short-circuit current density as well as power conversion efficiency compared to the devices sensitized with the crude extract. Among the three complexes, the Zn-complex afforded the highest efficiency (1.20%), attributed to favourable electronic coupling and reduced recombination losses. Computational studies conducted through quantum chemical calculations based on the curcumin structure supported the experimental findings. The findings from this study demonstrate that metal ions-natural dye complexes have potential for application as low-cost, eco-friendly and sustainable sensitizers, thereby opening a novel horizon in green photovoltaic technologies.
Open Access
Article
28 November 2025Sustainable Bioplastic Using Lignin Extracted from Neolamarckia cadamba Bark by Deep Eutectic Solvent
Lignin, a highly complex and abundant biopolymer, forms an integral part of plant cell walls and represents a promising resource for sustainable industrial applications. Lignin has recently gained attention due to its potential use in biofuels, bioplastics, adhesives, and antioxidant formulations. This paper focuses on lignin extraction from Neolamarckia cadamba bark by deep eutectic solvent (DES) composed of thymol and menthol. Extracted lignin and starch (extracted from Colocasia esculenta roots) were used for the synthesis of bioplastic. The extracted lignin was characterized through multiple analytical techniques, including UV-V is spectroscopy, FTIR, and visual staining with safranin. Bioplastic was characterized for thermal resistance, absorbance, and solubility. The moisture content was obtained as 29.59%, water solubility as 72.61% with almost completely (98%) biodegradable. The work contributes to valorising environmental biomass and enhancing the industrial relevance of lignin. Furthermore, it aligns with the sustainable development goals by transforming bio-waste into valuable bioproducts, such as bioplastics, biochemicals, bioadsorbents, etc. The outcomes of this research may serve as a foundation for future studies in lignin-based material innovation and biorefinery integration.
Open Access
Article
28 November 2025Binocular Camera-Based Depth Recognition for Motion Monitoring and Response Analysis of Flexible Floating Structures for Offshore Photovoltaics
Driven by the global goal of carbon neutrality, offshore floating photovoltaic (OFPV) technology has become a primary focus of photovoltaic research. In particular, flexible thin-film structures have become a central focus of research in sustainable energy development. It offers numerous advantages, including light weight, low cost, and strong adaptability to the marine environment. However, traditional experimental methods still face challenges in accurately capturing the motion response of flexible thin films. To address this issue, this study proposes a motion measurement and monitoring framework based on binocular vision. The framework is validated using gyroscope data, and the results demonstrate its high accuracy and real-time performance. The research team conducted experiments on a flexible floating photovoltaic structure in a wave flume, applying the proposed framework to monitor its motion response under wave excitation. The experimental results show that wave height and wave period have significant effects on the acceleration response of the thin film: higher wave heights lead to notably greater accelerations, whereas longer wave periods result in a gradual decrease in acceleration. Overall, the proposed framework provides reliable technical support for the design optimization and safety assessment of flexible thin-film FPV structures.
Open Access
Article
27 November 2025The Limits of RGB-Based Vegetation Indexes under Canopy Degradation: Insights from UAV Monitoring of Harvested Cereal Fields
Unmanned Aerial Vehicles (UAVs) equipped with RGB cameras are increasingly used as low-cost tools for crop monitoring, offering a range of vegetation indexes in the visible spectral range. These indexes have often been reported to correlate with other multispectral indexes such as the Normalized Difference Vegetation Index (NDVI) during active growth stages. However, still efforts should be done about their performance under conditions of canopy degradation. In this study, UAV flights were conducted over a cereal field immediately after harvest, when the canopy consisted mostly of bare soil and dry residues. RGB-based indexes were calculated from the orthomosaic, normalized to a [0–1] scale, and compared to NDVI derived from a multispectral sensor. Data preprocessing included ground control point (GCP) georeferencing, removal of NoData pixels, and raster alignment. Results revealed very weak correlations between RGB indexes and NDVI (Pearson r < 0.15), with Visible Atmospherically Resistant Index (VARI) showing almost no variability across the field. Although the Leaf Index (GLI), yielded the lowest error values, all RGB indexes failed to reproduce the variability of NDVI under post-harvest conditions. These findings highlight a critical methodological limitation: RGB indexes are unsuitable for vegetation monitoring when canopy cover is severely reduced. While they remain useful during active growth, their reliability diminishes in degraded or post-harvest scenarios, thereby limiting their application in assessing abiotic stress in cereals.
Open Access
Article
27 November 2025Lyz1-Expressing Alveolar Type II Cells Contribute to Lung Regeneration
The alveolar units, composed of alveolar epithelial type II cells (AT2) and type I cells (AT1), are essential for efficient gas exchange. While AT2 cells are known to play critical roles in alveolar homeostasis and regeneration, the contribution of heterogeneous AT2 cells to lung repair remains poorly understood. Here, we identified a distinct AT2 subpopulation that exclusively expressed Lysozyme 1 (Lyz1) through single-cell RNA sequencing (scRNA-seq) analyses. Cell fate mapping revealed that the Lyz1CreERT2 mouse strain specifically labeled Lyz1-expressing AT2 cells in vivo at homeostasis. Following lung injury, Lyz1+ AT2 cells expanded and contributed to alveolar regeneration by generating both self-renewing AT2 cells and differentiating AT1 cells. We further observed the emergence of de novo Lyz1-expressing cells in the airways after lung injury. Additionally, Lyz1+ AT2 cells displayed significantly enhanced proliferative capacity compared with general bulk AT2 cells in 3D organoid cultures. These findings define Lyz1+ AT2 cells as a previously unrecognized progenitor population, expanding the paradigm of alveolar regeneration and providing insight into how epithelial diversity supports lung regeneration.
Open Access
Review
26 November 2025Prebiotic and Probiotic Foods in MASLD: Microbiome-Mediated Therapeutic Strategies
Through the use of prebiotics and probiotics, fermented foods offer significant health benefits by enhancing host nutrition and microbiota composition while providing distinctive flavor profiles. Fermentation substantially alters the bioactive compounds in these foods compared to their natural state. Additionally, fermented foods contain probiotics that can modulate consumers’ gut microbiomes, which in turn regulate host biochemistry to help combat various metabolic diseases. Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a growing global health burden. Gut microbiome dysbiosis, combined with unbalanced nutritional intake, is considered a primary driver of disease pathogenesis. Fermented foods can modify the bioavailability of micronutrients—including carbohydrates, polyphenols, and vitamins—thereby influencing host metabolism. Moreover, the probiotics present in fermented foods, along with their modulatory effects on the gut microbiota, contribute to both the management and prevention of MASLD. Modern fermentation approaches, leveraging synthetic biology, systems biology, and metabolic engineering, can further maximize these health benefits. This review summarizes the components, bioactive compounds, and mechanistic pathways by which fermented foods influence the pathogenesis of MASLD, and highlights the potential applications of modern fermentation technologies to enhance their health-promoting properties.
Open Access
Article
26 November 2025Machine Learning in Forensic Anthropology: Sex Classification of Fingerprints
A Fingerprint plays an important role in identifying an individual in forensic and criminal investigations. Fingerprint ridge density is considered one of the most important features for sex classification. The present study intends to classify sex using fingerprint ridge density through a machine learning model, i.e., Random Forest. A total of 2040 fingerprints of 204 participants (102 males and 102 females) were collected from the north Indian population using a standard methodology. Ridge density in the three topological areas of fingerprints,i.e., radial, ulnar, and proximal areas, was assessed. Taking all the areas into consideration, the data of fingerprint ridge density was used to train the Random forest algorithm. The training and testing of the model data were taken in a ratio of 70:30, respectively (training dataset = 1428; testing dataset = 612). Random forest provided an accuracy of 81.53% in sex classification using fingerprint ridge density. The paper discusses the evaluation report of the accuracy of the parameters of the Random forest in detail. The study concludes that the machine learning models, such as Random forest can be utilized for sex classification from fingerprint ridge density. The study proposes its direct application in forensic examinations, especially when there is no clue about the perpetrator, and the sex of the perpetrator can be predicted from fingerprints recovered from the crime scene using the present customized model.
Open Access
Article
25 November 2025Self-Determination of Adolescents with Intellectual and Developmental Disabilities in China: Evidence from Students and Teachers
Self-determination is closely associated with individuals’ autonomy and independence and is crucial for people with intellectual and developmental disabilities. This study investigated the self-determination of adolescents with intellectual and developmental disabilities in China. Using the AIR Self-Determination Scale, data were collected from 116 students and 29 corresponding special education teachers. Findings indicated that the adolescent with intellectual and developmental disabilities had a moderate level of self-determination. However, teachers consistently rated students’ self-determination lower than students’ self-rating. Students’ self-evaluations of their self-determination were significantly influenced by geographic location, age, and disability severity, and teacher evaluations were affected by students’ age and disability severity, as well as teachers’ teaching experience and subject area. The study revealed that teachers face notable challenges in their conceptual understanding and pedagogical implementation of self-determination instruction. Based on these findings, recommendations are proposed across four domains: parents, teachers, schools, and broader society.
Open Access
Article
25 November 2025Dissimilar Joining of 316L and A131 Steel by Shield Metal Arc and Tungsten Inert Gas Welding to Evaluate Bending and Tensile Behavior
In this paper, the effect of filler metal and type of welding on the strength and ductility of dissimilar welding of two different grades of stainless steel was investigated. One of the benefits of stainless steel is its corrosion resistance, which is often necessary for equipment longevity in these facilities. During shipbuilding, as required, stainless steel 316L needs to be welded to the shipbuilding-grade carbon steel A131. In these applications, welding between the two should demonstrate superior strength during vessel construction. To provide a clear illustration, experimental work was needed to allow a careful selection of the joining procedure and filler metal or electrode. The current research work includes a comparative experimental analysis of dissimilar-metal welding (SS-316L & A131 steel). The reasons for choosing these two materials are their greater corrosion resistance and high strength in humid environments. Furthermore, two different welding methods (SMAW & TIG) with varying filler metals were employed in the experiment. The ultimate tensile strength and yield strength of the SMAW welds using E308-16 filler metal were the highest among all, while the TIG welds with ER308L showed superior bending strength. Observations suggest that SMAW with the E308-16 electrode exhibits superior tensile strength, while TIG joints with ER 308L filler provide better bending strength for the welding of SS-316L and shipbuilding (SB) grade A131 steels.
Open Access
Article
25 November 2025Ambient Air Pollution Exposure Influences Dementia through the Bidirectional Pathways of Psychological Factors and Brain Structure
Exposure to air pollution contributes to increased dementia risk, which may be mediated through its impact on psychological and brain structural changes. However, the underlying mechanisms remain poorly understood. We analyzed data from the UK Biobank of 263,095 participants aged 40 years and older. We examined the association between air pollution and incident dementia using Cox proportional hazard regression models. Mediation analysis was performed to explore the mediating roles of psychological and brain structural factors on these associations. Structural equation model (SEM) and bidirectional Mendelian randomization (MR) analyses were further employed to explore the potential pathways involving psychological factors and brain structure in this relationship. During an over 13-year follow-up, a total of 3039 dementia cases were identified. We observed significant associations between air pollution and dementia, with each interquartile range (IQR) increase in air pollution associated with a 5~9% increased risk of dementia. We observed that both psychological and brain structural factors mediated the air pollution-dementia association, particularly loneliness, social isolation, lack of enthusiasm, and reductions in volumes of the amygdala, hippocampus, temporal pole, and frontal pole, with mediation proportions ranging from 4.23% to 11.11%. SEM and MR analyses revealed bidirectional pathways linking air pollution exposure to dementia through psychological factors and brain structural changes: (1) air pollution → psychological disturbances → brain structural damage → dementia; (2) air pollution → brain structural damage → psychiatric disorders → dementia. These findings elucidate the interplay between psychological well-being and neuroanatomical integrity in mediating the neurocognitive impacts of air pollution, offering insights for targeted interventions to mitigate dementia risk associated with environmental exposures.
