bluuebunny/crossref_metadata_2025 huggingface dataset:
Bioprospecting Endophytic Fungi of Forest Plants for Bioactive Metabolites with Antibacterial, Antifungal, and Antioxidant Potentials
Authors: El-Sayed El-Sayed R. , Baskaran Abirami , Pomarańska Oliwia , Mykhailova Daria , Dunal Anna , Dudek Anita , Satam Sahil , Strzała Tomasz , Łyczko Jacek , Olejniczak Teresa , Boratyński Filip
Published: October 2024

The growing emergence of multi-drug resistant microbial strains has kept the scientific world searching for novel bioactive compounds with specific chemical characteristics. Accordingly, researchers have started exploring the understudied metabolites from endophytes as a new source of bioactive compounds. In this context, the current study was designed to evaluate the bioactive properties of endophytic fungi from the Mokrzański forest in Wrocław, Poland that have not yet been fully researched. Forty-three endophytic fungi were isolated from twelve distinct plants. Following their cultivation, fungal extracts were separately prepared from biomass and cell-free filtrates, and their antibacterial, antifungal (against human and plant pathogens), and antioxidant properties were examined. Five promising fungi after screening were identified to possess all of these activities. These strains and their respective plant hosts were Trichoderma harzianum BUK-T (Fagus sylvatica), Aspergillus ochraceus ROB-L1 (Robinia pseudoacacia), Chaetomium cochliodes KLON-L1, Fusarium tricinctum KLON-L2 (Acer platanoides), and Penicillium chrysogenum SOS-B2 (Pinus sylvestris). Moreover, gamma irradiation at several doses (Gy) was separately applied to the fungal cultures to study their effects on the recorded activities. Finally, compounds after preparative thin-layer chromatography fractionation of the five fungal strains were identified by GC-MS. These findings suggest that the isolated endophytic fungi could serve as novel sources of bioactive metabolites with antibacterial, antifungal, and antioxidant properties, potentially paving the way for future research and the development of new bioactive compounds.
Overview of Liquid Sample Preparation Techniques for Analysis, Using Metal-Organic Frameworks as Sorbents
Authors: Woźniak Jakub , Nawała Jakub , Dziedzic Daniel , Popiel Stanisław
Published: October 2024

The preparation of samples for instrumental analysis is the most essential and time-consuming stage of the entire analytical process; it also has the greatest impact on the analysis results. Concentrating the sample, changing its matrix, and removing interferents are often necessary. Techniques for preparing samples for analysis are constantly being developed and modified to meet new challenges, facilitate work, and enable the determination of analytes in the most comprehensive concentration range possible. This paper focuses on using metal-organic frameworks (MOFs) as sorbents in the most popular techniques for preparing liquid samples for analysis, based on liquid-solid extraction. An increase in interest in MOFs-type materials has been observed for about 20 years, mainly due to their sorption properties, resulting, among others, from the high specific surface area, tunable pore size, and the theoretically wide possibility of their modification. This paper presents certain advantages and disadvantages of the most popular sample preparation techniques based on liquid-solid extraction, the newest trends in the application of MOFs as sorbents in those techniques, and, most importantly, presents the reader with a summary, which a specific technique and MOF for the desired application. To make a tailor-made and well-informed choice as to the extraction technique.
Genetic and Anthropometric Interplay: How Waist-to-Hip Ratio Modulates LDL-c Levels in Mexican Population
Authors: Hernández-Guerrero César , Arenas Erika , García-Mena Jaime , Mendivil Edgar J. , Ramos-Lopez Omar , Teruel Graciela
Published: October 2024

Background/Objectives: Genetic factors contribute to the physiopathology of obesity and its comorbidities. This study aimed to investigate the association of the SNPs ABCA1 (rs9282541), ADIPOQ (rs2241766), FTO (rs9939609), GRB14 (rs10195252), and LEPR (rs1805134) with various clinical, anthropometric, and biochemical variables. Methods: The study included 396 Mexican mestizo individuals with obesity and 142 individuals with normal weight. Biochemical markers were evaluated from peripheral blood samples, and SNP genotyping was performed using PCR with TaqMan probes. A genetic risk score (GRS) was computed using an additive model. Results: No significant associations were found between the SNPs ABCA1, ADIPOQ, FTO, and LEPR with obesity. However, the T allele of the GRB14 SNP was significantly associated with obesity (χ2 = 5.93, p = 0.01; OR = 1.52; 95% CI: 1.08–2.12). A multivariate linear regression model (adjusted R-squared: 0.1253; p < 0.001) predicting LDL-c levels among all participants (n = 538) identified significant (p < 0.05) beta coefficients for several anthropometric and biochemical variables, as well as for the GRS. Additionally, the interaction between the GRS and the waist-to-hip ratio (WHR) showed a negative beta coefficient (BC = −26.5307; p = 0.014). Participants with a WHR < 0.839 showed no effect of GRS on LDL-c concentration, while those with a WHR > 0.839 exhibited a greater effect of GRS (~9) at lower LDL-c concentrations (~50 mg/dL) and a lesser effect of GRS (~7) at higher LDL-c concentrations (~250 mg/dL). Conclusions: A significant interaction between genetics and WHR influences LDL-c in Mexicans, which may contribute to the prevention and clinical management of dyslipidemia and cardiovascular disease.
Effects of Dietary Quality on Vaginal Microbiome Composition Throughout Pregnancy in a Multi-Ethnic Cohort
Authors: Miller Corrie , Morikawa Kira , Benny Paula , Riel Jonathan , Fialkowski Marie K. , Qin Yujia , Khadka Vedbar , Lee Men-Jean
Published: October 2024

Background: Vaginal Lactobacillus predominance is associated with improved vaginal health and reduced pregnancy complications. Little is known about how dietary quality may improve vaginal microbial composition or about dietary interventions that may promote Lactobacillus abundance. To understand the host factors affecting vaginal microbiota during pregnancy in a multi-ethnic cohort in Hawai`i. We hypothesize that better diet quality improves vaginal microbial composition, as represented by Lactobacillus abundance and depletion of anaerobic organisms. Methods: We compared comprehensive diet quality, as measured by the Healthy Eating Index-2015 (HEI-2015), to taxonomic classifications of bacteria present within the vagina. Participants of the four predominant ethnic groups in Hawai’i (Japanese, Filipino, Non-Hispanic White and Native Hawaiian) completed Quantitative Food Frequency Questionnaires (QFFQs) and collected vaginal swabs during each trimester. 16s rRNA amplicon sequencing (V2–V9 regions) was performed on vaginal samples. HEI-2015 scores and macro- and micronutrient intake were compared with the predominant species present using the Mann–Whitney-U test, PERMANOVA, and the Pearson correlation coefficient. A mixed-effects logistics regression model was used to predict the depletion of Lactobacillus species while accounting for confounding demographic factors. Results: Matched, longitudinal data for 40 participants demonstrated three predominant Lactobacillus species: L. crispatus, L. iners, and L. gasseri, with another subset of samples with anaerobic abundance. (Primarily, Atopobium vaginae, Prevotella, and Gardnerella vaginalis.) Non-Hispanic White participants had lower amounts of Lactobacillus iners compared to other racial and ethnic groups. HEI scores correlated with the chao index and observed species number primarily in the first trimester (r = 0.25, p < 0.05). Greater carbohydrate intake was associated with a higher abundance of L. crispatus, while lower carbohydrate intake trended towards more L. iners (0.056) and anaerobic species. Conclusions: Increased carbohydrate consumption and improved diet quality may be associated with beneficial vaginal microbial composition in pregnancy.
Development of a Benzophenone-Free Red Propolis Extract and Evaluation of Its Efficacy against Colon Carcinogenesis
Authors: Squarisi Iara Silva , Ribeiro Victor Pena , Ribeiro Arthur Barcelos , de Souza Letícia Teixeira Marcos , Junqueira Marcela de Melo , de Oliveira Kátia Mara , Hayot Gaelle , Dickmeis Thomas , Bastos Jairo Kenupp , Veneziani Rodrigo Cassio Sola , Ambrósio Sérgio Ricardo , Tavares Denise Crispim
Published: October 2024

Background/Objectives: Brazilian red propolis has attracted attention for its pharmacological properties. However, signs of toxicity were recently observed in long-term studies using the hydroalcoholic extract of red propolis (RPHE), likely due to polyprenylated benzophenones. This study aimed to develop a benzophenone-free red propolis extract (BFRP) and validate an HPLC-PDA method to quantify its main constituents: isoliquiritigenin, vestitol, neovestitol, medicarpine, and 7-O-methylvestitol. Methods: BFRP’s toxicity was assessed in zebrafish larvae through a vibrational startle response assay (VSRA) and morphological analysis. Genotoxicity was evaluated using the micronucleus test in rodents, and the extract’s effects on chemically induced preneoplastic lesions in rat colon were studied. An HPLC-PDA method was used to quantify BFRP’s main compounds. Results: BFRP primarily contained vestitol (128.24 ± 1.01 μg/mL) along with isoliquiritigenin, medicarpin, neovestitol, and 7-O-methylvestitol. Zebrafish larvae exposed to 40 µg/mL of BFRP exhibited toxicity, higher than the 10 µg/mL for RPHE, though no morphological differences were found. Fluorescent staining in the notochord, branchial arches, and mouth was observed in larvae treated with both BFRP and RPHE. No genotoxic or cytotoxic effects were observed up to 2000 mg/kg in rodents, with no impact on hepatotoxicity or nephrotoxicity markers. Chemoprevention studies showed a 41.6% reduction in preneoplastic lesions in rats treated with 6 mg/kg of BFRP. Conclusions: These findings indicate that BFRP is a safe, effective propolis-based extract with potential applications for human health, demonstrating reduced toxicity and chemopreventive properties.
Establishing a Relationship between In Vitro Potency in Cell-Based Assays and Clinical Efficacious Concentrations for Approved GLP-1 Receptor Agonists
Authors: Boianelli Alessandro , Nordell Pär , Earl Joseph , Naylor Jacqueline , Hornigold David , Jansson Löfmark Rasmus , Sundqvist Monika
Published: October 2024

Background: Glucagon-like peptide-1 receptor agonists (GLP-1RAs) play an important role in the treatment of type 2 diabetes (T2D) and obesity. The relationship between efficacy and dosing regimen has been studied extensively for this class of molecules. However, a comprehensive analysis of the translation of in vitro data to in vivo efficacious exposure is still lacking. Methods: We collected clinical pharmacokinetics for five approved GLP-1RAs to enable the simulation of exposure profiles and compared published clinical efficacy endpoints (HbA1c and body weight) with in-house in vitro potency values generated in different cell-based assays. Additionally, we investigated the correlation with target coverage, expressed as a ratio between the steady state drug exposure and unbound potency, body weight, or HbA1c reduction in patients with T2D. Results: We found that the best correlation with in vivo efficacy was seen for in vitro potency data generated in cellular assays performed in the absence of any serum albumin or using ovalbumin. Residual variability was larger using in vitro potency data generated in endogenous cell lines or in the presence of human serum albumin. For the human receptor assay with no albumin, exposures above 100-fold in vitro EC50 resulted in >1.5% point HbA1c reduction, while a 5% BW reduction was related to approximately 3× higher exposures. A similar relationship was seen in the ovalbumin assay. Conclusions: Overall, the relationship established for in vitro potency and in vivo efficacy will help to increase confidence in human dose prediction and trial design for new GLP-1RAs in the discovery and early clinical phases.
Development of a Theoretical Continuous Glucose Monitoring Module for Pharmacy Students: Preparing Pharmacists for the Future
Authors: Kinny Florian , Ali Sherazi Bushra , Dabidian Armin , Laeer Stephanie , Obarcanin Emina
Published: October 2024

To enhance the digital competencies of pharmacy students, the Institute of Clinical Pharmacy and Pharmacotherapy at Heinrich-Heine University Duesseldorf developed and evaluated a theoretical module on digital health and data analysis. This innovative module integrated a continuous glucose-monitoring (CGM) wearable device into teaching, providing students with in-depth practical experience and a 2.5 h seminar on digital health and CGM systems. Students’ knowledge of CGM and self-assessment of their CGM competencies were assessed in a pre-post manner. Additionally, students’ satisfaction with the module and their perceptions of the future integration of digital health training and the role of wearables in pharmacy practice were also assessed after the module. A total of 39 final-year pharmacy students completed the module conducted in June 2024 as part of the clinical pharmacy seminar. In total, 32 students completed the pre- and post-knowledge tests and self-assessment questionnaires. Both the knowledge and the students’ self-assessment of CGM-related skills after the module increased significantly (p < 0.05). Students expanded their knowledge regarding digital health solutions, in particular the CGM systems, and increased their self-reported competence in CGM-related skills. With this module, an important foundation was laid, as this is the first theoretical module including the essentials of CGM digital health tools for pharmacy students in Germany.
High-Strength Welding of Silica Glass Using Double-Pulse Femtosecond Laser under Non-Optical Contact Conditions
Authors: Gao Zheng , He Jiahua , Jia Xianshi , Yi Zhaoxi , Li Cheng , Zhang Shifu , Wang Cong , Duan Ji’an
Published: October 2024

Ultrafast laser welding technology for transparent materials has developed rapidly in recent years; however, high-strength non-optical contact transparent material welding has been a challenge. This work presents a welding method for silica glass using a double-pulse femtosecond (fs) laser and optimizes the laser processing parameters to enhance the welding performance. The welding characteristics of silica glass are analyzed under different time delays by controlling the pulse delay of double pulses. In addition to comprehensively study the influence of various experimental conditions on double-pulse fs laser welding, multi-level tests are designed for five factors, including average laser power, pulse delay, scanning interval, scanning speed, and repetition rate. Finally, by optimizing the parameters, a welding strength of 57.15 MPa is achieved at an average power of 3500 mW, repetition rate of 615 kHz, pulse delay of 66.7 ps, scanning interval of 10 µm, and scanning speed of 1000 µm/s. This work introduces a new approach to glass welding and presents optimal parameters for achieving higher welding strength, which can be widely used in aerospace, microelectronic packaging, microfluidics, and other fields.
Switchable Dual-Wavelength Fiber Laser with Narrow-Linewidth Output Based on Parity-Time Symmetry System and the Cascaded FBG
Authors: Wang Kaiwen , Yin Bin , Lv Chao , Lv Yanzhi , Wang Yiming , Liang Hao , Wang Qun , Wang Shiyang , Yu Fengjie , Zhang Zhong , Li Ziwang , Wu Songhua
Published: October 2024

In this paper, a dual-wavelength narrow-linewidth fiber laser based on parity-time (PT) symmetry theory is proposed and experimentally demonstrated. The PT-symmetric filter system consists of two optical couplers (OCs), four polarization controllers (PCs), a polarization beam splitter (PBS), and cascaded fiber Bragg gratings (FBGs), enabling stable switchable dual-wavelength output and single longitudinal-mode (SLM) operation. The realization of single-frequency oscillation requires precise tuning of the PCs to match gain, loss, and coupling coefficients to ensure that the PT-broken phase occurs. During single-wavelength operation at 1548.71 nm (λ1) over a 60-min period, power and wavelength fluctuations were observed to be 0.94 dB and 0.01 nm, respectively, while for the other wavelength at 1550.91 nm (λ2), fluctuations were measured at 0.76 dB and 0.01 nm. The linewidths of each wavelength were 1.01 kHz and 0.89 kHz, with a relative intensity noise (RIN) lower than −117 dB/Hz. Under dual-wavelength operation, the maximum wavelength fluctuations for λ1 and λ2 were 0.03 nm and 0.01 nm, respectively, with maximum power fluctuations of 3.23 dB and 2.38 dB. The SLM laser source is suitable for applications in long-distance fiber-optic sensing and coherent LiDAR detection.
Screening Germplasms and Detecting Quantitative Trait Loci for High Sucrose Content in Soybean
Authors: Kang Se-Hee , Shin Seo-Young , Kang Byeong Hee , Chowdhury Sreeparna , Lee Won-Ho , Kim Woon Ji , Lee Jeong-Dong , Lee Sungwoo , Choi Yu-Mi , Ha Bo-Keun
Published: October 2024

Sucrose is a desirable component of processed soybean foods and animal feed, and thus, its content is used as an important characteristic for assessing the quality of soybean seeds. However, few studies have focused on the quantitative trait loci (QTLs) associated with sucrose regulation in soybean seeds. This study aims to measure the sucrose content of 1014 soybean accessions and identify genes related to high sucrose levels using QTL analysis. Colorimetric analysis based on the enzymatic reaction of invertase (INV) and glucose oxidase (GOD) was employed to test the germplasms. A total of six high-sucrose genetic resources (IT186230, IT195321, IT263138, IT263276, IT263286, and IT276521) and two low-sucrose genetic resources (IT025668 and IT274054) were identified. Two F2:3 populations, IT186230 × IT025668 and Ilmi × IT186230, were then established from these germplasms. QTL analysis identified four QTLs (qSUC6.1, qSUC11.1, qSUC15.1, and qSUC17.1), explaining 7.3–27.6% of the phenotypic variation in the sugar content. Twenty candidate genes were found at the four QTLs. Notably, Glyma.17G152300, located in the qSUC17.1 QTL region, exhibited a 17-fold higher gene expression in the high-sucrose germplasm IT186230 compared to the control germplasm Ilmi, confirming its role as a major gene regulating the sucrose content in soybean. These results may assist in marker-assisted selection for breeding programs that aim to develop soybean lines with a higher sucrose content.
Abstracts of the 2024 50th Annual NATAS Conference
Authors: Advincula Rigoberto , Bowman Christopher , Smith Dennis , Schoch Karl , Adams Tina , Stewart Cathy , Judovits Lawrence , Pilato Louis
Published: October 2024

The 50th annual conference of the North American Thermal Analysis Society is being held jointly with the 8th Baekeland Symposium to bring those communities together. NATAS offers scientists and practitioners the opportunity to explore the frontiers of thermal analysis, rheology, and materials characterization, learn of developments in instrumentation and software, as well as applications in a variety of industrial settings. The Baekeland Symposium has a record of showcasing the latest scientific, technical and industrial innovations in the field of high performance thermosetting polymers. This year is the first joint meeting of the two organizations and is expected to provide opportunities for new collaborations and exchange of ideas. Presentations and posters by renowned scientists and graduate students set the stage for excellent discussions and an ideal environment to learn about state-of-the-art techniques and exciting new developments in thermal analysis and materials research.
Piperazine-Based Mixed Solvents for CO2 Capture in Bubble-Column Scrubbers and Regeneration Heat
Authors: Chen Pao-Chi , Jhuang Jyun-Hong , Lin Zhong-Yi
Published: October 2024

This work used piperazine (PZ) as a base solvent, blended individually with five amines, which were monoethanolamine (MEA), secondary amines (DIPAs), tertiary amines (TEAs), stereo amines (AMPs), and diethylenetriamine (DETA), to prepare mixed solvents at the desired concentrations as the test solvents. A continuous bubble-column scrubber with one stage (1 s) was first used for the test. Six parameters were selected, including the type of mixed solvent (A), the ratio of mixed solvents (B), the solvent feed rate (C), the gas flow rate (D), the concentration of the mixed solvents (E), and the liquid temperature (F), each one having five levels. Using the Taguchi experimental design, only 25 runs were required. The outcome data, such as the absorption efficiency (EF), the absorption rate (RA), the overall mass-transfer coefficient (KGa), and the absorption factor (φ), could be determined under steady-state conditions. The optimal mixed solvents were found to be A1 (PZ + MEA) and A2 (PZ + DIPA). The parameter importance and optimal conditions for EF, RA, KGa, and ϕ were determined separately; the verification of all optimal conditions was successful. This analysis found that the importance of the parameters was D > C > A > E > B > F, and the gas flow rate (D) was the most important factor. Subsequently, multiple-stage scrubbers were used to capture CO2. Comparing 1 s and 3 s (three-stage scrubber), EF, RA, KGa, and φ increased by 33%, 29%, 22%, and 38%, respectively. The desorption tests for the four optimal scrubbed solutions, including multiple stages, showed that the heat of regeneration for the three scrubbers was 3.57–8.93 GJ/t, in the temperature range of 110–130 °C, while A2 was the best solvent. Finally, the heat regeneration mechanism was also discussed in this work.
Safety of Hydrogen Storage Technologies
Authors: Davies Emma , Ehrmann Andrea , Schwenzfeier-Hellkamp Eva
Published: October 2024

While hydrogen is regularly discussed as a possible option for storing regenerative energies, its low minimum ignition energy and broad range of explosive concentrations pose safety challenges regarding hydrogen storage, and there are also challenges related to hydrogen production and transport and at the point of use. A risk assessment of the whole hydrogen energy system is necessary to develop hydrogen utilization further. Here, we concentrate on the most important hydrogen storage technologies, especially high-pressure storage, liquid hydrogen in cryogenic tanks, methanol storage, and salt cavern storage. This review aims to study the most recent research results related to these storage techniques by describing typical sensors and explosion protection measures, thus allowing for a risk assessment of hydrogen storage through these technologies.
Environmental Impact of Polyurethane-Based Aerogel Production: Influence of Solvents and Solids Content
Authors: Aldaghi Seyed Ahmad , Costamagna Mattia , Perucca Massimo , Pinilla-Peñalver Esther , Cantero Darío , Romero Amaya , Sánchez-Silva Luz
Published: October 2024

This study provides a comprehensive analysis of the environmental impacts associated with the synthesis of polyurethane (PUR) aerogels. The synthesis process incorporates various solvents and solids contents into the formulation, with the primary objective of enhancing the physical properties of the aerogels for broad industrial applications. Nine experimental scenarios were explored, grouped into two sets based on the variables studied. A detailed Life Cycle Assessment (LCA) was conducted to evaluate the environmental impacts of all formulated PUR aerogels. The findings indicate that a solvent solution of 100% ethyl acetate (EtOAc) results in lower environmental impacts compared to other tested formulations. Notably, a solvent solution comprising 75% acetonitrile (ACN) and 25% EtOAc exhibited the highest environmental Key Performance Indicator (εKPI) among the tested material formulations, closely followed by the PUR aerogel obtained using acetone as a solvent. Furthermore, this study underscores the necessity of performing an integrated LCA that considers both environmental and functional aspects. While reducing the solids content is environmentally advantageous, it may present challenges in terms of material functionality. This is illustrated by the PUR aerogel synthesized with the lowest solids content of 3.2 wt.%, which demonstrated high deformability, thereby complicating the determination of a reliable Young’s modulus for analysis.
Why Do Companies Share Buybacks? Evidence from the UK
Authors: Jamadar Yasmin , Reyad Hossain Mohammad , Alam Md. Kausar , Thakur Oli Ahad , Mamun Syed A.
Published: October 2024

We examine the key drivers behind management decisions on share repurchase from various theoretical perspectives, including the free cash flow theory and the signaling theory/hypothesis. Specifically, we investigate the relationship between share repurchase and three key drivers: surplus cash, undervaluation, and leverage, along with several control variables. Using a sample of UK-listed non-financial companies from 2012 to 2022, we apply logistic regression, standard OLS regression, and Tobit regression to identify the factors influencing share repurchase. Our findings reveal that firms repurchase shares to distribute cash to shareholders with surplus cash and Surplus investing cash flow. This study also finds that undervalued smaller firms with lower market-to-book ratios and lower leverage are more likely to repurchase shares. Our study highlights the key factors motivating companies’ share repurchases, such as undervaluation, surplus cash, and leverage, examined from various theoretical perspectives, including the free cash flow theory and signaling theory. Focusing on the UK context, as well as adding a new angle in regard to applying logistic regression, standard OLS regression, and Tobit regression in combination, this research contributes to the existing body of knowledge in corporate finance. The outcome of the study has plausible implications for financial managers and investors in selecting stocks. Its practical implications will help investors gain a better understanding of the factors and forces influencing share repurchase decisions.
Estimating Vertical Distribution of Total Suspended Matter in Coastal Waters Using Remote-Sensing Approaches
Authors: Zhang Hailong , Ren Xin , Wang Shengqiang , Li Xiaofan , Sun Deyong , Wang Lulu
Published: October 2024

The vertical distribution of the marine total suspended matter (TSM) concentration significantly influences marine material transport, sedimentation processes, and biogeochemical cycles. Traditional field observations are constrained by limited spatial and temporal coverage, necessitating the use of remote-sensing technology to comprehensively understand TSM variations over extensive areas and periods. This study proposes a remote-sensing approach to estimate the vertical distribution of TSM concentrations using MODIS satellite data, with the Bohai Sea and Yellow Sea (BSYS) as a case study. Extensive field measurements across various hydrological conditions and seasons enabled accurate reconstruction of in situ TSM vertical distributions from bio-optical parameters, including the attenuation coefficient, particle backscattering coefficient, particle size, and number concentration, achieving a determination coefficient of 0.90 and a mean absolute percentage error of 26.5%. In situ measurements revealed two distinct TSM vertical profile types (vertically uniform and increasing) and significant variation in TSM profiles in the BSYS. Using surface TSM concentrations, wind speed, and water depth, we developed and validated a remote-sensing approach to classify TSM vertical profile types, achieving an accuracy of 84.3%. Combining this classification with a layer-to-layer regression model, we successfully estimated TSM vertical profiles from MODIS observation. Long-term MODIS product analysis revealed significant spatiotemporal variations in TSM vertical distributions and column-integrated TSM concentrations, particularly in nearshore regions. These findings provide valuable insights for studying marine sedimentation and biological processes and offer a reference for the remote-sensing estimation of the TSM vertical distribution in other marine regions.
Research on the Method of Imperfect Wheat Grain Recognition Utilizing Hyperspectral Imaging Technology
Authors: Zhang Hongtao , Zheng Li , Tan Lian , Yang Jiapeng , Gao Jiahui
Published: October 2024

As the primary grain crop in China, wheat holds a significant position in the country’s agricultural production, circulation, consumption, and various other aspects. However, the presence of imperfect grains has greatly impacted wheat quality and, subsequently, food security. In order to detect perfect wheat grains and six types of imperfect grains, a method for the fast and non-destructive identification of imperfect wheat grains using hyperspectral images was proposed. The main contents and results are as follows: (1) We collected wheat grain hyperspectral data. Seven types of wheat grain samples, each containing 300 grains, were prepared to construct a hyperspectral imaging system for imperfect wheat grains, and visible near-infrared hyperspectral data from 2100 wheat grains were collected. The Savitzky–Golay algorithm was used to analyze the hyperspectral images of wheat grains, selecting 261 dimensional effective hyperspectral datapoints within the range of 420.61–980.43 nm. (2) The Successive Projections Algorithm was used to reduce the dimensions of the 261 dimensional hyperspectral datapoints, selecting 33 dimensional hyperspectral datapoints. Principal Component Analysis was used to extract the optimal spectral wavelengths, specifically selecting hyperspectral images at 647.57 nm, 591.78 nm, and 568.36 nm to establish the dataset. (3) Particle Swarm Optimization was used to optimize the Support Vector Machines model, Convolutional Neural Network model, and MobileNet V2 model, which were established to recognize seven types of wheat grains. The comprehensive recognition rates were 93.71%, 95.14%, and 97.71%, respectively. The results indicate that a larger model with more parameters may not necessarily yield better performance. The research shows that the MobileNet V2 network model exhibits superior recognition efficiency, and the integration of hyperspectral image technology with the classification model can accurately identify imperfect wheat grains.
Deep-Learning-Based Real-Time Passive Non-Line-of-Sight Imaging for Room-Scale Scenes
Authors: Li Yuzhe , Zhang Yuning
Published: October 2024

Non-line-of-sight imaging is a technique for reconstructing scenes behind obstacles. We report a real-time passive non-line-of-sight (NLOS) imaging method for room-scale hidden scenes, which can be applied to smart home security monitoring sensing systems and indoor fast fuzzy navigation and positioning under the premise of protecting privacy. An unseen scene encoding enhancement network (USEEN) for hidden scene reconstruction is proposed, which is a convolutional neural network designed for NLOS imaging. The network is robust to ambient light interference conditions on diffuse reflective surfaces and maintains a fast reconstruction speed of 12.2 milliseconds per estimation. The consistency of the mean square error (MSE) is verified, and the peak signal-to-noise ratio (PSNR) values of 19.21 dB, 15.86 dB, and 13.62 dB are obtained for the training, validation, and test datasets, respectively. The average values of the structural similarity index (SSIM) are 0.83, 0.68, and 0.59, respectively, and are compared and discussed with the corresponding indicators of the other two models. The sensing system built using this method will show application potential in many fields that require accurate and real-time NLOS imaging, especially smart home security systems in room-scale scenes.
PGMF-VINS: Perpendicular-Based 3D Gaussian–Uniform Mixture Filter
Authors: Deng Wenqing , Yan Zhe , Hu Bo , Dong Zhiyan , Zhang Lihua
Published: October 2024

Visual–Inertial SLAM (VI-SLAM) has a wide range of applications spanning robotics, autonomous driving, AR, and VR due to its low-cost and high-precision characteristics. VI-SLAM is divided into localization and mapping tasks. However, researchers focus more on the localization task while the robustness of the mapping task is often ignored. To address this, we propose a map-point convergence strategy which explicitly estimates the position, the uncertainty, and the stability of the map point (SoM). As a result, the proposed method can effectively improve the quality of the whole map while ensuring state-of-the-art localization accuracy. The convergence strategy mainly consists of a perpendicular-based triangulation and 3D Gaussian–uniform mixture filter, and we name it PGMF, perpendicular-based 3D Gaussian–uniform mixture filter. The algorithm is extensively tested on open-source datasets, which shows the RVM (Ratio of Valid Map points) of our algorithm exhibits an average increase of 0.1471 compared to VINS-mono, with a variance reduction of 68.8%.
Comment on Koutsoyiannis, D. Net Isotopic Signature of Atmospheric CO2 Sources and Sinks: No Change Since the Little Ice Age. Sci 2024, 6, 17
Authors: Kleber Arno
Published: October 2024

In his paper [...]
Definite Change Since the Formation of the Earth. Reply to Kleber, A. Comment on “Koutsoyiannis, D. Net Isotopic Signature of Atmospheric CO2 Sources and Sinks: No Change Since the Little Ice Age. Sci 2024, 6, 17”
Authors: Koutsoyiannis Demetris
Published: October 2024

Careful inspection of the title and graphical abstract of the original paper [...]
Position Matters: Effect of Nitro Group in Chalcones on Biological Activities and Correlation via Molecular Docking
Authors: Hidalgo Alam Yair , Romero-Ceronio Nancy , Lobato-García Carlos Ernesto , Herrera-Ruiz Maribel , Vázquez-Cancino Romario , Peña-Morán Omar Aristeo , Vilchis-Reyes Miguel Ángel , Gallegos-García Ammy Joana , Medrano-Sánchez Eric Jaziel , Hernández-Abreu Oswaldo , Gómez-Rivera Abraham
Published: October 2024

A series of nine nitro group-containing chalcones were synthesized to investigate their anti-inflammatory and vasorelaxant activities via in vivo, ex vivo, and in silico studies. The anti-inflammatory effects of the compounds were evaluated via a TPA-induced mouse ear edema model, and the vasorelaxant effects were evaluated via an isolated organ model in addition to molecular docking studies. The compounds with the highest anti-inflammatory activity were 2 (71.17 ± 1.66%), 5 (80.77 ± 2.82%), and 9 (61.08 ± 2.06%), where the nitro group is located at the ortho position in both rings, as confirmed by molecular docking with COX-1 and COX-2. The compounds with the highest vasorelaxant activity were 1 (81.16 ± 7.55%), lacking a nitro group, and 7 (81.94 ± 2.50%), where the nitro group is in the para position of the B ring; both of these compounds interact with the eNOS enzyme during molecular docking. These results indicate that the position of the nitro group in the chalcone plays an important role in these anti-inflammatory and vasorelaxant activities.
Human Target Proteins for Benzo(a)pyrene and Acetaminophen (And Its Metabolites): Insights from Inverse Molecular Docking and Molecular Dynamics Simulations
Authors: Montero-Pérez Yina , Pájaro-Castro Nerlis , Coronado-Posada Nadia , Ahumedo-Monterrosa Maicol , Olivero-Verbel Jesus
Published: October 2024

Acetaminophen (APAP) is a widely used analgesic and antipyretic, whereas benzo(a)pyrene (B[a]P) is a carcinogen with significant global health risks due to environmental exposure. While APAP is generally safe at therapeutic doses, co-exposure to B[a]P can exacerbate its toxicity. This study aimed to identify potential human target proteins for B[a]P and APAP through inverse molecular docking and molecular dynamics simulations. We performed inverse docking with B[a]P, APAP, and three APAP metabolites against 689 human proteins involved in various biological processes. Five proteins were selected based on high docking affinity and their involvement in multiple pathways. Molecular dynamics simulations revealed that B[a]P primarily interacted via hydrophobic and π-stacking interactions with proteins like LXR-β, HSP90α, HSP90β, and AKT1, while AM404 formed hydrogen bonds and hydrophobic interactions. The simulations confirmed that the complexes had high conformational stability, except for protein AKT1. These results provide insights into the potential impacts of B[a]P and AM404 on protein functions and their implications for understanding the toxic effects of combined exposure.
Exploring Children’s Journeys into the Youth Justice System from Multiple Perspectives: An Interpretative Phenomenological Analysis
Authors: Smith Hannah , Paddock Elizabeth
Published: October 2024

In order to contribute to research into youth crime prevention, the current study aimed to explore the experiences of children in conflict with the law prior to receiving their first caution or conviction. Participants were recruited at a Youth Justice Service and included five children working with the service, their five case managers, and two of their parents/guardians. Data was collected using semi-structured interviews and timelines were used to support the children in sharing their experiences. Data was analysed using Interpretative Phenomenological Analysis, which focuses on understanding how individuals experience the world and how they make sense of those experiences. Six group experiential themes were identified within the analysis. These consider the events leading up to offending and whether it could have been predicted, the extent to which the children felt supported, the effect of school practices, the impact of peer influences, difficulties with managing emotions, and the children’s readiness for change. Each theme is discussed and recommendations for practice and future research are considered. The importance of placing children’s experiences at the forefront of research is highlighted throughout.
Digital Mirrors: AI Companions and the Self
Authors: Kouros Theodoros , Papa Venetia
Published: October 2024

This exploratory study examines the socio-technical dynamics of Artificial Intelligence Companions (AICs), focusing on user interactions with AI platforms like Replika 9.35.1. Through qualitative analysis, including user interviews and digital ethnography, we explored the nuanced roles played by these AIs in social interactions. Findings revealed that users often form emotional attachments to their AICs, viewing them as empathetic and supportive, thus enhancing emotional well-being. This study highlights how AI companions provide a safe space for self-expression and identity exploration, often without fear of judgment, offering a backstage setting in Goffmanian terms. This research contributes to the discourse on AI’s societal integration, emphasizing how, in interactions with AICs, users often craft and experiment with their identities by acting in ways they would avoid in face-to-face or human-human online interactions due to fear of judgment. This reflects front-stage behavior, in which users manage audience perceptions. Conversely, the backstage, typically hidden, is somewhat disclosed to AICs, revealing deeper aspects of the self.
Comparative Evaluation of Traditional and Advanced Algorithms for Photovoltaic Systems in Partial Shading Conditions
Authors: Sørensen Robert , Mihet-Popa Lucian
Published: October 2024

The optimization of photovoltaic (PV) systems is vital for enhancing efficiency and economic viability, especially under Partial Shading Conditions (PSCs). This study focuses on the development and comparison of traditional and advanced algorithms, including Perturb and Observe (P&O), Incremental Conductance (IC), Fuzzy Logic Control (FLC), Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Artificial Neural Networks (ANN), for efficient Maximum Power Point Tracking (MPPT). Simulations conducted in the MATLAB/Simulink software package evaluated these algorithms’ performances under various shading scenarios. The results indicate that, while traditional methods like P&O and IC are effective under uniform conditions, advanced techniques, particularly ANN-based MPPT, exhibit superior efficiency and faster convergence under PSCs. This study concludes that integrating Artificial Intelligence (AI) and Machine Learning (ML) into MPPT algorithms significantly enhances the reliability and efficiency of PV systems, paving the way for a broader adoption of solar energy technologies in diverse environmental conditions. These findings contribute to advancing renewable energy technology and supporting green energy transition.
Simulation and Analysis of Factors Influencing Climate Adaptability and Strategic Application in Traditional Courtyard Residences in Hot-Summer and Cold-Winter Regions: A Case Study of Xuzhou, China
Authors: Zhang Minghao , Fang Zhezhe , Liu Qian , Zhang Fangyu
Published: October 2024

Residential buildings consume significant amounts of energy worldwide. Traditional courtyard houses have substantial energy-saving potential due to their low energy consumption and high climate adaptability, which has heightened interest in their climate-responsive design. In recent years, extensive research on traditional houses has been conducted in China, indicating significant variations in energy performances among traditional courtyards within hot-summer and cold-winter climate zones. Therefore, this study, based on research conducted on traditional courtyard houses in the Xuzhou area and utilizing Ecotect and Phoenics ecotechnology software for simulation analysis, comparatively examines the factors influencing energy consumption to assess the energy-saving potential of these houses in hot-summer and cold-winter climate zones. Research has indicated that when traditional Xuzhou courtyard houses meet certain criteria—including an orientation of 20° east of south for the main building, width-to-depth ratio of 2:1, roof slope of 35°, courtyard width-to-depth ratio of 1.7:1, use of branch pick windows, building height of 4.5 m, and a specific window-to-wall ratio—they achieve optimal climate adaptability. This study proposes dimensions for traditional residential buildings suited to the Xuzhou climate and explores their practical application, providing targeted optimization and retrofitting suggestions to support sustainable architectural and ecological development.
Coupled Analysis of Risk Factor for Tailing Pond Dam Failure Accident Based on N–K Model and SNA
Authors: Yuan Liwei , Chen Di , Li Sumin , Wang Guolong , Li Yanlin , Li Bin , Chen Minghui
Published: October 2024

The failure of tailings pond dams represents a complex coupled system involving various risk factors, including human, governance, facilities, and environmental aspects. It is crucial to identify key risk factors at the system level to enhance the safety management of tailings ponds. We analyzed 74 cases of tailings pond dam failure accidents, both domestically and internationally, from the perspectives of human, governance, facility, and environment. We employed the 2–4 Model to identify and extract the causes of dam failures, summarizing these into four primary risk factors and 40 secondary risk factors, while constructing a risk coupling mechanism model. The natural killing (N–K) model was implemented to analyze the risk coupling values of primary risk factors and quantify these couplings. The N–K model facilitated an analysis of the risk coupling values of first-level risk factors, while social network analysis (SNA) was employed to visualize the relationships among second-level risk factors and assess the centrality and accessibility of nodes within the risk factor network. The out-degree of the risk nodes was corrected by integrating the N–K model with the SNA, leading to the identification of key risk factors associated with tailings pond dam failures and the formulation of corresponding safety prevention and control strategies. The findings indicate that managing multi-risk factor coupling is an effective approach to mitigating the occurrence of tailings pond dam failure accidents. Notably, unfavorable environmental risk factors significantly contribute to the coupling of human–governance–facility–environmental risks, necessitating targeted management strategies. Furthermore, inadequate safety supervision, weak safety awareness, inadequate receipt and inspection, and irregular operation represent additional key risk factors requiring focused prevention and control efforts.
Linear Arrangement of Euler Sums with Multiple Argument
Authors: Sofo Anthony
Published: October 2024

We investigate the linear arrangement of Euler harmonic sums that may be expressed in closed form in terms of special functions such as the classical Riemann zeta function and the Dirichlet eta function. Particular emphasis is given to Euler harmonic sums with even weight. New examples highlighting the theorems will be presented.
Modified Double Inertial Extragradient-like Approaches for Convex Bilevel Optimization Problems with VIP and CFPP Constraints
Authors: Zeng Yue , Ceng Lu-Chuan , Zheng Liu-Fang , Wang Xie
Published: October 2024

Convex bilevel optimization problems (CBOPs) exhibit a vital impact on the decision-making process under the hierarchical setting when image restoration plays a key role in signal processing and computer vision. In this paper, a modified double inertial extragradient-like approach with a line search procedure is introduced to tackle the CBOP with constraints of the CFPP and VIP, where the CFPP and VIP represent a common fixed point problem and a variational inequality problem, respectively. The strong convergence analysis of the proposed algorithm is discussed under certain mild assumptions, where it constitutes both sections that possess a mutual symmetry structure to a certain extent. As an application, our proposed algorithm is exploited for treating the image restoration problem, i.e., the LASSO problem with the constraints of fractional programming and fixed-point problems. The illustrative instance highlights the specific advantages and potential infect of the our proposed algorithm over the existing algorithms in the literature, particularly in the domain of image restoration.
Multi-Attribute Three-Way Decision Approach Based on Ideal Solutions under Interval-Valued Fuzzy Soft Environment
Authors: Qin Hongwu , Han Yanyan , Ma Xiuqin
Published: October 2024

The interval-valued fuzzy soft set (IVFSS) model, which combines the benefits of the soft set model with the interval-valued fuzzy set (IVFS) model, is a growing and effective mathematical tool for processing hazy data. In detail, this model is characterized by symmetry, which has the lower and upper membership degree. The study of decision-making based on IVFSS has picked up more steam recently. However, existing multi-attribute decision-making (MADM) methods can only sort alternative schemes, but are not able to classify them, which is detrimental to decision-makers’ efficient decision-making. In this paper, we propose a multi-attribute three-way decision-making (MATWDM) algorithm based on ideal solutions for IVFSS. MATWDM is extended to the IVFSS environment by incorporating the concept of the ideal solution, offering a more adaptable and comprehensive approach for addressing uncertain MADM issues. The method not only obtains the ranking results of the alternatives, but also divides them into acceptance domain, rejection domain, and delayed-decision domain, which makes the decision results more reasonable and effective, facilitating decision-makers to make better decisions. We apply the proposed three-way decision algorithm to two practical cases as diverse as mine emergency decision and Homestay selection decision. Additionally, the effectiveness and viability of the suggested method are confirmed by experimental findings.
Insights in Synthetic Bioengineering and Aspects of Creating a New Biotechnology
Authors: Kahar Prihardi
Published: October 2024

Many useful chemicals have been industrially produced using genetic recombination technology in microorganisms and animal cells [...]