bluuebunny/crossref_metadata_2025 huggingface dataset:
Third-Generation Anticancer Photodynamic Therapy Systems Based on Star-like Anionic Polyacrylamide Polymer, Gold Nanoparticles, and Temoporfin Photosensitizer
Authors: Yeshchenko Oleg , Khort Pavlo , Fedotov Oles , Chumachenko Vasyl , Virych Pavlo , Warren Hunter S. , Booth Brian W. , Bliznyuk Valery , Kutsevol Nataliya
Published: May 2024

Photodynamic therapy (PDT) is a non-invasive anticancer treatment that uses special photosensitizer molecules (PS) to generate singlet oxygen and other reactive oxygen species (ROS) in a tissue under excitation with red or infrared light. Though the method has been known for decades, it has become more popular recently with the development of new efficient organic dyes and LED light sources. Here we introduce a ternary nanocomposite: water-soluble star-like polymer/gold nanoparticles (AuNP)/temoporfin PS, which can be considered as a third-generation PDT system. AuNPs were synthesized in situ inside the polymer molecules, and the latter were then loaded with PS molecules in an aqueous solution. The applied method of synthesis allows precise control of the size and architecture of polymer nanoparticles as well as the concentration of the components. Dynamic light scattering confirmed the formation of isolated particles (120 nm diameter) with AuNPs and PS molecules incorporated inside the polymer shell. Absorption and photoluminescence spectroscopies revealed optimal concentrations of the components that can simultaneously reduce the side effects of dark toxicity and enhance singlet oxygen generation to increase cancer cell mortality. Here, we report on the optical properties of the system and detailed mechanisms of the observed enhancement of the phototherapeutic effect. Combinations of organic dyes with gold nanoparticles allow significant enhancement of the effect of ROS generation due to surface plasmonic resonance in the latter, while the application of a biocompatible star-like polymer vehicle with a dextran core and anionic polyacrylamide arms allows better local integration of the components and targeted delivery of the PS molecules to cancer cells. In this study, we demonstrate, as proof of concept, a successful application of the developed PDT system for in vitro treatment of triple-negative breast cancer cells under irradiation with a low-power LED lamp (660 nm). We consider the developed nanocomposite to be a promising PDT system for application to other types of cancer.
Polarization-Addressable Optical Movement of Plasmonic Nanoparticles and Hotspot Spin Vortices
Authors: Balestrieri Sergio , Romano Silvia , Iodice Mario , Coppola Giuseppe , Zito Gianluigi
Published: May 2024

Spin–orbit coupling in nanoscale optical fields leads to the emergence of a nontrivial spin angular momentum component, transverse to the orbital momentum. In this study, we initially investigate how this spin–orbit coupling effect influences the dynamics in gold monomers. We observe that localized surface plasmon resonance induces self-generated transverse spin, affecting the trajectory of the nanoparticles as a function of the incident polarization. Furthermore, we investigate the spin–orbit coupling in gold dimers. The resonant spin momentum distribution is characterized by the unique formation of vortex and anti-vortex spin angular momentum pairs on opposite surfaces of the nanoparticles, also affecting the particle motion. These findings hold promise for various fields, particularly for the precision control in the development of plasmonic thrusters and the development of metasurfaces and other helicity-controlled system aspects. They offer a method for the development of novel systems and applications in the realm of spin optics.
Reply to Palumbo et al. Comment on “Flatscher et al. Impact of Mediterranean Diet on Lipid Composition in the Colaus-PsyColaus Study. Nutrients 2023, 15, 4659”
Authors: Flatscher Mélisande , Garnier Antoine , Marques-Vidal Pedro , Kraege Vanessa
Published: May 2024

We thank the authors of the commentary [...]
Plate Food Waste in Food Services: A Systematic Review and Meta-Analysis
Authors: Guimarães Nathalia Sernizon , Reis Marcela Gomes , Fontes Luciano de Alvarenga , Zandonadi Renata Puppin , Botelho Raquel Braz Assunção , Alturki Hmidan A. , Saraiva Ariana , Raposo António
Published: May 2024

Food waste is considered to be a social, environmental, administrative, and economic problem. Given the large-scale production and distribution of food, food waste in food services has been widely discussed by experts, professors, and scientists in the field. This systematic review aimed to understand which food service has the highest percentage of plate food waste. A systematic review and meta-analysis were conducted until January 2024 in ten electronic databases: MEDLINE, Embase, IBECS, BINACIS, BDENF, CUMED, BDNPAR, ARGMSAL, Cochrane Library, Sustainable Development Goals, and the gray literature. The protocol was previously registered with PROSPERO under the code CRD42024501971. Studies that have assessed plate food waste in food services were included. There were no restrictions on language, publication location, or date. The risk of bias analysis was carried out using the JBI instrument. A proportion meta-analysis was carried out using R software (version 4.2.1). This systematic review with meta-analysis showed that the type of distribution and the food service are the factors that have the greatest impact on the percentage and per capita of plate food waste. In the face of increased waste, interventions should be targeted by type and distribution system, diners, and meals in order to lessen the impact of these factors.
A Study of Vitamin D Status and Its Influencing Factors among Pregnant Women in Szeged, Hungary: A Secondary Outcome of a Case–Control Study
Authors: Polanek Evelin , Sisák Anita , Molnár Regina , Máté Zsuzsanna , Horváth Edina , Németh Gábor , Orvos Hajnalka , Paulik Edit , Szabó Andrea
Published: May 2024

Adequate vitamin D (VD) intake during pregnancy is needed for fetal development and maternal health maintenance. However, while there is no doubt regarding its importance, there is not a unified recommendation regarding adequate intake. The main aim of our study was to measure the VD serum level of studied women, together with its potential influencing factors: demographic (i.e., age, level of education, relationship status and type of residence), conception and pregnancy related factors. Results are based on secondary data analyses of a retrospective case–control study of 100 preterm and 200 term pregnancies, where case and control groups were analyzed together. Data collection was based on a self-administered questionnaire, health documentation, and maternal serum VD laboratory tests. VD intake was evaluated by diet and dietary supplement consumption. According to our results, 68.1% of women took some kind of prenatal vitamin, and only 25.9% of them knew about its VD content. Only 12.1% of included women reached the optimal, 75 nmol/L serum VD level. Higher maternal serum levels were associated with early pregnancy care visits (p = 0.001), assisted reproductive therapy (p = 0.028) and advice from gynecologists (p = 0.049). A correlation was found between VD intake and serum levels (p < 0.001). Despite the compulsory pregnancy counselling in Hungary, health consciousness, VD intake and serum levels remain below the recommendations. The role of healthcare professionals is crucial during pregnancy regarding micronutrients intake and the appropriate supplementation dose.
VEEV TC-83 Triggers Dysregulation of the Tryptophan–Kynurenine Pathway in the Central Nervous System That Correlates with Cognitive Impairment in Tg2576 Mice
Authors: Fongsaran Chanida , Dineley Kelly T. , Paessler Slobodan , Cisneros Irma E.
Published: May 2024

Neurodegenerative diseases are chronic conditions affecting the central nervous system (CNS). Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by the accumulation of amyloid beta in the limbic and cortical brain regions. AD is presumed to result from genetic abnormalities or environmental factors, including viral infections, which may have deleterious, long-term effects. In this study, we demonstrate that the Venezuelan equine encephalitis virus (VEEV) commonly induces neurodegeneration and long-term neurological or cognitive sequelae. Notably, the effects of VEEV infection can persistently influence gene expression in the mouse brain, suggesting a potential link between the observed neurodegenerative outcomes and long-term alterations in gene expression. Additionally, we show that alphavirus encephalitis exacerbates the neuropathological profile of AD through crosstalk between inflammatory and kynurenine pathways, generating a range of metabolites with potent effects. Using a mouse model for β-amyloidosis, Tg2576 mice, we found that cognitive deficits and brain pathology were more severe in Tg2576 mice infected with VEEV TC-83 compared to mock-infected controls. Thus, during immune activation, the kynurenine pathway plays a more active role in the VEEV TC-83-infected cells, leading to increases in the abundance of transcripts related to the kynurenine pathway of tryptophan metabolism. This pathway generates several metabolites with potent effects on neurotransmitter systems as well as on inflammation, as observed in VEEV TC-83-infected animals.
Arylamines QSAR-Based Design and Molecular Dynamics of New Phenylthiophene and Benzimidazole Derivatives with Affinity for the C111, Y268, and H73 Sites of SARS-CoV-2 PLpro Enzyme
Authors: Sabadini Gianfranco , Mellado Marco , Morales César , Mella Jaime
Published: May 2024

A non-structural SARS-CoV-2 protein, PLpro, is involved in post-translational modifications in cells, allowing the evasion of antiviral immune response mechanisms. In this study, potential PLpro inhibitory drugs were designed using QSAR, molecular docking, and molecular dynamics. A combined QSAR equation with physicochemical and Free-Wilson descriptors was formulated. The r2, q2, and r2test values were 0.833, 0.770, and 0.721, respectively. From the equation, it was found that the presence of an aromatic ring and a basic nitrogen atom is crucial for obtaining good antiviral activity. Then, a series of structures for the binding sites of C111, Y268, and H73 of PLpro were created. The best compounds were found to exhibit pIC50 values of 9.124 and docking scoring values of −14 kcal/mol. The stability of the compounds in the cavities was confirmed by molecular dynamics studies. A high number of stable contacts and good interactions over time were exhibited by the aryl-thiophenes Pred14 and Pred15, making them potential antiviral candidates.
An Overview of Hydrothermally Synthesized Titanate Nanotubes: The Factors Affecting Preparation and Their Promising Pharmaceutical Applications
Authors: Saker Ranim , Shammout Hadi , Regdon Géza , Sovány Tamás
Published: May 2024

Recently, titanate nanotubes (TNTs) have been receiving more attention and becoming an attractive candidate for use in several disciplines. With their promising results and outstanding performance, they bring added value to any field using them, such as green chemistry, engineering, and medicine. Their good biocompatibility, high resistance, and special physicochemical properties also provide a wide spectrum of advantages that could be of crucial importance for investment in different platforms, especially medical and pharmaceutical ones. Hydrothermal treatment is one of the most popular methods for TNT preparation because it is a simple, cost-effective, and environmentally friendly water-based procedure. It is also considered as a strong candidate for large-scale production intended for biomedical application because of its high yield and the special properties of the resulting nanotubes, especially their small diameters, which are more appropriate for drug delivery and long circulation. TNTs’ properties highly differ according to the preparation conditions, which would later affect their subsequent application field. The aim of this review is to discuss the factors that could possibly affect their synthesis and determine the transformations that could happen according to the variation of factors. To fulfil this aim, relevant scientific databases (Web of Science, Scopus, PubMed, etc.) were searched using the keywords titanate nanotubes, hydrothermal treatment, synthesis, temperature, time, alkaline medium, post treatment, acid washing, calcination, pharmaceutical applications, drug delivery, etc. The articles discussing TNTs preparation by hydrothermal synthesis were selected, and papers discussing other preparation methods were excluded; then, the results were evaluated based on a careful reading of the selected articles. This investigation and comprehensive review of different parameters could be the answer to several problems concerning establishing a producible method of TNTs production, and it might also help to optimize their characteristics and then extend their application limits to further domains that are not yet totally revealed, especially the pharmaceutical industry and drug delivery.
On-Chip Supercontinuum Generation Pumped by Short Wavelength Fiber Lasers
Authors: Chen Peng , Long Zhe , Cheng Qi , Song Maozhuang , Wang Wei , Liu Ruixue , Zhang Zheng , Xia Kai , Yang Zhen , Qian Lei , Bai Shengchuang , Wang Xunsi , Yang Peilong , Xu Peipeng , Yousef El Sayed , Wang Rongping
Published: May 2024

Supercontinuum (SC) generation pumped by fiber lasers with short wavelengths below 2.0 μm is important since it can provide a compact light source for various applications. We review the progress of SC generation in various materials regarding the formation of the waveguides and point out the existing issues in the current investigations and possible solutions in the future.
Forage Plant Ecophysiology under Different Stress Conditions
Authors: Grimoldi Agustín A. , Di Bella Carla E.
Published: May 2024

Forage production often occurs in fragile environments with low fertility and various limitations [...]
Anti-Melanogenic Effects of Cnidium monnieri Extract via p38 Signaling-Mediated Proteasomal Degradation of Tyrosinase
Authors: Choi Soon Ho , Kim Hyunggun , Hwang-Bo Jeon , Kim Kyoung Mi , Kwon Jeong Eun , Lee Sung Ryul , Hwang Sun Ha , Kang Se Chan , Lee Yeong-Geun
Published: May 2024

Cnidium monnieri fructus is widely used in traditional Oriental medicine for treating female genital disorders, male impotence, frigidity, and skin-related conditions in East Asia. However, the role of C. monnieri fructus extract (CMFE) in melanin synthesis is not well elucidated. This study aimed to investigate the anti-melanogenesis effect and mechanism of action of CMFE in α-MSH-stimulated B16F10 cells. Intracellular melanin content and tyrosinase activity were measured in α-MSH-stimulated B16F10 cells treated with various concentrations of CMFE (0.5–5 μg/mL). mRNA and protein levels of tyrosinase and MITF were evaluated using qRT-PCR and ting. CMFE’s effect on the proteasomal degradation of tyrosinase was confirmed using a proteasomal degradation inhibitor, MG132. CMFE treatment activated p38, a protein associated with proteasomal degradation. Treatment with CMFE at up to 5 μg/mL showed no significant cytotoxicity. CMFE significantly reduced α-MSH-stimulated melanin production (43.29 ± 3.55% decrease, p < 0.05) and cellular tyrosinase activity (31.14 ± 3.15% decrease, p < 0.05). Although mRNA levels of MITF and tyrosinase increased, CMFE suppressed tyrosinase protein levels. The suppressive effect of CMFE on tyrosinase protein was blocked by MG132. CMFE inhibited melanogenesis by promoting the proteasome degradation of tyrosinase through p38 activation. These findings suggest that CMFE has the potential to be a natural whitening agent for inhibiting melanogenesis.
Effects of Organic Fertilizer on Photosynthesis, Yield, and Quality of Pakchoi under Different Irrigation Conditions
Authors: Lin Shudong , Wei Kai , Wang Quanjiu , Sun Yan , Deng Mingjiang , Tao Wanghai
Published: May 2024

Water scarcity and the overuse of chemical fertilizers present significant challenges to modern agriculture, critically affecting crop photosynthesis, yield, quality, and productivity sustainability. This research assesses the impact of organic fertilizer on the photosynthetic attributes, yield, and quality of pakchoi under varying irrigation water conditions, including fresh water and brackish water. Findings reveal that the modified rectangular hyperbolic model most accurately captures the photosynthetic reaction to organic fertilization, outperforming other evaluated models. The maximum net photosynthesis rate (Pnmax), yield, soluble sugar (SS), and soluble protein content (SP) all exhibited a downward-opening quadratic parabolic trend with increasing amounts of organic fertilizer application. Specifically, under fresh-water irrigation, the optimal Pnmax, yield, SS, and SP were obtained at organic fertilizer rates of 65.77, 74.63, 45.33, and 40.79 kg/ha, respectively, achieving peak values of 20.71 µmol/(m2·s), 50,832 kg/ha, 35.63 g/kg, and 6.25 g/kg. This investigation provides a foundational basis for further research into the intricate relationship between water salinity stress and nutrient management, with the goal of crafting more sophisticated and sustainable farming methodologies. The insights gained could significantly influence organic fertilizer practices, promoting not only higher yields but also superior quality in agricultural outputs.
Identification of Novel Loci Precisely Modulating Pre-Harvest Sprouting Resistance and Red Color Components of the Seed Coat in T. aestivum L.
Authors: Afonnikova Svetlana D. , Kiseleva Antonina A. , Fedyaeva Anna V. , Komyshev Evgenii G. , Koval Vasily S. , Afonnikov Dmitry A. , Salina Elena A.
Published: May 2024

The association between pre-harvest sprouting (PHS) and seed coat color has long been recognized. Red-grained wheats generally exhibit greater PHS resistance compared to white-grained wheat, although variability in PHS resistance exists within red-grained varieties. Here, we conducted a genome-wide association study on a panel consisting of red-grained wheat varieties, aimed at uncovering genes that modulate PHS resistance and red color components of seed coat using digital image processing. Twelve loci associated with PHS traits were identified, nine of which were described for the first time. Genetic loci marked by SNPs AX-95172164 (chromosome 1B) and AX-158544327 (chromosome 7D) explained approximately 25% of germination index variance, highlighting their value for breeding PHS-resistant varieties. The most promising candidate gene for PHS resistance was TraesCS6B02G147900, encoding a protein involved in aleurone layer morphogenesis. Twenty-six SNPs were significantly associated with grain color, independently of the known Tamyb10 gene. Most of them were related to multiple color characteristics. Prioritization of genes within the revealed loci identified TraesCS1D03G0758600 and TraesCS7B03G1296800, involved in the regulation of pigment biosynthesis and in controlling pigment accumulation. In conclusion, our study identifies new loci associated with grain color and germination index, providing insights into the genetic mechanisms underlying these traits.
Response of Functional Traits of Aquatic Plants to Water Depth Changes under Short-Term Eutrophic Clear-Water Conditions: A Mesocosm Study
Authors: Liu Yang , Ndirangu Leah , Li Wei , Pan Junfeng , Cao Yu , Jeppesen Erik
Published: May 2024

Aquatic plants play a key role in the structuring and functioning of shallow lake ecosystems. However, eutrophication often triggers shifts in plant communities and species diversity, especially in the early stages when the water is still clear. Additionally, water depth is an important factor regulating aquatic plant communities. We conducted a 50-day mesocosm study to investigate how water depth (50 cm and 100 cm) affected the functional traits (vertical expansion versus horizontal colonisation) of 20 aquatic plants under eutrophic clear-water conditions. Among the selected species, the submerged plants Hydrocotyle vulgaris and Limnophila indica exhibited higher plant height or biomass in deeper water, while the emergent plants Myriophyllum aquaticum showed the opposite trend. Additionally, Ludwigia peploides subsp. stipulacea exhibited better vertical growth than the remaining species, and the submerged species Vallisneria denseserrulata had better horizontal colonisation. There was a positive correlation between plant height and rhizome length, indicating the absence of a trade-off between vertical growth and horizontal expansion. Our findings suggest an overall resilience of aquatic plants to varying water depths within our study range and highlight the importance of analysing functional traits when selecting appropriate species in freshwater ecosystem restoration, particularly in the face of climate change-induced water depth fluctuations.
A New Strategy for the Treatment of Old Corrugated Container Pulping Wastewater by the Ozone-Catalyzed Polyurethane Sponge Biodegradation Process
Authors: Cai Yuxuan , Huang Shaozhe , Xiong Jianhua
Published: May 2024

Old Corrugated Container (OCC) pulping wastewater has a complex organic composition and high levels of biotoxicity. The presence of dissolved and colloidal substances (DCSs) is a major limiting factor for pulp and paper companies to achieve closed-water recycling. In order to solve this problem, the coupled ozone-catalyzed oxidation and biodegradation (OCB) method was used to treat OCC pulping wastewater in this study. A polyurethane sponge was used as the basic skeleton, loaded with nano TiO2 and microorganisms, respectively, and then put into a reactor. After an 8-min ozone-catalyzed oxidation reaction, a 10-h biological reaction was carried out. The process was effective in removing organic pollutants such as COD and BOD5 from OCC paper whitewater. The removal rates of COD and BOD5 were 81.5% and 85.1%, respectively. By using the polyurethane sponge to construct a microenvironment suitable for microbial growth and metabolism, this study successfully applied and optimized engineered bacteria—white rut fungi (WRF)—in the system to achieve practical degradation of OCC pulping wastewater. Meanwhile, the biocompatibility of different microbial communities on the polyurethane sponge was analyzed by examining the degradation performance of OCC pulping wastewater. The structure of microbial communities loaded on the polyurethane sponge was analyzed to understand the degradation mechanism and microbial reaction behavior. White-rot fungi (Phanerochaete) contributed more to the degradation of OCC wastewater, and new strains adapted to OCC wastewater degradation were generated.
Synthesis of New Ruthenium Complexes and Their Exploratory Study as Polymer Hybrid Composites in Organic Electronics
Authors: Ballinas-Indilí Ricardo , Sánchez Vergara María Elena , Rosales-Amezcua Saulo C. , Hernández Méndez Joaquín André , López-Mayorga Byron , Miranda-Ruvalcaba René , Álvarez-Toledano Cecilio
Published: May 2024

Polymeric hybrid films, for their application in organic electronics, were produced from new ruthenium indanones in poly(methyl methacrylate) (PMMA) by the drop-casting procedure. Initially, the synthesis and structural characterization of the ruthenium complexes were performed, and subsequently, their properties as a potential semiconductor material were explored. Hence hybrid films in ruthenium complexes were deposited using PMMA as a polymeric matrix. The hybrid films were characterized by infrared spectrophotometry and atomic force microscopy. The obtained results confirmed that the presence of the ruthenium complexes enhanced the mechanical properties in addition to increasing the transmittance, favoring the determination of their optical parameters. Both hybrid films exhibited a maximum stress around 10.5 MPa and a Knoop hardness between 2.1 and 18.4. Regarding the optical parameters, the maximum transparency was obtained at wavelengths greater than 590 nm, the optical band gap was in the range of 1.73–2.24 eV, while the Tauc band gap was in the range of 1.68–2.17 eV, and the Urbach energy was between 0.29 and 0.50 eV. Consequently, the above comments are indicative of an adequate semiconductor behavior; hence, the target polymeric hybrid films must be welcomed as convenient candidates as active layers or transparent electrodes in organic electronics.
Digital Light Processing Route for 3D Printing of Acrylate-Modified PLA/Lignin Blends: Microstructure and Mechanical Performance
Authors: Guessasma Sofiane , Stephant Nicolas , Durand Sylvie , Belhabib Sofiane
Published: May 2024

In this study, digital light processing (DLP) was utilized to generate 3D-printed blends composed of photosensitive acrylate-modified polylactic acid (PLA) resin mixed with varying weight ratios of lignin extracted from softwood, typically ranging from 5 wt% to 30 wt%. The microstructure of these 3D-printed blends was examined through X-ray microtomography. Additionally, the tensile mechanical properties of all blends were assessed in relation to the weight ratio and post-curing treatment. The results suggest that post-curing significantly influences the tensile properties of the 3D-printed composites, especially in modulating the brittleness of the prints. Furthermore, an optimal weight ratio was identified to be around 5 wt%, beyond which UV light photopolymerization experiences compromises. These findings regarding acrylate-modified PLA/lignin blends offer a cost-effective alternative for producing 3D-printed bio-sourced components, maintaining technical performance in reasonable-cost, low-temperature 3D printing, and with a low environmental footprint.
Well Selection for CO2 Huff-n-Puff in Unconventional Oil Reservoirs Based on Improved Fuzzy Method
Authors: Liu Yunfeng , Zhu Yangwen , Liao Haiying , Yu Hongmin , Fang Xin , Zhang Yao
Published: May 2024

The implementation of CO2 huff-n-puff in unconventional oil reservoirs represents a green development technology that integrates oil recovery and carbon storage, emphasizing both efficiency and environmental protection. A rational well selection method is crucial for the success of CO2 huff-n-puff development. This paper initially identifies eight parameters that influence the effectiveness of CO2 huff-n-puff development and conducts a systematic analysis of the impact of each factor on development effectiveness. A set of factors for well selection decisions is established with seven successful CO2 huff-n-puff cases. Subsequently, the influencing factors are classified into positive, inverse, and moderate indicators. By using an exponential formulation, a method for calculating membership degrees is calculated to accurately represent the nonlinearity of each parameter’s influence on development, resulting in a dimensionless fuzzy matrix. Furthermore, with the oil exchange ratio serving as a pivotal parameter reflecting development effectiveness, recalibration of weighting factors is performed in conjunction with the dimensionless fuzzy matrix. The hierarchical order of weighting factors, from primary to secondary, is as follows: porosity, reservoir temperature, water saturation, formation pressure, reservoir thickness, crude oil density, crude oil viscosity, and permeability. The comprehensive decision factor and oil exchange ratio exhibit a positive correlation, affirming the reliability of the weighting factors. Finally, utilizing parameters of the Ordos Basin as a case study, the comprehensive decision factor is calculated, with a value of 0.617, and the oil exchange ratio is predicted as 0.354 t/t, which falls between the Chattanooga and Eagle Ford reservoirs. This approach, which incorporates exponential membership degrees and recalibrated weighting factors derived from actual cases, breaks the limitations of linear membership calculation methods and human factors in expert scoring methods utilized in existing decision-making methodologies. It furnishes oilfield decision-makers with a swifter and more precise well selection method.
A Deep Learning Classification Scheme for PolSAR Image Based on Polarimetric Features
Authors: Zhang Shuaiying , Cui Lizhen , Dong Zhen , An Wentao
Published: May 2024

Polarimetric features extracted from polarimetric synthetic aperture radar (PolSAR) images contain abundant back-scattering information about objects. Utilizing this information for PolSAR image classification can improve accuracy and enhance object monitoring. In this paper, a deep learning classification method based on polarimetric channel power features for PolSAR is proposed. The distinctive characteristic of this method is that the polarimetric features input into the deep learning network are the power values of polarimetric channels and contain complete polarimetric information. The other two input data schemes are designed to compare the proposed method. The neural network can utilize the extracted polarimetric features to classify images, and the classification accuracy analysis is employed to compare the strengths and weaknesses of the power-based scheme. It is worth mentioning that the polarized characteristics of the data input scheme mentioned in this article have been derived through rigorous mathematical deduction, and each polarimetric feature has a clear physical meaning. By testing different data input schemes on the Gaofen-3 (GF-3) PolSAR image, the experimental results show that the method proposed in this article outperforms existing methods and can improve the accuracy of classification to a certain extent, validating the effectiveness of this method in large-scale area classification.
Radar-Based Precipitation Nowcasting Based on Improved U-Net Model
Authors: Tan Youwei , Zhang Ting , Li Leijing , Li Jianzhu
Published: May 2024

Rainfall nowcasting is the basis of extreme rainfall monitoring, flood prevention, and water resource scheduling. Based on the structural features of the U-Net model, we proposed the Double Recurrent Residual Attention Gates U-Net (DR2A-UNet) deep-learning model to carry out radar echo extrapolation. The model was trained with mean square error (MSE) and balanced mean square error (BMSE) as loss functions, respectively. The dynamic Z-R relationship was applied for quantitative rainfall estimation. The reference U-Net model, U-Net++, and the ConvLSTM were used as control experiments to carry out radar echo extrapolation. The results showed that the model trained by BMSE had better extrapolation. For 1 h lead time, the rainfall nowcasted by each model could reflect the actual rainfall process. DR2A-UNet performed significantly better than other models for intense rainfall, with a higher extrapolation accuracy for echo intensity and variability processes. At the 2 h lead time, the nowcast accuracy of each model was significantly reduced, but the echo extrapolation and rainfall nowcasting of DR2A-UNet were better.
Near-Real Prediction of Earthquake-Triggered Landslides on the Southeastern Margin of the Tibetan Plateau
Authors: Zhang Aomei , Wang Xianmin , Xu Chong , Yang Qiyuan , Guo Haixiang , Li Dongdong
Published: May 2024

Earthquake-triggered landslides (ETLs) feature large quantities, extensive distributions, and enormous losses to human lives and critical infrastructures. Near-real spatial prediction of ETLs can rapidly predict the locations of coseismic landslides just after a violent earthquake and is a vital technical support for emergency response. However, near-real prediction of ETLs has always been a great challenge with relatively low accuracy. This work proposes an ensemble prediction model of EnPr by integrating machine learning tree models and a deep learning convolutional neural network. EnPr exhibits relatively strong prediction and generalization performance and achieves relatively accurate prediction of ETLs. Six great seismic events occurring from 2008 to 2022 on the southeastern margin of the Tibetan Plateau are selected to conduct ETL prediction. In a chronological order, the 2008 Ms 8.0 Wenchuan, 2010 Ms 7.1 Yushu, 2013 Ms 7.0 Lushan, and 2014 Ms 6.5 Ludian earthquakes are employed for model training and learning. The 2017 Ms 7.0 Jiuzhaigou and 2022 Ms 6.1 Lushan earthquakes are adopted for ETL prediction. The prediction accuracy merits of ACC and AUC attain 91.28% and 0.85, respectively, for the Jiuzhaigou earthquake. The values of ACC and AUC achieve 93.78% and 0.88, respectively, for the Lushan earthquake. The proposed EnPr algorithm outperforms the algorithms of XGBoost, random forest (RF), extremely randomized trees (ET), convolutional neural network (CNN), and Transformer. Moreover, this work reveals that seismic intensity, high and steep relief, pre-seismic fault tectonics, and pre-earthquake road construction have played significant roles in coseismic landslide occurrence and distribution. The EnPr model uses globally accessible open datasets and can therefore be used worldwide for new large seismic events in the future.
Assessing Lidar Ratio Impact on CALIPSO Retrievals Utilized for the Estimation of Aerosol SW Radiative Effects across North Africa, the Middle East, and Europe
Authors: Moustaka Anna , Korras-Carraca Marios-Bruno , Papachristopoulou Kyriakoula , Stamatis Michael , Fountoulakis Ilias , Kazadzis Stelios , Proestakis Emmanouil , Amiridis Vassilis , Tourpali Kleareti , Georgiou Thanasis , Solomos Stavros , Spyrou Christos , Zerefos Christos , Gkikas Antonis
Published: May 2024

North Africa, the Middle East, and Europe (NAMEE domain) host a variety of suspended particles characterized by different optical and microphysical properties. In the current study, we investigate the importance of the lidar ratio (LR) on Cloud-Aerosol Lidar with Orthogonal Polarization–Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIOP-CALIPSO) aerosol retrievals towards assessing aerosols’ impact on the Earth-atmosphere radiation budget. A holistic approach has been adopted involving collocated Aerosol Robotic Network (AERONET) observations, Radiative Transfer Model (RTM) simulations, as well as reference radiation measurements acquired using spaceborne (Clouds and the Earth’s Radiant Energy System-CERES) and ground-based (Baseline Surface Radiation Network-BSRN) instruments. We are assessing the clear-sky shortwave (SW) direct radiative effects (DREs) on 550 atmospheric scenes, identified within the 2007–2020 period, in which the primary tropospheric aerosol species (dust, marine, polluted continental/smoke, elevated smoke, and clean continental) are probed using CALIPSO. RTM runs have been performed relying on CALIOP retrievals in which the default and the DeLiAn (Depolarization ratio, Lidar ratio, and Ångström exponent)-based aerosol-speciated LRs are considered. The simulated fields from both configurations are compared against those produced when AERONET AODs are applied. Overall, the DeLiAn LRs leads to better results mainly when mineral particles are either solely recorded or coexist with other aerosol species (e.g., sea-salt). In quantitative terms, the errors in DREs are reduced by ~26–27% at the surface (from 5.3 to 3.9 W/m2) and within the atmosphere (from −3.3 to −2.4 W/m2). The improvements become more significant (reaching up to ~35%) for moderate-to-high aerosol loads (AOD ≥ 0.2).
Research on Bearing Surface Scratch Detection Based on Improved YOLOV5
Authors: Jia Huakun , Zhou Huimin , Chen Zhehao , Gao Rongke , Lu Yang , Yu Liandong
Published: May 2024

Bearings are crucial components of machinery and equipment, and it is essential to inspect them thoroughly to ensure a high pass rate. Currently, bearing scratch detection is primarily carried out manually, which cannot meet industrial demands. This study presents research on the detection of bearing surface scratches. An improved YOLOV5 network, named YOLOV5-CDG, is proposed for detecting bearing surface defects using scratch images as targets. The YOLOV5-CDG model is based on the YOLOV5 network model with the addition of a Coordinate Attention (CA) mechanism module, fusion of Deformable Convolutional Networks (DCNs), and a combination with the GhostNet lightweight network. To achieve bearing surface scratch detection, a machine vision-based bearing surface scratch sensor system is established, and a self-made bearing surface scratch dataset is produced as the basis. The scratch detection final Average Precision (AP) value is 97%, which is 3.4% higher than that of YOLOV5. Additionally, the model has an accuracy of 99.46% for detecting defective and qualified products. The average detection time per image is 263.4 ms on the CPU device and 12.2 ms on the GPU device, demonstrating excellent performance in terms of both speed and accuracy. Furthermore, this study analyzes and compares the detection results of various models, demonstrating that the proposed method satisfies the requirements for detecting scratches on bearing surfaces in industrial settings.
PV Panel Model Parameter Estimation by Using Particle Swarm Optimization and Artificial Neural Network
Authors: Lo Wai-Lun , Chung Henry Shu-Hung , Hsung Richard Tai-Chiu , Fu Hong , Shen Tak-Wai
Published: May 2024

Photovoltaic (PV) panels are one of the popular green energy resources and PV panel parameter estimations are one of the popular research topics in PV panel technology. The PV panel parameters could be used for PV panel health monitoring and fault diagnosis. Recently, a PV panel parameters estimation method based in neural network and numerical current predictor methods has been developed. However, in order to further improve the estimation accuracies, a new approach of PV panel parameter estimation is proposed in this paper. The output current and voltage dynamic responses of a PV panel are measured, and the time series of the I–V vectors will be used as input to an artificial neural network (ANN)-based PV model parameter range classifier (MPRC). The MPRC is trained using an I–V dataset with large variations in PV model parameters. The results of MPRC are used to preset the initial particles’ population for a particle swarm optimization (PSO) algorithm. The PSO algorithm is used to estimate the PV panel parameters and the results could be used for PV panel health monitoring and the derivation of maximum power point tracking (MMPT). Simulations results based on an experimental I–V dataset and an I–V dataset generated by simulation show that the proposed algorithms can achieve up to 3.5% accuracy and the speed of convergence was significantly improved as compared to a purely PSO approach.
A Portable Readout System for Biomarker Detection with Aptamer-Modified CMOS ISFET Array
Authors: Ryazantsev Dmitriy , Shustinskiy Mark , Sheshil Andrey , Titov Alexey , Grudtsov Vitaliy , Vechorko Valerii , Kitiashvili Irakli , Puchnin Kirill , Kuznetsov Alexander , Komarova Natalia
Published: May 2024

Biosensors based on ion-sensitive field effect transistors (ISFETs) combined with aptamers offer a promising and convenient solution for point-of-care testing applications due to the ability for fast and label-free detection of a wide range of biomarkers. Mobile and easy-to-use readout devices for the ISFET aptasensors would contribute to further development of the field. In this paper, the development of a portable PC-controlled device for detecting aptamer-target interactions using ISFETs is described. The device assembly allows selective modification of individual ISFETs with different oligonucleotides. Ta2O5-gated ISFET structures were optimized to minimize trapped charge and capacitive attenuation. Integrated CMOS readout circuits with linear transfer function were used to minimize the distortion of the original ISFET signal. An external analog signal digitizer with constant voltage and superimposed high-frequency sine wave reference voltage capabilities was designed to increase sensitivity when reading ISFET signals. The device performance was demonstrated with the aptamer-driven detection of troponin I in both reference voltage setting modes. The sine wave reference voltage measurement method reduced the level of drift over time and enabled a lowering of the minimum detectable analyte concentration. In this mode (constant voltage 2.4 V and 10 kHz 0.1Vp-p), the device allowed the detection of troponin I with a limit of detection of 3.27 ng/mL. Discrimination of acute myocardial infarction was demonstrated with the developed device. The ISFET device provides a platform for the multiplexed detection of different biomarkers in point-of-care testing.
Optical Flow-Based Obstacle Detection for Mid-Air Collision Avoidance
Authors: Vera-Yanez Daniel , Pereira António , Rodrigues Nuno , Molina José Pascual , García Arturo S. , Fernández-Caballero Antonio
Published: May 2024

The sky may seem big enough for two flying vehicles to collide, but the facts show that mid-air collisions still occur occasionally and are a significant concern. Pilots learn manual tactics to avoid collisions, such as see-and-avoid, but these rules have limitations. Automated solutions have reduced collisions, but these technologies are not mandatory in all countries or airspaces, and they are expensive. These problems have prompted researchers to continue the search for low-cost solutions. One attractive solution is to use computer vision to detect obstacles in the air due to its reduced cost and weight. A well-trained deep learning solution is appealing because object detection is fast in most cases, but it relies entirely on the training data set. The algorithm chosen for this study is optical flow. The optical flow vectors can help us to separate the motion caused by camera motion from the motion caused by incoming objects without relying on training data. This paper describes the development of an optical flow-based airborne obstacle detection algorithm to avoid mid-air collisions. The approach uses the visual information from a monocular camera and detects the obstacles using morphological filters, optical flow, focus of expansion, and a data clustering algorithm. The proposal was evaluated using realistic vision data obtained with a self-developed simulator. The simulator provides different environments, trajectories, and altitudes of flying objects. The results showed that the optical flow-based algorithm detected all incoming obstacles along their trajectories in the experiments. The results showed an F-score greater than 75% and a good balance between precision and recall.
How Power Affects Moral Judgments: The Presence of Harm to Life Modifies the Association between Power and Moral Choices
Authors: Zheng Mufan , Guinote Ana , Luo Wei
Published: May 2024

Lammers and Stapel reported that high power increases deontological (rule-based) moral thinking, and low power increases utilitarian (outcome-based) moral thinking. However, the dilemmas were mild and did not involve harm to life. Here, we examined whether the presence or absence of harm to life affects the moral decisions of powerholders. To help establish the replicability and validity of the effects of power on moral judgments in the absence of harm to life, we first performed an exact replication of a study conducted by Lammers and Stapel, and this experiment was followed up by a similar study in an organizational context in China (Studies 1 and 2). Studies 3 and 4 investigated whether power and the presence/absence of harm to life interacted with preferences for deontological versus utilitarian moral judgments. Power consistently triggered deontological thinking. However, power differences in moral reasoning only emerged when there was no harm to life. Harm prompted deontological responses among control and powerless individuals, which nullified differences across the power conditions. The findings demarcate the generalizability of the association between power and a moral thinking style.
Changes in Forest Cover of Municipalities in Poland in 1990–2018
Authors: Kociuba Dagmara , Gawrysiak Leszek , Kociuba Waldemar
Published: May 2024

The study is part of the trend of searching for research methods to demonstrate changes in forest cover at the level of basic units of public administration with greater precision and accuracy. The purpose of the article is to present, for the first time, changes in forest cover of municipalities in Poland from 1990 to 2018 using CORINE Land Cover (CLC) data. The contributions of this study are threefold. Firstly, using GIS and CLC data (3.1. Forests), multivariate analyses of forest cover changes were carried out for 2481 municipalities for the CLC data collection years (1990, 2000, 2006, 2012, 2018), which showed the temporal and spatial dynamics of changes, with a predominance of deforestation in 1990–2000 and 2012–2018, and afforestation in 2000–2006 and 2006–2012. Secondly, the formal, legal and financial rationale for these changes was indicated. The increase in afforestation was a result of financial incentives under the National Program for Increasing Forest Cover and the EU’s Common Agricultural Policy (under Rural Development Programs—RDPs). Deforestation was related to a decrease in the supply of land for afforestation, the competitiveness of subsidies implemented under RDPs, and statutory liberalization of logging. Thirdly, the main discrepancies between the data obtained from CLC and from the public data collected by Statistics Poland (GUS) and the State Forests were indicated, which ranged from −32 kha to +310 kha, corresponding to percentage differences of 2.3% and 1.8%, respectively. This was mainly influenced by the differences in the complexity and updating of data collected for state and private forests, as well as delays in introducing changes to the land register by the public administration. This work contributes significantly to our understanding of the dynamics of forest cover changes in relation to the actual degree of forestation and deforestation, and the determinants of forest transformation in Polish municipalities, as well as demonstrating the new applicability of CLC data and their limitations related mainly to the generalization of forest cover area.
Perceptions and Attitudes of SMEs and MNCs Managers Regarding CSR Implementation: Insights from Companies Operating in the Retail Sector
Authors: Modreanu Andra , Toma Sorin-George , Burcea Marin , Grădinaru Cătălin
Published: May 2024

To establish a responsible business environment, it is important to analyze the way corporate social responsibility (CSR) is implemented within the business world. In this respect, managers play a crucial role in designing and applying the CSR concept and practices. Therefore, this paper aims to identify and analyze the perceptions and attitudes of medium-sized enterprises (SMEs) and multinational companies (MNCs) managers in the Romanian retail sector related to CSR implementation. A documentary research approach and a qualitative research methodology through the use of four focus groups were utilized to fulfill the above-mentioned purpose. Additionally, the authors employed content analysis and Nvivo 14 software to process the collected data. The findings indicate that the size of firms represents a key element of managers’ perceptions and attitudes regarding CSR. Particularly, SME managers have a lower level of familiarity with the concept and the potential advantages for business compared to MNC managers. Furthermore, when it comes to CSR practices, MNCs use a comprehensive approach to meeting the demands of their stakeholders, whereas SMEs prioritize the requirements of their employees. One major obstacle in implementing the CSR concept continues to be the high expenses involved in the businesses.