bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating Hydrogen in Zirconium Alloys by Means of Neutron Imaging
Authors: Weick Sarah , Grosse Mirco
Published: February 2024

Neutrons interact with the magnetic moment of the atomic shell of an atom, as is common for X-rays, but mainly they interact directly with the nucleus. Therefore, the atomic number and the related number of electrons does not play a role in the strength of an interaction. Instead, hydrogen that is nearly invisible for X-rays has a higher attenuation for neutrons than most of the metals, e.g., zirconium, and thus would be visible through dark contrast in neutron images. Consequently, neutron imaging is a precise, non-destructive method to quantify the amount of hydrogen in materials with low attenuation. Because nuclear fuel cladding tubes of light water reactors are made of zirconium (98%), the hydrogen amount and distribution in metallic claddings can be investigated. Even hydrogen concentrations smaller than 10 wt.ppm can be determined locally with a spatial resolution of less than 10 μm (with a high-resolution neutron microscope). All in all, neutron imaging is a very fast and precise method for several applications. This article explains the basics of neutron imaging and provides samples of investigation possibilities, e.g., for hydrogen in zirconium alloy cladding tubes or in situ investigations of hydrogen diffusion in metals.
Microstructure and Mechanical Properties of Ti-6Al-4V Welds Produced with Different Processes
Authors: Tolvanen Sakari , Pederson Robert , Klement Uta
Published: February 2024

The effect of defects and microstructure on the mechanical properties of Ti-6Al-4V welds produced by tungsten inert gas welding; plasma arc welding; electron beam welding; and laser beam welding was studied in the present work. The mechanical properties of different weld types were evaluated with respect to micro hardness; yield strength; ultimate tensile strength; ductility; and fatigue at room temperature and at elevated temperatures (200 °C and 250 °C). Metallographic investigation was carried out to characterize the microstructures of different weld types, and fractographic investigation was conducted to relate the effect of defects on fatigue performance. Electron and laser beam welding produced welds with finer microstructure, higher tensile ductility, and better fatigue performance than tungsten inert gas welding and plasma arc welding. Large pores, and pores located close to the specimen surface, were found to be most detrimental to fatigue life.
Phase Diagram Mapping out the Complex Magnetic Structure of Single Crystals of (Gd, Er)B4 Solid Solutions
Authors: Masunaga Sueli H. , Barbeta Vagner B. , Abud Fábio , Torikachvili Milton S. , Jardim Renato F.
Published: February 2024

Measurements of specific heat and magnetization in single crystals were used to map out the magnetic phase diagram of Gd1−xErxB4 (x = 0.2 and 0.4) solid solutions along the c-axis. While GdB4 orders antiferromagnetically (AF) at 41.7 K, with the easy plane of magnetization oriented perpendicularly to the c-axis, ErB4 displays AF ordering below 15.4 K, with the easy axis along c. Therefore, in solid solutions, the competition between the different spin anisotropies, as well as frustration, lead to a complex spin configuration. These measurements reveal that a 40% substitution of Er for Gd is sufficient for generating a phase diagram similar to the one for the ErB4 system, characterized by the occurrence of plateau phases and other exotic features attributed to the interplay of competing magnetic anisotropies.
Optimal Selection for Redox Couples and Enhanced Performance through Magnetic Nanofluid Electrolyte in Solar Flow Batteries
Authors: Gu Zixing , Lu Ping , Zhang Zihan , Ma Qiang , Su Huaneng , Xu Qian
Published: February 2024

The limited photoelectric conversion efficiency poses one of the critical constraints on commercializing solar flow batteries (SFBs). This study compares the chemical and photoelectrochemical properties of three commonly used redox couples. Additionally, magnetic Fe3O4 nanoparticles, for the first time, are introduced to optimize the electrolyte, and they are compared with the original electrolyte. Across different redox couples, the variations in semiconductor flat-band potentials and carrier concentrations result in changes in photoelectric current density. Notably, FeCl2/FeCl3 redox coupled with TiO2 photoelectrodes exhibits the highest photoelectric current density, reaching 75.7 µA cm−2. However, the trade-off of this electrolyte, i.e., providing high photocurrent while being unable to supply sufficient open-circuit voltage, imposes limitations on the practical application of SFBs. Alternatively, for TEMPO and 4-OH-TEMPO electrolytes, which can provide a higher open-circuit voltage, the electrochemical activity is enhanced, and the solution ohmic resistance is reduced by introducing magnetic nanoparticles to form a magnetic nanofluid. As a result, the photoanode’s photocurrent density increases by 36.6% and 17.0%, respectively, in the two electrolytes. The work reported here effectively addresses the current issue of low photocurrent density in SFBs and presents new optimization strategies for SFBs.
Brominated Depsidones with Antibacterial Effects from a Deep-Sea-Derived Fungus Spiromastix sp.
Authors: Huang Zequan , Liu Dong , Chen Shang , Ren Jinwei , Gao Chenghai , Li Zhiyong , Fan Aili , Lin Wenhan
Published: February 2024

Eleven new brominated depsidones, namely spiromastixones U-Z5 (1–11) along with five known analogues (12–16), were isolated from a deep-sea-derived fungus Spiromastix sp. through the addition of sodium bromide during fermentation. Their structures were elucidated by extensive analysis of the spectroscopic data including high-resolution MS and 1D and 2D NMR data. Compounds 6–10 and 16 exhibited significant inhibition against Gram-positive bacteria including methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecium (VRE) with MIC values ranging from 0.5 to 2.0 μM. Particularly, tribrominated 7 displayed the strongest activity against MRSA and VRE with a MIC of 0.5 and 1.0 μM, respectively, suggesting its potential for further development as a new antibacterial agent.
Current Updates on Involvement of Artificial Intelligence and Machine Learning in Semen Analysis
Authors: Panner Selvam Manesh Kumar , Moharana Ajaya Kumar , Baskaran Saradha , Finelli Renata , Hudnall Matthew C. , Sikka Suresh C.
Published: February 2024

Background and Objectives: Infertility rates and the number of couples undergoing reproductive care have both increased substantially during the last few decades. Semen analysis is a crucial step in both the diagnosis and the treatment of male infertility. The accuracy of semen analysis results remains quite poor despite years of practice and advancements. Artificial intelligence (AI) algorithms, which can analyze and synthesize large amounts of data, can address the unique challenges involved in semen analysis due to the high objectivity of current methodologies. This review addresses recent AI advancements in semen analysis. Materials and Methods: A systematic literature search was performed in the PubMed database. Non-English articles and studies not related to humans were excluded. We extracted data related to AI algorithms or models used to evaluate semen parameters from the original studies, excluding abstracts, case reports, and meeting reports. Results: Of the 306 articles identified, 225 articles were rejected in the preliminary screening. The evaluation of the full texts of the remaining 81 publications resulted in the exclusion of another 48 articles, with a final inclusion of 33 original articles in this review. Conclusions: AI and machine learning are becoming increasingly popular in biomedical applications. The examination and selection of sperm by andrologists and embryologists may benefit greatly from using these algorithms. Furthermore, when bigger and more reliable datasets become accessible for training, these algorithms may improve over time.
Effect of Different Microstructures on Surface Residual Stress of Induction-Hardened Bearing Steel
Authors: Lu Shao-Quan , Chiu Liu-Ho
Published: February 2024

JIS SUJ2 steel is most widely used in bearing steel. The advantages are good hardenability, excellent fatigue, wear resistance and comprehensive mechanical properties. The wear resistance and fatigue resistance of this steel are attracting more attention, and the residual stress state and its distribution on the surface of the heat affected zone are critical factors affecting the fatigue life and wear resistance of the parts. In this study, SUJ2 is used as a material by which to study the surface residual stress and retained austenite distribution of induction-hardened steel. Quenching and tempering treatments were used to obtain different microstructures and an induction method was used to re-quench the case region. After the heat treatment, the residual stress and retained austenite volume on the surface were analyzed by X-ray diffraction and analyses of the microstructure and the hardness were also conducted. The results show that the microstructure after heat treatment contains unsolved carbides, tempered martensite and retained austenite. In the induction-hardened area, the residual stress is all compressive, and the values are more than −750 MPa. In conclusion, the microstructures of the specimens before induction hardening have a significant impact on the effective case depth for the same output power condition and the surface residual stress changes from a tensile to a compressive state. In the induction-hardened area, the maximum of the residual compressive stress was increased as the austenitized temperature of quenching increased.
Deciphering the Role of the Gut Microbiota in Exposure to Emerging Contaminants and Diabetes: A Review
Authors: Li Xueqing , Niu Huixia , Huang Zhengliang , Zhang Man , Xing Mingluan , Chen Zhijian , Wu Lizhi , Xu Peiwei
Published: February 2024

Emerging pollutants, a category of compounds currently not regulated or inadequately regulated by law, have recently become a focal point of research due to their potential toxic effects on human health. The gut microbiota plays a pivotal role in human health; it is particularly susceptible to disruption and alteration upon exposure to a range of toxic environmental chemicals, including emerging contaminants. The disturbance of the gut microbiome caused by environmental pollutants may represent a mechanism through which environmental chemicals exert their toxic effects, a mechanism that is garnering increasing attention. However, the discussion on the toxic link between emerging pollutants and glucose metabolism remains insufficiently explored. This review aims to establish a connection between emerging pollutants and glucose metabolism through the gut microbiota, delving into the toxic impacts of these pollutants on glucose metabolism and the potential role played by the gut microbiota.
Engineered Nanomaterial Coatings for Food Packaging: Design, Manufacturing, Regulatory, and Sustainability Implications
Authors: Olawore Oluwafemi , Ogunmola Motunrayo , Desai Salil
Published: February 2024

The food industry is one of the most regulated businesses in the world and follows strict internal and regulated requirements to ensure product reliability and safety. In particular, the industry must ensure that biological, chemical, and physical hazards are controlled from the production and distribution of raw materials to the consumption of the finished product. In the United States, the FDA regulates the efficacy and safety of food ingredients and packaging. Traditional packaging materials such as paper, aluminum, plastic, and biodegradable compostable materials have gradually evolved. Coatings made with nanotechnology promise to radically improve the performance of food packaging materials, as their excellent properties improve the appearance, taste, texture, and shelf life of food. This review article highlights the role of nanomaterials in designing and manufacturing anti-fouling and antimicrobial coatings for the food packaging industry. The use of nanotechnology coatings as protective films and sensors to indicate food quality levels is discussed. In addition, their assessment of regulatory and environmental sustainability is developed. This review provides a comprehensive perspective on nanotechnology coatings that can ensure high-quality nutrition at all stages of the food chain, including food packaging systems for humanitarian purposes.
Assessing Acceptability: The Role of Understanding Participant, Neighborhood, and Community Contextual Factors in Designing a Community-Tailored Cooking Intervention
Authors: Farmer Nicole , Tuason Ralph , Middleton Kimberly R. , Ude Assumpta , Tataw-Ayuketah Gladys , Flynn Sharon , Kazmi Narjis , Baginski Alyssa , Mitchell Valerie , Powell-Wiley Tiffany M. , Wallen Gwenyth R.
Published: February 2024

Background: Cooking is an identified dietary strategy that is positively associated with optimal diet quality. Prior to initiating cooking interventions, evaluating the prospective acceptability of the intervention among community members living within low food access areas and understanding geospatial food shopping locations may aid in designing community-tailored interventions. Methods: A sequential mixed methods study was conducted to determine the prospective acceptability of a planned community-located cooking intervention among African American adults living in a low food access area and with at least one cardiovascular disease risk factor. A semi-structured guide was used to conduct five virtual focus groups. Qualitative data were analyzed using thematic analysis and validated through participant check-in interviews. Survey responses were analyzed based on descriptive data. Geospatial analysis of participant locations that were reported for food shopping was conducted to show food environment utilization. Results: Focus groups with study participants (n = 20, all female, mean age 60.3, SD 9.3, mean cooking frequency per week 4.0, food insecure n = 7) were conducted between March and April, 2021. Thematic analysis of the focus group transcripts identified five main themes as follows: (A) Barriers to Cooking (family and caregiving, transportation, COVID-19 pandemic, time availability, household composition); (B) Motivators for Cooking (family, caregiving, health, enjoyment, COVID-19 pandemic); (C) Strategies (food shopping, social support, social media, meal planning); (D) Neighborhood (gentrification, perceived safety, stigmatization, disparities in grocery stores); (E) and Acceptability of the Intervention (reasons to participate, barriers, recruitment, intervention delivery). Participant validation interviews confirmed the themes and subthemes as well as the illustrative quotes. Geospatial analysis showed a majority of locations were outside of the participants’ residential areas. Conclusions: Prospective acceptability of a community-tailored cooking intervention found that the planned intervention could be modified to address individual level factors, such as caregiving and health, community contextual factors, such as perceived safety, and the general health needs of the community.
Integrating Artificial Intelligence and PET Imaging for Drug Discovery: A Paradigm Shift in Immunotherapy
Authors: McGale Jeremy P. , Howell Harrison J. , Beddok Arnaud , Tordjman Mickael , Sun Roger , Chen Delphine , Wu Anna M. , Assi Tarek , Ammari Samy , Dercle Laurent
Published: February 2024

The integration of artificial intelligence (AI) and positron emission tomography (PET) imaging has the potential to become a powerful tool in drug discovery. This review aims to provide an overview of the current state of research and highlight the potential for this alliance to advance pharmaceutical innovation by accelerating the development and deployment of novel therapeutics. We previously performed a scoping review of three databases (Embase, MEDLINE, and CENTRAL), identifying 87 studies published between 2018 and 2022 relevant to medical imaging (e.g., CT, PET, MRI), immunotherapy, artificial intelligence, and radiomics. Herein, we reexamine the previously identified studies, performing a subgroup analysis on articles specifically utilizing AI and PET imaging for drug discovery purposes in immunotherapy-treated oncology patients. Of the 87 original studies identified, 15 met our updated search criteria. In these studies, radiomics features were primarily extracted from PET/CT images in combination (n = 9, 60.0%) rather than PET imaging alone (n = 6, 40.0%), and patient cohorts were mostly recruited retrospectively and from single institutions (n = 10, 66.7%). AI models were used primarily for prognostication (n = 6, 40.0%) or for assisting in tumor phenotyping (n = 4, 26.7%). About half of the studies stress-tested their models using validation sets (n = 4, 26.7%) or both validation sets and test sets (n = 4, 26.7%), while the remaining six studies (40.0%) either performed no validation at all or used less stringent methods such as cross-validation on the training set. Overall, the integration of AI and PET imaging represents a paradigm shift in drug discovery, offering new avenues for more efficient development of therapeutics. By leveraging AI algorithms and PET imaging analysis, researchers could gain deeper insights into disease mechanisms, identify new drug targets, or optimize treatment regimens. However, further research is needed to validate these findings and address challenges such as data standardization and algorithm robustness.
Development of Biotinylated Liposomes Encapsulating Metformin for Therapeutic Targeting of Inflammation-Based Diseases
Authors: Ailuno Giorgia , Baldassari Sara , Balboni Alice , Pastorino Sara , Zuccari Guendalina , Cortese Katia , Barbieri Federica , Drava Giuliana , Florio Tullio , Caviglioli Gabriele
Published: February 2024

Inflammation is a physiological response to a damaging stimulus but sometimes can be the cause of the onset of neurodegenerative diseases, atherosclerosis, and cancer. These pathologies are characterized by the overexpression of inflammatory markers like endothelial adhesion molecules, such as Vascular Cell Adhesion Molecule-1 (VCAM-1). In the present work, the development of liposomes for therapeutic targeted delivery to inflamed endothelia is described. The idea is to exploit a three-step pretargeting system based on the biotin–avidin high-affinity interaction: the first step involves a previously described biotin derivative bearing a VCAM-1 binding peptide; in the second step, the avidin derivative NeutrAvidinTM, which strongly binds to the biotin moiety, is injected; the final step is the administration of biotinylated liposomes that would bind to NeutravidinTM immobilized onto VCAM-1 overexpressing endothelium. Stealth biotinylated liposomes, prepared via the thin film hydration method followed by extrusion and purification via size exclusion chromatography, have been thoroughly characterized for their chemico-physical and morphological features and loaded with metformin hydrochloride, a potential anti-inflammatory agent. The three-step system, tested in vitro on different cell lines via confocal microscopy, FACS analysis and metformin uptake, has proved its suitability for therapeutic applications.
3D Printing of Biodegradable Polymeric Microneedles for Transdermal Drug Delivery Applications
Authors: Aldawood Faisal Khaled , Parupelli Santosh Kumar , Andar Abhay , Desai Salil
Published: February 2024

Microneedle (MN) technology is an optimal choice for the delivery of drugs via the transdermal route, with a minimally invasive procedure. MN applications are varied from drug delivery, cosmetics, tissue engineering, vaccine delivery, and disease diagnostics. The MN is a biomedical device that offers many advantages including but not limited to a painless experience, being time-effective, and real-time sensing. This research implements additive manufacturing (AM) technology to fabricate MN arrays for advanced therapeutic applications. Stereolithography (SLA) was used to fabricate six MN designs with three aspect ratios. The MN array included conical-shaped 100 needles (10 × 10 needle) in each array. The microneedles were characterized using optical and scanning electron microscopy to evaluate the dimensional accuracy. Further, mechanical and insertion tests were performed to analyze the mechanical strength and skin penetration capabilities of the polymeric MN. MNs with higher aspect ratios had higher deformation characteristics suitable for penetration to deeper levels beyond the stratum corneum. MNs with both 0.3 mm and 0.4 mm base diameters displayed consistent force–displacement behavior during a skin-equivalent penetration test. This research establishes guidelines for fabricating polymeric MN for high-accuracy and low-cost 3D printing.
Aphid Resistance Segregates Independently of Cardenolide and Glucosinolate Content in an Erysimum cheiranthoides (Wormseed Wallflower) F2 Population
Authors: Mirzaei Mahdieh , Younkin Gordon C. , Powell Adrian F. , Alani Martin L. , Strickler Susan R. , Jander Georg
Published: February 2024

Plants in the genus Erysimum produce both glucosinolates and cardenolides as a defense mechanism against herbivory. Two natural isolates of Erysimum cheiranthoides (wormseed wallflower) differed in their glucosinolate content, cardenolide content, and their resistance to Myzus persicae (green peach aphid), a broad generalist herbivore. Both classes of defensive metabolites were produced constitutively and were not further induced by aphid feeding. To investigate the relative importance of glucosinolates and cardenolides in E. cheiranthoides defense, we generated an improved genome assembly, genetic map, and segregating F2 population. The genotypic and phenotypic analysis of the F2 plants identified quantitative trait loci, which affected glucosinolates and cardenolides, but not the aphid resistance. The abundance of most glucosinolates and cardenolides was positively correlated in the F2 population, indicating that similar processes regulate their biosynthesis and accumulation. Aphid reproduction was positively correlated with glucosinolate content. Although the overall cardenolide content had little effect on aphid growth and survival, there was a negative correlation between aphid reproduction and helveticoside abundance. However, this variation in defensive metabolites could not explain the differences in aphid growth on the two parental lines, suggesting that processes other than the abundance of glucosinolates and cardenolides have a predominant effect on aphid resistance in E. cheiranthoides.
Morphological Variation and Spatial Metabolic Variations in Rhodiola sachalinensis A.Bor. in Different Natural Distribution Areas
Authors: Chang Qiuyang , Liu Xu , Li Yi , Zhao Wen , Tang Zhonghua , Liu Yang , Mu Liqiang
Published: February 2024

To explore the genetic diversity and metabolic characteristics among different locations of wild Rhodiola sachalinensis A.Boriss., we collected specimens from two sites (DHL: 128°23′06″ N, 44°26′31″ E; FHS: 127°59′26″ N, 44°7′22″ E) and measured various biological traits, such as leaf length, leaf width, and plant height. We conducted metabolic analyses to investigate variations among different plant parts. Our study revealed that while the various plant parts of wild R. sachalinensis A.Boriss. from these two locations showed overall numerical similarities, they exhibited relatively high coefficients of variation in traits such as leaf length, leaf width, plant height, and stem thickness. Furthermore, utilizing gas chromatography–mass spectrometry (GS-MS), we detected significant differences in primary metabolites among different plant parts from both locations. Using orthogonal partial least squares discriminant analysis (OPLS-DA), we identified 42 and 34 different metabolites in the roots, stems, and leaves of plants from the DHL site and 62 and 50 different metabolites in the roots, stems, and leaves of plants from the FHS site. Metabolic heatmaps suggested that sugar metabolism was more active in the roots compared to other plant parts. Through KEGG pathway analysis, we determined that the primary metabolic differences were concentrated in the citric acid cycle (TCA cycle) and amino acid metabolism, including pathways related to glycine, serine, and threonine metabolism, as well as alanine, aspartate, and glutamate metabolism. These findings indicate that wild R. sachalinensis A.Boriss. plants from different locations not only exhibit significant variations in biological traits but also demonstrate notable distinctions in the distribution of primary metabolites among different plant parts.
Bioinformatic Analysis of Codon Usage Bias of HSP20 Genes in Four Cruciferous Species
Authors: Ji Huiyue , Liu Junnan , Chen Yineng , Yu Xinyi , Luo Chenlu , Sang Luxi , Zhou Jiayu , Liao Hai
Published: February 2024

Heat shock protein 20 (HSP20) serves as a chaperone and plays roles in numerous biological processes, but the codon usage bias (CUB) of its genes has remained unexplored. This study identified 140 HSP20 genes from four cruciferous species, Arabidopsis thaliana, Brassica napus, Brassica rapa, and Camelina sativa, that were identified from the Ensembl plants database, and we subsequently investigated their CUB. As a result, the base composition analysis revealed that the overall GC content of HSP20 genes was below 50%. The overall GC content significantly correlated with the constituents at three codon positions, implying that both mutation pressure and natural selection might contribute to the CUB. The relatively high ENc values suggested that the CUB of the HSP20 genes in four cruciferous species was relatively weak. Subsequently, ENc exhibited a negative correlation with gene expression levels. Analyses, including ENc-plot analysis, neutral analysis, and PR2 bias, revealed that natural selection mainly shaped the CUB patterns of HSP20 genes in these species. In addition, a total of 12 optimal codons (ΔRSCU > 0.08 and RSCU > 1) were identified across the four species. A neighbor-joining phylogenetic analysis based on coding sequences (CDS) showed that the 140 HSP20 genes were strictly and distinctly clustered into 12 subfamilies. Principal component analysis and cluster analysis based on relative synonymous codon usage (RSCU) values supported the fact that the CUB pattern was consistent with the genetic relationship at the gene level and (or) species levels. These results will not only enrich the HSP20 gene resource but also advance our understanding of the CUB of HSP20 genes, which may underlie the theoretical basis for exploration of their genetic and evolutionary pattern.
Research Progress on Plant Responses to Stress Combinations in the Context of Climate Change
Authors: Jing Zeyao , Liu Na , Zhang Zongxian , Hou Xiangyang
Published: February 2024

In the context of climate change, the frequency and intensity of extreme weather events are increasing, environmental pollution and global warming are exacerbated by anthropogenic activities, and plants will experience a more complex and variable environment of stress combinations. Research on plant responses to stress combinations is crucial for the development and utilization of climate-adaptive plants. Recently, the concept of stress combinations has been expanded from simple to multifactorial stress combinations (MFSCs). Researchers have realized the complexity and necessity of stress combination research and have extensively employed composite gradient methods, multi-omics techniques, and interdisciplinary approaches to integrate laboratory and field experiments. Researchers have studied the response mechanisms of plant reactive oxygen species (ROS), phytohormones, transcription factors (TFs), and other response mechanisms under stress combinations and reached some generalized conclusions. In this article, we focus on the research progress and methodological dynamics of plant responses to stress combinations and propose key scientific questions that are crucial to address, in the context of plant responses to stress assemblages, conserving biodiversity, and ensuring food security. We can enhance the search for universal pathways, identify targets for stress combinations, explore adaptive genetic responses, and leverage high-technology research. This is in pursuit of cultivating plants with greater tolerance to stress combinations and enabling their adaptation to and mitigation of the impacts of climate change.
Genetic Diversity and Structure of Terminalia bellerica (Gaertn. Roxb.) Population in India as Revealed by Genetic Analysis
Authors: Umesh Kanna Subramani , Parthiban Kalappan Thangamuthu , Senthilraja Kandasamy , Venkatesan Subramanian , Udhaya Nandhini Dhandayuthapani , Mohan Kumar Shanmugam , Dhasarathan Manickam , Kumaresan Palaniyappan , Sai Makkena Jaswanth , Raveendran Muthurajan , Geethalakshmi Vellingiri
Published: February 2024

In this study, an extensive exploration survey of wild progeny was conducted which yielded 18 candidate plus trees (CPTs) of Terminalia bellerica. Seeds of these CPTs were collected from diverse locations between 10°54′ and 28°07′ E longitude, and 76°27′ and 95°32′ N latitude, covering 18 different locations across 5 states of the Indian subcontinent. The objective of the progeny trial was to assess genetic associations and variability in growth and physio-chemical characteristics. Significant variations (p < 0.05) were observed among the growth traits, encompassing plant height, basal diameter, girth at breast height and volume, as well as physio-chemical characteristics such as leaf length, width, area and chlorophyll content, carotenoids, and protein in the progeny trial. Broad-sense heritability (h2b) estimates were consistently high, exceeding 80% for all growth and physiological related traits under investigation except for plant height, leaf length, and girth at breast height. A correlation study revealed that selecting based on plant height, leaf area, and girth at breast height effectively enhances T. bellerica volume. A moderate genetic advance in percent of the mean (GAM) was observed for most traits, except leaf length, leaf width, girth at breast height, and plant height. Across all 13 traits, phenotypic coefficient of variation (PCV) surpassed genotypic coefficient of variation (GCV). Utilizing principal component analysis (PCA) and dendrogram construction categorized the genotypes into seven distinct groups. In conclusion, the study has demonstrated that targeting girth at breast height and plant height would be a highly effective strategy for the establishment of elite seedling nurseries and clonal seed nurseries for varietal and hybridization programs in the future.
The Confluence of Digital Literacy and Eco-Consciousness: Harmonizing Digital Skills with Sustainable Practices in Education
Authors: Lo Noble Po-Kan
Published: February 2024

This study investigates the implementation and impact of maker culture—viewed as a tool for developing green digital skills—in higher education institutions in Hong Kong. Maker culture, a collaborative educational approach, embraces students’ capacity for self-paced, autonomous learning and applies this knowledge to creative problem-solving and innovation, key aspects of sustainability education. An empirical study was conducted, focusing on the experiences of teachers in the higher education sector in Hong Kong. Eight individuals were interviewed to gain insights into their perceptions and experiences with maker education within sustainability contexts. The sample was limited to ensure cross-sectional comparability and direct weighting of teachers’ experiences within a singular, complementary educational setting. The findings provide valuable insights into the benefits and challenges of integrating maker education into traditional educational systems to foster green digital skills. It became evident that adequate resources, effective teachers, and improved administrative systems play significant roles in the successful implementation of this approach. Maker education, as a tool for developing green digital skills, offers a promising alternative to traditional performance-based studies. It has the potential to lead to a future of education that is creative, innovative, and student-directed, fostering sustainability competencies. Therefore, despite the challenges, with the right support and resources, the integration of maker culture into educational systems could significantly transform teaching and learning processes, advancing sustainable education.
Study on the Gelation Process and Mechanical Properties of Organic Polymer Grouting Materials Applied to Fissure Sealing in Underground Mines
Authors: Zhang Xuanning , Wang Ende
Published: February 2024

In this study, organic polymer polyurethane grouting materials were prepared using isocyanate and polyether polyol as the main agents and various additives, the slurry coagulation process was investigated, and the mechanical properties of the polymer samples were tested to explore the influence of the density and soaking time of the polymer on the strength of the samples. The microstructure of the polymer was observed via electron microscopy, and relying on image analysis software, the structural parameters of the polymer cell were analyzed and calculated; the model equation between density and yield strength was established based on the strength model of porous materials developed by Gibson and Ashby. The results show that the initial viscosity and gel time of the polyurethane slurry decrease with the increase of the initial temperature, and the viscosity changes abruptly when the slurry reaches the gel point. The mechanical properties of the polymer increased with increasing density and decreased with increasing soaking time. The interior of the polymer is a porous structure and the pores are approximately spherical; the higher the density of the polymer material, the more uniform the stress distribution of the material, and the higher the percentage of the matrix, which in turn leads to better mechanical properties of the material. The diameter of the polymer cell is negatively correlated with the density, and the model established based on the microscopic parameters of the cell can better predict the yield strength of the polymer. This study helps to deepen the understanding of the microstructure and mechanical properties of polyurethane and provides a certain reference for the application of polyurethane in underground mine reinforcement engineering.
A Holistic Review of 3-Dimethylamino-1-Arylpropenones Based Disperse Dyes for Dyeing Polyester Fabrics: Synthesis, Characterization, and Antimicrobial Activities
Authors: Al-Etaibi Alya M. , El-Apasery Morsy Ahmed
Published: February 2024

The enaminone compounds 3-Dimethylamino-1-arylpropenones produced in this review was synthesized by reacting para-methylacetophenone and para-nitroacetophenone with dimethylformamide dimethyl acetal. In this review article, we discuss how to create novel disperse colors by reacting enaminone derivatives 3a and 3b with phenyldiazonium salt. The highly productive procedure of creating new disperse dyes was followed by the process of dyeing polyester fabrics at temperatures between 70 and 130 °C. As a result, the colours’ resistance to light, rubbing, perspiration, and washing fastness was assessed. In an effort to show the additional value of these dyes, the expected biological activity of the synthetic dyes against fungus, yeast, and Gram-positive and Gram-negative bacteria was also assessed. We have applied zinc oxide nanoparticles for polyester fabrics treatment to impact them a self-cleaning quality, increase their light fastness, enhance their antibacterial efficacy, and enhance UV protection as part of our ongoing strategy to obtain polyester fabrics with newly acquired specifications.
The Glucocorticoid Receptor’s tau1c Activation Domain 35 Years on—Making Order out of Disorder
Authors: Wright Anthony P. H.
Published: February 2024

Almost exactly 35 years after starting to work with the human glucocorticoid receptor (hGR), it is interesting for me to re-evaluate the data and results obtained in the 1980s–1990s with the benefit of current knowledge. What was understood then and how can modern perspectives increase that understanding? The hGR’s tau1c activation domain that we delineated was an enigmatic protein domain. It was apparently devoid of secondary and tertiary protein structures but nonetheless maintained gene activation activity in the absence of other hGR domains, not only in human cells but also in yeast, which is evolutionarily very divergent from humans and which does not contain hGR or other nuclear receptors. We now know that the basic machinery of cells is much more conserved across evolution than was previously thought, so the hGR’s tau1c domain was able to utilise transcription machinery components that were conserved between humans and yeast. Further, we can now see that structure–function aspects of the tau1c domain conform to a general mechanistic framework, such as the acidic exposure model, that has been proposed for many activation domains. As for many transcription factor activation domains, it is now clear that tau1c activity requires regions of transient secondary structure. We now know that there is a tendency for positive Darwinian selection to target intrinsically disordered protein domains. It will be interesting to study the distribution and nature of the many single nucleotide variants of the hGR in this respect.
Fine Calibration Method for Laser Altimeter Pointing and Ranging Based on Dense Control Points
Authors: Xu Chaopeng , Mo Fan , Wang Xiao , Yang Xiaomeng , Xie Junfeng , Wen Zhen
Published: February 2024

Satellite laser altimetry technology, a novel space remote sensing technique, actively acquires high-precision elevation information about the Earth’s surface. However, the accuracy of laser altimetry can be compromised by alterations in the satellite-ground environment, thermal dynamics, and cosmic radiation. These factors may induce subtle variations in the installation and internal structure of the spaceborne laser altimeter on the satellite platform, diminishing measurement precision. In-orbit calibration is thus essential to enhancing the precision of laser altimetry. Through collaborative calculations between satellite and ground stations, we can derive correction parameters for laser pointing and ranging, substantially improving the accuracy of satellite laser altimetry. This paper introduces a sophisticated calibration method for laser altimeter pointing and ranging that utilizes dense control points. The approach interpolates discrete ground control point data into continuous simulated terrain using empirical Bayesian kriging, subsequently categorizing the data for either pointing or ranging calibration according to their respective functions. Following this, a series of calibration experiments are conducted, prioritizing “pointing” followed by “ranging” and continuing until the variation in the ranging calibration results falls below a predefined threshold. We employed experimental data from ground control points (GCPs) in Xinjiang and Inner Mongolia, China, to calibrate the GaoFen-7 (GF-7) satellite Beam 2 laser altimeter as per the outlined method. The calibration outcomes were then benchmarked against those gleaned from infrared laser detector calibration, revealing disparities of 1.12 s in the pointing angle and 2 cm in the ranging correction value. Post validation with ground control points, the measurement accuracy was refined to 0.15 m. The experiments confirm that the proposed calibration method offers accuracy comparable to that of infrared laser detector calibration and can facilitate the updating of 1:10,000 topographic maps utilizing stereo optical imagery. Furthermore, this method is more cost-effective and demands fewer personnel for ground control point collection, enhancing resource efficiency compared to traditional infrared laser detector calibration. The proposed approach surpasses terrain-matching limitations when calibrating laser ranging parameters and presents a viable solution for achieving frequent and high-precision in-orbit calibration of laser altimetry satellites.
Extension of Operating Range in Hybrid Cascaded H-Bridge Inverters with Capacitor Voltage Balancing Capability
Authors: Tirupathi Abhilash , Pribadi Jonathan , Kim Min-Seok , Lee Dong-Choon
Published: February 2024

In this article, a generalized control scheme is proposed to extend the operating range of three-phase hybrid cascaded H-bridge (HCHB) inverters into various voltage levels without necessitating alterations to the core structure or the integration of additional H-bridge submodules. This study addresses a critical challenge related to capacitor voltage drift at various modulation indices and power factors, which is a serious impediment to various applications. To overcome this challenge, a novel balancing control scheme has been developed based on the injection of two independent offset voltages to simultaneously control the DC-link and flying capacitors. A distinctive aspect of the proposed technique involves adjusting the common reference voltage to attain the nearest level in the same cluster, thereby mitigating the insufficiency of redundant switching states. The effectiveness of the proposed technique to regulate the capacitor voltages at various operating conditions has been verified through simulation and experimental results.
Assessment of Drivers’ Mental Workload by Multimodal Measures during Auditory-Based Dual-Task Driving Scenarios
Authors: Huang Jiaqi , Zhang Qiliang , Zhang Tingru , Wang Tieyan , Tao Da
Published: February 2024

Assessing drivers’ mental workload is crucial for reducing road accidents. This study examined drivers’ mental workload in a simulated auditory-based dual-task driving scenario, with driving tasks as the main task, and auditory-based N-back tasks as the secondary task. A total of three levels of mental workload (i.e., low, medium, high) were manipulated by varying the difficulty levels of the secondary task (i.e., no presence of secondary task, 1-back, 2-back). Multimodal measures, including a set of subjective measures, physiological measures, and behavioral performance measures, were collected during the experiment. The results showed that an increase in task difficulty led to increased subjective ratings of mental workload and a decrease in task performance for the secondary N-back tasks. Significant differences were observed across the different levels of mental workload in multimodal physiological measures, such as delta waves in EEG signals, fixation distance in eye movement signals, time- and frequency-domain measures in ECG signals, and skin conductance in EDA signals. In addition, four driving performance measures related to vehicle velocity and the deviation of pedal input and vehicle position also showed sensitivity to the changes in drivers’ mental workload. The findings from this study can contribute to a comprehensive understanding of effective measures for mental workload assessment in driving scenarios and to the development of smart driving systems for the accurate recognition of drivers’ mental states.
Optical Sensing Using Hybrid Multilayer Grating Metasurfaces with Customized Spectral Response
Authors: Elshorbagy Mahmoud H. , Cuadrado Alexander , Alda Javier
Published: February 2024

Customized metasurfaces allow for controlling optical responses in photonic and optoelectronic devices over a broad band. For sensing applications, the spectral response of an optical device can be narrowed to a few nanometers, which enhances its capabilities to detect environmental changes that shift the spectral transmission or reflection. These nanophotonic elements are key for the new generation of plasmonic optical sensors with custom responses and custom modes of operation. In our design, the metallic top electrode of a hydrogenated amorphous silicon thin-film solar cell is combined with a metasurface fabricated as a hybrid dielectric multilayer grating. This arrangement generates a plasmonic resonance on top of the active layer of the cell, which enhances the optoelectronic response of the system over a very narrow spectral band. Then, the solar cell becomes a sensor with a response that is highly dependent on the optical properties of the medium on top of it. The maximum sensitivity and figure of merit (FOM) are SB = 36,707 (mA/W)/RIU and ≈167 RIU−1, respectively, for the 560 nm wavelength using TE polarization. The optical response and the high sensing performance of this device make it suitable for detecting very tiny changes in gas media. This is of great importance for monitoring air quality and thecomposition of gases in closed atmospheres.
Comparative Analysis of Integrated Filtering Methods Using UWB Localization in Indoor Environment
Authors: Ranjan Rahul , Shin Donggyu , Jung Yoonsik , Kim Sanghyun , Yun Jong-Hwan , Kim Chang-Hyun , Lee Seungjae , Kye Joongeup
Published: February 2024

This research delves into advancing an ultra-wideband (UWB) localization system through the integration of filtering technologies (moving average (MVG), Kalman filter (KF), extended Kalman filter (EKF)) with a low-pass filter (LPF). We investigated new approaches to enhance the precision and reduce noise of the current filtering methods—MVG, KF, and EKF. Using a TurtleBot robotic platform with a camera, our research thoroughly examines the UWB system in various trajectory situations (square, circular, and free paths with 2 m, 2.2 m, and 5 m distances). Particularly in the square path trajectory with the lowest root mean square error (RMSE) values (40.22 mm on the X axis, and 78.71 mm on the Y axis), the extended Kalman filter with low-pass filter (EKF + LPF) shows notable accuracy. This filter stands out among the others. Furthermore, we find that integrated method using LPF outperforms MVG, KF, and EKF consistently, reducing the mean absolute error (MAE) to 3.39% for square paths, 4.21% for circular paths, and 6.16% for free paths. This study highlights the effectiveness of EKF + LPF for accurate indoor localization for UWB systems.
Monitoring Disease Severity of Mild Cognitive Impairment from Single-Channel EEG Data Using Regression Analysis
Authors: Khatun Saleha , Morshed Bashir I. , Bidelman Gavin M.
Published: February 2024

A deviation in the soundness of cognitive health is known as mild cognitive impairment (MCI), and it is important to monitor it early to prevent complicated diseases such as dementia, Alzheimer’s disease (AD), and Parkinson’s disease (PD). Traditionally, MCI severity is monitored with manual scoring using the Montreal Cognitive Assessment (MoCA). In this study, we propose a new MCI severity monitoring algorithm with regression analysis of extracted features of single-channel electro-encephalography (EEG) data by automatically generating severity scores equivalent to MoCA scores. We evaluated both multi-trial and single-trail analysis for the algorithm development. For multi-trial analysis, 590 features were extracted from the prominent event-related potential (ERP) points and corresponding time domain characteristics, and we utilized the lasso regression technique to select the best feature set. The 13 best features were used in the classical regression techniques: multivariate regression (MR), ensemble regression (ER), support vector regression (SVR), and ridge regression (RR). The best results were observed for ER with an RMSE of 1.6 and residual analysis. In single-trial analysis, we extracted a time–frequency plot image from each trial and fed it as an input to the constructed convolutional deep neural network (CNN). This deep CNN model resulted an RMSE of 2.76. To our knowledge, this is the first attempt to generate automated scores for MCI severity equivalent to MoCA from single-channel EEG data with multi-trial and single data.