bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of Glucose on the Interaction of Bisphenol A and Bovine Hemoglobin Characterized by Spectroscopic and Molecular Docking Techniques
Authors: Li Xianheng , Li Huan , Lai Keqiang , Miao Junjian
Published: September 2023

The interaction mechanism of hemoglobin (Hb) with bisphenol A (BPA) in diabetic patients and the difference with healthy people have been studied using spectroscopic and molecular docking techniques at several glucose (Glc) concentration, with bovine hemoglobin (BHb) instead of Hb. It is found that Glc can interact with BHb–BPA and affect its molecular structure, resulting in an altered microenvironment for tyrosine (Tyr) and tryptophan (Trp) in BHb–BPA. It is also found that Glc can bind to BHb alone, and its effect on the molecular structure of BHb is weaker than that on the structure of BHb in BHb–BPA complex. The results of circular dichroism (CD) and Fourier transform infrared spectroscopy (FTIR) indicate that Glc causes an increase in the content of the α-helix and a decrease in that of the β-sheet of BHb–BPA by 1.5–1.9% and 3.1%, respectively. The results of molecular docking show that Glc binds to BHb–BPA through hydrogen and hydrophobic bonds, and the position of binding differs from that of Glc binding to BHb alone, which may be attributed to the fact that BPA affects the protein molecular structure of BHb and has an effect on the binding of BHb to Glc. This study provides some theoretical basis for the mechanism of BPA toxicity in vivo for people with different blood glucose levels.
A Neutral Polysaccharide from Spores of Ophiocordyceps gracilis Regulates Oxidative Stress via NRF2/FNIP1 Pathway
Authors: Wang Yue , Wei Shixiang , Lian Hui , Tong Lingling , Yang Linhui , Ren Bo , Guo Dongsheng , Huang He
Published: September 2023

Ophiocordyceps gracilis (O. gracilis) is a parasitic fungus used in traditional Chinese medicine and functional foods. In this study, a neutral heteropolysaccharide (GSP-1a) was isolated from spores of O. gracilis, and its structure and antioxidant capacities were investigated. GSP-1a was found to have a molecular weight of 72.8 kDa and primarily consisted of mannose (42.28%), galactose (35.7%), and glucose (22.02%). The backbone of GSP-1a was composed of various sugar residues, including →6)-α-D-Manp-(1→, →2,6)-α-D-Manp-(1→, →2,4,6)-α-D-Manp-(1→, →6)-α-D-Glcp-(1→, and →3,6)-α-D-Glcp-(1→, with some branches consisting of →6)-α-D-Manp-(1→ and α-D-Gal-(1→. In vitro, antioxidant activity assays demonstrated that GSP-1a exhibited scavenging effects on hydroxyl radical (•OH), 2,2′-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid radical cation (ABTS•+), and 2,2-diphenyl-1-picrylhydrazyl radical (DPPH•). Moreover, GSP-1a was found to alleviate H2O2-induced oxidative stress in HepG2 cells by reducing the levels of reactive oxygen species (ROS) and malondialdehyde (MDA), while enhancing the activities of superoxide dismutase (SOD). Furthermore, GSP-1a upregulated the mRNA expression of antioxidant enzymes such as Ho-1, Gclm, and Nqo1, and regulated the NRF2/KEAP1 and FNIP1/FEM1B pathways. The findings elucidated the structural types of GSP-1a and provided a reliable theoretical basis for its usage as a natural antioxidant in functional foods or medicine.
Influence of Race and High Laminar Shear Stress on TNFR1 Signaling in Endothelial Cells
Authors: Aldokhayyil Maitha , Gomez Dulce H. , Cook Marc D. , Kavazis Andreas N. , Roberts Michael D. , Geetha Thangiah , Brown Michael D.
Published: September 2023

Tumor necrosis factor (TNF) binding to endothelial TNF receptor-I (TNFR-I) facilitates monocyte recruitment and chronic inflammation, leading to the development of atherosclerosis. In vitro data show a heightened inflammatory response and atherogenic potential in endothelial cells (ECs) from African American (AA) donors. High laminar shear stress (HSS) can mitigate some aspects of racial differences in endothelial function at the cellular level. We examined possible racial differences in TNF-induced monocyte adhesion and TNFR1 signaling complex expression/activity, along with the effects of HSS. Tohoku Hospital Pediatrics-1 (THP-1) monocytes were used in a co-culture system with human umbilical vein ECs (HUVECs) from Caucasian American (CA) and AA donors to examine racial differences in monocyte adhesion. An in vitro exercise mimetic model was applied to investigate the potential modulatory effect of HSS. THP-1 adherence to ECs and TNF-induced nuclear factor kappa B (NF-κB) DNA binding were elevated in AA ECs compared to CA ECs, but not significantly. We report no significant racial differences in the expression of the TNFR-I signaling complex. Application of HSS significantly increased the expression and shedding of TNFR-I and the expression of TRAF3, and decreased the expression of TRAF5 in both groups. Our data does not support TNF-induced NF-κB activation as a potential mediator of racial disparity in this model. Other pathways and associated factors activated by the TNFR1 signaling complex are recommended targets for future research.
Platelets in Renal Disease
Authors: Gomchok Drolma , Ge Ri-Li , Wuren Tana
Published: September 2023

Kidney disease is a major global health concern, affecting millions of people. Nephrologists have shown interest in platelets because of coagulation disorders caused by renal diseases. With a better understanding of platelets, it has been found that these anucleate and abundant blood cells not only play a role in hemostasis, but also have important functions in inflammation and immunity. Platelets are not only affected by kidney disease, but may also contribute to kidney disease progression by mediating inflammation and immune effects. This review summarizes the current evidence regarding platelet abnormalities in renal disease, and the multiple effects of platelets on kidney disease progression. The relationship between platelets and kidney disease is still being explored, and further research can provide mechanistic insights into the relationship between thrombosis, bleeding, and inflammation related to kidney disease, and elucidate targeted therapies for patients with kidney disease.
The Effect of Polymer Blends on the In Vitro Release/Degradation and Pharmacokinetics of Moxidectin-Loaded PLGA Microspheres
Authors: Zhang Hongjuan , Yang Zhen , Wu Di , Hao Baocheng , Liu Yu , Wang Xuehong , Pu Wanxia , Yi Yunpeng , Shang Ruofeng , Wang Shengyi
Published: September 2023

To investigate the effect of polymer blends on the in vitro release/degradation and pharmacokinetics of moxidectin-loaded PLGA microspheres (MOX-MS), four formulations (F1, F2, F3 and F4) were prepared using the O/W emulsion solvent evaporation method by blending high (75/25, 75 kDa) and low (50/50, 23 kDa) molecular weight PLGA with different ratios. The addition of low-molecular-weight PLGA did not change the release mechanism of microspheres, but sped up the drug release of microspheres and drastically shortened the lag phase. The in vitro degradation results show that the release of microspheres consisted of a combination of pore diffusion and erosion, and especially autocatalysis played an important role in this process. Furthermore, an accelerated release method was also developed to reduce the period for drug release testing within one month. The pharmacokinetic results demonstrated that MOX-MS could be released for at least 60 days with only a slight blood drug concentration fluctuation. In particular, F3 displayed the highest AUC and plasma concentration (AUC0–t = 596.53 ng/mL·d, Cave (day 30-day 60) = 8.84 ng/mL), making it the optimal formulation. Overall, these results indicate that using polymer blends could easily adjust hydrophobic drug release from microspheres and notably reduce the lag phase of microspheres.
Functional Profiling of Soft Tissue Sarcoma Using Mechanistic Models
Authors: Payá-Milans Miriam , Peña-Chilet María , Loucera Carlos , Esteban-Medina Marina , Dopazo Joaquín
Published: September 2023

Soft tissue sarcoma is an umbrella term for a group of rare cancers that are difficult to treat. In addition to surgery, neoadjuvant chemotherapy has shown the potential to downstage tumors and prevent micrometastases. However, finding effective therapeutic targets remains a research challenge. Here, a previously developed computational approach called mechanistic models of signaling pathways has been employed to unravel the impact of observed changes at the gene expression level on the ultimate functional behavior of cells. In the context of such a mechanistic model, RNA-Seq counts sourced from the Recount3 resource, from The Cancer Genome Atlas (TCGA) Sarcoma project, and non-diseased sarcomagenic tissues from the Genotype-Tissue Expression (GTEx) project were utilized to investigate signal transduction activity through signaling pathways. This approach provides a precise view of the relationship between sarcoma patient survival and the signaling landscape in tumors and their environment. Despite the distinct regulatory alterations observed in each sarcoma subtype, this study identified 13 signaling circuits, or elementary sub-pathways triggering specific cell functions, present across all subtypes, belonging to eight signaling pathways, which served as predictors for patient survival. Additionally, nine signaling circuits from five signaling pathways that highlighted the modifications tumor samples underwent in comparison to normal tissues were found. These results describe the protective role of the immune system, suggesting an anti-tumorigenic effect in the tumor microenvironment, in the process of tumor cell detachment and migration, or the dysregulation of ion homeostasis. Also, the analysis of signaling circuit intermediary proteins suggests multiple strategies for therapy.
A Comprehensive Analysis of Chloroplast Genome Provides New Insights into the Evolution of the Genus Chrysosplenium
Authors: Yang Tiange , Wu Zhihua , Tie Jun , Qin Rui , Wang Jiangqing , Liu Hong
Published: September 2023

Chrysosplenium, a perennial herb in the family Saxifragaceae, prefers to grow in low light and moist environments and is divided into two sections of Alternifolia and Oppositifolia based on phyllotaxy. Although there has been some progress in the phylogeny of Chrysosplenium over the years, the phylogenetic position of some species is still controversial. In this study, we assembled chloroplast genomes (cp genomes) of 34 Chrysosplenium species and performed comparative genomic and phylogenetic analyses in combination with other cp genomes of previously known Chrysosplenium species, for a total of 44 Chrysosplenium species. The comparative analyses revealed that cp genomes of Chrysosplenium species were more conserved in terms of genome structure, gene content and arrangement, SSRs, and codon preference, but differ in genome size and SC/IR boundaries. Phylogenetic analysis showed that cp genomes effectively improved the phylogenetic support and resolution of Chrysosplenium species and strongly supported Chrysosplenium species as a monophyletic taxon and divided into three branches. The results also showed that the sections of Alternifolia and Oppositifolia were not monophyletic with each other, and that C. microspermum was not clustered with other Chrysosplenium species with alternate leaves, but with C. sedakowii into separate branches. In addition, we identified 10 mutational hotspot regions that could serve as potential DNA barcodes for Chrysosplenium species identification. In contrast to Peltoboykinia, the clpP and ycf2 genes of Chrysosplenium were subjected to positive selection and had multiple significant positive selection sites. We further detected a significant positive selection site on the petG gene between the two sections of Chrysosplenium. These evolutionary characteristics may be related to the growth environment of Chrysosplenium species. This study enriches the cp genomes of Chrysosplenium species and provides a reference for future studies on its evolution and origin.
Current Trends of Bacterial and Fungal Optoproteins for Novel Optical Applications
Authors: Ramírez Martínez Carolina , Gómez-Pérez Leonardo S. , Ordaz Alberto , Torres-Huerta Ana Laura , Antonio-Perez Aurora
Published: September 2023

Photoproteins, luminescent proteins or optoproteins are a kind of light-response protein responsible for the conversion of light into biochemical energy that is used by some bacteria or fungi to regulate specific biological processes. Within these specific proteins, there are groups such as the photoreceptors that respond to a given light wavelength and generate reactions susceptible to being used for the development of high-novel applications, such as the optocontrol of metabolic pathways. Photoswitchable proteins play important roles during the development of new materials due to their capacity to change their conformational structure by providing/eliminating a specific light stimulus. Additionally, there are bioluminescent proteins that produce light during a heatless chemical reaction and are useful to be employed as biomarkers in several fields such as imaging, cell biology, disease tracking and pollutant detection. The classification of these optoproteins from bacteria and fungi as photoreceptors or photoresponse elements according to the excitation-emission spectrum (UV-Vis-IR), as well as their potential use in novel applications, is addressed in this article by providing a structured scheme for this broad area of knowledge.
Hybrids Composed of an Fe-Containing Wells–Dawson Polyoxometalate and Carbon Nanomaterials as Promising Electrocatalysts for the Oxygen Reduction Reaction
Authors: Novais Hugo C. , Jarrais Bruno , Mbomekallé Israël-Martyr , Teillout Anne-Lucie , Oliveira Pedro de , Freire Cristina , Fernandes Diana M.
Published: September 2023

The oxygen reduction reaction (ORR) is a key cathodic reaction in energy-converting systems, such as fuel cells (FCs). Thus, it is of utmost importance to develop cost-effective and efficient electrocatalysts (ECs) without noble metals to substitute the Pt-based ones. This study focuses on polyoxometalate (POM)-based ECs for ORR applications. A Wells–Dawson POM salt K7 [P2W17(FeOH2)O61].·20H2O was immobilised onto graphene flakes and multiwalled carbon nanotubes doped with nitrogen, denominated as P2W17Fe@GF_N8 and P2W17Fe@MWCNT_N8. The successful preparation of the composites was proved with various characterisation techniques, including FTIR, XPS and SEM. Both materials showed good ORR performance in an alkaline medium with similar potential onset values of ~0.84 V vs. RHE and diffusion-limiting current densities of −3.9 and −3.3 mA cm−2 for P2W17Fe@MWCNT_N8 and P2W17Fe@GF_N8, respectively. Furthermore, both composites presented low Tafel slopes (48–58 mV dec−1). Chronoamperometric tests revealed that the as-prepared nanocomposites rendered a significant improvement achieving between 90 and 94% of current retention in tolerance to methanol in comparison with Pt/C, and moderate to good long-term electrochemical stability with current retentions comprised between 68 and 88%. This work reinforces the use of POMs as important electroactive species for the preparation of alternative ORR electrocatalysts, exhibiting good activity, stability and selectivity towards the ORR in the presence of methanol.
Prospects for Biological Control of Macadamia Felted Coccid in Hawaii with Metaphycus macadamiae Polaszek & Noyes, a New Encyrtid Wasp Native to New South Wales, Australia
Authors: Yalemar Juliana A. , Tateno-Bisel Amber P. , Chun Stacey G. , Ramadan Mohsen M.
Published: September 2023

Macadamia felted coccid (MFC), Acanthococcus ironsidei (Williams) (Hemiptera: Eriococcidae), was first discovered in 2005 on the Island of Hawaii. Host plants are restricted to Macadamia species, with Macadamia integrifolia Maiden & Betche (Proteaceae) being grown in Hawaii for nut production. Approximately 6839 hectares macadamia nuts are harvested in Hawaii with an estimated farm value of USD 48.8 million (2019–2020 records). Exploration in Australia started in November 2013 for the evaluation of potential parasitoids being host specific for introduction into Hawaii. A dominant solitary endoparasitoid of MFC from New South Wales was discovered and described as Metaphycus macadamiae Polaszek & Noyes sp. n (Hymenoptera: Encyrtidae: Encyrtinae). Biology and host specificity testing were conducted at the Hawaii Department of Agriculture, Insect Containment Facility, on nine hemipteran and three lepidopteran eggs. Results indicated that M. macadamiae is host specific to MFC. There has been no evidence of parasitism or host feeding on any of the non-target insect hosts that were tested. Parasitoid emergence from the control (MFC) averaged 30.2% compared to 0% on non-target hosts. A low rate of parasitoid emergence in the laboratory (average 30.2%) and an increased rate of MFC nymphal mortality was due to adult feeding. Field parasitism reached up to 32.7% emergence in Alstonville, New South Wales, Australia. We report on the parasitoid performance in native Australia, rearing biology, host specificity testing, and the extant natural enemies associated with MFC in Hawaii. A petition to release this parasitoid for the biocontrol of MFC in Hawaii is pending. Once permitted for release, the colony will be shared with South African Mac Nut Association for their biocontrol program of this invasive pest. They will conduct their own testing before approval for release.
Regime Shifts in the Damage Caused by Tropical Cyclones in the Guangdong–Hong Kong–Macao Greater Bay Area of China
Authors: Zheng Manli , Mu Lin , Li Wenjuan , Wang Fei , Li Yan
Published: September 2023

Tropical cyclones (TCs) pose a significant threat in terms of wind-induced damage and storm risk to the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) of China. In this research, annual power dissipation index (PDI) and storm surge and wave destructive potential (SDP) index from June to November were used to estimate the damage caused by the TC events in the buffer zone of the GBA. The regime shifts in 1993 and 2013 were identified through the Bayesian changepoint detection in six TC datasets. The TC-induced damage during 1994–2012 (the low-damage period) was weaker than that in 1977–1993 and 2013–2020 (the high-damage periods). The intensity and size of stronger TCs are the dominant factors responsible for the interdecadal changes in the TC damage. This may be explained by the influences of sea surface temperature (SST), surface latent heat flux and mid-level relative humidity. During high-damage periods, TCs can extract more energy from the ocean, leading to increased TC intensity and larger size. Conversely, during low-damage periods, TCs undergo a decrease in energy intake, resulting in reduced TC power and smaller size. The variations in the SST are relative to the Luzon Strait transport. In addition, the reduction in TC translation speed is unfavorable for the development of TCs in low-damage periods. Further research suggested that mid-level steering flow affects the TC movement velocity. The results offer valuable insights into the variations in the TC-induced damage in the GBA.
Transfer Learning with Deep Neural Network toward the Prediction of Wake Flow Characteristics of Containerships
Authors: Lee Min-Kyung , Lee Inwon
Published: September 2023

In this study, deep neural network (DNN) and transfer learning (TL) techniques were employed to predict the viscous resistance and wake distribution based on the positions of flow control fins (FCFs) applied to containerships of various sizes. Both methods utilized data collected through computational fluid dynamics (CFD) analysis. The position of the flow control fin (FCF) and hull form information were utilized as input data, and the output data included viscous resistance coefficients and components of propeller axial velocity. The base DNN model was trained and validated using a source dataset from a 1000 TEU containership. The grid search cross-validation technique was employed to optimize the hyperparameters of the base DNN model. Then, transfer learning was applied to predict the viscous resistance and wake distribution for containerships of varying sizes. To enhance the accuracy of feature prediction with a limited amount of data, learning rate optimization was conducted. Transfer learning involves retraining and reconfiguring the base DNN model, and the accuracy was verified based on the fine-tuning method of the learning model. The results of this study can provide hull designers for containerships with performance evaluation information by predicting wake distribution, without relying on CFD analysis.
Effects of Interaction of Protein Hydrolysate and Arbuscular Mycorrhizal Fungi Effects on Citrus Growth and Expressions of Stress-Responsive Genes (Aquaporins and SOSs) under Salt Stress
Authors: Lu Qi , Jin Longfei , Wang Peng , Liu Feng , Huang Bei , Wen Mingxia , Wu Shaohui
Published: September 2023

Protein hydrolysates (PHs) and arbuscular mycorrhizal fungi (AMF) are environmentally friendly biostimulants that effectively promote crop growth and alleviate the damage from abiotic stress. However, the physiological and molecular regulatory mechanisms are still unclear. This study aimed to explore the effects of PHs and AMF on growth, mineral nutrient absorption, and expression of Aquaporins and SOSs in Goutoucheng (Citrus aurantium) under salt stress. Results showed that PH application and AMF inoculation significantly promoted plant growth and enhanced mineral element absorption and sodium effluxion in citrus under salt stress. The biomass, root activity, leaves mineral nutrition contents in PHs, AMF, and combined (PHs and AMF) treatments were significantly higher than those of control. Leaves sodium content in three treatments was significantly lower than in the control. AMF and combined treatments showed dominant effects than PHs alone. Besides, PHs interacted with AMF on growth, nutrient absorption, and sodium effluxion. Importantly, AMF and PHs induced stress-responsive genes. PIP1, PIP3, SOS1, and SOS3 expression in PHs and AMF treatments was significantly higher than control. Thus, it was concluded that AMF and PHs enhanced the salt tolerance of citrus by promoting nutrient absorption and sodium effluxion via up-regulating the expression of PIPs and SOSs. The mixed application of PHs and AMF had a better effect.
The Impact of Internet Use on Farmers’ Land Transfer under the Framework of Transaction Costs
Authors: Wu Yangchenhao , Duan Kaifeng , Zhang Wang
Published: September 2023

The problems that exist in China’s agricultural operations are not only on a small scale; more seriously, there are also problems of land fragmentation and the mismatch of human and land resources. Land transfer is expected to be a tool for solving these problems. The land transfer market development is slow, leaving farmers facing serious information asymmetry. On the back of the information explosion brought about by information technology represented by the Internet, exploring the impact of Internet use on land transfer can provide ideas to improve the solution of land problems. Based on the cost theory analysis framework of new institutional economics, this paper empirically examines the impact of Internet use on farmers’ land transfer behavior. The results of the study show that Internet use can significantly increase the probability and scale of household land transfer by reducing the fixed and variable costs of transactions. This conclusion still holds after using instrumental variables to address endogeneity. The impact of Internet use on land transfer is heterogeneous, with the younger, more educated, and higher-income household heads tending to participate in the land transfer market on a larger land transfer scale. Therefore, rural Internet infrastructure should be further improved to alleviate information asymmetry in the land transfer market, further strengthen the training of Internet use skills of farmers, stimulate the enthusiasm of farmers to participate in the land transfer market, further increase farmers’ income, enhance the elasticity of farmers’ response to the use of the Internet to reduce transaction costs, and promote land transfer.
A Deep Learning Framework for Intelligent Fault Diagnosis Using AutoML-CNN and Image-like Data Fusion
Authors: Gao Yan , Chai Chengzhang , Li Haijiang , Fu Weiqi
Published: September 2023

Intelligent fault diagnosis (IFD) is essential for preventative maintenance (PM) in Industry 4.0. Data-driven approaches have been widely accepted for IFD in smart manufacturing, and various deep learning (DL) models have been developed for different datasets and scenarios. However, an automatic and unified DL framework for developing IFD applications is still required. Hence, this work proposes an efficient framework integrating popular convolutional neural networks (CNNs) for IFD based on time-series data by leveraging automated machine learning (AutoML) and image-like data fusion. After normalisation, uniaxial or triaxial signals are reconstructed into -channel pseudo-images to satisfy the input requirements for CNNs and achieve data-level fusion simultaneously. Then, the model training, hyperparameter optimisation, and evaluation can be taken automatically based on AutoML. Finally, the selected model can be deployed on a cloud server or an edge device (via tiny machine learning). The proposed framework and method were validated via two case studies, demonstrating the framework’s availability for the automatic development of IFD applications and the effectiveness of the proposed data-level fusion method.
BIoTS-Path: Certification Transmission of Supply Chains Based on Blockchain–Internet of Things Architectures by Validating the Information Path
Authors: Gonzalez-Amarillo Carlos Andrés , Fraga Vazquez Anabel , Ramirez-Gonzalez Gustavo Adolfo , Mendoza-Moreno Miguel Angel , Corrales Muñoz Juan Carlos
Published: September 2023

A food traceability system (FTS) can record information about processes along a production chain to determine their safety and quality. Under the Internet of Things (IoT) concept, the communication technologies that support FTSs act as platforms for mass access to information with limited security. However, the integrity of the collected data is not immune to security attacks. This paper proposes a point-to-point information transmission path with no edges or access boundaries (no intermediaries) to transmit data with integrity. This route is possible thanks to the architectural articulation of a hardware device (sensor BIoTS) at the perception layer, with the Blockchain architecture at the application layer. This pairing makes an ecosystem with the ability to trace and certify in parallel the products, the supply chain processes, and the data recorded in it possible. The design of the security testing ecosystem is based on the theoretical and technical principles of cybersecurity. It is executed through mathematical models that define the probability of attacks’ success against the transmitted data’s integrity. The security tests performed allow for establishing that this BIoTS information transmission route is unlikely to suffer from transmission vulnerabilities and that it is not prone to security attacks against integrity. This work paves the way toward fully integrating Blockchain technology in dedicated IoT architectures.
Vibrations of Nonlocal Polymer-GPL Plates at Nanoscale: Application of a Quasi-3D Plate Model
Authors: Zou Yunhe , Kiani Yaser
Published: September 2023

An analysis is performed in this research to obtain the natural frequencies of a graphene-platelet-reinforced composite plate at nanoscale. To this end, the nonlocal elasticity theory is applied. A composite laminated plate is considered where each layer is reinforced with GPLs. The amount of GPLs may be different between the layers, which results in functionally graded media. To establish the governing equations of the plate, a quasi-3D plate model is used, which takes the non-uniform shear strains as well as normal strain through the thickness into account. With the aid of the Hamilton principle, the governing equations of the plate are established. For the case of a plate that is simply supported all around, natural frequencies are obtained using the well-known Navier solution method. The results of this study are compared with the available data in the open literature, and, after that, novel numerical results are provided to explore the effects of different parameters. It is depicted that, with the introduction of GPLs in the matrix of the composite media, the natural frequencies of the plate enhance. Also, a proper graded pattern in GPL-reinforced composite plates, i.e., an FG-X pattern, results in the maximum frequencies of the plate. In addition, the introduced quasi-3D plate theory is accurate in the estimation of the natural frequencies of thick nanocomposite plates at nanoscale.
Distinguishing Bladder Cancer from Cystitis Patients Using Deep Learning
Authors: Shih Dong-Her , Shih Pai-Ling , Wu Ting-Wei , Lee Chen-Xuan , Shih Ming-Hung
Published: September 2023

Urinary tract cancers are considered life-threatening conditions worldwide, and Bladder Cancer is one of the most malignant urinary tract tumors, with an estimated number of more than 1.3 million cases worldwide each year. Bladder Cancer is a heterogeneous disease; the main symptom is painless hematuria. However, patients with Bladder Cancer may initially be misdiagnosed as Cystitis or infection, and cystoscopy alone may sometimes be misdiagnosed as urolithiasis or Cystitis, thereby delaying medical attention. Early diagnosis of Bladder Cancer is the key to successful treatment. This study uses six deep learning methods through different oversampling techniques and feature selection, and then through dimensionality reduction techniques, to establish a set that can effectively distinguish between Bladder Cancer and Cystitis patient’s deep learning model. The research results show that based on the laboratory clinical dataset, the deep learning model proposed in this study has an accuracy rate of 89.03% in distinguishing between Bladder Cancer and Cystitis, surpassing the results of previous studies. The research model developed in this study can be provided to clinicians as a reference to differentiate between Bladder Cancer and Cystitis.
Two-Dimensional Scattering of Line Source Electromagnetic Waves by a Layered Obstacle
Authors: Athanasiadis Christodoulos E. , Roupa Paraskevi
Published: September 2023

We consider the scattering problem of line source electromagnetic waves using a multi-layered obstacle with a core, which may be a perfect conductor, a dielectric, or has an impedance surface. We formulate this problem in two dimensions and we prove some useful scattering relations. In particular, we state and prove a reciprocity principle and a general scattering theorem for line source waves for any possible positions of the source. These theorems can be used to approximate the far-field pattern in the low-frequency theory. Moreover, an optical theorem is recovered as a corollary of the general scattering theorem. Finally, we obtain a mixed reciprocity relation which can be used in proving the uniqueness results of the inverse scattering problems.
Astaxanthin: Past, Present, and Future
Authors: Nishida Yasuhiro , Berg Pernilla , Shakersain Behnaz , Hecht Karen , Takikawa Akiko , Tao Ruohan , Kakuta Yumeka , Uragami Chiasa , Hashimoto Hideki , Misawa Norihiko , Maoka Takashi
Published: September 2023

Astaxanthin (AX), a lipid-soluble pigment belonging to the xanthophyll carotenoids family, has recently garnered significant attention due to its unique physical properties, biochemical attributes, and physiological effects. Originally recognized primarily for its role in imparting the characteristic red-pink color to various organisms, AX is currently experiencing a surge in interest and research. The growing body of literature in this field predominantly focuses on AXs distinctive bioactivities and properties. However, the potential of algae-derived AX as a solution to various global environmental and societal challenges that threaten life on our planet has not received extensive attention. Furthermore, the historical context and the role of AX in nature, as well as its significance in diverse cultures and traditional health practices, have not been comprehensively explored in previous works. This review article embarks on a comprehensive journey through the history leading up to the present, offering insights into the discovery of AX, its chemical and physical attributes, distribution in organisms, and biosynthesis. Additionally, it delves into the intricate realm of health benefits, biofunctional characteristics, and the current market status of AX. By encompassing these multifaceted aspects, this review aims to provide readers with a more profound understanding and a robust foundation for future scientific endeavors directed at addressing societal needs for sustainable nutritional and medicinal solutions. An updated summary of AXs health benefits, its present market status, and potential future applications are also included for a well-rounded perspective.
The Influence of the Genotype and Planting Density on the Structure and Composition of Root and Rhizosphere Microbial Communities in Maize
Authors: Zhang Yang , Lin Jianxin , Chen Shanhu , Lu Heding , Liao Changjian
Published: September 2023

Maize has the largest cultivation area of any crop in the world and plays an important role in ensuring food security. High-density planting is essential for maintaining high maize yields in modern intensive agriculture. Nonetheless, how high-density planting and the tolerance of individual genotypes to such planting shape the root-associated microbiome of maize is still unknown. In this study, we analyzed the root and rhizosphere bacterial communities of two maize accessions with contrasting shoot architectures grown under high- and low-density planting conditions. Our results suggested that maize hosted specific, distinct bacterial communities in the root endocompartment and that the maize genotype had a significant effect on the selection of specific microbes from the rhizosphere. High-density planting also had significant effects on root-associated bacterial communities. Specifically, genotype and high-density planting coordinated to shape the structure, composition, and function of root and rhizosphere bacterial communities. Taken together, our results provide insights into how aboveground plant architecture and density may alter the belowground bacterial community in root-associated compartments of maize.
Rapid Diagnostic of Streptococcus suis in Necropsy Samples of Pigs by thrA-Based Loop-Mediated Isothermal Amplification Assay
Authors: Hess Julian , Kreitlow Antonia , Rohn Karl , Hennig-Pauka Isabel , Abdulmawjood Amir
Published: September 2023

Streptococcus (S.) suis presents a serious threat to the pig industry as well as food safety and public health. Although several LAMP assays have been developed for the identification of S. suis, no universal assay is so far available for the field-suitable examination of clinical pig specimens. Based on the thrA housekeeping gene, a new loop-mediated isothermal amplification (LAMP) assay was developed and validated for the detection of S. suis in the brain and joints of pigs. For this LAMP assay, two different methods for the extraction of DNA from brain and joint swabs were compared. Using the LPTV boiling method, the detection limit of LAMP was 1.08 CFU/reaction, while the detection limit was 53.8 CFU/reaction using a commercial DNA extraction kit. The detection limits of thrA-LAMP in combination with the LPTV boiling method were 104–105 CFU/swab in the presence of brain tissue and 103–104 CFU/swab in the presence of joint tissue. The diagnostic quality criteria of LAMP were determined by the examination of 49 brain swabs and 34 joint swabs obtained during routine diagnostic necropsies. Applying the LPTV boiling method to brain swabs, the sensitivity, specificity, and positive and negative predictive values of thrA-LAMP were 88.0, 95.8, 95.7, and 88.5% using cultural investigation as a reference method, and 76.7, 100, 100, and 73.1% using real-time PCR as a reference method. Based on these results, the thrA-LAMP assay combined with the LPTV boiling method is suitable for rapid detection of S. suis from brain swabs.
Prebiotics in New-Born and Children’s Health
Authors: Selvamani Shanmugaprakasham , Kapoor Nidhi , Ajmera Arun , El Enshasy Hesham Ali , Dailin Daniel Joe , Sukmawati Dalia , Abomoelak Mona , Nurjayadi Muktiningsih , Abomoelak Bassam
Published: September 2023

At present, prebiotics, like probiotics, are receiving more attention as a promising tool for health maintenance. Many studies have recognized the role of prebiotics in preventing and treating various illnesses including metabolic disorders, gastrointestinal disorders, and allergies. Naturally, prebiotics are introduced to the human body in the first few hours of life as the mother breastfeeds the newborn. Prebiotic human milk oligosaccharides (HMOs) are the third largest constituent of human breastmilk. Studies have proven that HMOs modulate an infant’s microbial composition and assist in the development of the immune system. Due to some health conditions of the mother or beyond the recommended age for breastfeeding, infants are fed with formula. Few types of prebiotics have been incorporated into formula to yield similar beneficial impacts similar to breastfeeding. Synthetic HMOs have successfully mimicked the bifidogenic effects of breastmilk. However, studies on the effectiveness and safety of consumption of these synthetic HMOs are highly needed before massive commercial production. With the introduction of solid foods after breastfeeding or formula feeding, children are exposed to a range of prebiotics that contribute to further shaping and maturing their gut microbiomes and gastrointestinal function. Therefore, this review evaluates the functional role of prebiotic interventions in improving microbial compositions, allergies, and functional gastrointestinal disorders in children.
The Mechanism of the Formation of the Spin Hall Effect in a Sharp Focus
Authors: Kotlyar Victor V. , Stafeev Sergey S. , Telegin Alexey M. , Kozlova Elena S.
Published: September 2023

We have shown how the spin Hall effect is formed in a tight focus for two light fields with initial linear polarization. We have demonstrated that an even number of local subwavelength regions appear in which the sign of the longitudinal projection of the spin angular momentum (the third Stokes component) alternates. When an optical vortex with topological charge n and linear polarization passes through an ideal spherical lens, additional optical vortices with topological charges n + 2, n − 2, n + 1, and n − 1 with different amplitudes are formed in the converged beam. The first two of these vortices have left and right circular polarizations and the last two vortices have linear polarization. Since circularly polarized vortices have different amplitudes, their superposition will have elliptical polarization. The sign of this elliptical polarization (left or right) will change over the beam cross section with the change in the sign of the difference in the amplitudes of optical vortices with circular polarization. We also have shown that optical vortices with topological charges n + 2, n − 2 propagate in the opposite direction near the focal plane, and together with optical vortices with charges n + 1, n − 1, they form an azimuthal energy flow at the focus.
Self-Adjusting Optical Systems Based on Reinforcement Learning
Authors: Mareev Evgenii , Garmatina Alena , Semenov Timur , Asharchuk Nika , Rovenko Vladimir , Dyachkova Irina
Published: September 2023

Progress in the field of machine learning has enhanced the development of self-adjusting optical systems capable of autonomously adapting to changing environmental conditions. This study demonstrates the concept of self-adjusting optical systems and presents a new approach based on reinforcement learning methods. We integrated reinforcement learning algorithms into the setup for tuning the laser radiation into the fiber, as well as into the complex for controlling the laser-plasma source. That reduced the dispersion of the generated X-ray signal by 2–3 times through automatic adjustment of the position of the rotating copper target and completely eliminated the linear trend arising from the ablation of the target surface. The adjustment of the system was performed based on feedback signals obtained from the spectrometer, and the movement of the target was achieved using a neural network-controlled stepper motor. As feedback, the second harmonic of femtosecond laser radiation was used, the intensity of which has a square root dependence on the X-ray yield. The developed machine learning methodology allows the considered systems to optimize their performance and adapt in real time, leading to increased efficiency, accuracy, and reliability.
Optimizing and Analyzing Performance of Motor Fault Diagnosis Algorithms for Autonomous Vehicles via Cross-Domain Data Fusion
Authors: Xie Fengyun , Li Gang , Fan Qiuyang , Xiao Qian , Zhou Shengtong
Published: September 2023

Electric motors play a pivotal role in the functioning of autonomous vehicles, necessitating accurate fault diagnosis to ensure vehicle safety and reliability. In this paper, a novel motor fault diagnosis approach grounded in vibration signals to enhance fault detection performance is presented. The method involves capturing vibration signals from the motor across various operational states and frequencies using vibration sensors. Subsequently, the signals undergo transformation into frequency domain representations through fast Fourier transform. This includes normalizing and concatenating the amplitude frequency and phase frequency signals into comprehensive frequency domain information. Leveraging Gramian image-encoding attributes, cross-domain fusion of time-domain and frequency-domain data is achieved. Finally, the fused Gram angle field map is fed into the ConvMixer deep learning model, augmented by the ECA mechanism to facilitate precise motor fault identification. Experimental outcomes underscore the efficacy of cross-domain data fusion, showcasing improved pattern recognition and recognition rates for the models compared to traditional time-domain methods. Additionally, a comparative analysis of various deep learning models highlights the superior performance of the ECA-ConvMixer model. This study makes significant contributions by introducing a cross-domain data fusion method, merging time-domain and frequency-domain information to enhance motor vibration signal analysis. Additionally, the incorporation of the ECA-ConvMixer deep learning model, equipped with attention mechanisms, effectively captures critical features, thus serving as a robust tool for motor fault diagnosis. These innovations not only enhance diagnostic accuracy but also have broad applications in areas like autonomous vehicles and industry, leading to reduced maintenance expenses and enhanced equipment reliability.
Evaluation of Satellite-Derived Precipitation Products for Streamflow Simulation of a Mountainous Himalayan Watershed: A Study of Myagdi Khola in Kali Gandaki Basin, Nepal
Authors: Aryal Aashutosh , Tran Thanh-Nhan-Duc , Kumar Brijesh , Lakshmi Venkataraman
Published: September 2023

This study assesses four Satellite-derived Precipitation Products (SPPs) that are corrected and validated against gauge data such as Soil Moisture to Rain—Advanced SCATterometer V1.5 (SM2RAIN-ASCAT), Multi-Source Weighted-Ensemble Precipitation V2.8 (MSWEP), Global Precipitation Measurement Integrated Multi-satellitE Retrievals for GPM Final run V6 (GPM IMERGF), and Climate Hazards Group InfraRed Precipitation with Station (CHIRPS). We evaluate the performance of these SPPs in Nepal’s Myagdi Khola watershed, located in the Kali Gandaki River basin, for the period 2009–2019. The SPPs are evaluated by validating the gridded precipitation products using the hydrological model, Soil and Water Assessment Tool (SWAT). The results of this study show that the SM2RAIN-ASCAT and GPM IMERGF performed better than MSWEP and CHIRPS in accurately simulating daily and monthly streamflow. GPM IMERGF and SM2RAIN-ASCAT are found to be the better-performing models, with higher NSE values (0.63 and 0.61, respectively) compared with CHIRPS and MSWEP (0.45 and 0.41, respectively) after calibrating the model with monthly data. Moreover, SM2RAIN-ASCAT demonstrated the best performance in simulating daily and monthly streamflow, with NSE values of 0.57 and 0.63, respectively, after validation. This study’s findings support the use of satellite-derived precipitation datasets as inputs for hydrological models to address the hydrological complexities of mountainous watersheds.
Detection of Macroalgal Bloom from Sentinel−1 Imagery
Authors: Chowdhury Sree Juwel Kumar , Harun-Al-Rashid Ahmed , Yang Chan-Su , Shin Dae-Woon
Published: September 2023

The macroalgal bloom (MAB) is caused by brown algae forming a floating mat. Most of its parts stay below the water surface, unlike green algae; thus, its backscatter value becomes weaker in the synthetic aperture radar (SAR) images, such as Sentinel−1, due to the dampening effect. Thus, brown algae patches appear to be thin strands in contrast to green algae and their detection by using a global threshold, which is challenging due to a similarity between the MAB patch and the ship’s sidelobe in the case of pixel value. Therefore, a novel approach is proposed to detect the MAB from the Sentinel−1 image by eliminating the ship’s sidelobe. An individually optimized threshold is applied to extract the MAB and the ships with sidelobes from the image. Then, parameters are adjusted based on the object’s area information and the ratio of length and width to filter out ships with sidelobes and clutter objects. With this method, an average detection accuracy of 82.2% is achieved by comparing it with the reference data. The proposed approach is simple and effective for detecting the thin MAB patch from the SAR image.
Surface Subsidence Monitoring of Mining Areas in Hunan Province Based on Sentinel-1A and DS-InSAR
Authors: Zhang Liya , Gao Pengfei , Gan Zhengzheng , Wu Wenhao , Sun Yafeng , Zhu Chuanguang , Long Sichun , Liu Maoqi , Peng Hui
Published: September 2023

Monitoring the surface subsidence in mining areas is conducive to the prevention and control of geological disasters, and the prediction and early warning of accidents. Hunan Province is located in South China. The mineral resource reserves are abundant; however, large and medium-sized mines account for a low proportion of the total, and the concentration of mineral resource distribution is low, meaning that traditional mining monitoring struggles to meet the needs of large-scale monitoring of mining areas in the province. The advantages of Interferometric Synthetic Aperture Radar (InSAR) technology in large-scale deformation monitoring were applied to identify and monitor the surface subsidence of coal mining fields in Hunan Province based on a Sentinel-1A dataset of 86 images taken from 2018 to 2020, and the process of developing surface subsidence was inverted by selecting typical mining areas. The results show that there are 14 places of surface subsidence in the study area, and accidents have occurred in 2 mining areas. In addition, the railway passing through the mining area of Zhouyuan Mountain is affected by the surface subsidence, presenting a potential safety hazard.