bluuebunny/crossref_metadata_2025 huggingface dataset:
Actin-Interacting Amphidinolides: Syntheses and Mechanisms of Action of Amphidinolides X, J, and K
Authors: Costa Anna M.
Published: July 2023

Amphidinolides are a family of more than forty macrolides of varying sizes and complex structures isolated from dinoflagellates of the genus Amphidinium. Although all of them display potent-to-moderate cytotoxicity, their full bioactivity profile and mode of action have not been fully investigated. Access to enough material is needed for these studies, but samples of these compounds are limited due to the minute amounts that can only be obtained by either large-scale cultivation of the organism that produces them or by total synthesis. Of all the amphidinolides known to date, only the targets of five of them (B1, H1, J, K, and X) have been examined and all have been found to interact with actin, a crucial cytoskeletal protein. This paper reviews what is currently known about actin-interacting amphidinolides, with a focus on the research of our group. Amphidinolides J and X are F-actin destabilizers, whereas Amphidinolides H1 and K stabilize actin filaments, likely via different mechanisms. More precise details of the interaction between amphidinolides and actin are missing.
Iodine(V)-Based Oxidants in Oxidation Reactions
Authors: Shetgaonkar Samata E. , Jothish Subhiksha , Dohi Toshifumi , Singh Fateh V.
Published: July 2023

The chemistry of hypervalent iodine reagents has now become quite valuable due to the reactivity of these compounds under mild reaction conditions and their resemblance in chemical properties to transition metals. The environmentally friendly nature of these reagents makes them suitable for Green Chemistry. Reagents with a dual nature, such as iodine(III) reagents, are capable electrophiles, while iodine(V) reagents are known for their strong oxidant behavior. Various iodine(V) reagents including IBX and DMP have been used as oxidants in organic synthesis either in stoichiometric or in catalytic amounts. In this review article, we describe various oxidation reactions induced by iodine(V) reagents reported in the past decade.
Combination of an Oxindole Derivative with (−)-β-Elemene Alters Cell Death Pathways in FLT3/ITD+ Acute Myeloid Leukemia Cells
Authors: Alanazi Jowaher , Bender Onur , Dogan Rumeysa , Malik Jonaid Ahmad , Atalay Arzu , Ali Taha F. S. , Beshr Eman A. M. , Shawky Ahmed M. , Aly Omar M. , Alqahtani Yasir Nasser H. , Anwar Sirajudheen
Published: July 2023

Acute myeloid leukemia (AML) is one of the cancers that grow most aggressively. The challenges in AML management are huge, despite many treatment options. Mutations in FLT3 tyrosine kinase receptors make the currently available therapies less responsive. Therefore, there is a need to find new lead molecules that can specifically target mutated FLT3 to block growth factor signaling and inhibit AML cell proliferation. Our previous studies on FLT3-mutated AML cells demonstrated that β-elemene and compound 5a showed strong inhibition of proliferation by blocking the mutated FLT3 receptor and altering the key apoptotic genes responsible for apoptosis. Furthermore, we hypothesized that both β-elemene and compound 5a could be therapeutically effective. Therefore, combining these drugs against mutated FLT3 cells could be promising. In this context, dose–matrix combination-based cellular inhibition analyses, cell morphology studies and profiling of 43 different apoptotic protein targets via combinatorial treatment were performed. Our studies provide strong evidence for the hypothesis that β-elemene and compound 5a combination considerably increased the therapeutic potential of both compounds by enhancing the activation of several key targets implicated in AML cell death.
Performance Evaluation and Oil Displacement Effect of Amphiphilic Polymer Heavy Oil Activator
Authors: Zhi Jiqiang , Liu Yikun , Chen Jinfeng , Jiang Nan , Xu Dezhu , Bo Lifeng , Qu Guohui
Published: July 2023

A heavy oil activator is an amphiphilic polymer solution that contains hydrophilic and oleophobic groups. It can enhance heavy oil recovery efficiency. This paper studied the changes in the distribution of the remaining oil after activator flooding and the performance of heavy oil’s active agent. Nuclear magnetic resonance spectroscopy, laser confocal microscopy, microscopic visualization, and CT scanning techniques were used to analyze crude oil utilization, and the distribution characteristics of the remaining oil during activator flooding of heavy oil. The results showed that the heavy oil activator solution presented a dense spatial network and good viscosification ability. The activator could reduce the interfacial tension of oil and water, disassemble the heavy components of dispersed heavy oil and reduce the viscosity of heavy oil. The utilization degree of the remaining oil in small and middle pores increased significantly after activator flooding, the remaining oil associated with membranous-like and clusterlike structures was utilized to a high degree, and the decline of light/heavy fraction in heavy oil slowed down. Heavy oil activator improved the swept volume and displacement efficiency of heavy oil, playing a significant role in improving the extent of recovery of heavy oil reservoirs.
Effects of Capsaicin on Glucose Uptake and Consumption in Hepatocytes
Authors: Zeng Haolong , Shi Nian , Peng Wenlei , Yang Qing , Ren Jingnan , Yang Hong , Chen Lingling , Chen Yijie , Guo Jun
Published: July 2023

Obesity represents a major health challenge because it substantially increases the risk of metabolic diseases. Capsaicin, the major active ingredient of Capsicum spp., has been reported to possess anti-obesity activity. Hereon, the effect of capsaicin on glucose uptake and consumption in hepatocytes was extensively studied. Capsaicin was shown to accelerate the glucose uptake/consumption and the ATP production of hepatocytes. The elevation of intracellular Ca2+ was thought to be a potential mechanism. By transcriptome analysis, 78, 146 and 507 differentially expressed genes (DEGs) were identified between capsaicin and the control group for 4 h, 12 h and 24 h treatments. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that most of the DEGs were involved in canonical pathways, like MAPK and PI3K-AKT signaling pathways. Clustering analysis showed that many DEGs were associated with glucose and amino acid metabolism. The variation trend in genes related to glucose and amino acid metabolism (like CTH, VEGFA, PCK2 and IGFBP3) in the quantitative PCR (q-PCR) assay was consistent with the transcriptome data. These results demonstrated that capsaicin efficiently accelerated the glucose uptake and consumption of hepatocytes.
Effect of Molecular Weight on Phase Equilibrium in the Polystyrene–Poly(methyl methacrylate) System
Authors: Chalykh Anatoly E. , Nikulova Uliana V.
Published: July 2023

Data on the solubility of oligomer polystyrene (PS) and poly(methyl methacrylate) (PMMA) of various molecular weights have been obtained. The binodal and spinodal curves of the phase state diagram with the upper critical solution temperature (UCST) are constructed through simulation within the framework of the Flory–Huggins theory. The influence of the molecular weight of polymers on the contribution to their mixing has been compared, and correlation curves have been plotted. The interaction parameters were calculated and the mixing thermodynamics of the components was evaluated. The largest contribution was made by the entropy component. Also, it has been shown using IR spectroscopy that there is no interaction between the functional groups of polystyrene and poly(methyl methacrylate) in a homogeneous mixture.
Liquid-Metal Core–Shell Particles Coated with Folate and Phospholipids for Targeted Drug Delivery and Photothermal Treatment of Cancer Cells
Authors: Ahn Suyeon , Kang Seung Hyun , Woo Hyunjeong , Kim Kyobum , Koo Hyung-Jun , Lee Hee-Young , Choi Yonghyun , Kang Shin Hyuk , Choi Jonghoon
Published: July 2023

Recently, several methods have been used for cancer treatment. Among them, chemotherapy is generally used, but general anticancer drugs may affect normal cells and tissues, causing various side effects. To reduce the side effects and increase the efficacy of anticancer drugs, a folate-based liquid-metal drug nanodelivery system was used to target the folate receptor, which is highly expressed in cancer cells. A phospholipid-based surface coating was formed on the surface of liquid-metal nanoparticles to increase their stability, and doxorubicin was loaded as a drug delivery system. Folate on the lipid shell surface increased the efficiency of targeting cancer cells. The photothermal properties of liquid metal were confirmed by near-infrared (NIR) laser irradiation. After treating cancerous and normal cells with liquid-metal particles and NIR irradiation, the particles were specifically bound to cancer cells for drug uptake, confirming photothermal therapy as a drug delivery system that is expected to induce cancer cell death through comprehensive effects such as vascular embolization in addition to targeting cancer cells.
Associated Factors of Exclusive Breastfeeding Intention among Pregnant Women in Najran, Saudi Arabia
Authors: Ibrahim Heba A. , Alshahrani Mohammed A. , Al-Thubaity DaifAllah D. , Sayed Samiha H. , Almedhesh Sultan A. , Elgzar Wafaa T.
Published: July 2023

The exclusive breastfeeding (EBF) intention conceived by pregnant women is the most important predictor of breastfeeding (BF) initiation, duration, and continuation. This study explores the associated factors of EBF intention among pregnant women. This was a descriptive cross-sectional study conducted from November 2022 to January 2023 with 382 pregnant women who came to the outpatient clinic in the Maternal and Children Hospital (MCH). Four instruments were used for data collection: the Infant Feeding Intention scale, the Gender-Friendly BF Knowledge scale (GFBKS), the Iowa Infant Feeding Attitude scale (IIFAS), and the basic data questionnaire. The study findings indicated that 51.8% and 75.9% of gravida women had adequate knowledge and a positive attitude regarding BF. Furthermore, 56.3% of the participants had a high intention for EBF. Binary logistic regression illustrated that occupational status, antenatal care, plan for the current pregnancy, BF practice, last child delivery mode, medical disorder during the current pregnancy, age, BF knowledge, and attitude are potential predictors. The goodness of fit test revealed that 46.8% of the EBF intention could be anticipated through the positive pre-mentioned factors. The low EBF intention is modifiable by addressing the previously positive predictors. BF educational interventions should be tailored based on EBF intention predictors in order to be effective and lead to behavior change.
How Attention Changes in Response to Carbohydrate Mouth Rinsing
Authors: Hosang Thomas J. , Laborde Sylvain , Löw Andreas , Sprengel Michael , Baum Niels , Jacobsen Thomas
Published: July 2023

Research investigating the effects of carbohydrate (CHO) mouth rinsing on neurocognitive functions is currently limited and has yielded inconsistent results. In this study, we employed the event-related potential (ERP) electroencephalography technique to investigate the effect of CHO mouth rinsing on electrophysiological correlates of visuospatial attention. Using a double-blind, non-nutritive sweetener (NNS)-controlled, within-subjects design, 53 young adults performed a standard cognitive task (modified Simon task) on two separate days in a fasted state (16 h). Intermittently, mouth rinsing was performed either with a CHO (glucose, 18%, 30 mL) or an NNS solution (aspartame, 0.05%, 30 mL). Results revealed that relative to NNS, electrophysiological correlates of both more bottom-up controlled visuospatial attention (N1pc-ERP component) were decreased in response to CHO rinsing. In contrast, compared to NNS, more top-down controlled visuospatial attention (N2pc-ERP component) was increased after CHO rinsing. Behavioral performance, however, was not affected by mouth rinsing. Our findings suggest that orosensory signals can impact neurocognitive processes of visuospatial attention in a fasted state. This may suggest a central mechanism underlying the ergogenic effects of carbohydrate mouth rinsing on endurance performance could involve modulations of attentional factors. Methodologically, our study underlines that understanding the effects of carbohydrate mouth rinsing at the central level may require combining neuroscientific methods and manipulations of nutritional states.
A Comprehensive Review of the Effect of Honey on Human Health
Authors: Palma-Morales Marta , Huertas Jesús , Rodríguez-Pérez Celia
Published: July 2023

Honey is a nutritious, healthy, and natural food, to which antioxidant, anti-inflammatory, and antimicrobial properties have been attributed, mainly due to its content of phenolic compounds. The aim of this review is to analyze the available evidence of the effect of honey on humans. Forty-eight clinical trials published between 1985 and 2022 were analyzed, with a total of 3655 subjects. More beneficial effects of honey intake than no or negative effects on different cardiovascular and metabolic risk factors, glucose tolerance, mucositis caused by chemo-radiotherapy, cough in children and wound healing, among others have been observed. Although the number of studies conducted to date is limited and the different investigations are not standardized, beneficial effects of honey intake have been observed, especially when its intake replaces the intake of other sweeteners. In addition, honey could be a safe adjuvant to be administered alongside drugs used for certain diseases.
Discovery of New Uracil and Thiouracil Derivatives as Potential HDAC Inhibitors
Authors: Elbatrawy Omnia R. , Hagras Mohamed , El Deeb Moshira A. , Agili Fatimah , Hegazy Maghawry , El-Husseiny Ahmed A. , Mokhtar Mahmoud Mohamed , Elkhawaga Samy Y. , Eissa Ibrahim H. , El-Kalyoubi Samar
Published: July 2023

Background: Histone deacetylase inhibitors (HDACIs) are a relatively new class of potential drugs for treating cancer. Aim: Discovery of new anticancer agents targeting HDAC. Methods: New uracil and thiouracil derivatives panels were designed and synthesized as HDAC inhibitors. The synthesized compounds were tested against MCF-7, HepG2, and HCT-116. HDAC1 and HDAC4 inhibitory activities of these compounds were tested. The most active member was tested for its potential against cell cycle, apoptosis, caspase-3, and caspase-8. Docking studies were carried out against HDAC1. Results: Compounds 5a, 5b, 5f, 5i, 5k, and 5m exhibited promising cytotoxic activities. HDAC1 and HDAC4 inhibitory activities of these compounds were tested. Regarding the HDAC1 inhibitory activity, compound 5m was the most potent member (IC50 = 0.05 µg/mL) compared to trichostatin A (IC50 = 0.0349 µg/mL). For HDAC4, compound 5m showed superior activity (IC50 = 2.83 µg/mL) than trichostatin A (IC50 = 3.349 µg/mL). Compound 5m showed a high potential to arrest the HCT116 cell cycle at the G0-G1 phase. In addition, it showed an almost 17 times apoptotic effect (37.59%) compared to the control cells (2.17%). Furthermore, Compound 5m showed significant increases in the levels of caspase-3 and caspase-8. Finally, the uracil and thiouracil derivatives showed accepted binding mods against HDAC. Conclusions: Compound 5m has potential anticancer activity targeting HDAC with a significant apoptotic effect.
Application of Ligand- and Structure-Based Prediction Models for the Design of Alkylhydrazide-Based HDAC3 Inhibitors as Novel Anti-Cancer Compounds
Authors: Bülbül Emre F. , Robaa Dina , Sun Ping , Mahmoudi Fereshteh , Melesina Jelena , Zessin Matthes , Schutkowski Mike , Sippl Wolfgang
Published: July 2023

Histone deacetylases (HDAC) represent promising epigenetic targets for several diseases including different cancer types. The HDAC inhibitors approved to date are pan-HDAC inhibitors and most show a poor selectivity profile, side effects, and in particular hydroxamic-acid-based inhibitors lack good pharmacokinetic profiles. Therefore, the development of isoform-selective non-hydroxamic acid HDAC inhibitors is a highly regarded field in medicinal chemistry. In this study, we analyzed different ligand-based and structure-based drug design techniques to predict the binding mode and inhibitory activity of recently developed alkylhydrazide HDAC inhibitors. Alkylhydrazides have recently attracted more attention as they have shown promising effects in various cancer cell lines. In this work, pharmacophore models and atom-based quantitative structure–activity relationship (QSAR) models were generated and evaluated. The binding mode of the studied compounds was determined using molecular docking as well as molecular dynamics simulations and compared with known crystal structures. Calculated free energies of binding were also considered to generate QSAR models. The created models show a good explanation of in vitro data and were used to develop novel HDAC3 inhibitors.
Eco-Friendly Synthesis of 1H-benzo[d]imidazole Derivatives by ZnO NPs Characterization, DFT Studies, Antioxidant and Insilico Studies
Authors: Mohammed Samar M. , Shehab Wesam S. , Emwas Abdul-Hamid M. , Jaremko Mariusz , Abdellattif Magda H. , Zordok Wael A. , Tantawy Eman S.
Published: July 2023

Benzimidazoles are classified as a category of heterocyclic compounds. Molecules having benzimidazole motifs show promising utility in organic and scientific studies. A series of mono-substituted benzimidazoles were synthesized by ZnO-NPs via cyclocondensation between substituted aromatic aldehydes and o-phenylene diamine. The synthesized compounds were characterized and compared with the traditional methods. The nano-catalyzed method displayed a higher yield, shorter time and recyclable catalyst. The DFT study and antioxidant activity were investigated for benzo[d]imidazole derivatives. Compound 2a exhibited the highest antioxidant activity among the tested compounds. We focused on the catalytic activity of ZnO in the synthesis of heterocyclic structures with the goal of stimulating further progress in this field. The superiorities of this procedure are high yield of product, low amounts of catalyst and short reaction time.
Efficacy and Safety of Low-Intensity Pulsed Ultrasound-Induced Blood–Retinal Barrier Opening in Mice
Authors: Bourdin Alexandre , Ortoli Manon , Karadayi Remi , Przegralek Lauriane , Sennlaub Florian , Bodaghi Bahram , Guillonneau Xavier , Carpentier Alexandre , Touhami Sara
Published: July 2023

Systemic drugs can treat various retinal pathologies such as retinal cancers; however, their ocular diffusion may be limited by the blood–retina barrier (BRB). Sonication corresponds to the use of ultrasound (US) to increase the permeability of cell barriers including in the BRB. The objective was to study the efficacy and safety of sonication using microbubble-assisted low-intensity pulsed US in inducing a transient opening of the BRB. The eyes of C57/BL6J mice were sonicated at different acoustic pressures (0.10 to 0.50 MPa). Efficacy analyses consisted of fluorescein angiography (FA) performed at different timepoints and the size of the leaked molecules was assessed using FITC-marked dextrans. Tolerance was assessed by fundus photographs, optical coherence tomography, immunohistochemistry, RT-qPCR, and electroretinograms. Sonication at 0.15 MPa was the most suitable pressure for transient BRB permeabilization without altering the morphology or function of the retina. It did not increase the expression of inflammation or apoptosis markers in the retina, retinal pigment epithelium, or choroid. The dextran assay suggested that drugs up to 150 kDa in size can cross the BRB. Microbubble-assisted sonication at an optimized acoustic pressure of 0.15 MPa provides a non-invasive method to transiently open the BRB, increasing the retinal diffusion of systemic drugs without inducing any noticeable side-effect.
Recent Advances in Cell Membrane Coated-Nanoparticles as Drug Delivery Systems for Tackling Urological Diseases
Authors: Yao Cenchao , Zhang Dahong , Wang Heng , Zhang Pu
Published: July 2023

Recent studies have revealed the functional roles of cell membrane coated-nanoparticles (CMNPs) in tackling urological diseases, including cancers, inflammation, and acute kidney injury. Cells are a fundamental part of pathology to regulate nearly all urological diseases, and, therefore, naturally derived cell membranes inherit the functional role to enhance the biopharmaceutical performance of their encapsulated nanoparticles on drug delivery. In this review, methods for CMNP synthesis and surface engineering are summarized. The application of different types of CMNPs for tackling urological diseases is updated, including cancer cell membrane, stem cell membrane, immune cell membrane, erythrocytes cell membranes, and extracellular vesicles, and their potential for clinical use is discussed.
Comparative Study on the Stiffness of Poly(lactic acid) Reinforced with Untreated and Bleached Hemp Fibers
Authors: Aguado Roberto J. , Bastida Gabriela A. , Espinach Francisco X. , Llorens Joan , Tarrés Quim , Delgado-Aguilar Marc , Mutjé Pere
Published: July 2023

Composite materials containing natural reinforcement fibers, generally called biocomposites, have attracted the interest of both researchers and manufacturers, but the most environmentally advantageous combinations include a bio-based matrix, as well. With this in mind, a poly(lactic acid) (PLA) matrix was reinforced with natural fibers from hemp, both untreated strands (UHSs) and soda-bleached fibers (SBHFs). The preparation of the subsequent fully bio-sourced, discontinuously reinforced composites involved kinetic mixing, intensive single-screw extrusion, milling, and injection molding. Up to a fiber content of 30 wt%, the tensile modulus increased linearly with the volume fraction of the dispersed phase. Differences between SBHFs (up to 7.6 Gpa) and UHSs (up to 6.9 Gpa) were hardly significant (p = 0.1), but SBHF-reinforced composites displayed higher strain at failure. In any case, for the same fiber load (30 wt%), the Young’s modulus of PLA/hemp biocomposites was greater than that of glass fiber (GF)-reinforced polypropylene (5.7 GPa), albeit lower than that of PLA/GF (9.8 GPa). Considering all the measurements, the contribution of each phase was analyzed by applying the Hirsch model and the Tsai-Pagano model. As a concluding remark, although the intrinsic tensile modulus of SBHFs was lower than that of GF, the efficiency of those natural fibers as reinforcement (according to the rule of mixtures) was found to be higher.
Bulk Polymerization of Acrylic Acid Using Dielectric-Barrier Discharge Plasma in a Mesoporous Material
Authors: Mieles Matthew , Harper Sky , Ji Hai-Feng
Published: July 2023

This research investigated a non-thermal, dielectric-barrier discharge (DBD) plasma-based approach to prepare poly(acrylic acid) (PAA) from acrylic acid in its liquid state at atmospheric temperature and pressure. Neither additives nor solvents were needed, and the polymerization was accomplished both as a film and inside a sheet of mesoporous paper. All prepared samples were characterized and the DBD plasma-initiated kinetics were analyzed for the polymerization of acrylic acid. Using FTIR semi-quantitative analysis, the degree of polymerization was monitored, and the reaction followed an overall second-order kinetic model with respect to the DBD-initiated polymerization. Additionally, the application of a PAA-modified paper as a water retention cloth or ‘wet wipe’ was investigated. The results showed that the PAA-modified paper substrates using DBD plasma increased water retention as a function of plasma treatment time.
Prospects for Recyclable Multilayer Packaging: A Case Study
Authors: Seier Martina , Archodoulaki Vasiliki-Maria , Koch Thomas , Duscher Bernadette , Gahleitner Markus
Published: July 2023

Food preservation is an essential application for polymers, particularly in packaging. Complex multilayer films, such as those used for modified atmosphere packaging (MAP), extend the shelf life of sensitive foods. These mostly contain various polymers to achieve the necessary combination of mechanic, optic, and barrier properties that limit their recyclability. As the European Union’s Circular Economy Action Plan calls for sustainable products and business models, including waste prevention policies and recycling quotas, with plastic packaging being a high priority, solutions towards more sustainable multilayer packaging are urgently needed. This study evaluated and compared the recycling potential of functionally equivalent PET (polyethylene terephthalate) and PP (polypropylene) post-consumer MAP through structure analysis and recycling simulation. The structure analysis revealed that both types of MAP contained functional (stability) and barrier layers (oxygen and moisture). The recycling simulation showed that the PP-based packaging was recyclable 10 times, maintaining its mechanical properties and functionality. At the same time, the PET-based MAP resulted in a highly brittle material that was unsuitable for reprocessing into similar economic value products. The secondary material from the PP-based MAP was successfully manufactured into films, demonstrating the functional possibility of closed-loop recycling. The transition from a linear to a circular economy for MAP is currently still limited by safety concerns due to a lack of sufficient and efficient purification methods, but the proper design of multilayers for recyclability is a first step towards circularity.
Thermal Performance of Multifunctional Facade Solution Containing Phase Change Materials: Experimental and Numerical Analysis
Authors: Amaral C. , Gomez F. , Moreira M. , Silva T. , Vicente R.
Published: July 2023

This work focuses on the development and analysis of a new multifunctional facade panel incorporating PCM in foam layers. The thermal performance was analysed recurring to a hotbox heat flux meter method to determine the thermal transmittance (U-value) and the main findings are presented. The experimental setup was based on the steady-state approach, using climatic chambers, assuring a stable thermal environment. Even small fractions of PCM achieved a small reduction in thermal amplitude. Numerical simulations using Ansys Fluent were developed to evaluate the performance of PCM use over a wide range of temperature boundary conditions and operating modes. These numerical models were calibrated and validated using the results of experimental tests, achieving a correlation factor of 0.9674, and, thus, accurately representing a real-world scenario. The decrement factor (f) was used to analyse the data. It was identified that the efficiency of the panel and size of the optimum region increased with the PCM fraction growth. The results showed the significant potential of the multi-layered panel, with the thermal regulator effect of the PCM incorporated, on indoor space temperature so as to reach good thermal comfort levels. The efficiency of the panel can be improved by nearly 50% depending on the input boundary conditions. The efficiency of the panel and the size of the optimum region increase with growth in the PCM fraction. The simulated behaviour was at an optimum when the input mean temperature was 20 °C for a room temperature of between 18–20 °C.
When Convolutional Neural Networks Meet Laser-Induced Breakdown Spectroscopy: End-to-End Quantitative Analysis Modeling of ChemCam Spectral Data for Major Elements Based on Ensemble Convolutional Neural Networks
Authors: Yu Yan , Yao Meibao
Published: July 2023

Modeling the quantitative relationship between target components and measured spectral information is an essential part of laser-induced breakdown spectroscopy (LIBS) analysis. However, many traditional multivariate analysis algorithms must reduce the spectral dimension or extract the characteristic spectral lines in advance, which may result in information loss and reduced accuracy. Indeed, improving the precision and interpretability of LIBS quantitative analysis is a critical challenge in Mars exploration. To solve this problem, this paper proposes an end-to-end lightweight quantitative modeling framework based on ensemble convolutional neural networks (ECNNs). This method eliminates the need for dimensionality reduction of the raw spectrum along with other pre-processing operations. We used the ChemCam calibration dataset as an example to verify the effectiveness of the proposed approach. Compared with partial least squares regression (a linear method) and extreme learning machine (a nonlinear method), our proposed method resulted in a lower root-mean-square error for major element prediction (54% and 73% lower, respectively) and was more stable. We also delved into the internal learning mechanism of the deep CNN model to understand how it hierarchically extracts spectral information features. The experimental results demonstrate that the easy-to-use ECNN-based regression model achieves excellent prediction performance while maintaining interpretability.
High-Resolution Azimuth Missing Data SAR Imaging Based on Sparse Representation Autofocusing
Authors: Jiang Nan , Du Huagui , Ge Shaodi , Zhu Jiahua , Feng Dong , Wang Jian , Huang Xiaotao
Published: July 2023

Due to significant electromagnetic interference, radar interruptions, and other factors, Azimuth Missing Data (AMD) may occur in Synthetic Aperture Radar (SAR) echo, resulting in severe defocusing and even false targets. An important approach to solving this problem is to utilize Compressed Sensing (CS) methods on AMD echo to reconstruct complete echo, which can be abbreviated as the AMD Imaging Algorithm (AMDIA). However, the State-of-the-Art AMDIA (SOA-AMDIA) do not consider the influence of motion phase errors, resulting in an unacceptable estimation error of the complete echo reconstruction. Therefore, in order to enhance the practical applicability of AMDIA, this article proposes an improved AMDIA using Sparse Representation Autofocusing (SRA-AMDIA). The proposed SRA-AMDIA aims to accurately focus the imaging result, even in the Phase Error AMD (PE-AMD) echo case. Firstly, a Phase-Compensation Function (PCF) based on the phase history of the scene centroid is designed. When the PCF is multiplied with the PE-AMD echo in the range-frequency domain, a coarse-focused sparse representation signal can be obtained in the range-Doppler domain. However, due to the influence of unknown PE, the sparsity of this sparse representation signal is unsatisfying, breaking the sparse constraints requirement of the CS method. Therefore, we introduced a minimum entropy autofocusing algorithm to autofocus this sparse representation signal. Next, the estimated PE is compensated for this sparse representation signal, and a more sparse representation signal is obtained. Hence, the non-PE complete echo can be reconstructed. Finally, the estimated complete echo can be used with classic imaging algorithms to obtain high-resolution imaging results under the PE-AMD condition. Simulation and real measured data have verified the effectiveness of the proposed SRA-AMDIA.
A Multi-Target Detection Method Based on Improved U-Net for UWB MIMO Through-Wall Radar
Authors: Pan Jun , Zheng Zhijie , Zhao Di , Yan Kun , Nie Jinliang , Zhou Bin , Fang Guangyou
Published: July 2023

Ultra-wideband (UWB) multiple-input multiple-output (MIMO) through-wall radar is widely used in through-wall human target detection for its good penetration characteristics and resolution. However, in actual detection scenarios, weak target masking and adjacent target unresolving will occur in through-wall imaging due to factors such as resolution limitations and differences in human reflectance, which will reduce the probability of target detection. An improved U-Net model is proposed in this paper to improve the detection probability of through-wall targets. In the proposed detection method, a ResNet module and a squeeze-and-excitation (SE) module are integrated in the traditional U-Net model. The ResNet module can reduce the difficulty of feature learning and improve the accuracy of detection. The SE module allows the network to perform feature recalibration and learn to use global information to emphasize useful features selectively and suppress less useful features. The effectiveness of the proposed method is verified via simulations and experiments. Compared with the order statistics constant false alarm rate (OS-CFAR), the fully convolutional networks (FCN) and the traditional U-Net, the proposed method can detect through-wall weak targets and adjacent unresolving targets effectively. The detection precision of the through-wall target is improved, and the missed detection rate is minimized.
Snow Cover and Climate Change and Their Coupling Effects on Runoff in the Keriya River Basin during 2001–2020
Authors: Yan Wei , Wang Yifan , Ma Xiaofei , Liu Minghua , Yan Junhui , Tan Yaogeng , Liu Sutao
Published: July 2023

As a significant component of the cryosphere, snow cover plays a crucial role in modulating atmospheric circulation and regional hydrological equilibrium. Therefore, studying the dynamics of snow cover and its response to climate change is of great significance for regional water resource management and disaster prevention. In this study, reanalysis climate datasets and a new MODIS snow cover extent product over China were used to analyze the characteristics of climate change and spatiotemporal variations in snow cover in the Keriya River Basin (KRB). Furthermore, the effects of climate factors on snow cover and their coupling effects on runoff were quantitatively evaluated by adopting partial least squares regression (PLSR) method and structural equation modeling (SEM), respectively. Our findings demonstrated the following: (1) Air temperature and precipitation of KRB showed a significant increase at rates of 0.24 °C/decade and 14.21 mm/decade, respectively, while the wind speed did not change significantly. (2) The snow cover frequency (SCF) in the KRB presented the distribution characteristics of “low in the north and high in the south”. The intra-annual variation of snow cover percentage (SCP) of KRB displayed a single peak (in winter), double peaks (in spring and autumn), and stability (SCP > 75%), whose boundary elevations were 4000 m and 6000 m, respectively. The annual, summer, and winter SCP in the KRB declined, while the spring and autumn SCP experienced a trend showing an insignificant increase during the hydrological years of 2001–2020. Additionally, both the annual and seasonal SCF (except autumn) will be further increased in more than 50% of the KRB, according to estimates. (3) Annual and winter SCF were controlled by precipitation, of which the former showed a mainly negative response, while the latter showed a mainly positive response, accounting for 43.1% and 76.16% of the KRB, respectively. Air temperature controlled SCF changes in 45% of regions in spring, summer, and autumn, mainly showing negative effects. Wind speed contributed to SCF changes in the range of 11.23% to 26.54% across annual and seasonal scales. (4) Climate factors and snow cover mainly affect annual runoff through direct influences, and the total effect was as follows: precipitation (0.609) > air temperature (−0.122) > SCP (0.09).
A Silicon Sub-Bandgap Near-Infrared Photodetector with High Detectivity Based on Textured Si/Au Nanoparticle Schottky Junctions Covered with Graphene Film
Authors: Dai Xiyuan , Wu Li , Liu Kaixin , Ma Fengyang , Yang Yanru , Yu Liang , Sun Jian , Lu Ming
Published: July 2023

We present a straightforward approach to develop a high-detectivity silicon (Si) sub-bandgap near-infrared (NIR) photodetector (PD) based on textured Si/Au nanoparticle (NP) Schottky junctions coated with graphene film. This is a photovoltaic-type PD that operates at 0 V bias. The texturing of Si is to trap light for NIR absorption enhancement, and Schottky junctions facilitate sub-bandgap NIR absorption and internal photoemission. Both Au NPs and the texturing of Si were made in self-organized processes. Graphene offers additional pathways for hot electron transport and to increase photocurrent. Under 1319 nm illumination at room temperature, a responsivity of 3.9 mA/W and detectivity of 7.2 × 1010 cm × (Hz)1/2/W were obtained. Additionally, at −60 °C, the detectivity increased to 1.5 × 1011 cm × (Hz)1/2/W, with the dark current density reduced and responsivity unchanged. The result of this work demonstrates a facile method to create high-performance Si sub-bandgap NIR PDs for promising applications at ambient temperatures.
Ocean-Surface Wave Measurements Using Scintillation Theories on Seaborne Software-Defined GPS and SBAS Reflectometry Observations
Authors: Tsai Lung-Chih , Chien Hwa , Su Shin-Yi , Liu Chao-Han , Schuh Harald , Alizadeh Mohamad Mahdi , Wickert Jens
Published: July 2023

In this study, a low-cost, software-defined Global Positioning System (GPS) and Satellite-Based Augmentation System (SBAS) Reflectometry (GPS&SBAS-R) system has been built and proposed to measure ocean-surface wave parameters on board the research vessel New Ocean Researcher 1 (R/V NOR-1) of Taiwan. A power-law, ocean-wave spectrum model has been used and applied with the Small Perturbation Method approach to solve the electromagnetic wave scattering problem from rough ocean surface, and compared with experimental seaborne GPS&SBAS-R observations. Meanwhile, the intensity scintillations of high-sampling GPS&SBAS-R signal acquisition data are thought to be caused by the moving of rough surfaces of the targeted ocean. We found that each derived scintillation power spectrum is a Fresnel-filtering result on ocean-surface elevation fluctuations and depends on the First Fresnel Zone (FFZ) distance and the ocean-surface wave velocity. The determined ocean-surface wave speeds have been compared and validated against nearby buoy measurements.
The smashHitCore Ontology for GDPR-Compliant Sensor Data Sharing in Smart Cities
Authors: Kurteva Anelia , Chhetri Tek Raj , Tauqeer Amar , Hilscher Rainer , Fensel Anna , Nagorny Kevin , Correia Ana , Zilverberg Albert , Schestakov Stefan , Funke Thorben , Demidova Elena
Published: July 2023

The adoption of the General Data Protection Regulation (GDPR) has resulted in a significant shift in how the data of European Union citizens is handled. A variety of data sharing challenges in scenarios such as smart cities have arisen, especially when attempting to semantically represent GDPR legal bases, such as consent, contracts and the data types and specific sources related to them. Most of the existing ontologies that model GDPR focus mainly on consent. In order to represent other GDPR bases, such as contracts, multiple ontologies need to be simultaneously reused and combined, which can result in inconsistent and conflicting knowledge representation. To address this challenge, we present the smashHitCore ontology. smashHitCore provides a unified and coherent model for both consent and contracts, as well as the sensor data and data processing associated with them. The ontology was developed in response to real-world sensor data sharing use cases in the insurance and smart city domains. The ontology has been successfully utilised to enable GDPR-complaint data sharing in a connected car for insurance use cases and in a city feedback system as part of a smart city use case.
Performance Analysis of Relay-Aided Hybrid FSO/RF Cooperation Communication System over the Generalized Turbulence Channels with Pointing Errors and Nakagami-m Fading Channels
Authors: Wu Yan , Li Gang , Kong Dejin
Published: July 2023

To improve the performance of fee-space optical communication systems, this paper analyzes the performance of a relay-aided hybrid fee-space optical (FSO)/radio frequency (RF) cooperation system based on a selective combination and decoding forward transmission scheme. In this system, the FSO sub-link experienced Málaga turbulence with pointing errors and the RF sub-link suffered Nakagami-m fading. Firstly, the probability density function (PDF) and cumulative distribution function (CDF) of the end-to-end output signal-to-noise ratio (SNR) of the relay-aided hybrid FSO/RF system are derived. Then, using the extended generalized bivariate Meijer’s G-function (EGBMGF) and the approximate analytical formula of the generalized Gauss–Laguerre integral, mathematical expressions of the end-to-end average bit error rate (ABER) and outage probability of the relay-aided hybrid FSO/RF system with different subcarrier intensity modulation and different detection schemes are derived. Through a simulation analysis of the system, the results show that compared with the other three modulation technologies, the hybrid FSO/RF direct link and relay-aided hybrid FSO/RF system with coherent binary phase shift keying (CBPSK) modulation have the best bit error performance. Compared with direct detection, the hybrid direct link and relay-aided hybrid system with coherent detection can significantly improve the communication performance. Increasing the RF fading parameter m can further improve the bit error and outage performance of the hybrid direct link and relay-aided hybrid system; the hybrid direct link can significantly mitigate the degradation of communication performance in the FSO system caused by pointing errors, and the relay-aided hybrid system can further improve the communication performance; under weak turbulence conditions, the impact of pointing errors on the performance of the relay-aided hybrid system can even be ignored. The greater the total number of paths in the relay-aided hybrid system, the better the communication performance of the system; however, the more hops, the worse the performance of the system. The outage probability of the hybrid direct link and relay-aided hybrid system are very sensitive to the decision threshold, and the larger the decision threshold, the worse the outage performance. The transmission distance of different hybrid direct links has little impact on the performance of hybrid direct links and relay-aided hybrid systems. Improving the signal-to-noise ratio of RF sub-links significantly improves the performance of hybrid direct links and relay-aided hybrid systems.
Extreme Early Image Recognition Using Event-Based Vision
Authors: Abubakar Abubakar , AlHarami AlKhzami , Yang Yin , Bermak Amine
Published: July 2023

While deep learning algorithms have advanced to a great extent, they are all designed for frame-based imagers that capture images at a high frame rate, which leads to a high storage requirement, heavy computations, and very high power consumption. Unlike frame-based imagers, event-based imagers output asynchronous pixel events without the need for global exposure time, therefore lowering both power consumption and latency. In this paper, we propose an innovative image recognition technique that operates on image events rather than frame-based data, paving the way for a new paradigm of recognizing objects prior to image acquisition. To the best of our knowledge, this is the first time such a concept is introduced featuring not only extreme early image recognition but also reduced computational overhead, storage requirement, and power consumption. Our collected event-based dataset using CeleX imager and five public event-based datasets are used to prove this concept, and the testing metrics reflect how early the neural network (NN) detects an image before the full-frame image is captured. It is demonstrated that, on average for all the datasets, the proposed technique recognizes an image 38.7 ms before the first perfect event and 603.4 ms before the last event is received, which is a reduction of 34% and 69% of the time needed, respectively. Further, less processing is required as the image is recognized 9460 events earlier, which is 37% less than waiting for the first perfectly recognized image. An enhanced NN method is also introduced to reduce this time.
Effects of Gas and Steam Humidity on Particulate Matter Measurements Obtained Using Light-Scattering Sensors
Authors: Kim Hyunsik , Kim Jeonghwan , Roh Seungjun
Published: July 2023

With the increasing need for particulate matter (PM) monitoring, the demand for light-scattering sensors that allow for real-time measurements of PM is increasing. This light-scattering method involves irradiating light to the aerosols in the atmosphere to analyze the scattered light and measure mass concentrations. Humidity affects the measurement results. The humidity in an outdoor environment may exist as gas or steam, such as fog. While the impact of humidity on the light-scattering measurement remains unclear, an accurate estimation of ambient PM concentration is a practical challenge. Therefore, this study investigated the effects of humidity on light-scattering measurements by analyzing the variation in the PM concentration measured by the sensor when relative humidity was due to gaseous and steam vapor. The gaseous humidity did not cause errors in the PM measurements via the light-scattering method. In contrast, steam humidity, such as that caused by fog, resulted in errors in the PM measurement. The results help determine the factors to be considered before applying a light-scattering sensor in an outdoor environment. Based on these factors, directions for technological development can be presented regarding the correction of measurement errors induced by vapor in outdoor environments.
Research on Adaptive 1DCNN Network Intrusion Detection Technology Based on BSGM Mixed Sampling
Authors: Ma Wei , Gou Chao , Hou Yunyun
Published: July 2023

The development of internet technology has brought us benefits, but at the same time, there has been a surge in network attack incidents, posing a serious threat to network security. In the real world, the amount of attack data is much smaller than normal data, leading to a severe class imbalance problem that affects the performance of classifiers. Additionally, when using CNN for detection and classification, manual adjustment of parameters is required, making it difficult to obtain the optimal number of convolutional kernels. Therefore, we propose a hybrid sampling technique called Borderline-SMOTE and Gaussian Mixture Model (GMM), referred to as BSGM, which combines the two approaches. We utilize the Quantum Particle Swarm Optimization (QPSO) algorithm to automatically determine the optimal number of convolutional kernels for each one-dimensional convolutional layer, thereby enhancing the detection rate of minority classes. In our experiments, we conducted binary and multi-class experiments using the KDD99 dataset. We compared our proposed BSGM-QPSO-1DCNN method with ROS-CNN, SMOTE-CNN, RUS-SMOTE-CNN, RUS-SMOTE-RF, and RUS-SMOTE-MLP as benchmark models for intrusion detection. The experimental results show the following: (i) BSGM-QPSO-1DCNN achieves high accuracy rates of 99.93% and 99.94% in binary and multi-class experiments, respectively; (ii) the precision rates for the minority classes R2L and U2R are improved by 68% and 66%, respectively. Our research demonstrates that BSGM-QPSO-1DCNN is an efficient solution for addressing the imbalanced data issue in this field, and it outperforms the five intrusion detection methods used in this study.