bluuebunny/crossref_metadata_2025 huggingface dataset:
Occupational Physical Activity and Cardiometabolic Risk Factors: A Cross-Sectional Study
Authors: Gómez-Recasens Montserrat , Alfaro-Barrio Silvana , Tarro Lucia , Llauradó Elisabet , Solà Rosa
Published: March 2023

Contradictory data exist on the impact of occupational physical activity (OPA) on cardiovascular health. We aimed to evaluate the association between OPA and cardiometabolic risk factors. A cross-sectional study was performed in an environmental services company in 2017 (Spain). OPA was classified by work categories as being low (≤3 METs) or moderate−high (>3 METs). Multiple linear and logistic binary regression models were used to assess the associations between OPA and cardiometabolic risk factors related to obesity, blood pressure, blood lipids, and associated medical conditions, adjusted by age, sex, alcohol consumption, and global physical activity. In total, 751 employees were included (547 males and 204 females), and 55.5% (n = 417) had moderate−high OPA. Significant inverse associations were observed between OPA and weight, body mass index, waist circumference, waist−hip ratio, and total cholesterol both overall and in males. OPA was significantly inversely related to dyslipidemia overall and in both sexes, while the overweight plus obesity rate was inversely related only in the total and male populations. OPA was associated with a better cardiometabolic risk factor profile, particularly in males. The fact that our models were also adjusted by global physical activity highlights the associations obtained as being independent of leisure time physical activity effects.
Level of Fruit and Vegetable Intake and Its Relationship with Risk for Malnutrition in China’s Adult Labor Force: China Nutrition and Health Surveillance, 2015–2017
Authors: Guo Qiya , Fang Hongyun , Zhao Liyun , Ju Lahong , Xu Xiaoli , Yu Dongmei
Published: March 2023

The purpose of this study was to analyze the fruit and vegetable intake status and examine both potential risk and protective action factors in the Chinese labor force population, while investigating the association between fruit and vegetable intake and malnutrition in this population. Data were derived from a population-based cross-sectional survey, the China Nutrition and Health Surveillance, 2015–2017. Sociodemographic information, physical measurements, and dietary intake data were collected. A total of 45,459 survey respondents aged 18–64 years old were included in the analysis. Fruit and vegetable consumption data were assessed by a food frequency questionnaire (FFQ), and the average daily intake was calculated. In 2015, the daily intake of fresh fruits, fresh vegetables, and combined fruits and vegetables among the Chinese labor force was 64.3 g, 210.0 g, and 330.0 g (median), respectively. Compared with the Dietary Guidelines for Chinese Residents (2022), 79.9% and 53.0% were at risk of inadequate fruit and vegetable intake, while 55.2% were at risk of inadequate intake of combined fruits and vegetables compared with the WHO recommendation. Multivariate logistic regression analysis showed that female gender, higher educational level, and higher income were protective factors for adequate fruit intake, while increasing age and living in the southern region were protective factors for adequate vegetable intake. The results confirmed that increasing vegetable intake helped urban labor force maintain normal BMI and control overweight. Increased fruit consumption may reduce the risk of underweight, but no clear negative association with overweight and obesity was observed. In conclusion, the consumption of fresh fruits and vegetables by the Chinese labor force was inadequate, especially for fruits. Interventions are needed to promote the daily intake of fruits and vegetables in this population. In addition, further in-depth studies in this area are recommended in populations with different health status.
Industrial and Ruminant Trans-Fatty Acids-Enriched Diets Differentially Modulate the Microbiome and Fecal Metabolites in C57BL/6 Mice
Authors: Mohammadi Farzad , Green Miranda , Tolsdorf Emma , Greffard Karine , Leclercq Mickael , Bilodeau Jean-François , Droit Arnaud , Foster Jane , Bertrand Nicolas , Rudkowska Iwona
Published: March 2023

Industrially originated trans-fatty acids (I-tFAs), such as elaidic acid (EA), and ruminant trans-fatty acids (R-tFAs), such as trans-palmitoleic acid (TPA), may have opposite effects on metabolic health. The objective was to compare the effects of consuming 2–3% I-tFA or R-tFA on the gut microbiome and fecal metabolite profile in mice after 7 and 28 days. Forty C57BL/6 mice were assigned to one of the four prepared formulations: lecithin nanovesicles, lecithin nanovesicles with EA or TPA, or water. Fecal samples and animals’ weights were collected on days 0, 7, and 28. Fecal samples were used to determine gut microbiome profiles by 16S rRNA sequencing and metabolite concentrations by GC/MS. At 28 days, TPA intake decreased the abundance of Staphylococcus sp55 but increased Staphylococcus sp119. EA intake also increased the abundance of Staphylococcus sp119 but decreased Ruminococcaceae UCG-014, Lachnospiraceae, and Clostridium sensu stricto 1 at 28 days. Fecal short-chain fatty acids were increased after TPA while decreased after EA after 7 and 28 days. This study shows that TPA and EA modify the abundance of specific microbial taxa and fecal metabolite profiles in distinct ways.
The Hedgehog Pathway as a Therapeutic Target in Chronic Myeloid Leukemia
Authors: Wu Andrew , Turner Kelly A. , Woolfson Adrian , Jiang Xiaoyan
Published: March 2023

Despite the development of therapeutic agents that selectively target cancer cells, relapse driven by acquired drug resistance and resulting treatment failure remains a significant issue. The highly conserved Hedgehog (HH) signaling pathway performs multiple roles in both development and tissue homeostasis, and its aberrant regulation is known to drive the pathogenesis of numerous human malignancies. However, the role of HH signaling in mediating disease progression and drug resistance remains unclear. This is especially true for myeloid malignancies. The HH pathway, and in particular the protein Smoothened (SMO), has been shown to be essential for regulating stem cell fate in chronic myeloid leukemia (CML). Evidence suggests that HH pathway activity is critical for maintaining the drug-resistant properties and survival of CML leukemic stem cells (LSCs), and that dual inhibition of BCR-ABL1 and SMO may comprise an effective therapeutic strategy for the eradication of these cells in patients. This review will explore the evolutionary origins of HH signaling, highlighting its roles in development and disease, which are mediated by canonical and non-canonical HH signaling. Development of small molecule inhibitors of HH signaling and clinical trials using these inhibitors as therapeutic agents in cancer and their potential resistance mechanisms, are also discussed, with a focus on CML.
A New Productive Approach and Formulative Optimization for Curcumin Nanoliposomal Delivery Systems
Authors: Piano Raffaella De , Caccavo Diego , Lamberti Gaetano , Remaut Katrien , Seynaeve Hanne , Barba Anna Angela
Published: March 2023

The use of natural resources and the enhancing of technologies are outlining the strategies of modern scientific-technological research for sustainable health products manufacturing. In this context, the novel simil-microfluidic technology, a mild production methodology, is exploited to produce liposomal curcumin as potential powerful dosage system for cancer therapies and for nutraceutical purposes. Through simil-microfluidic technology, based on interdiffusion phenomena of a lipid-ethanol phase in an aqueous flow, massive productions of liposomes at nanometric scale can be obtained. In this work, studies on liposomal production with useful curcumin loads were performed. In particular, process issues (curcumin aggregations) were elucidated and formulation optimization for curcumin load was performed. The main achieved result has been the definition of operative conditions for nanoliposomal curcumin production with interesting loads and encapsulation efficiencies.
Potential Allergenicity of Plants Used in Allergological Communication: An Untapped Tool for Prevention
Authors: Magyar Donát
Published: March 2023

Plants are often used to illustrate allergy-related medical products, services, patient information materials and news. The illustration of allergenic plants is an important tool in patient education, contributing to the prevention of pollinosis, as patients can recognize plants and avoid pollen exposure. In this study, it is aimed to evaluate the pictorial content of allergy-related websites depicting plants. A total of 562 different photographs depicting plants were collected using image search, identified and categorized according to their potential allergenicity. Of the total 124 plant taxa, 25% of plants were identified to the genus level and a further 68% were identified to the species level. Plants with low allergenicity were found in 85.4% of the pictures, while plants of high allergenicity were shown in only 4.5% of the pictorial information. Brassica napus was the most frequent species identified (8.9% of the overall identified plants), while blooming Prunoidae, Chrysanthemum spp. and Taraxacum officinale were also common. Considering both allergological and design aspects, some plant species have been proposed for more professional and responsible advertising. The internet has the potential to provide visual support for patient education in allergenic plants, but emphasis must be put on the transmission of the correct visual message.
Oral Delivery of Psoralidin by Mucoadhesive Surface-Modified Bilosomes Showed Boosted Apoptotic and Necrotic Effects against Breast and Lung Cancer Cells
Authors: Youness Rana Ahmed , Al-Mahallawi Abdulaziz Mohsen , Mahmoud Farah Haytham , Atta Hind , Braoudaki Maria , Fahmy Sherif Ashraf
Published: March 2023

This study aims to design and optimize chitosan-coated bilosomal formulations loaded with psoralidin (Ps-CS/BLs) with improved physicochemical properties, oral bioavailability, and boosted apoptotic and necrotic effects. In this regard, uncoated bilosomes loaded with Ps (Ps/BLs) were nanoformulated using the thin-film hydration technique using different molar ratios of phosphatidylcholine (PC), cholesterol (Ch), Span 60 (S60), and sodium deoxycholate (SDC) (1:0.4:0.2:0.125, 1:0.4:0.2:0.25, and 1:0.4:0.2:0.5, respectively). The best-optimized formulation with respect to size, PDI, zeta potential, and EE% was selected and then coated with chitosan at two different concentrations (0.125 and 0.25 w/v%), forming Ps-CS/BLs. The optimized Ps/BLs and Ps-CS/BLs showed a spherical shape and relatively homogenous size with negligible apparent agglomerations. Additionally, it was demonstrated that coating Ps/BLs with chitosan has significantly increased the particle size from 123.16 ± 6.90 in the case of Ps/BLs to 183.90 ± 15.93 nm in the case of Ps-CS/BLs. In addition, Ps-CS/BLs exhibited higher zeta potential (+30.78 ± 1.44 mV) as compared to Ps/BLs (−18.59 ± 2.13 mV). Furthermore, Ps-CS/BL showed enhanced entrapment efficiency (EE%) of 92.15 ± 7.20% as compared to Ps/BLs (68.90 ± 5.95%). Moreover, Ps-CS/BLs exhibited a more sustained release behavior of Ps compared to Ps/BLs over 48 h, and both formulations were best obeying the Higuchi diffusion model. More importantly, Ps-CS/BLs displayed the highest mucoadhesive efficiency% (74.89 ± 3.5%) as compared to Ps/BLs (26.78 ± 2.9%), indicating the ability of the designed nanoformulation to improve oral bioavailability and extend the residence time inside the gastrointestinal tract upon oral administration. Moreover, upon evaluating the apoptotic and necrotic effects of free Ps and Ps-CS/BLs on human breast cancer cell lines (MCF-7) and human lung adenocarcinoma cell lines (A549), there was a dramatic increase in the percentages of the apoptotic and necrotic cell compared to the control and free Ps. Our findings suggest the possible oral use of Ps-CS/BLs in hampering breast and lung cancers.
Self-Healing Hydrogels Fabricated by Introducing Antibacterial Long-Chain Alkyl Quaternary Ammonium Salt into Marine-Derived Polysaccharides for Wound Healing
Authors: Li Rongkai , Qi Qinbing , Wang Chunhua , Hou Guige , Li Chengbo
Published: March 2023

The development of hydrogels as wound dressings has gained considerable attention due to their promising ability to promote wound healing. However, in many cases of clinical relevance, repeated bacterial infection, which might obstruct wound healing, usually occurs due to the lack of antibacterial properties of these hydrogels. In this study, we fabricated a new class of self-healing hydrogel with enhanced antibacterial properties based on dodecyl quaternary ammonium salt (Q12)-modified carboxymethyl chitosan (Q12-CMC), aldehyde group- modified sodium alginate (ASA), Fe3+ via Schiff bases and coordination bonds (QAF hydrogels). The dynamic Schiff bases and coordination interactions conferred excellent self-healing abilities to the hydrogels, while the incorporation of dodecyl quaternary ammonium salt gave the hydrogels superior antibacterial properties. Additionally, the hydrogels displayed ideal hemocompatibility and cytocompatibility, crucial for wound healing. Our full-thickness skin wound studies demonstrated that QAF hydrogels could result in rapid wound healing with reduced inflammatory response, increased collagen disposition and improved vascularization. We anticipate that the proposed hydrogels, possessing both antibacterial and self-healing properties, will emerge as a highly desirable material for skin wound repair.
Impact of In-Process Crystallinity of Biodegradable Scaffolds Fabricated by Material Extrusion on the Micro- and Nanosurface Topography, Viability, Proliferation, and Differentiation of Human Mesenchymal Stromal Cells
Authors: Lužanin Ognjan , Gudurić Vera , Bernhardt Anne , Movrin Dejan , Damjanović-Vasilić Ljiljana , Terek Pal , Ostojić Gordana , Stankovski Stevan
Published: March 2023

Due to affordability, and the ability to parametrically control the vital processing parameters, material extrusion is a widely accepted technology in tissue engineering. Material extrusion offers sufficient control over pore size, geometry, and spatial distribution, and can also yield different levels of in-process crystallinity in the resulting matrix. In this study, an empirical model based on four process parameters—extruder temperature, extrusion speed, layer thickness, and build plate temperature—was used to control the level of in-process crystallinity of polylactic acid (PLA) scaffolds. Two sets of scaffolds were fabricated, with low- and high-crystallinity content, and subsequently seeded with human mesenchymal stromal cells (hMSC). The biochemical activity of hMSC cells was tested by examining the DNA content, lactate dehydrogenase (LDH) activity, and alkaline phosphatase (ALP) tests. The results of this 21-day in vitro experiment showed that high level crystallinity scaffolds performed significantly better in terms of cell response. Follow-up tests revealed that the two types of scaffolds were equivalent in terms of hydrophobicity, and module of elasticity. However, detailed examination of their micro- and nanosurface topographic features revealed that the higher crystallinity scaffolds featured pronounced nonuniformity and a larger number of summits per sampling area, which was the main contributor to a significantly better cell response.
Sustainable Flame-Retardant Additives for Polymers: Future Perspectives
Authors: Saeb Mohammad Reza , Vahabi Henri
Published: March 2023

The increased use of plastics, particularly in terms of the use of polymers in electronics and electrical devices commonly used in homes, offices, schools, restaurants, and vehicles, has caused increased fire risks [...]
Biodegradable Block Poly(ester amine)s with Pendant Hydroxyl Groups for Biomedical Applications
Authors: Śmigiel-Gac Natalia , Smola-Dmochowska Anna , Janeczek Henryk , Dobrzyński Piotr
Published: March 2023

The article presents the results of the synthesis and characteristics of the amphiphilic block terpolymers, built of a hydrophilic polyesteramine block, and hydrophobic blocks made of lactidyl and glycolidyl units. These terpolymers were obtained during the copolymerization of L-lactide with glycolide carried out in the presence of previously produced macroinitiators with protected amine and hydroxyl groups. The terpolymers were prepared to produce a biodegradable and biocompatible material containing active hydroxyl and/or amino groups, with strong antibacterial properties and high surface wettability by water. The control of the reaction course, the process of deprotection of functional groups, and the properties of the obtained terpolymers were made based on 1H NMR, FTIR, GPC, and DSC tests. Terpolymers differed in the content of amino and hydroxyl groups. The values of average molecular mass oscillated from about 5000 g/mol to less than 15,000 g/mol. Depending on the length of the hydrophilic block and its composition, the value of the contact angle ranged from 50° to 20°. The terpolymers containing amino groups, capable of forming strong intra- and intermolecular bonds, show a high degree of crystallinity. The endotherm responsible for the melting of L-lactidyl semicrystalline regions appeared in the range from about 90 °C to close to 170 °C, with a heat of fusion from about 15 J/mol to over 60 J/mol.
Power Flow in Multimode Graded-Index Microstructured Polymer Optical Fibers
Authors: Savović Svetislav , Simović Ana , Drljača Branko , Kovačević Milan , Kuzmanović Ljubica , Djordjevich Alexandar , Aidinis Konstantinos , Min Rui
Published: March 2023

We investigate mode coupling in a multimode graded-index microstructured polymer optical fiber (GI mPOF) with a solid core by solving the time-independent power flow equation (TI PFE). Using launch beams with various radial offsets, it is possible to calculate for such an optical fiber the transients of the modal power distribution, the length Lc at which an equilibrium mode distribution (EMD) is reached, and the length zs for establishing a steady-state distribution (SSD). In contrast to the conventional GI POF, the GI mPOF explored in this study achieves the EMD at a shorter length Lc. The earlier shift to the phase of slower bandwidth decrease would result from the shorter Lc. These results are helpful for the implementation of multimode GI mPOFs as a part of communications and optical fiber sensory systems.
Characteristics of Epoxy Composites Containing Carbon Nanotubes/Graphene Mixtures
Authors: Dyachkova Tatiana P. , Khan Yulian A. , Burakova Elena A. , Galunin Evgeny V. , Shigabaeva Gulnara N. , Stolbov Dmitry N. , Titov Georgy A. , Chapaksov Nikolay A. , Tkachev Alexey G.
Published: March 2023

The paper considers the development of fillers representing mixtures of carbon nanotubes and graphene materials (graphene oxide and graphene nanoplatelets) in different mass ratios to modify epoxy resin. The graphene type and content effect on the dispersed phase particle effective sizes—both in aqueous suspensions and the resin—was analyzed. Hybrid particles were characterized by Raman spectroscopy and electron microscopy. The composites containing 0.15–1.00 wt.% CNTs/GO and CNTs/GNPs were thermogravimetrically analyzed, and their mechanical characteristics were determined. SEM images of the composite fracture surfaces were acquired. Optimal dispersions containing 75–100 nm particles were obtained at the CNTs:GO mass ratio of 1:4. It was shown that the CNTs can be located between the GO layers and on the GNP surface. The samples containing up to 0.2 wt.% CNTs/GO (at 1:1 and 1:4 ratios) were stable when heated in air up to 300 °C. For 0.15–0.20 wt.% CNTs/GO (at 1:1 ratio), the tensile strength and modulus of the composite increased by 84–88 and 40%, respectively. The increase in the strength characteristics was found to occur due to the interaction of the filler layered structure with the polymer matrix. The obtained composites can be used as structural materials in different fields of engineering.
Degradation Behavior of 3D-Printed Residue of Astragalus Particle/Poly(Lactic Acid) Biocomposites under Soil Conditions
Authors: Yu Wangwang , Shi Jianan , Qiu Rui , Lei Wen
Published: March 2023

Astragalus is widely cultivated in China, and the residue of Astragalus particles (ARP) can be used as reinforcements in fused filament-fabricated (FFF) natural fiber/Poly(lactic acid)(PLA) biocomposites. To clarify the degradation behavior of such biocomposites, 3D-printed 11 wt% ARP/PLA samples were buried in soil, and the effects of soil burial duration on the physical appearance, weight, flexural properties, morphology, thermal stability, melting, and crystallization properties were investigated. At the same time, 3D-printed PLA was chosen as a reference. The results showed that, with prolonged soil burial, the transparency of PLA decreased (but not obviously), while the surface photographs of ARP/PLA became gray with some black spots and crevices; especially after 60 days, the color of the samples became extremely heterogeneous. After soil burial, the weight, flexural strength, and flexural modulus of the printed samples all reduced, and greater losses happened to ARP/PLA pieces than pure PLA. With an increase in soil burial time, the glass transition, cold crystallization, and melting temperatures, as well as the thermal stability of PLA and ARP/PLA samples, all increased gradually. Additionally, soil burial had a greater effect on the thermal properties of ARP/PLA. The results showed that the degradation behavior of ARP/PLA was more significantly affected by soil burial than the behavior of PLA. Additionally, ARP/PLA more easily degraded in soil than PLA.
Transformer Aided Adaptive Extended Kalman Filter for Autonomous Vehicle Mass Estimation
Authors: Zhang Hui , Yang Zichao , Xiong Huiyuan , Zhu Taohong , Long Zhineng , Wu Weibin
Published: March 2023

Vehicle mass is crucial to autonomous vehicles control. Affected by the nonlinearity of vehicle dynamics between vehicle states, it is still a tough issue to estimate vehicle mass precisely and stably. The transformer aided adaptive extended Kalman filter is proposed to further improve the accuracy and stability of estimation. Firstly, the transformer-based estimator is introduced to provide an accurate pre-estimation of vehicle mass, with the nonlinear dynamics among vehicle states being learned. Secondly, on the basis of comparing the real-time input and training data of neural network, the weight adjustment module is designed to present an adaptive law. Finally, the adaptive extended Kalman filter is proposed to meet the demand of accuracy and stability, where the pre-estimation of transformer-based estimator is integrated with the adaptive law. Dataset is collected by conducting heavy-duty vehicle simulation. The mean absolute percentage error, mean absolute error, root mean square error and convergence rate averaged over simulation tests are 0.90%, 256.47 kg, 357.01 kg and 184 steps, respectively. The results show the outperformance of the proposed method in terms of accuracy and stability.
Waste Biomass Based Carbon Aerogels Prepared by Hydrothermal-carbonization and Their Ethanol Cracking Performance for H2 Production
Authors: Zhang Jialin , Hu Song , Ding Yong , Huang Rui , Ren Qiangqiang , Su Sheng , Wang Yi , Jiang Long , Xu Jun , Xiang Jun
Published: March 2023

Biomass occupies a significant proportion of municipal solid waste. For the high-value processing of waste biomass, a hydrothermal-carbonization method was chosen because of the advantages of effective and mild conditions. Four typical types of waste biomass (banana peel, mangosteen peel, orange peel, and pomelo peel) were used in this work to prepare high-value carbon aerogels (CA) via hydrothermal-carbonization treatment for cracking ethanol. Four kinds of CA all had good performances in the ethanol cracking reaction and improved the yield of H2 from 21 wt% to about 40 wt%. The banana peel-based carbon aerogel (BPCA) showed the best performance in the reaction; it cracked ethanol and obtained 41.86 wt% of H2. The mechanism of ethanol cracking by CA was revealed: On one hand, the self-cracking of ethanol was improved due to the extension of residence time, which benefited from the abundant pores in CA. On the other hand, the heterogeneous reaction occurred on the surface of CA where the inorganic components, mainly Ca, Mg, and K, can promote the bond-breaking and reorganization in ethanol. The CO2 in byproducts was also fixed by Ca and Mg, improving the positive cracking reaction.
The Landscape of Scholarly Book Publishing in Croatia: Finding Pathways for Viable Open Access Models
Authors: Melinščak Zlodi Iva
Published: March 2023

(1) Background: Open access to scholarly works is globally recognized as a goal to be achieved as soon as possible; however, there is not yet a general understanding of how to achieve open access for books. In considering the most appropriate models of transition, an accurate and detailed insight into national and regional specifics can be of great importance. The aim of this research is to show the current state of scholarly book publishing in Croatia: recognising the key stakeholders, their characteristics, and the current level of open access to scholarly books. (2) Methods: The existing data from two different sources were used: the data about the public subsidies for book publishers by the Ministry of Science and Education and the data on published books from the Croatian Scientific Bibliography CROSBI, both for the period from 2018 to 2021. (3) Results: In the four-year period, 224 Croatian publishers were awarded subsidies to publish 2359 book titles. The majority of the publishers received support for only a small number of titles and relatively low amounts of subsidies. More than half of the titles are published by small private commercial publishers. However, the uptake of digital publishing among commercial publishers is very modest. Open access to scholarly books is almost entirely in the domain of non-commercial publishers. Most open access titles are available on the websites of their publishers. (4) Conclusions: The analysis of the data from these two sources have resulted in an overview of the current state of book publishing in Croatia. Such an overview provides a good basis for designing future measures and creating a national open science plan and can also be a useful contribution to international discussions.
Seg-Road: A Segmentation Network for Road Extraction Based on Transformer and CNN with Connectivity Structures
Authors: Tao Jingjing , Chen Zhe , Sun Zhongchang , Guo Huadong , Leng Bo , Yu Zhengbo , Wang Yanli , He Ziqiong , Lei Xiangqi , Yang Jinpei
Published: March 2023

Acquiring road information is important for smart cities and sustainable urban development. In recent years, significant progress has been made in the extraction of urban road information from remote sensing images using deep learning (DL) algorithms. However, due to the complex shape, narrowness, and high span of roads in the images, the results are often unsatisfactory. This article proposes a Seg-Road model to improve road connectivity. The Seg-Road uses a transformer structure to extract the long-range dependency and global contextual information to improve the fragmentation of road segmentation and uses a convolutional neural network (CNN) structure to extract local contextual information to improve the segmentation of road details. Furthermore, a novel pixel connectivity structure (PCS) is proposed to improve the connectivity of road segmentation and the robustness of prediction results. To verify the effectiveness of Seg-Road for road segmentation, the DeepGlobe and Massachusetts datasets were used for training and testing. The experimental results show that Seg-Road achieves state-of-the-art (SOTA) performance, with an intersection over union (IoU) of 67.20%, mean intersection over union (MIoU) of 82.06%, F1 of 91.43%, precision of 90.05%, and recall of 92.85% in the DeepGlobe dataset, and achieves an IoU of 68.38%, MIoU of 83.89%, F1 of 90.01%, precision of 87.34%, and recall of 92.86% in the Massachusetts dataset, which is better than the values for CoANet. Further, it has higher application value for achieving sustainable urban development.
Cloud Mesoscale Cellular Classification and Diurnal Cycle Using a Convolutional Neural Network (CNN)
Authors: Segal Rozenhaimer Michal , Nukrai David , Che Haochi , Wood Robert , Zhang Zhibo
Published: March 2023

Marine stratocumulus (MSC) clouds are important to the climate as they cover vast areas of the ocean’s surface, greatly affecting radiation balance of the Earth. Satellite imagery shows that MSC clouds exhibit different morphologies of closed or open mesoscale cellular convection (MCC) but many limitations still exist in studying MCC dynamics. Here, we present a convolutional neural network algorithm to classify pixel-level closed and open MCC cloud types, trained by either visible or infrared channels from a geostationary SEVIRI satellite to allow, for the first time, their diurnal detection, with a 30 min. temporal resolution. Our probability of detection was 91% and 92% for closed and open MCC, respectively, which is in line with day-only detection schemes. We focused on the South-East Atlantic Ocean during months of biomass burning season, between 2016 and 2018. Our resulting MCC type area coverage, cloud effective radii, and cloud optical depth probability distributions over the research domain compare well with monthly and daily averages from MODIS. We further applied our algorithm on GOES-16 imagery over the South-East Pacific (SEP), another semi-permanent MCC domain, and were able to show good prediction skills, thereby representing the SEP diurnal cycle and the feasibility of our method to be applied globally on different satellite platforms.
Rapid Mapping of Slow-Moving Landslides Using an Automated SAR Processing Platform (HyP3) and Stacking-InSAR Method
Authors: Yi Yaning , Xu Xiwei , Xu Guangyu , Gao Huiran
Published: March 2023

The increasing number of landslide hazards worldwide has placed greater demands on the production and updating of landslide inventory maps. As an important data source for landslide detection, interferometric synthetic aperture radar (InSAR) data processing is time-consuming and also requires specialized knowledge, which severely hinders its widespread application. At present, a new cloud-based online platform, i.e., Alaska Satellite Facility’s Hybrid Pluggable Processing Pipeline (ASF HyP3) was developed for massive SAR data processing. In this study, combining the HyP3 online platform and Stacking-InSAR method, we constructed a new easy-to-use processing chain for rapidly identifying slow-moving landslides over large areas. With this processing chain, a total of 923 interferometric pairs covering an area of over 1800 km2 were processed within a few hours (about 4 to 5 h). A total of 81 slow-moving landslides were immediately detected and mapped using Stacking-InSAR method, of which 65 landslides were confirmed by previous studies and 16 landslides were newly detected. Results show that the new processing chain can greatly improve the efficiency of wide-area landslide mapping and is expected to serve as an effective tool for rapid updating the existing landslide inventories and contribute to the prevention and management of geological hazards.
Optimization of Airborne Scatterometer NRCS Semicircular Sampling for Sea Wind Retrieval
Authors: Nekrasov Alexey , Khachaturian Alena , Fidge Colin
Published: March 2023

Airborne scatterometer capability depends on not only the device’s technical characteristics but also the scheme used for surface observations. Typically, a rotating-beam scatterometer uses a circular scheme for sampling normalized radar cross-sections (NRCS) at wind measurements over the sea. Here, we investigate wind retrieval using an updated semicircular scheme, providing the NRCS sampling at various combinations of incidence angles within the range 30° to 60°. The effectiveness of the wind retrieval using our semicircular sampling scheme was evaluated using Monte Carlo simulations, and we then developed corresponding wind algorithms that used a geophysical model function (GMF). As a result of the study, we found that a semicircular sampling scheme is well suited for wind retrieval over the sea using a rotating-beam scatterometer. We showed that a semicircular scheme can provide wind retrieval accuracies similar to those achievable with a conventional circular scheme, although the semicircular scheme requires approximately three times the number of NRCS samples integrated in each azimuth sector. Most importantly, however, the semicircular scheme enabled a maximum altitude for wind retrieval of twice the height possible with a circular scheme. In this study, we also demonstrate that the wind speed accuracy tends to increase with an increase in the incidence angle and similarly for the wind direction accuracy. Nonetheless, we then show that the simultaneous use of the NRCS sampling scheme at several incidence angles can increase the wind retrieval accuracy, especially when three or four incidence angles are used. The obtained results can be used to enhance airborne scatterometers and multimode radars operated in a scatterometer mode, including airborne high-altitude conical scanning radars, and can be applied to new remote sensing systems’ development.
Vibro-Acoustic Sensing of Instrument Interactions as a Potential Source of Texture-Related Information in Robotic Palpation
Authors: Sühn Thomas , Esmaeili Nazila , Mattepu Sandeep Y. , Spiller Moritz , Boese Axel , Urrutia Robin , Poblete Victor , Hansen Christian , Lohmann Christoph H. , Illanes Alfredo , Friebe Michael
Published: March 2023

The direct tactile assessment of surface textures during palpation is an essential component of open surgery that is impeded in minimally invasive and robot-assisted surgery. When indirectly palpating with a surgical instrument, the structural vibrations from this interaction contain tactile information that can be extracted and analysed. This study investigates the influence of the parameters contact angle α and velocity v→ on the vibro-acoustic signals from this indirect palpation. A 7-DOF robotic arm, a standard surgical instrument, and a vibration measurement system were used to palpate three different materials with varying α and v→. The signals were processed based on continuous wavelet transformation. They showed material-specific signatures in the time–frequency domain that retained their general characteristic for varying α and v→. Energy-related and statistical features were extracted, and supervised classification was performed, where the testing data comprised only signals acquired with different palpation parameters than for training data. The classifiers support vector machine and k-nearest neighbours provided 99.67% and 96.00% accuracy for the differentiation of the materials. The results indicate the robustness of the features against variations in the palpation parameters. This is a prerequisite for an application in minimally invasive surgery but needs to be confirmed in realistic experiments with biological tissues.
An Integrated Single-Beam Three-Axis High-Sensitivity Magnetometer
Authors: Su Shengran , Xu Zhenyuan , He Xiang , Yin Chanling , Kong Miao , Zhang Xuyuan , Ruan Yi , Li Kan , Lin Qiang
Published: March 2023

Three-axis atomic magnetometers have great advantages for interpreting information conveyed by magnetic fields. Here, we demonstrate a compact construction of a three-axis vector atomic magnetometer. The magnetometer is operated with a single laser beam and with a specially designed triangular 87Rb vapor cell (side length is 5 mm). The ability of three-axis measurement is realized by reflecting the light beam in the cell chamber under high pressure, so that the atoms before and after reflection are polarized along two different directions. It achieves a sensitivity of 40 fT/Hz in x-axis, 20 fT/Hz in y-axis, and 30 fT/Hz in z-axis under spin-exchange relaxation-free regime. The crosstalk effect between different axes is proven to be little in this configuration. The sensor configuration here is expected to form further values, especially for vector biomagnetism measurement, clinical diagnosis, and field source reconstruction.
Quantum Binary Field Multiplication with Optimized Toffoli Depth and Extension to Quantum Inversion
Authors: Jang Kyungbae , Kim Wonwoong , Lim Sejin , Kang Yeajun , Yang Yujin , Seo Hwajeong
Published: March 2023

The Shor’s algorithm can find solutions to the discrete logarithm problem on binary elliptic curves in polynomial time. A major challenge in implementing Shor’s algorithm is the overhead of representing and performing arithmetic on binary elliptic curves using quantum circuits. Multiplication of binary fields is one of the critical operations in the context of elliptic curve arithmetic, and it is especially costly in the quantum setting. Our goal in this paper is to optimize quantum multiplication in the binary field. In the past, efforts to optimize quantum multiplication have centred on reducing the Toffoli gate count or qubits required. However, despite the fact that circuit depth is an important metric for indicating the performance of a quantum circuit, previous studies have lacked sufficient consideration for reducing circuit depth. Our approach to optimizing quantum multiplication differs from previous work in that we aim at reducing the Toffoli depth and full depth. To optimize quantum multiplication, we adopt the Karatsuba multiplication method which is based on the divide-and-conquer approach. In summary, we present an optimized quantum multiplication that has a Toffoli depth of one. Additionally, the full depth of the quantum circuit is also reduced thanks to our Toffoli depth optimization strategy. To demonstrate the effectiveness of our proposed method, we evaluate its performance using various metrics such as the qubit count, quantum gates, and circuit depth, as well as the qubits-depth product. These metrics provide insight into the resource requirements and complexity of the method. Our work achieves the lowest Toffoli depth, full depth, and the best trade-off performance for quantum multiplication. Further, our multiplication is more effective when not used in stand-alone cases. We show this effectiveness by using our multiplication to the Itoh–Tsujii algorithm-based inversion of F(x8+x4+x3+x+1).
Lite and Efficient Deep Learning Model for Bearing Fault Diagnosis Using the CWRU Dataset
Authors: Yoo Yubin , Jo Hangyeol , Ban Sang-Woo
Published: March 2023

Bearing defects are a common problem in rotating machines and equipment that can lead to unexpected downtime, costly repairs, and even safety hazards. Diagnosing bearing defects is crucial for preventative maintenance, and deep learning models have shown promising results in this field. On the other hand, the high complexity of these models can lead to high computational and data processing costs, making their practical implementation challenging. Recent studies have focused on optimizing these models by reducing their size and complexity, but these methods often compromise classification performance. This paper proposes a new approach that reduces the dimensionality of input data and optimizes the model structure simultaneously. A much lower input data dimension than that of existing deep learning models was achieved by downsampling the vibration sensor signals used for bearing defect diagnosis and constructing spectrograms. This paper introduces a lite convolutional neural network (CNN) model with fixed feature map dimensions that achieve high classification accuracy with low-dimensional input data. The vibration sensor signals used for bearing defect diagnosis were first downsampled to reduce the dimensionality of the input data. Next, spectrograms were constructed using the signals of the minimum interval. Experiments were conducted using the vibration sensor signals from the Case Western Reserve University (CWRU) dataset. The experimental results show that the proposed method could be highly efficient in terms of computation while maintaining outstanding classification performance. The results show that the proposed method outperformed a state-of-the-art model for bearing defect diagnosis under different conditions. This approach is not limited to the field of bearing failure diagnosis, but could be applied potentially to other fields that require the analysis of high-dimensional time series data.
Relationship between the Use of Social Networks and Mistrust of Mass Media among Mexican Youth: A Mixed-Methods and NLP Study
Authors: de la Garza Montemayor Daniel Javier , Pineda Rasgado Xunaxhi Monserrat
Published: March 2023

The relationship between trust and media consumption has been a subject continually studied in communication sciences. There are various studies that indicate that the greater the confidence in a certain medium, the greater the consumption. However, due to the consolidation of digital media and specifically social networks as the main sources of information among the young, the question of whether trust in these media affects their consumption arises again. To examine this relationship, a study was carried out with a mixed methodology. On the one hand, a survey was carried out in which young Mexican university students were asked about the media that they trusted the most and those that they used the most. On the other hand, interviews were conducted with university professors regarding their observations of the behavior of students in relation to usage and trust in these media. In general, the results allow us to conclude that trust in the media is not a variable that impacts the consultation of a specific media outlet given that, despite mistrust, there may be a high rate of usage.
Spatiotemporal Variations in Water Quality of the Transboundary Shari-Goyain River, Bangladesh
Authors: Pandit Debasish , Haque Mohammad Mahfujul , Harun-Al-Rashid Ahmed , Sarker Bishwajit , Hossain Mohammad Amzad , Schneider Petra , Kunda Mrityunjoy
Published: March 2023

This study aimed to investigate the seasonal and spatial variations in water quality parameters and determine the main contamination sources in the Shari-Goyain River, Bangladesh. Therefore, surface water was sampled monthly from six sampling sites, where six water quality parameters were evaluated. Data were analyzed by applying the Canadian Council of Ministers of the Environment (CCME) water quality index (WQI) and multivariate statistical methods. The results reveals that most of the examined water quality parameters crossed the acceptable range, and significant variations were observed spatiotemporally (p < 0.05). Based on the CCME WQI value, the water quality of the river is classified as poor to marginal with a score range between 33.40 and 51.30. This range of values demonstrates that the river’s water quality is far from desirable for aquatic life and that it is being impacted and deteriorated by external drivers. Principal component analysis (PCA) retained two principal components (Factors 1 and 2), explaining about 79.17% of the total variance in the studied parameters and identified acidic pollution sources. Cluster analysis also reveals relative differences in water quality throughout sites and seasons, which supported the CCME WQI and PCA. Finally, Kruskal-Wallis one-way analysis of variance by ranks has identified coal mine drainage (CMD) as the main pollutant source for the Shari-Goyain River. In order to mitigate the CMD impact on land and water, different nature-based solutions are proposed, particularly passive mine water treatment approaches through constructed wetlands that could also mitigate the transboundary waters problem.
Empirical Study of the Environmental Kuznets Curve in China Based on Provincial Panel Data
Authors: Yan Jun , Lu Wenting , Xu Xiaoyan , Lian Jiamin
Published: March 2023

The Environmental Kuznets Curve is a key indicator to measure the relationship between the environmental pollution level and economic development. Considering that China’s economic development is a superposing process of multiple industrial technologies, in order to restore the classical Environmental Kuznets Curve estimation as much as possible, this paper selects the data of six types of pollutants between provinces (except Tibet) in China during 2011–2017 to construct a comprehensive environmental pollution degree indicator, which is more objective than the single indicator in traditional research; estimates the Environmental Kuznets Curve with per capita disposable income; and then conducts a panel regression analysis based on the econometric model. Research shows that the relationship between comprehensive environmental pollution and economic development basically presents an inverted U-shape, which is consistent with the basic characteristics of the traditional Environmental Kuznets Curve, and the inflection point of the curve is 34,243.2 in RMB. Finally, according to the results, effective suggestions are put forward to correctly handle the relationship between economic development and environmental governance and optimize the path of environmental governance in China.
The Effects of Workaholism on Employee Burnout and Turnover Intent at Deluxe Hotels during the COVID-19 Pandemic: Evidence across Generations
Authors: Jung Hyo-Sun , Jung Yoon-Sik , Yoon Hye-Hyun
Published: March 2023

The coronavirus has caused unprecedented damage to the hospitality industry that cannot be compared to those caused by previous global crises. This study hypothesized that employee burnout and turnover intent can vary depending on their perceptions of workaholism, with the assumption that workaholism’s negative impact differs across generations. This study demonstrated that workaholism among hotel employees tends to increase their burnout and turnover intent. The examination of the intergenerational moderating role in the relationship between the influence of workaholism on burnout and turnover intent revealed that compared to Generations X and Y, Generation Z has a stronger negative relationship with workaholism.
The Role of Intersection Geometry in Urban Air Pollution Management
Authors: Šarić Ammar , Sulejmanović Suada , Albinović Sanjin , Pozder Mirza , Ljevo Žanesa
Published: March 2023

Air pollution represents one of the most complex problems of humanity. Traffic contributes significantly to this by emitting large amounts of harmful gases. This problem is particularly pronounced at urban intersections due to frequent changes in vehicle movement dynamics. This paper primarily presents the influence of intersection geometry on pollutant emissions levels. In addition, the influence of various traffic policies promoting greater use of public transport and zero-emission vehicles is also examined. The research combines the field part of recording existing intersections in Sarajevo, Bosnia and Herzegovina with traffic microsimulation. Detailed data on vehicles’ movements were obtained by advanced video processing using the DataFromSky tool, while the PTV Vissim 2022 and Bosch ESTM (2022) software were used to simulate traffic and estimate emissions at geometrically different intersections. The results showed that, in saturated traffic conditions, signalized intersections cause up to 50% lower emissions compared with two-lane and turbo roundabouts and that the impact of the geometric change is more significant than the impact of zero-emission vehicles. In unsaturated conditions, the differences in emissions at different intersections are negligible, with the highest reductions in pollution achieved by using zero-emission vehicles.