bluuebunny/crossref_metadata_2025 huggingface dataset:
Light Weight, Flexible and Ultrathin PTFE@Ag and Ni@PVDF Composite Film for High-Efficient Electromagnetic Interference Shielding
Authors: Liu Hongbo , Huang Jiajie , Guo Bingzhi
Published: July 2023

Dopamine was used to modify polytetrafluoroethylene (PTFE) in order to obtain functional polydopamine (PDA) surface-modified PTFE microporous film (PTFE@PDA). Ag was deposited on the surface of PTFE@PDA using electroless plating in order to obtain Ag-wrapped PTFE@PDA film (PTFE@Ag). A liquid-phase chemical reduction method was employed to prepare nickel nanochains. A Ni@PVDF cast film was obtained by mechanically blended nickel nanochains and polyimide (PVDF). The above two films were hot pressed to give a flexible, ultra-thin, and highly effective electromagnetic shielding composite film with a “3+2” layered structure. IR, XRD, and TEM results showed the PTFE@PDA film surface was coated by a tight plating layer of Ag particles with a particle size of 100~200 nm. PTFE@Ag+Ni@PVDF composite film exhibited excellent electromagnetic shielding effectiveness, with the conductivity of 7507.5 S/cm and the shielding effectiveness of 69.03 dB in the X-band range. After a 2000-cycle bending, this value still remained at 51.90 dB. Furthermore, the composite film presented excellent tensile strength of 62.1 MPa. It has great potential for applications in flexible and wearable intelligent devices.
Dimensional Stability and Reproducibility of Varying FFF Models for Aligners in Comparison to Plaster Models
Authors: Lümkemann Nina , Klimenta Melisa , Hoffmann Moritz , Meinen John , Stawarczyk Bogna
Published: July 2023

To test the impact of FFF filaments, printing parameters, thermoforming foils, repeated thermoforming cycles, and type of jaw on the dimensional stability of FFF models for aligners and to compare them with plaster models, FFF models (maxilla, n = 48; mandible, n = 48) from two filaments (SIMPLEX aligner and Renfert PLA HT, both Renfert GmbH) were fabricated using four printing parameters (one, two, or three loops; four loops acted as the default) and conventional plaster models (n = 12) based on a young, female dentition. All models were thermoformed under pressure three times in total using two different thermoforming foils, namely 0.75 mm × 125 mm Ø aligner foil (CA Pro+ Clear Aligner, Scheu Dental) and 1.0 mm × 125 mm Ø Duran foil (Duran+, Scheu Dental). Aligner foil was heated at 220 °C for 25 s and Duran foil at 220 °C for 30 s. All models were scanned after fabrication as well as after each thermoforming cycle. The obtained STL datasets were analyzed using the local best-fit method (GOM Inspect Pro, Carl Zeiss Metrology GmbH). Data were analyzed using a Kolmogorov–Smirnov-test, a one-way ANOVA with post-hoc Scheffé, and a t-test (p < 0.05). The dimensional stability of the models was most strongly affected by the printing parameters (number of loops; ηp2 = 0.768, p < 0.001) followed by the thermoforming foil used (ηp2 = 0.663, p < 0.001) as well as the type of model (ηp2 = 0.588, p < 0.001). In addition, various interactions showed an influence on the dimensional stability (ηp2 = 0.041–0.386, p < 0.035). SIMPLEX maxillary models (default; four loops), thermoformed using aligner foil, showed higher deformation stability than did plaster models. These initial FFF models provide comparable precision to plaster models, but the dimensional stability of the FFF models, in contrast to that of plaster models, decreases with increasing numbers of thermoforming cycles.
First Conclusions on Damage Behaviour of Recycled Carbon Staple Fibre Yarn Using X-ray and Acoustic Emission Techniques
Authors: Becker Christian , Hausmann Joachim , Krummenacker Janna , Motsch-Eichmann Nicole
Published: July 2023

This paper presents the first results on the characterisation of the damage behaviour of recycled carbon fibre (rCF) rovings manufactured into unidirectionally (UD) reinforced plates. In the first step, the mechanical properties of several material combinations were determined by mechanical tests (tensile, flexural, compression). This proves the usability of the material for load-bearing structures. For example, a tensile modulus of up to 80 GPa and a tensile strength of 800 MPa were measured. Subsequently, the fracture surface was analysed by scanning electron microscopy (SEM) to characterise the fibre–matrix adhesion and to obtain first indications of possible failure mechanisms. Despite the high mechanical properties, poor fibre–matrix adhesion was found for all matrix systems. In situ X-ray microscopy tests were then performed on smaller specimens under predefined load levels as transverse tensile and bending tests. The results provide further predictions of the failure behaviour and can be compared to the previous test results. The three-dimensional scan reconstruction results were used to visualise the failure behaviour of the staple fibres in order to detect fibre pull-out and fibre or inter-fibre failure and to draw initial conclusions about the damage behaviour in comparison to conventional fibre composites. In particular, a benign failure behaviour in the transverse tensile test was demonstrated with this procedure. In addition, first concepts and tests for the integration of AE analysis into the in situ setup of the X-ray microscope are presented.
Natural Solid-State Hydrogel Electrolytes Based on 3D Pure Cotton/Graphene for Supercapacitor Application
Authors: Mohammed Nujud Badawi , Batoo Khalid Mujasam , Hussain Sajjad , Subramaniam Ramesh , Kasi Ramesh , Bhuyan Mrutunjaya , Imran Ahamad , Muthuramamoorthy Muthumareeswaran
Published: July 2023

A conductive cotton hydrogel with graphene and ions can come into contact with electrodes in solid electrolytes at the molecular level, leading to a more efficient electrochemical process in supercapacitors. The inherently soft nature of cotton mixed with hydrogel provides superior flexibility of the electrolyte, which benefits the devices in gaining high flexibility. Herein, we report on the current progress in solid-state hydrogel electrolytes based on 3D pure cotton/graphene and present an overview of the future direction of research. The ionic conductivity of a complex hydrogel significantly increased by up to 13.9 × 10−3 S/cm at 25 °C, due to the presence of graphene, which increases ionic conductivity by providing a smooth pathway for the transport of charge carriers and the polymer. Furthermore, the highest specific capacitance of 327 F/g at 3 mV/s was achieved with cyclic voltammetry measurement and a galvanostatic charge–discharge measurement showed a peak value of 385.4 F/g at 100 mA/g current density. Furthermore, an electrochemical analysis demonstrated that a composite cotton/graphene-based hydrogel electrolyte is electrically stable and could be used for the design of next-generation supercapacitors.
Double Photoionization of Nitrosyl Chloride by Synchrotron Radiation in the 24–70 eV Photon Energy Range
Authors: Schio Luca , Alagia Michele , Richter Robert , Zhaunerchyk Vitali , Stranges Stefano , Pirani Fernando , Vecchiocattivi Franco , Parriani Marco , Falcinelli Stefano
Published: July 2023

The behavior of nitrosyl chloride (ClNO) exposed to ionizing radiation was studied by direct probing valence-shell electrons in temporal coincidence with ions originating from the fragmentation process of the transient ClNO2+. Such a molecular dication was produced by double photoionization with synchrotron radiation in the 24–70 eV photon energy range. The experiment has been conducted at the Elettra Synchrotron Facility of Basovizza (Trieste, Italy) using a light beam linearly polarized with the direction of the polarization vector parallel to the ClNO molecular beam axis. ClNO molecules crossing the photon beam at right angles in the scattering region are generated by effusive expansion and randomly oriented. The threshold energy for the double ionization of ClNO (30.1 ± 0.1 eV) and six dissociation channels producing NO+/Cl+, N+/Cl+, N+/O+, O+/Cl+, ClN+/O+, NO+/Cl2+ ion pairs, with their relative abundance and threshold energies, have been measured.
Evaluation of Silk Fibroin/Gellan Gum Hydrogels with Controlled Molecular Weight through Silk Fibroin Hydrolysis for Tissue Engineering Application
Authors: Park Sunjae , Kim Soo-In , Choi Joo-Hee , Kim Se-Eun , Choe Seung-Ho , Son Youngjun , Kang Tae-woong , Song Jeong-Eun , Khang Gilson
Published: July 2023

Hydrogel is a versatile material that can be manipulated to achieve the desired physicochemical properties, such as stiffness, pore size, and viscoelasticity. Traditionally, these properties have been controlled through parameters such as concentration and pH adjustments. In this study, we focused on exploring the potential of hydrolyzed silk fibroin (HSF) as a molecular weight-modulating agent to control the physicochemical properties of double-composite hydrogels. We developed a synergistic dual-crosslinked hydrogel by combining ionically crosslinked silk fibroin with gellan gum (GG). The hydrolysis of silk fibroin not only enhanced its hydrophilicity but also enabled adjustments in its mechanical properties, including the pore size, initial modulus elasticity, and relaxation time. Moreover, biocompatibility assessments based on cell viability tests confirmed the potential of these hydrogels as biocompatible materials. By highlighting the significance of developing an HSF/GG dual-crosslinked hydrogel, this study contributes to the advancement of novel double-composite hydrogels with remarkable biocompatibility. Overall, our findings demonstrate the capability of controlling the mechanical properties of hydrogels through molecular weight modulation via hydrolysis and highlight the development of a biocompatible HSF/GG dual-crosslinked hydrogel with potential biomedical applications.
Correction: Bassani, D.; Moro, S. Past, Present, and Future Perspectives on Computer-Aided Drug Design Methodologies. Molecules 2023, 28, 3906
Authors: Bassani Davide , Moro Stefano
Published: July 2023

In the published publication [...]
Dietary Strategies for Complementary Feeding between 6 and 24 Months of Age: The Evidence
Authors: Harrison Leila , Padhani Zahra , Salam Rehana , Oh Christina , Rahim Komal , Maqsood Maria , Ali Anna , Charbonneau Kimberly , Keats Emily C. , Lassi Zohra S. , Imdad Aamer , Owais Aatekah , Das Jai , Bhutta Zulfiqar A.
Published: July 2023

Suboptimal complementary feeding practices remain highly prevent. This review aims to comprehensively synthesize new emerging evidence on a set of topics related to the selection and consumption of complementary foods. We synthesized evidence related to five key topics focused on nutritional interventions that target the complementary feeding period, based on four systematic reviews that include updated evidence to February 2022. While there have been many studies examining interventions during the complementary feeding period, there is an overall lack of relevant information through which to draw conclusions on the ideal feeding schedule by food type. Similarly, few studies have examined the effects of animal milk versus infant formula for non-breastfed infants (6–11 months), though those that did found a greater risk of anemia among infants who were provided cow’s milk. This review highlights a number of interventions that are successful at improving micronutrient status and anthropometry during the complementary feeding period, including fortified blended foods, locally and commercially produced supplementary foods, and small-quantity lipid-based nutrient supplements. Complementary feeding education for caregivers can also be used to improve nutrition outcomes among infants in both food secure and insecure populations.
Fermented Rice Bran Supplementation Inhibits LPS-Induced Osteoclast Formation and Bone Resorption in Mice
Authors: Noguchi Takahiro , Kitaura Hideki , Marahleh Aseel , Agista Afifah Zahra , Ohsaki Yusuke , Shirakawa Hitoshi , Mizoguchi Itaru
Published: July 2023

Fermented rice bran (FRB) is known to have numerous beneficial bioactivities, amongst which is its anti-inflammatory properties when used as a supplement. To determine its effects, we examined osteoclastogenesis and bone resorption caused by injections of lipopolysaccharide (LPS), using mice with and without FRB supplementation. The results were favorable: those that received FRB showed reduced osteoclast numbers and bone resorption compared to those with the control diet. Notably, receptor activator of NF-κB ligand (RANKL) and tumor necrosis factor-α (TNF-α) mRNA levels were shown to be lower in the LPS-treated animals with FRB supplementation. FRB’s inhibitory effect on RANKL- and TNF-α-induced osteoclastogenesis was further confirmed in vitro. In culture, macrophages exhibited decreased TNF-α mRNA levels when treated with FRB extract and LPS versus treatment with LPS alone, but there was no significant change in RANKL levels in osteoblasts. We can conclude that FRB supplementation dampens the effect of LPS-induced osteoclastogenesis and bone resorption by controlling TNF-α expression in macrophages and the direct inhibition of osteoclast formation.
Effects of FODMAPs and Gluten on Gut Microbiota and Their Association with the Metabolome in Irritable Bowel Syndrome: A Double-Blind, Randomized, Cross-Over Intervention Study
Authors: Nordin Elise , Hellström Per M. , Dicksved Johan , Pelve Erik , Landberg Rikard , Brunius Carl
Published: July 2023

Background: A mechanistic understanding of the effects of dietary treatment in irritable bowel syndrome (IBS) is lacking. Our aim was therefore to investigate how fermentable oligo- di-, monosaccharides, and polyols (FODMAPs) and gluten affected gut microbiota and circulating metabolite profiles, as well as to investigate potential links between gut microbiota, metabolites, and IBS symptoms. Methods: We used data from a double-blind, randomized, crossover study with week-long provocations of FODMAPs, gluten, and placebo in participants with IBS. To study the effects of the provocations on fecal microbiota, fecal and plasma short-chain fatty acids, the untargeted plasma metabolome, and IBS symptoms, we used Random Forest, linear mixed model and Spearman correlation analysis. Results: FODMAPs increased fecal saccharolytic bacteria, plasma phenolic-derived metabolites, 3-indolepropionate, and decreased isobutyrate and bile acids. Gluten decreased fecal isovalerate and altered carnitine derivatives, CoA, and fatty acids in plasma. For FODMAPs, modest correlations were observed between microbiota and phenolic-derived metabolites and 3-indolepropionate, previously associated with improved metabolic health, and reduced inflammation. Correlations between molecular data and IBS symptoms were weak. Conclusions: FODMAPs, but not gluten, altered microbiota composition and correlated with phenolic-derived metabolites and 3-indolepropionate, with only weak associations with IBS symptoms. Thus, the minor effect of FODMAPs on IBS symptoms must be weighed against the effect on microbiota and metabolites related to positive health factors.
The Glutaminase-1 Inhibitor [11C-carbony]BPTES: Synthesis and Positron Emission Tomography Study in Mice
Authors: Zhang Yiding , Kumata Katsushi , Xie Lin , Kurihara Yusuke , Ogawa Masanao , Kokufuta Tomomi , Nengaki Nobuki , Zhang Ming-Rong
Published: July 2023

Bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl)ethyl sulfide (BPTES) is a selective inhibitor of glutaminase-1 (GLS1), consequently inhibiting glutaminolysis. BPTES is known for its potent antitumor activity and plays a significant role in senescent cell removal. In this study, we synthesized [11C-carbonyl]BPTES ([11C]BPTES) as a positron emission tomography (PET) probe for the first time and assessed its biodistribution in mice using PET. [11C]BPTES was synthesized by the reaction of an amine precursor () with [11C-carbonyl]phenylacetyl acid anhydride ([11C]2), which was prepared from [11C]CO2 and benzyl magnesium chloride, followed by in situ treatment with isobutyl chloroformate. The decay-corrected isolated radiochemical yield of [11C]BPTES was 9.5% (based on [11C]CO2) during a synthesis time of 40 min. A PET study with [11C]BPTES showed high uptake levels of radioactivity in the liver, kidney, and small intestine of mice.
Dulaglutide Ameliorates Intrauterine Adhesion by Suppressing Inflammation and Epithelial–Mesenchymal Transition via Inhibiting the TGF-β/Smad2 Signaling Pathway
Authors: Wang Yifan , Wang Yixiang , Wu Yang , Wang Yiqing
Published: July 2023

Intrauterine adhesion (IUA) is a common gynecological disease with limited therapeutic options. Dulaglutide is a long-acting glucagon-like peptide-1 (GLP-1) analog with some anti-fibrotic and anti-inflammatory properties; however, its action on IUA remains uncertain. The purpose of the experiments in this study was to explore the effect of dulaglutide on IUA and to elucidate its mechanism to provide new ideas for the clinical treatment of IUA. An IUA mouse model was established via mechanical curettage and inflammation induction; mice received subcutaneous injection with three doses of dulaglutide once a day for two weeks (treatment) or equal amounts of sterile ddH2O (control), and sham-operated mice were treated similarly to the control mice. Mice were sacrificed, and uterine tissues were subjected to hematoxylin and eosin (H&E) and Masson’s trichrome staining for histomorphological and pathological analyses and real-time quantitative polymerase chain reaction (RT-qPCR) and Western blotting (WB) for gene and protein expression analyses. Dulaglutide improved the shape of the uterine cavity, increased endometrial thickness and the number of glands, and significantly reduced the area of collagen fiber deposition in the endometrium. It significantly reduced collagen type I A 1 (COL1A1), interleukin-1beta (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), C-C motif chemokine ligand 2 (CCL2), F4/80 (macrophage), vimentin and transforming growth factor-beta (TGF-β) mRNA levels and COL1A1, IL-1β, IL-6, TNF-α, F4/80, vimentin, E-cadherin, TGF-β, and p-Smad2 protein expression levels. This study demonstrates that dulaglutide reduces inflammatory responses by inhibiting M1 macrophage polarization and inflammatory factor release and may ameliorate fibrosis by inhibiting epithelial–mesenchymal transition (EMT) via TGF-β/Smad2 signaling.
An Atomistic Study of the Tensile Deformation of Carbon Nanotube–Polymethylmethacrylate Composites
Authors: Raj Anshu , Alvi Sk Md Ahnaf Akif , Islam Khayrul , Motalab Mohammad , Xu Shuozhi
Published: July 2023

There has been growing interest in polymer/carbon nanotube (CNT) composites due to an exceptional enhancement in mechanical, structural, thermal, and electronic properties resulting from a small percentage of CNTs. However, the performance of these composites is influenced by the type of polymer used. PMMA is a polymer of particular interest among many other polymers because of its biomaterial applications due to its biocompatibility, non-toxicity, and non-biodegradability. In this research, we utilized a reactive force field to conduct molecular dynamics simulations to investigate changes in the mechanical properties of single-walled carbon nanotube (SWCNT)-reinforced Poly (methyl methacrylate) (PMMA) matrix composites. To explore the potential of SWCNT-reinforced PMMA composites in these applications, we conducted simulations with varying CNT diameters (0.542–1.08 nm), CNT volume fractions (8.1–16.5%), and temperatures (100 K–700 K). We also analyzed the dependence of Young’s modulus and interaction energy with different CNT diameters, along with changes in fracture toughness with varying temperatures. Our findings suggest that incorporating a small amount of SWCNT into the PMMA polymer matrix could significantly enhance the mechanical properties of the resulting composite. It is also found that the double-walled carbon nanotube has roughly twice the tensile strength of SWCNT, while maintaining the same simulation cell dimensions.
Effect of Grafting Conditions on the Interfacial Properties of Silane Modified Wood Veneer/PE Film Plywood
Authors: Chang Liang , Wang Yuanwu , Chen Xueqi , Ren Yiping , Luo Xiaoxi
Published: July 2023

In order to elucidate the importance of grafting in the compatibilization process of silane coupling agents, poplar veneer was treated with silane coupling agents and grafted under different heating conditions. The treated veneers were used composited with PE film to prepare different plywood samples. XPS and WCA were used to analyze the effect of grafting conditions on the surface properties of the silane-treated veneer. The results showed that free silanols can physically be adsorbed onto all silane-treated veneer surfaces, forming hydrogen–Si–O–Si– bonds and therefore increasing the water contact angle. Only under heating conditions could the –Si–O–Si– be converted into covalent –Si–O–C– bonds, which helped to improve the bonding strength. When silane-treated veneer was grafted at 120 °C for 90 min, the tensile shear strength of plywood reached 1.03 MPa, meeting the requirements of GB/T 9846.3-2004 for outdoor materials. Enhanced interlock between silane-modified veneer and PE film was observed under the optimal grafting condition by SEM. The better interface structure allowed improvement of thermal stability. DMA results showed that the retention rate in storage modulus at 130 °C was 60% for the grafted sample, while the retention rate for the ungrafted sample was only 31%.
Landslide Identification Method Based on the FKGRNet Model for Remote Sensing Images
Authors: Xu Bing , Zhang Chunju , Liu Wencong , Huang Jianwei , Su Yujiao , Yang Yucheng , Jiang Weijie , Sun Wenhao
Published: July 2023

Currently, researchers commonly use convolutional neural network (CNN) models for landslide remote sensing image recognition. However, with the increase in landslide monitoring data, the available multimodal landslide data contain rich feature information, and existing landslide recognition models have difficulty utilizing such data. A knowledge graph is a linguistic network knowledge base capable of storing and describing various entities and their relationships. A landslide knowledge graph is used to manage multimodal landslide data, and by integrating this graph into a landslide image recognition model, the given multimodal landslide data can be fully utilized for landslide identification. In this paper, we combine knowledge and models, introduce the use of landslide knowledge graphs in landslide identification, and propose a landslide identification method for remote sensing images that fuses knowledge graphs and ResNet (FKGRNet). We take the Loess Plateau of China as the study area and test the effect of the fusion model by comparing the baseline model, the fusion model and other deep learning models. The experimental results show that, first, with ResNet34 as the baseline model, the FKGRNet model achieves 95.08% accuracy in landslide recognition, which is better than that of the baseline model and other deep learning models. Second, the FKGRNet model with different network depths has better landslide recognition accuracy than its corresponding baseline model. Third, the FKGRNet model based on feature splicing outperforms the fused feature classifier in terms of both accuracy and F1-score on the landslide recognition task. Therefore, the FKGRNet model can make fuller use of landslide knowledge to accurately recognize landslides in remote sensing images.
Leveraging CNNs for Panoramic Image Matching Based on Improved Cube Projection Model
Authors: Gao Tian , Lan Chaozhen , Wang Longhao , Huang Wenjun , Yao Fushan , Wei Zijun
Published: July 2023

Three-dimensional (3D) scene reconstruction plays an important role in digital cities, virtual reality, and simultaneous localization and mapping (SLAM). In contrast to perspective images, a single panoramic image can contain the complete scene information because of the wide field of view. The extraction and matching of image feature points is a critical and difficult part of 3D scene reconstruction using panoramic images. We attempted to solve this problem using convolutional neural networks (CNNs). Compared with traditional feature extraction and matching algorithms, the SuperPoint (SP) and SuperGlue (SG) algorithms have advantages for handling images with distortions. However, the rich content of panoramic images leads to a significant disadvantage of these algorithms with regard to time loss. To address this problem, we introduce the Improved Cube Projection Model: First, the panoramic image is projected into split-frame perspective images with significant overlap in six directions. Second, the SP and SG algorithms are used to process the six split-frame images in parallel for feature extraction and matching. Finally, matching points are mapped back to the panoramic image through coordinate inverse mapping. Experimental results in multiple environments indicated that the algorithm can not only guarantee the number of feature points extracted and the accuracy of feature point extraction but can also significantly reduce the computation time compared to other commonly used algorithms.
Crop Mapping without Labels: Investigating Temporal and Spatial Transferability of Crop Classification Models Using a 5-Year Sentinel-2 Series and Machine Learning
Authors: Rusňák Tomáš , Kasanický Tomáš , Malík Peter , Mojžiš Ján , Zelenka Ján , Sviček Michal , Abrahám Dominik , Halabuk Andrej
Published: July 2023

Multitemporal crop classification approaches have demonstrated high performance within a given season. However, cross-season and cross-region crop classification presents a unique transferability challenge. This study addresses this challenge by adopting a domain generalization approach, e.g., by training models on multiple seasons to improve generalization to new, unseen target years. We utilize a comprehensive five-year Sentinel-2 dataset over different agricultural regions in Slovakia and a diverse crop scheme (eight crop classes). We evaluate the performance of different machine learning classification algorithms, including random forests, support vector machines, quadratic discriminant analysis, and neural networks. Our main findings reveal that the transferability of models across years differs between regions, with the Danubian lowlands demonstrating better performance (overall accuracies ranging from 91.5% in 2022 to 94.3% in 2020) compared to eastern Slovakia (overall accuracies ranging from 85% in 2022 to 91.9% in 2020). Quadratic discriminant analysis, support vector machines, and neural networks consistently demonstrated high performance across diverse transferability scenarios. The random forest algorithm was less reliable in generalizing across different scenarios, particularly when there was a significant deviation in the distribution of unseen domains. This finding underscores the importance of employing a multi-classifier analysis. Rapeseed, grasslands, and sugar beet consistently show stable transferability across seasons. We observe that all periods play a crucial role in the classification process, with July being the most important and August the least important. Acceptable performance can be achieved as early as June, with only slight improvements towards the end of the season. Finally, employing a multi-classifier approach allows for parcel-level confidence determination, enhancing the reliability of crop distribution maps by assuming higher confidence when multiple classifiers yield similar results. To enhance spatiotemporal generalization, our study proposes a two-step approach: (1) determine the optimal spatial domain to accurately represent crop type distribution; and (2) apply interannual training to capture variability across years. This approach helps account for various factors, such as different crop rotation practices, diverse observational quality, and local climate-driven patterns, leading to more accurate and reliable crop classification models for nationwide agricultural monitoring.
Heterogeneous Network Switching Strategy Based on Communication Blind Area Dwell Time
Authors: Zhang Cheng , Tang Yanfeng , Wang Xiuzhuo , Zhang Yan , Li Xiuyang
Published: July 2023

The limitation of indoor visible light coverage and the attenuation of its signal when propagating in line-of-sight has seriously affected the stable communication of receiving devices when users move randomly and also aggravated the power consumption of visible light networking systems. According to the above situation, on the basis of the heterogeneous networking of visible light communication (VLC) and RF communication integration, this article proposes a horizontal–vertical collaborative handover strategy based on the communication blind area dwell time (CBD-HVHO). Combining asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) technology with networking handover technology, ACO-OFDM is used to determine the indoor communication blind area by calculating the bit error rate (BER) value at the signal receiver while reducing the multipath interference generated by visible light signals during channel transmission. To achieve this, set the communication blind channel interruption time as the threshold time, compare the communication blind area dwell time with the threshold time, and finally combine the horizontal and vertical collaborative handover strategies based on the communication blind area dwell time. The simulation results show that the handover probability is 0.009, the average number of handovers is 1.006, and the average network throughput is 195.2826 Mbps. Compared with the previously proposed immediate vertical handover (I-VHO) scheme and the dwell vertical handover (D-VHO) scheme, the communication stability is significantly improved, and the power consumption of the network system is reduced to a certain extent.
Analysis of Friction Noise Mechanism in Lead Screw System of Autonomous Vehicle Seats and Dynamic Instability Prediction Based on Deep Neural Network
Authors: Nam Jaehyeon , Kim Soul , Ko Dongshin
Published: July 2023

This study investigated the squeal mechanism induced by friction in a lead screw system. The dynamic instability in the friction noise model of the lead screw was derived through a complex eigenvalue analysis via a finite element model. A two degree of freedom model was described to analyze the closed solutions generated in the lead screw, and the friction noise sensitivity was examined. The analysis showed that the main source of friction noise in the lead screw was the bending mode pair, and friction-induced instability occurred when the ratio of the stiffness of the bending pair modes was 0.9–1. We also built an architecture to predict multiple outputs from a single model using deep neural networks and demonstrated that friction-induced instability can be predicted by deep neural networks. In particular, instability with nonlinearity was predicted very accurately by deep neural networks with a maximum absolute difference of about 0.035.
Near-Field Beamforming Algorithms for UAVs
Authors: Zhang Yinan , Wang Guangxue , Peng Shirui , Leng Yi , Yu Guowen , Wang Bingqie
Published: July 2023

This study presents three distributed beamforming algorithms to address the challenges of positioning and signal phase errors in unmanned aerial vehicle (UAV) arrays that hinder effective beamforming. Firstly, the array’s received signal phase error model was analyzed under near-field conditions. In the absence of navigation data, a beamforming algorithm based on the Extended Kalman Filter (EKF) was proposed. In cases where navigation data were available, Taylor expansion was utilized to simplify the model, the non-Gaussian noise of the compensated received signal phase was approximated to Gaussian noise, and the noise covariance matrix in the Kalman Filter (KF) was estimated. Then, a beamforming algorithm based on KF was developed. To further estimate the Gaussian noise distribution of the received signal phase, the noise covariance matrix was iteratively estimated using unscented transformation (UT), and here, a beamforming algorithm based on the Unscented Kalman Filter (UKF) was proposed. The proposed algorithms were validated through simulations, illustrating their ability to suppress the malign effects of errors on near-field UAV array beamforming. This study provides a reference for the implementation of UAV array beamforming under varying conditions.
A DDoS Detection Method Based on Feature Engineering and Machine Learning in Software-Defined Networks
Authors: Liu Zhenpeng , Wang Yihang , Feng Fan , Liu Yifan , Li Zelin , Shan Yawei
Published: July 2023

Distributed denial-of-service (DDoS) attacks pose a significant cybersecurity threat to software-defined networks (SDNs). This paper proposes a feature-engineering- and machine-learning-based approach to detect DDoS attacks in SDNs. First, the CSE-CIC-IDS2018 dataset was cleaned and normalized, and the optimal feature subset was found using an improved binary grey wolf optimization algorithm. Next, the optimal feature subset was trained and tested in Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (k-NN), Decision Tree, and XGBoost machine learning algorithms, from which the best classifier was selected for DDoS attack detection and deployed in the SDN controller. The results show that RF performs best when compared across several performance metrics (e.g., accuracy, precision, recall, F1 and AUC values). We also explore the comparison between different models and algorithms. The results show that our proposed method performed the best and can effectively detect and identify DDoS attacks in SDNs, providing a new idea and solution for the security of SDNs.
Study on Surrounding Rock Failure Law of Gob-Side Entry Based on the Second Invariant of Deviatoric Stress
Authors: Liu Xiaozhou , Xu Hu , Li Ben , He Wenrui , Liang Xian , Xia Hongchun
Published: July 2023

The second invariant of deviatoric stress of the coal and rock mass is closely related to the distortion energy driving the deformation and failure of the surrounding rock. Based on the second invariant of deviatoric stress, this study built a global model of gob-side entry with different widths of the coal pillar through numerical analysis, and compared and analyzed the evolution law of the surrounding rock distortion energy, plastic location state, and roadway deformation with the width of the coal pillar. This study concluded that the peak distortion energy in the virgin coal rib and the roof and floor of the gob-side entry gradually increases with the reduction in the coal pillar width. When the coal pillar width is 5 m, the second invariant peak value of deviatoric stress in the virgin coal rib reaches the maximum of 294.8 MPa2. When the width of the coal pillar is reduced from 30 m to 5 m, the second invariant of the deviatoric stress in the side of the coal pillar and the roof and floor of the side presents the law of first increasing and then decreasing. The greater the damage degree of the coal pillar, the smaller the distortion energy it contains. The distortion energy is the key factor in driving the deformation and failure of the surrounding rock. The greater the distortion energy, the greater the deformation degree of the surrounding rock, the more vulnerable it is to external mining stress disturbance, and the greater the difficulty in controlling the stability of the roadway-surrounding rock.
Evaluation of Anti-Aging Effect in Biochar-Modified Bitumen
Authors: Celauro Clara , Teresi Rosalia , Dintcheva Nadka Tz.
Published: July 2023

Increasing environmental awareness has led to a great research effort towards the formulation of increasingly sustainable pavements, mainly by developing bituminous mixtures incorporating waste materials. Furthermore, some waste materials have been proved to be useful for enhancing the performance of road bitumen and bituminous products, so their use is a potential solution for ensuring environmental, economic, and also technical benefits. Amongst the different wastes to be used for bitumen modification, a possible one is that obtained via the pyrolysis of biomass, named biochar. In the research reported here, a selected biochar was added to bitumen to verify the possibility of improving bitumen performance in terms of photo-oxidation resistance, which is a major problem in urban areas where black flexible pavements contribute to the urban heat island effect. Different biochar amounts were selected, and two different aging methods were performed: short-term aging and UVB aging resistance; they were monitored using rheological and spectroscopic analysis. The structural changes in bitumen in terms of carbonyl and hydroxyl accumulation were observed at various UV irradiation times. All the experimental data indicate that the use of biochar can have a positive effect on the UV resistance of bitumen, lowering its photo-oxidation tendency. This may lead to reductions in use of natural, non-renewable materials, since intervention maintenance may be scheduled at longer terms.
Transcending Time and Space: Survey Methods, Uncertainty, and Development in Human Migration Prediction
Authors: Pu Tongzheng , Huang Chongxing , Yang Jingjing , Huang Ming
Published: July 2023

As a fundamental, holistic, and strategic issue facing human society, human migration is a key factor affecting the development of countries and cities, given the constantly changing population numbers. The fuzziness of the spatiotemporal attributes of human migration limits the pool of open-source data for human migration prediction, leading to a relative lag in human migration prediction algorithm research. This study expands the definition of human migration research, reviews the progress of research into human migration prediction, and classifies and compares human migration algorithms based on open-source data. It also explores the critical uncertainty factors restricting the development of human migration prediction. Based on the analysis, there is no “best” migration prediction model, and data are key to forecasting human migration. Social media’s popularity and its increase in data have enabled the application of artificial intelligence in population migration prediction, which has attracted the attention of researchers and government administrators. Future research will aim to incorporate uncertainty into the predictive analysis framework, and explore the characteristics of population migration behaviors and their interactions. The integration of machine-learning and traditional data-driven models will provide a breakthrough for this purpose.
Less Is More: Preventing Household Food Waste through an Integrated Mobile Application
Authors: Castro Cynthia , Chitikova Ekaterina , Magnani Giulia , Merkle Julian , Heitmayer Maxi
Published: July 2023

This paper proposes an intervention using personal Information and Communication Technologies (ICTs) to help consumers reduce household food waste. Across the global food-supply chain, about one-third of all edible food is lost or wasted each year, and this issue is particularly pressing in in the Global North. We present a detailed overview of consumer activity in relation to household food waste using the Multilayered Installation Design Approach (MID). We trace consumer activity along the acquisition, storage, consumption, and disposal stages and provide a comprehensive set of recommendations on how to use personal ICTs to reduce household food waste rooted in the extant empirical literature. We then develop a concept for an application that integrates the full suite of potential avenues for intervention in one place.
Spatiotemporal Variation in Carbon Emissions in China’s Tourism Industry during the COVID-19 Pandemic and Ecological Compensation Mechanism
Authors: Chen Bo , Tang Wenling , Chen Zhida , Yang Xiyuan
Published: July 2023

The COVID-19 pandemic has significantly impacted the tourism industry while providing a unique opportunity for ecological restoration in tourist attractions. This study highlights the variations in carbon emissions and the corresponding ecological compensation in China’s tourism industry across 31 provinces before and after the COVID-19 outbreak in 2019–2020. The findings reveal a substantial decline in carbon emissions stemming from China’s tourism industry in 2020, reducing by 207.0461 million tons, a remarkable 74.71% decrease compared to 2019. Shanxi exhibited the most significant reduction among the provinces, whereas Shanghai had the most minor decrease. Additionally, natural scenic areas in China experienced a 3.4% growth in carbon sinks, with an increase of 76.6271 million tons in 2020. Henan, Hubei, and Guangxi were the provinces with the highest increments. However, some provinces witnessed a decline in carbon sinks due to climate change, with Zhejiang Province, Inner Mongolia Autonomous Region, and Jilin Province displaying the most substantial reductions in 2020 compared to 2019. Furthermore, the estimated ecological compensation for the tourism industry in all 31 provinces of China amounts to approximately CNY 6.948 billion. This study provides valuable insights into carbon emission reduction in the tourism industry, ecological compensation mechanisms during unexpected public events, and the sustainable development of nature-based tourist destinations. To advance the goals of achieving peak carbon emissions and carbon neutrality, future research should prioritize tracking and classifying tourism-related carbon emissions, precisely classifying carbon sinks in natural scenic areas, and establishing interprovincial ecological compensation mechanisms.
The Impact of Green Finance on Carbon Emissions in China: An Energy Consumption Optimization Perspective
Authors: Xu Weicheng , Feng Xiaoyi , Zhu Yiying
Published: July 2023

From the perspective of energy consumption optimization, this paper studies the impact of green finance on carbon emissions in China. Firstly, based on the theoretical perspective, this paper explores the mechanism and path by which green finance influences carbon emissions, and analyzes the role of energy consumption in this process. Then, this paper utilizes the STIRPAT model, chain multiple mediation effect model and panel threshold model to empirically analyze the influence of green finance on carbon emissions, using provincial data from China from 2005 to 2019. The results are as follows: (1) Green finance significantly reduces carbon emissions. After accounting for potential endogeneity, this conclusion is still valid. The heterogeneity test reveals that the inhibitory effect is more remarkable in northern regions, high-carbon emission regions and energy-rich regions. (2) The results of the bootstrap test reveal that at the national level, green finance decreases carbon emissions through three paths: green technological innovation, ecological evolution of the industrial structure and green technological innovation facilitating ecological evolution of the industrial structure. Furthermore, in energy-rich regions, green finance significantly inhibits carbon emissions through all three paths, while in energy-poor regions, green finance reduces carbon emissions only through green technological innovation. (3) There is a nonlinear relationship between green finance and carbon emissions. Specifically, regardless of energy intensity or energy consumption structure, only when it is below the threshold can green finance significantly inhibit carbon emissions. Thus, realizing energy consumption optimization is an effective way to ensure the carbon emission reduction effect of green finance.
Presenting a Novel Evolutionary Method for Reserve Constrained Multi-Area Economic/Emission Dispatch Problem
Authors: Lotfi Hossein , Nikkhah Mohammad Hasan
Published: July 2023

Economic dispatch (ED) attempts to find the most cost-effective combination of power generation units while meeting operational constraints. Another problem that can’t be resolved by standard economic dispatch problems is figuring out the method of generating dispatch that would be most cost-effective in meeting the local demand without exceeding the tie-line capacity. Making a trade-off between fuel costs and environmental concerns, a contentious problem in industrialized countries, seems essential. As a result, this study introduces a multi-objective approach for different ED problems, such as multi-area emission economic dispatch (MAEED) and reserve constrained multi-area emission economic dispatch (RCMAEED), when there are real-world restrictions present, like the valve point effect (VPE), prohibited operating zones (POZs), multi-fuel operation (MFO), and ramp-rate (RR) restrictions. In this study, the generation cost and emissions are taken into consideration as objective functions. Since the MAED problem in the power system is inherently nonlinear, adding the aforementioned restrictions makes the problem even more challenging. To address the complexity of the multi-objective optimization problem, the modified grasshopper optimization (MGO) algorithm, based on the chaos mechanism, is proposed in this paper. The proposed method has been tested on a four-area power system with sixteen electrical generators, and the results are contrasted with those of previous evolutionary techniques. Based on the results, it can be concluded that using the proposed MGO method to solve the MAED and RCMAED problems will result in generation costs that are around $300 and $600 less than using the MPSO and PSO methods, respectively. Also, the proposed MGO method has reduced emission levels by roughly 30% as compared to the GO method in order to solve the RCMAEED problem.
Evaluating the Spatial Quality of Urban Living Streets: A Case Study of Hengyang City in Central South China
Authors: Duan Jingpeng , Liao Jianjun , Liu Jing , Gao Xiaoxuan , Shang Ailin , Huang Zhihuan
Published: July 2023

Evaluating the spatial quality of a living street entails identifying and assessing the outdoor space that influences residents’ leisure and recreation, which may contribute to urban renewal. The application of multi-source data and deep learning technology enables an objective evaluation of large-scale spatial quality as opposed to the traditional questionnaire survey or experts’ subjective evaluation. Based on street view images, points of interest, and road network data, this study developed subjective and objective evaluation indicators for the central city of Hengyang using semantic segmentation and ArcGIS spatial analysis. This study then assigned weights to each indicator and calculated the spatial quality score for living streets. In addition, the subjective evaluations of the street view images were compared to test and verify the validation of the objective evaluation model. Finally, the study analyzed the accessibility within 500 m of the study area using Spatial Syntax and ArcGIS to overlay the low spatial quality score with the highest accessibility to identify the streets with the highest priority in the subsequent urban plan. The results indicate that the spatial quality of living in the west of Hengyang is higher than that in its northeast region. In addition, Xiao Xia Street, Guanghui Street, and Hengqi Road comprised the majority of the areas that required a priority update. Correspondingly, our research is expected to be a useful management tool for identifying urban street space issues and guiding urban renewal.