bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of Dietary Polyphenols in Pregnancy and Pregnancy-Related Disorders
Authors: Nacka-Aleksić Mirjana , Pirković Andrea , Vilotić Aleksandra , Bojić-Trbojević Žanka , Jovanović Krivokuća Milica , Giampieri Francesca , Battino Maurizio , Dekanski Dragana
Published: December 2022

Polyphenols are a group of phytochemicals with extensive biological functions and health-promoting potential. These compounds are present in most foods of plant origin and their increased widespread availability through the intake of nutritional supplements, fortified foods, and beverages, has also led to increased exposure throughout gestation. In this narrative review, we focus on the role of polyphenols in both healthy and pathological pregnancy. General information related to their classification and function is followed by an overview of their known effects in early-pregnancy events, including the current insights into molecular mechanisms involved. Further, we provide an overview of their involvement in some of the most common pregnancy-associated pathological conditions, such as preeclampsia and gestational diabetes mellitus. Additionally, we also discuss the estimated possible risk of polyphenol consumption on pregnancy outcomes. The consumption of dietary polyphenols during pregnancy needs particular attention considering the possible effects of polyphenols on the mechanisms involved in maternal adaptation and fetal development. Further studies are strongly needed to unravel the in vivo effects of polyphenol metabolites during pregnancy, as well as their role on advanced maternal age, prenatal nutrition, and metabolic risk of the offspring.
Research Trends in Advanced Glycation End Products and Obesity: Bibliometric Analysis
Authors: Liman Patricia , Anastasya Karina , Salma Nabila , Yenny Yenny , Faradilla Meutia
Published: December 2022

The aim of this study was to conduct a bibliometric analysis of the scientific articles on advanced glycation end products (AGEs) and obesity. English-language journal articles about AGEs and obesity were retrieved from the Scopus database. The OpenRefine application was used for data cleaning, the VOSviewer software program for analysis of the trends of year of publication, country, institution, journal, authors, references, and keywords. Microsoft Excel and Tableau Public were applied for the visualizing of the publication trends. Data collection was performed on 3 February 2022, from a total of 1170 documents. The Mann–Whitney test and Spearman test with software SPSS ver.28.0.1.1. were used to assess the relation between open access journal statuses, years of publications, and CiteScore. The results of the study showed that there was an increase in studies on processed foods, including AGEs and obesity. The United States was the country with the largest contribution in this field, with the highest number of citations. The Nutrients journal published the largest number of articles on this topic, particularly in the last two years. The present focus of the studies is on ultra-processed foods. The open access journals have younger medians of the year of publication and higher medians for number of citations than do closed access journals (p < 0.001 and p < 0.05, respectively). A strong negative association was seen between CiteScore and the year of publication (r = −0.64 [95% CI: −0.67, −0.60]), p < 0.001. We present this bibliometric analysis to furnish the most recent data on the description, visualization, and analysis of AGEs and obesity.
The Effect of Authentic Leadership on Nurses’ Trust in Managers and Job Performance: A Cross-Sectional Study
Authors: Alilyyani Bayan
Published: December 2022

Background: Nurse leaders have the responsibility to build healthy work environments for staff nurses and enhance nurses’ outcomes. Authentic leadership is one of the leadership theories that have been shown to have positive impacts on nurses’ outcomes. The goal of this study was to test the effect of authentic leadership on trust in managers and job performance among nurses in Saudi Arabia. Methods: A non-experimental, cross-sectional design was applied. A total of 116 nurses who met the inclusion criteria completed the survey. To test the study variables, three different scales were used. The data in this study were analyzed using SPSS version 28.0.1.1. Results: The findings of this study showed that there were significant and positive effects of authentic leadership and its four components on trust in managers. However, no relationships were found between authentic leadership and its four elements, and job performance. Conclusions: Authentic leaders have the ability to improve work environments by building a trustful relationship with nurses. This study focuses on the role of authentic leadership in nursing practice and its essential effects to enhance the work environments. It also provides future researchers in Saudi Arabia with comprehensive knowledge about conducting studies of authentic leadership in nursing and examine its effects on outcomes related to nurses.
Albumin-Based Zn (II)-Quercetin Enzyme Mimic Scavenging ROS for Protection against Cardiotoxicity Induced by Doxorubicin
Authors: Shao Zehua , Li Ran , Shao Dongxing , Tang Hao , Han Yu
Published: December 2022

Doxorubicin (DOX) is a chemotherapeutic agent that can cause cardiotoxicity leading to progressive, chronic, life-threatening cardiomyopathy, called DOX-induced cardiomyopathy (DIC). DIC is a fatal cardiomyopathy with a worse prognosis compared to other cardiomyopathies and limits the use of DOX in malignancies due to its cardiotoxicity. DIC has been proven to be associated with reactive oxygen species (ROS)-induced side effect damage in cardiac myocytes. Currently, scavenging of reactive oxygen species is a practical strategy to reduce chemotherapy-associated DIC. Although quercetin has already been reported to have superior antioxidant activity, its clinical application is severely limited due to its rapid degradation and poor tissue absorption. Herein, we reported the preparation of a novel enzyme mimic via coordinated albumin, Zinc Ion (Zn2+) and quercetin. The enzyme mimics were capable of simultaneously increasing the biocompatibility and efficiently overcame the drawbacks of free quercetin, and were achieved by long circulation in vivo. Most importantly, these quercetin-based enzyme mimics had no effect on the antioxidant activity of quercetin. These beneficial therapeutic properties, together with high drug-carrying capacity and redox stimuli, will significantly improve quercetin’s alleviation of chemotherapeutic cardiotoxicity without causing significant side effects. Therefore, nanoparticles of albumin-based Zn (II)-Quercetin have a promising clinical application as an effective agent for mitigating the cardiotoxicity of chemotherapy.
Optimized Therapeutic 177Lu-Labeled PSMA-Targeted Ligands with Improved Pharmacokinetic Characteristics for Prostate Cancer
Authors: Wu Yitian , Zhang Xiaojun , Duan Xiaojiang , Yang Xing , Wang Feng , Zhang Jinming
Published: December 2022

Clinical trials have shown the significant efficacy of [177Lu]Lu-PSMA-617 for treating prostate cancer. However, the pharmacokinetic characteristics and therapeutic performance of [177Lu]Lu-PSMA-617 still need further improvement to meet clinical expectations. The aim of this study was to evaluate the feasibility and therapeutic potential of three novel 177Lu-labeled ligands for the treatment of prostate cancer. The novel ligands were efficiently synthesized and radiolabeled with non-carrier added 177Lu; the radiochemical purity of the final products was determined by Radio-HPLC. The specific cell-binding affinity to PSMA was evaluated in vitro using prostate cancer cell lines 22Rv1and PC-3. Blood pharmacokinetic analysis, biodistribution experiments, small animal SPCET imaging and treatment experiments were performed on normal and tumor-bearing mice. Among all the novel ligands developed in this study, [177Lu]Lu-PSMA-Q showed the highest uptake in 22Rv1 cells, while there was almost no uptake in PC-3 cells. As the SPECT imaging tracer, [177Lu]Lu-PSMA-Q is highly specific in delineating PSMA-positive tumors, with a shorter clearance half-life and higher tumor-to-background ratio than [177Lu]Lu-PSMA-617. Biodistribution studies verified the SPECT imaging results. Furthermore, [177Lu]Lu-PSMA-Q serves well as an effective therapeutic ligand to suppress tumor growth and improve the survival rate of tumor-bearing mice. All the results strongly demonstrate that [177Lu]Lu-PSMA-Q is a PSMA-specific ligand with significant anti-tumor effect in preclinical models, and further clinical evaluation is worth conducting.
Application of Microfluidics for Bacterial Identification
Authors: Daniel Fraser , Kesterson Delaney , Lei Kevin , Hord Catherine , Patel Aarti , Kaffenes Anastasia , Congivaram Harrshavasan , Prakash Shaurya
Published: December 2022

Bacterial infections continue to pose serious public health challenges. Though anti-bacterial therapeutics are effective remedies for treating these infections, the emergence of antibiotic resistance has imposed new challenges to treatment. Often, there is a delay in prescribing antibiotics at initial symptom presentation as it can be challenging to clinically differentiate bacterial infections from other organisms (e.g., viruses) causing infection. Moreover, bacterial infections can arise from food, water, or other sources. These challenges have demonstrated the need for rapid identification of bacteria in liquids, food, clinical spaces, and other environments. Conventional methods of bacterial identification rely on culture-based approaches which require long processing times and higher pathogen concentration thresholds. In the past few years, microfluidic devices paired with various bacterial identification methods have garnered attention for addressing the limitations of conventional methods and demonstrating feasibility for rapid bacterial identification with lower biomass thresholds. However, such culture-free methods often require integration of multiple steps from sample preparation to measurement. Research interest in using microfluidic methods for bacterial identification is growing; therefore, this review article is a summary of current advancements in this field with a focus on comparing the efficacy of polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), and emerging spectroscopic methods.
Flexible Method for Generating Arbitrary Vector Beams Based on Modified Off-Axis Interference-Type Hologram Encoding
Authors: Liu Zhiyu , Xie Yiyan , Zhu Wenxu , Fu Qianqian , Gao Feilong , Li Guoru , Wang Yiran , Su Xiancui , Zhang Bingyuan , Kumar Santosh
Published: December 2022

A novel experimental setup for the generation of arbitrary vector beams is proposed. The system major includes two reflective liquid crystal spatial light modulators (RLC-SLM) and a polarizing beam splitting prism. Moreover, this method is not limited by the wavelength of light wave and the pixel size of SLM. Theoretical analysis shows that when Gaussian beam or a plane beam is illuminated on a computer-generated hologram (CGH) specially designed in this work, the complex amplitudes of the vector field’s two orthogonal polarization components may be changed by modifying the encoding parameters, resulting in a vector beam with arbitrary complex amplitude and polarization in the output field. The experimental results also show that the two independent coding channels of the device have good polarization-selective imaging ability, which greatly improves the flexibility of generating arbitrary vector beams.
Transfer of Orbital Angular Momentum of Light Using Autler-Townes Splitting
Authors: Asadpour Seyyed Hossein , Hamedi Hamid Reza , Paspalakis Emmanuel
Published: December 2022

We propose a scheme to exchange optical vortices beyond electromagnetically induced transparency (EIT) but based on four-wave mixing (FWM) in a five-level atomic system consisting of two Λ subsystems linked via a weak driving field. When the laser fields are strong enough, the quantum interference responsible for the EIT in each Λ subsystem is washed out, giving rise to the Autler-Townes splitting (ATS). When only one of the control fields carries an optical vortex, it is shown that the generated FWM field obtains the vorticity of the vortex control. We distinguish between three different regimes, i.e., a pure EIT, a joint EIT-ATS, and a dual-ATS, where the optical angular momentum (OAM) translation can take place. Elaborating on the distinction between three regimes through numerical analysis, we find that the maximum energy conversion efficiency is obtained in the joint EIT-ATS and dual-ATS regimes. The latter is more favorable as the absorption losses vanish as the beam propagates into the atomic cloud. The results may find applications in the implementation of high-efficient frequency and OAM conversion devices for quantum information processing.
Analysis of Stress Relaxation in Bulk and Porous Ultra-High Molecular Weight Polyethylene (UHMWPE)
Authors: Statnik Eugene S. , Salimon Alexey I. , Gorshkova Yulia E. , Kaladzinskaya Natallia S. , Markova Ludmila V. , Korsunsky Alexander M.
Published: December 2022

The reported study was devoted to the investigation of viscoelastic behavior for solid and porous ultra-high molecular weight polyethylene (UHMWPE) under compression. The obtained experimental stress curves were interpreted using a two-term Prony series to represent the superposition of two coexisting activation processes corresponding to long molecular (~160 s) and short structural (~20 s) time scales, respectively, leading to good statistical correlation with the observations. In the case of porous polymer, the internal strain redistribution during relaxation was quantified using digital image correlation (DIC) analysis. The strongly inhomogeneous deformation of the porous polymer was found not to affect the relaxation times. To illustrate the possibility of generalizing the results to three dimensions, X-ray tomography was used to examine the porous structure relaxation at the macro- and micro-scale levels. DIC analysis revealed positive correlation between the applied force and relative density. The apparent stiffness variation for UHMWPE foams with mixed open and closed cells was described using a newly proposed three-term expression. Furthermore, in situ tensile loading and X-ray scattering study was applied for isotropic solid UHMWPE specimens to investigate the evolution of internal structure and orientation during drawing and stress relaxation in another loading mode.
Fabrication of Conductive Fabrics Based on SWCNTs, MWCNTs and Graphene and Their Applications: A Review
Authors: Alhashmi Alamer Fahad , Almalki Ghadah A.
Published: December 2022

In recent years, the field of conductive fabrics has been challenged by the increasing popularity of these materials in the production of conductive, flexible and lightweight textiles, so-called smart textiles, which make our lives easier. These electronic textiles can be used in a wide range of human applications, from medical devices to consumer products. Recently, several scientific results on smart textiles have been published, focusing on the key factors that affect the performance of smart textiles, such as the type of substrate, the type of conductive materials, and the manufacturing method to use them in the appropriate application. Smart textiles have already been fabricated from various fabrics and different conductive materials, such as metallic nanoparticles, conductive polymers, and carbon-based materials. In this review, we study the fabrication of conductive fabrics based on carbon materials, especially carbon nanotubes and graphene, which represent a growing class of high-performance materials for conductive textiles and provide them with superior electrical, thermal, and mechanical properties. Therefore, this paper comprehensively describes conductive fabrics based on single-walled carbon nanotubes, multi-walled carbon nanotubes, and graphene. The fabrication process, physical properties, and their increasing importance in the field of electronic devices are discussed.
Vat Photopolymerization 3D-Printing of Dynamic Thiol-Acrylate Photopolymers Using Bio-Derived Building Blocks
Authors: Shaukat Usman , Sölle Bernhard , Rossegger Elisabeth , Rana Sravendra , Schlögl Sandra
Published: December 2022

As an energy-efficient additive manufacturing process, vat photopolymerization 3D-printing has become a convenient technology to fabricate functional devices with high resolution and freedom in design. However, due to their permanently crosslinked network structure, photopolymers are not easily reprocessed or repaired. To improve the environmental footprint of 3D-printed objects, herein, we combine the dynamic nature of hydroxyl ester links, undergoing a catalyzed transesterification at elevated temperature, with an acrylate monomer derived from renewable resources. As a sustainable building block, we synthesized an acrylated linseed oil and mixed it with selected thiol crosslinkers. By careful selection of the transesterification catalyst, we obtained dynamic thiol-acrylate resins with a high cure rate and decent storage stability, which enabled the digital light processing (DLP) 3D-printing of objects with a structure size of 550 µm. Owing to their dynamic covalent bonds, the thiol-acrylate networks were able to relax 63% of their initial stress within 22 min at 180 °C and showed enhanced toughness after thermal annealing. We exploited the thermo-activated reflow of the dynamic networks to heal and re-shape the 3D-printed objects. The dynamic thiol-acrylate photopolymers also demonstrated promising healing, shape memory, and re-shaping properties, thus offering great potential for various industrial fields such as soft robotics and electronics.
Recent Advances in Limiting Fatigue Damage Accumulation Induced by Self-Heating in Polymer–Matrix Composites
Authors: Amraei Jafar , Katunin Andrzej
Published: December 2022

The self-heating effect can be considered as a catastrophic phenomenon that occurs in polymers and polymer–matrix composites (PMCs) subjected to fatigue loading or vibrations. This phenomenon appears in the form of temperature growth in such structures due to their relatively low thermal conductivities. The appearance of thermal stress resulting from temperature growth and the coefficient of thermal expansion (CTE) mismatch between fibers and neighboring polymer matrix initiates and/or accelerates structural degradation and consequently provokes sudden fatigue failure in the structures. Therefore, it is of primary significance for a number of practical applications to first characterize the degradation mechanism at the nano-, micro- and macroscales caused by the self-heating phenomenon and then minimize it through the implementation of numerous approaches. One viable solution is to cool the surfaces of considered structures using various cooling scenarios, such as environmental and operational factors, linked with convection, contributing to enhancing heat removal through convection. Furthermore, if materials are appropriately selected regarding their thermomechanical properties involving thermal conductivity, structural degradation may be prevented or at least minimized. This article presents a benchmarking survey of the conducted research studies associated with the fatigue performance of cyclically loaded PMC structures and an analysis of possible solutions to avoid structural degradation caused by the self-heating effect.
Effect of Structural Design on the Pore Structure, Water Resistance, and Mechanical Properties of Engineered Wood/Bamboo Laminated Composites
Authors: Zhu Xuguang , Li Xiaoyan , Zhang Zhiyuan , Cheng Lin , Wu Jue , Li Luming , Zhang Zhenhua , Liu Qingyuan , Zhao Pu , Rao Fei
Published: December 2022

An important principle in rational manufacturing design is matching the properties of composites to their intended uses. Herein, six laminated composites (LCs) were manufactured using fibrous moso bamboo and poplar veneer units, and their pore structure, water resistance, and mechanical properties were evaluated. The LC density (640–1290 kg/m3) increased significantly with increasing bamboo veneer unit content. The LC surface texture and roughness depended on the density and type of surface layer. With increasing LC density, the water absorption rate (WAR), width swelling rate (WSR), and thickness swelling rate (TSR) decreased exponentially and the mechanical properties increased linearly. This behavior was closely related to the changes in pore structure caused by density. Notably, the water resistance and mechanical properties of the LCs with densities higher than 910 kg/m3 were superior to the highest levels specified in GB/T 20241–2006 for ‘‘laminated veneer lumber’’ and GB/T 30364–2013 for “bamboo scrimber flooring”. Thus, these engineered materials are promising for outdoor structures and flooring.
New Bio-Based Polymer Sorbents out of Terpene Compounds or Vegetable Oils: Synthesis, Properties, Analysis of Sorption Processes
Authors: Sobiesiak Magdalena
Published: December 2022

This research presents a synthesis and characterization of new bio-based polymer sorbents. Natural origin substances such as terpenes (citral, limonene, and pinene) or vegetable oils (argan, linseed, and rapeseed oils) were used as monomers, and divinylbenzene was applied as the cross-linker. The newly prepared polymers were characterized by means of ATR-FTIR, TG/DTG and titration methods (acid and iodine values), and N2 physisorption experiments. Tests of sorption ability were carried out by a dynamic solid phase extraction method using a mixture of four phenols or single-component pharmaceutical solutions (salicylic acid, aspirin, ibuprofen, paracetamol, and ampicillin). The performed studies revealed that the terpene-based polymers possessed better-developed porous structures (420–500 m2/g) with more uniform pores than oil-based ones. However, the surface of the oil-based sorbents was more acidic in nature. The sorption tests showed that both the porosity and acidity of the surface significantly influenced the sorption. Recoveries of up to 90% were obtained for 2,4 dichlorophenol from C-DVB, L-DVB, and Ro-DVB. The lowest affinity to the polymers exhibited phenol (5–45%), aspirin (1–7%), and ampicillin (1–7%). A 70% recovery was achieved for ibuprofen from C-DVB. In-depth data analysis allowed the influence of various factors on the sorption process of test compounds of the studied polymers to be elucidated.
Attapulgite Nanorod-Incorporated Polyimide Membrane for Enhanced Gas Separation Performance
Authors: Zhang Shiyang , Lu Xiaochuang , Cai Mingwei , Wang Zhi , Han Zhenjing , Chen Zhiyin , Liu Rongtao , Li Kaixin , Min Yonggang
Published: December 2022

Polyimide (PI) membrane is an ideal gas separation material due to its advantages of high designability, good mechanical properties and easy processing; however, it has equilibrium limitations in gas selectivity and permeability. Introducing nanoparticles into polymers is an effective method to improve the gas separation performance. In this work, nano-attapulgite (ATP) functionalized with KH-550 silane coupling agent was used to prepare polyimide/ATP composite membranes by in-situ polymerization. A series of characterization and performance tests were carried out on the membranes. The obtained results suggested a significant increase in gas permeability upon increasing the ATP content. When the content of ATP was 50%, the gas permeability of H2, He, N2, O2, CH4, and CO2 reached 11.82, 12.44, 0.13, 0.84, 0.10, and 4.64 barrer, which were 126.87%, 119.40%, 160.00%, 140.00%, 150.00% and 152.17% higher than that of pure polyimide, respectively. No significant change in gas selectivity was observed. The gas permeabilities of membranes at different pressures were also investigated. The inefficient polymer chain stacking and the additional void volume at the interface between the polymer and TiO2 clusters leaded to the increase of the free volume, thus improving the permeability of the polyimide membrane. As a promising separation material, the PI/ATP composite membrane can be widely used in gas separation industry.
Incorporation of the Multi-Layer Plastic Packaging in the Asphalt Binders: Physical, Thermal, Rheological, and Storage Properties Evaluation
Authors: Qabur Ali , Baaj Hassan , El-Hakim Mohab
Published: December 2022

The amount of residual Multi-layer Plastic Packaging (MPP) in Canada has greatly increased in the last two decades, which has economic and environmental consequences. MPP is primarily made up of two or more layers of Polyethylene (PE), Polyester (PET), Nylon (NY), and Metalized Polyester (METPET). While MPP has not been used as an asphalt modifier, some of the materials commonly found in MPP, such as PE and PET, have also been successfully used as asphalt modifiers. Nevertheless, a few recent studies have demonstrated the potential for reusing MPP as an asphalt modifier to improve asphalt pavement performance. Recycling post-industrial MPP instead of using raw polymers could lead to economic and environmental benefits. However, a comprehensive study to evaluate MPP as a viable asphalt additive is lacking. The main objective of this study is to evaluate the feasibility of using MPP as an asphalt modifier via the wet method, considering the physical, thermal, rheological, and storage properties of the MPP-modified binder at different MPP concentrations (2%, 4%, and 8%) in asphalt cement (PG 58–28). MPP-modified binders were evaluated using the following instruments: Differential Scanning Calorimeter (DSC), Thermogravimetric Analysis (TGA), Superpave Dynamic Shear Rheometer (DSR), Rotational Viscosity (RV), and Environmental Scanning Electron Microscopy (ESEM). Test results indicated that the incorporation of MPP has a strong potential to improve permanent deformation resistance at high temperatures. In addition, MPP shows a moderate impact on fatigue cracking performance at intermediate temperatures. Overall, in low-temperature climates, using less than 4% of MPP additives would offer higher fatigue damage resistance along with adequate permanent deformation. In high-temperature climates, higher concentrations of additives may be preferable to resist permanent deformation. Finally, MPP is a challenge for existing recycling systems, and its incorporation into asphalt applications may develop more sustainable materials that would contribute to circular economy principles.
Thermomechanical Properties and Fracture Toughness Improvement of Thermosetting Vinyl Ester Using Liquid Metal and Graphene Nanoplatelets
Authors: Dang Thanh Kim Mai , Nikzad Mostafa , Truong Vi Khanh , Masood Syed , Nguyen Chung Kim , Sbarski Igor
Published: December 2022

In this study, a eutectic gallium–indium (EGaIn) alloy and graphene nanoplatelets (GnPs) were employed as reinforcements for a comonomer vinyl ester (cVE) resin at different weight fractions up to 2% via a direct polymerization process. First, the effect of EGaIn on the curing kinetics of cVE was evaluated. The thermal and mechanical properties, and the fracture toughness of two types of cVE composites consisting of EGaIn and GnPs were then studied. The results showed that sub-micron sized EGaIn (≤1 wt.%) could promote the curing reaction of cVE without changing the curing mechanism. However, with further increases in EGaIn loading between 1 and 2 wt.%, the curing reaction rate tends to decrease. Both EGaIn and GnPs showed a significant enhancement in strengthening and toughening the cVE matrix with the presence of filler loading up to 1 wt.%. EGaIn was more effective than GnPs in promoting the flexural and impact strength. An increase of up to 50% and 32% were recorded for these mechanical properties, when EGaln was used, as compared to 46%, and 18% for GnPs, respectively. In contrast, the GnPs/cVE composites exhibited a greater improvement in the fracture toughness and fracture energy by up to 50% and 56% in comparison with those of the EGaIn/cVE ones by up to 32% and 39%, respectively. Furthermore, the stiffness of both the EgaIn/cVE and GnPs/cVE composites showed a significant improvement with an increase of up to 1.76 and 1.83 times in the normalized storage modulus, respectively, while the glass transition temperature (Tg) values remained relatively constant. This work highlights the potential of EGaIn being employed as a filler in creating high-performance thermoset composites, which facilitates its widening applications in many structural and engineering fields, where both higher toughness and stiffness are required.
Water Level Change of Qinghai Lake from ICESat and ICESat-2 Laser Altimetry
Authors: Han Weixiao , Huang Chunlin , Gu Juan , Hou Jinliang , Zhang Ying , Wang Weizhen
Published: December 2022

Long-term satellite observations of the water levels of lakes are crucial to our understanding of lake hydrological basin systems. The Ice, Cloud, and Land Elevation satellite (ICESat) and ICESat-2 were employed to monitor the water level of Qinghai Lake in the hydrological basin. The median of absolute deviation (MAD) method was exploited to remove the outliers. The results confirmed that the MAD range of ICESat was from 0.0525 to 0.2470 m, and the range of σ was from 0.0778 to 0.3662 m; the MAD range of ICESat-2 was from 0.0291 to 0.0490 m, and the range of σ was from 0.0431 to 0.0726 m; ICESat-2 was less than that of ICESat. The reference ellipsoid and geoid transfer equations were applied to convert the water level to the World Geodetic System (WGS84) and Earth Gravitational Model 2008 (EGM2008) geoid. The water level, as derived from laser altimeters, was validated by the Xiashe Hydrological Station; with ICESat, the coefficient of association (R) was 0.8419, the root mean square error (RMSE) was 0.1449 m, and the mean absolute error (MAE) was 0.1144 m; with ICESat-2, the R was 0.6917, the RMSE was 0.0531 m, and the MAE was 0.0647 m. The water levels from ICESat-2 are much more accurate than those from ICESat. The two combined laser altimeters showed that the R was 0.9931, the RMSE was 0.1309 m, and the MAE was 0.1035 m. The water level rise was 3.6584 m from 2004 to 2020. The rising rate was 0.2287 m/a. The collaborative use of the ICESat-2 and ICESat satellites made it easier to obtain the lake water levels.
SCAD: A Siamese Cross-Attention Discrimination Network for Bitemporal Building Change Detection
Authors: Xu Chuan , Ye Zhaoyi , Mei Liye , Shen Sen , Zhang Qi , Sui Haigang , Yang Wei , Sun Shaohua
Published: December 2022

Building change detection (BCD) is crucial for urban construction and planning. The powerful discriminative ability of deep convolutions in deep learning-based BCD methods has considerably increased the accuracy and efficiency. However, dense and continuously distributed buildings contain a wide range of multi-scale features, which render current deep learning methods incapable of discriminating and incorporating multiple features effectively. In this work, we propose a Siamese cross-attention discrimination network (SCADNet) to identify complex information in bitemporal images and improve the change detection accuracy. Specifically, we first use the Siamese cross-attention (SCA) module to learn unchanged and changed feature information, combining multi-head cross-attention to improve the global validity of high-level semantic information. Second, we adapt a multi-scale feature fusion (MFF) module to integrate embedded tokens with context-rich channel transformer outputs. Then, upsampling is performed to fuse the extracted multi-scale information content to recover the original image information to the maximum extent. For information content with a large difference in contextual semantics, we perform filtering using a differential context discrimination (DCD) module, which can help the network to avoid pseudo-change occurrences. The experimental results show that the present SCADNet is able to achieve a significant change detection performance in terms of three public BCD datasets (LEVIR-CD, SYSU-CD, and WHU-CD). For these three datasets, we obtain F1 scores of 90.32%, 81.79%, and 88.62%, as well as OA values of 97.98%, 91.23%, and 98.88%, respectively.
A Survey of SAR Image Target Detection Based on Convolutional Neural Networks
Authors: Zhang Ying , Hao Yisheng
Published: December 2022

Synthetic Aperture Radar (SAR) target detection is a significant research direction in radar information processing. Aiming at the poor robustness and low detection accuracy of traditional detection algorithms, SAR image target detection based on the Convolutional Neural Network (CNN) is reviewed in this paper. Firstly, the traditional SAR image target detection algorithms are briefly discussed, and their limitations are pointed out. Secondly, the CNN’s network principle, basic structure, and development process in computer vision are introduced. Next, the SAR target detection based on CNN is emphatically analyzed, including some common data sets and image processing methods for SAR target detection. The research status of SAR image target detection based on CNN is summarized and compared in detail with traditional algorithms. Afterward, the challenges of SAR image target detection are discussed and future research is proposed. Finally, the whole article is summarized. By summarizing and analyzing prior research work, this paper is helpful for subsequent researchers to quickly recognize the current development status and identify the connections between various detection algorithms. Beyond that, this paper summarizes the problems and challenges confronting researchers in the future, and also points out the specific content of future research, which has certain guiding significance for promoting the progress of SAR image target detection.
Variations in the Equatorial Ionospheric F Region Current during the 2022 Tonga Volcanic Eruption
Authors: Wang Hui , Xia Hao , Zhang Kedeng
Published: December 2022

In this work, the temporal variations in the ionospheric F region current (FRC) during the 2022 volcanic eruption in Tonga are reported for the first time. The FRC increased and underwent several polarity reversals following the eruption, as observed by the dual Swarm satellites. By combining neutral wind observations derived from the Ionospheric Connection Explorer (ICON) satellite, we attempt to reveal the potential physical mechanisms responsible for these variations. The ICON and Swarm satellites were located at almost the same distance from the epicenter of the volcanic wave, thus providing a good opportunity for analyzing coordinated observations. The F-layer neutral wind data reflect eastward and westward fluctuations that are basically consistent with the polarity reversals identified in the FRC. The E-layer neutral wind also exhibits polarity reversals that affect the equatorial ionosphere electron density anomaly. These results show that the atmospheric fluctuations caused by the analyzed volcanic eruption affected the wind pattern distribution in the E-F region, thus further affecting the spatial distribution of the FRC and electron density in the F layer.
Absorption Pruning of Deep Neural Network for Object Detection in Remote Sensing Imagery
Authors: Wang Jielei , Cui Zongyong , Zang Zhipeng , Meng Xiangjie , Cao Zongjie
Published: December 2022

In recent years, deep convolutional neural networks (DCNNs) have been widely used for object detection tasks in remote sensing images. However, the over-parametrization problem of DCNNs hinders their application in resource-constrained remote sensing devices. In order to solve this problem, we propose a network pruning method (named absorption pruning) to compress the remote sensing object detection network. Unlike the classical iterative three-stage pruning pipeline used in existing methods, absorption pruning is designed as a four-stage pruning pipeline that only needs to be executed once, which differentiates it from existing methods. Furthermore, the absorption pruning no longer identifies unimportant filters, as in existing pruning methods, but instead selects filters that are easy to learn. In addition, we design a method for pruning ratio adjustment based on the object characteristics in remote sensing images, which can help absorption pruning to better compress deep neural networks for remote sensing image processing. The experimental results on two typical remote sensing data sets—SSDD and RSOD—demonstrate that the absorption pruning method not only can remove 60% of the filter parameters from CenterNet101 harmlessly but also eliminate the over-fitting problem of the pre-trained network.
An Equivalent Consumption Minimization Strategy for a Parallel Plug-In Hybrid Electric Vehicle Based on an Environmental Perceiver
Authors: Pu Shilin , Chu Liang , Hu Jincheng , Li Shibo , Hou Zhuoran
Published: December 2022

An energy management strategy is a key technology used to exploit the energy-saving potential of a plug-in hybrid electric vehicle. This paper proposes the environmental perceiver-based equivalent consumption minimization strategy (EP-ECMS) for parallel plug-in hybrid vehicles. In this method, the traffic characteristic information obtained from the intelligent traffic system is used to guide the adjustment of the equivalence factor, improving the environmental adaptiveness of the equivalent consumption minimization strategy (ECMS). Two main works have been completed. First, a high-accuracy environmental perceiver was developed based on a graph convolutional network (GCN) and attention mechanism to complete the traffic state recognition of all graph regions based on historical information. Moreover, it provides the grade of the corresponding region where the vehicle is located (for the ECMS). Secondly, in the offline process, the search for the optimal equivalent factor is completed by using the Harris hawk optimization algorithm based on the representative working conditions under various grades. Based on the identified traffic grades in the online process, the optimized equivalence factor tables are checked for energy management control. The simulation results show that the improved EP-ECMS can achieve 7.25% energy consumption optimization compared with the traditional ECMS.
Feature-Based Characterisation of Turned Surface Topography with Suppression of High-Frequency Measurement Errors
Authors: Podulka Przemysław
Published: December 2022

Errors that occur when surface topography is measured and analysed can be classified depending on the type of surface studied. Many types of surface topographies are considered when frequency-based errors are studied. However, turned surface topography is not comprehensively studied when data processing errors caused by false estimation (definition and suppression) of selected surface features (form or noise) are analysed. In the present work, the effects of the application of various methods (regular Gaussian regression, robust Gaussian regression, and spline and fast Fourier Transform filters) for the suppression of high-frequency measurement noise from the raw measured data of turned surface topography are presented and compared. The influence and usage of commonly used available commercial software, e.g., autocorrelation function, power spectral density, and texture direction, which function on the values of areal surface topography parameters from selected (ISO 25178) standards, are also introduced. Analysed surfaces were measured with a stylus or via non-contact (optical–white light interferometry) methods. It was found that the characterisation of surface topography, based on the analysis of selected features, can be crucial in reducing measurement and data analysis errors when various filters are applied. Moreover, the application of common functions can be advantageous when feature-based studies are proposed for both profile and areal data processing.
Image Translation by Ad CycleGAN for COVID-19 X-Ray Images: A New Approach for Controllable GAN
Authors: Liang Zhaohui , Huang Jimmy Xiangji , Antani Sameer
Published: December 2022

We propose a new generative model named adaptive cycle-consistent generative adversarial network, or Ad CycleGAN to perform image translation between normal and COVID-19 positive chest X-ray images. An independent pre-trained criterion is added to the conventional Cycle GAN architecture to exert adaptive control on image translation. The performance of Ad CycleGAN is compared with the Cycle GAN without the external criterion. The quality of the synthetic images is evaluated by quantitative metrics including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Peak Signal-to-Noise Ratio (PSNR), Universal Image Quality Index (UIQI), visual information fidelity (VIF), Frechet Inception Distance (FID), and translation accuracy. The experimental results indicate that the synthetic images generated either by the Cycle GAN or by the Ad CycleGAN have lower MSE and RMSE, and higher scores in PSNR, UIQI, and VIF in homogenous image translation (i.e., Y → Y) compared to the heterogenous image translation process (i.e., X → Y). The synthetic images by Ad CycleGAN through the heterogeneous image translation have significantly higher FID score compared to Cycle GAN (p < 0.01). The image translation accuracy of Ad CycleGAN is higher than that of Cycle GAN when normal images are converted to COVID-19 positive images (p < 0.01). Therefore, we conclude that the Ad CycleGAN with the independent criterion can improve the accuracy of GAN image translation. The new architecture has more control on image synthesis and can help address the common class imbalance issue in machine learning methods and artificial intelligence applications with medical images.
A Novel Adaptive Sensor Fault Estimation Algorithm in Robust Fault Diagnosis
Authors: Pazera Marcin , Witczak Marcin
Published: December 2022

The paper deals with a robust sensor fault estimation by proposing a novel algorithm capable of reconstructing faults occurring in the system. The provided approach relies on calculating the fault estimation adaptively in every discrete time instance. The approach is developed for the systems influenced by unknown measurement and process disturbance. Such an issue has been handled with applying the commonly known H∞ approach. The novelty of the proposed algorithm consists of eliminating a difference between consecutive samples of the fault in an estimation error. This results in a easier way of designing the robust estimator by simplification of the linear matrix inequalities. The final part of the paper is devoted to an illustrative example with implementation to a laboratory two-rotor aerodynamical system.
Inline Quality Monitoring of Reverse Extruded Aluminum Parts with Cathodic Dip-Paint Coating (KTL)
Authors: Pierer Alexander , Hauser Markus , Hoffmann Michael , Naumann Martin , Wiener Thomas , de León Melvin Alexis Lara , Mende Mattias , Koziorek Jiří , Dix Martin
Published: December 2022

Perfectly coated surfaces are an essential quality feature in the automotive and consumer goods industries. They are the result of an optimized, controlled coating process. Because entire assemblies could be rejected if Out-of-Specification (OOS) parts are installed, this has a severe economic impact. This paper presents a novel, line-integrated multi-camera system with intelligent algorithms for anomaly detection on small KTL-coated aluminum parts. The system also aims to automatize the previously used human inspection to a sophisticated and automated vision system that efficiently detects defects and anomalies on coated parts.
Box–Behnken Design Used to Optimize the Simultaneous Quantification of Amitriptyline and Propranolol in Tablet Dosages by RP-HPLC-DAD Method and Their Stability Tests
Authors: Khalid Mohammad , Ahmad Sarfaraz
Published: December 2022

This study’s goal is to use a Box–Behnken design [BBD] methodology to create a new reverse-phase high-performance liquid chromatography diode-array detection [RP-HPLC-DAD] method for the simultaneous quantification of Amitriptyline and Propranolol in tablet dosages. The amitriptyline and propranolol standard drug peaks were obtained using a C-18 column with a dimension of 4.6 × 100 mm and a particle size packing of 2.5 µm at the retention time of 5.328 and 7.48 min, respectively. The mobile phase composition was a 75:25 mixture of methanol and 0.1 percent orthophosphoric acid, flowing at 1.0 mL/min at 26 °C. The peaks were identified at 257 nm after injecting 20 µL of the sample. An assay of the marketed tablets was performed, and the result was 101.33 and 99.4% for amitriptyline and propranolol, respectively, when compared to the standard calibration curve. Forced degradation investigations, such as acid, base, H2O2, and neutral condition, were performed. The results for both medications in term of % degradation were as follows: amitriptyline (16.07, 91.92, 26.98, and 0.64) and propranolol (15.84, 11.52, 9.09, and 3.62). According to the ICH criteria, the findings of the validation parameters were within an acceptable range. The new RP-HPLC-DAD method with BBD application is easy, accurate, and time-saving.
Pollution of the Environment and Pollen: A Review
Authors: Vasilevskaya Natalia
Published: December 2022

Bioindication of the environment is one of the actively developing directions of ecology. Information about pollutants and the level of environmental pollution can be obtained as a result of studying the biological reaction of plants to pollution. Ecological palynology is a new direction, when pollen of various woody and herbaceous species is used for bioindication of the level of environmental pollution and the presence of mutagens. The review considers the morphological variability of pollen, its fertility and viability under the influence of pollutants, the possibility of its use as a bioindicator of pollution of urban areas by emissions of vehicle transport and industry.
Declaration of the Sustainable Development Goals of Mining Companies and the Effect of Their Activities in Selected Areas
Authors: Woźniak Justyna , Pactwa Katarzyna , Szczęśniewicz Mateusz , Ciapka Dominika
Published: December 2022

The article addresses the issues of sustainable development in relation to a selected group of mining companies. The main objective of the article was to verify the companies’ declarations on the convergence of sustainable development goals (SDGs) and the assessment of their actual actions. In order to achieve this objective, the authors hypothesized and adopted, among others, a multi-stage logical thinking-based methodology. In addition, several research methods were used, i.e., a review of regulations and scientific articles, a qualitative literature review—extracting and collecting information, developing a categorization framework, and a comparative method based on a case study. The study started with extracting and collecting social and environmental information disclosed by Polish mining companies at the level of declaring SDGs targets (KGHM, LW Bogdanka, and JSW). Sourced from reports and company statements. In the next step, a leader (KGHM) was selected, and a comparison was made with a global enterprise (Barrick Gold), according to the adopted categorization framework for social initiatives. Common areas of both SDGs declarations and actions for these entities were identified, and measures of their implementation were suggested. Two main metrics were proposed for the social area, i.e., health and safety in relation to the financial performance of the companies and diversity in management and supervisory bodies. The role and importance of the prioritization of ESG (environmental, social, and governance) disclosures by the industry players are indicated.