bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Effects of Cancer as a Traumatic Event on Italian Adolescents and Young Adults: Investigating Psychological Well-Being, Identity Construction and Coping Strategies
Authors: Ionio Chiara , Bigoni Francesca , Sacchi Maddalena , Zecca Marco , Bergami Elena , Landoni Marta , Ciuffo Giulia , Rovati Anna , Rizzi Damiano
Published: March 2023

Cancer in adolescence is considered a family disease that can have numerous negative psychological consequences for adolescents and the entire household. The aim of this study was to investigate the impact of oncological disease in adolescence, with particular reference to the psychological and post-traumatic consequences for the adolescents themselves and the family system. An explorative case–control study was conducted with 31 adolescents (mean age 18.03 ± 2.799) hospitalised for cancer at IRCCS San Matteo Hospital in Pavia and 47 healthy adolescents (mean age 16.17 ± 2.099). The two samples completed a survey that included sociodemographic information and questionnaires assessing psychological well-being, traumatic effects of the disease, and adequacy of the relationship with parents. 56.7% of oncology adolescents scored below average in psychological well-being, and a small proportion of them fell within the range of clinical concern for anger (9.7%), PTS (12.9%), and dissociation (12.9%). Compared with peers, there were no significant differences. However, in contrast to peers, oncology adolescents showed a strong influence of the traumatic event on the construction of their identity and life perspectives. A significantly positive correlation also emerged between adolescents’ psychological well-being and the relationship with their parents (mothers: r = 0.796; p < 0.01; fathers: r = 0.692; p < 0.01). Our findings highlight how cancer in adolescence could represent a central traumatic event that can shape the identity and life of teenagers who are in an intrinsically delicate and vulnerable stage of life.
Amphiphilic Cell-Penetrating Peptides Containing Arginine and Hydrophobic Residues as Protein Delivery Agents
Authors: Moreno Jonathan , Zoghebi Khalid , Salehi David , Kim Lois , Shoushtari Sorour Khayyatnejad , Tiwari Rakesh K. , Parang Keykavous
Published: March 2023

The entry of proteins through the cell membrane is challenging, thus limiting their use as potential therapeutics. Seven cell-penetrating peptides, designed in our laboratory, were evaluated for the delivery of proteins. Fmoc solid-phase peptide synthesis was utilized for the synthesis of seven cyclic or hybrid cyclic–linear amphiphilic peptides composed of hydrophobic (tryptophan (W) or 3,3-diphenylalanine (Dip) and positively-charged arginine (R) residues, such as [WR]4, [WR]9, [WWRR]4, [WWRR]5, [(RW)5K](RW)5, [R5K]W7, and [DipR]5. Confocal microscopy was used to screen the peptides as a protein delivery system of model cargo proteins, green and red fluorescein proteins (GFP and RFP). Based on the confocal microscopy results, [WR]9 and [DipR]5 were found to be more efficient among all the peptides and were selected for further studies. [WR]9 (1–10 µM) + protein (GFP and RFP) physical mixture did not show high cytotoxicity (>90% viability) in triple-negative breast cancer cells (MDA-MB-231) after 24 h, while [DipR]5 (1–10 µM) physical mixture with GFP exhibited more than 81% cell viability. Confocal microscopy images revealed internalization of GFP and RFP in MDA-MB-231 cells using [WR]9 (2–10 μM) and [DipR]5 (1–10 µM). Fluorescence-activated cell sorting (FACS) analysis indicated that the cellular uptake of GFP was concentration-dependent in the presence of [WR]9 in MDA-MB-231 cells after 3 h of incubation at 37 °C. The concentration-dependent uptake of GFP and RFP was also observed in the presence of [DipR5] in SK-OV-3 and MDA-MB-231 cells after 3 h of incubation at 37 °C. FACS analysis indicated that the cellular uptake of GFP in the presence of [WR]9 was partially decreased by methyl-β-cyclodextrin and nystatin as endocytosis inhibitors after 3 h of incubation in MDA-MB-231 cells, whereas nystatin and chlorpromazine as endocytosis inhibitors slightly reduced the uptake of GFP in the presence of [DipR]5 after 3 h of incubation in MDA-MB-231. [WR]9 was able to deliver therapeutically relevant proteins (Histone H2A) at different concentrations. These results provide insight into the use of amphiphilic cyclic peptides in the delivery of protein-related therapeutics.
Heparin Mimetics and Their Impact on Extracellular Matrix Protein Assemblies
Authors: Heide Fabian , Koch Manuel , Stetefeld Jörg
Published: March 2023

Heparan sulfate is a crucial extracellular matrix component that organizes structural features and functional protein processes. This occurs through the formation of protein–heparan sulfate assemblies around cell surfaces, which allow for the deliberate local and temporal control of cellular signaling. As such, heparin-mimicking drugs can directly affect these processes by competing with naturally occurring heparan sulfate and heparin chains that then disturb protein assemblies and decrease regulatory capacities. The high number of heparan-sulfate-binding proteins that are present in the extracellular matrix can cause obscure pathological effects that should be considered and examined in more detail, especially when developing novel mimetics for clinical use. The objective of this article is to investigate recent studies that present heparan-sulfate-mediated protein assemblies and the impact of heparin mimetics on the assembly and function of these protein complexes.
FOXO3-Activated circFGFBP1 Inhibits Extracellular Matrix Degradation and Nucleus Pulposus Cell Death via miR-9-5p/BMP2 Axis in Intervertebral Disc Degeneration In Vivo and In Vitro
Authors: Tan Yanlin , Wang Xiaobin , Zhang Yi , Dai Zhehao , Li Jing , Dong Chuning , Yao Xingwang , Lu Chang , Chen Fei
Published: March 2023

(1) Background: intervertebral disc degeneration (IVDD) defined as the degenerative changes in intervertebral disc is characterized by extracellular matrix (ECM) degradation and death in nucleus pulposus (NP) cells. (2) Methods: The model of IVDD was established in male Sprague Dawley rats using a puncture of a 21-gauge needle at the endplates located in the L4/5 intervertebral disc. Primary NP cells were stimulated by 10 ng/mL IL-1β for 24 h to mimic IVDD impairment in vitro. (3) Results: circFGFBP1 was downregulated in the IVDD samples. circFGFBP1 upregulation inhibited apoptosis and extracellular matrix (ECM) degradation and promoted proliferation in IL-1β-stimulated NP cells. Additionally, circFGFBP1 upregulation mitigated the loss of NP tissue and the destruction of the intervertebral disc structure in vivo during IVDD. FOXO3 could bind to the circFGFBP1 promoter to enhance its expression. circFGFBP1 upregulated BMP2 expression in NP via sponging miR-9-5p. FOXO3 enhanced the protection of circFGFBP1 in IL-1β-stimulated NP cells, whereas a miR-9-5p increase partly reversed the protection. miR-9-5p downregulation contributed to the survival of IL-1β-stimulated NP cells, which was partially reversed by BMP2 silence. (4) Conclusions: FOXO3 could activate the transcription of circFGFBP1 via binding to its promoter, which resulted in the enhancement of BMP2 via sponging miR-9-5p and then inhibited apoptosis and ECM degradation in NP cells during IVDD.
Mesoporous Organosilica Nanoparticles with Tetrasulphide Bond to Enhance Plasmid DNA Delivery
Authors: Zhang Yue , Xian He , Strounina Ekaterina , Gunther Kimberley S. , Sweet Matthew J. , Chen Chen , Yu Chengzhong , Wang Yue
Published: March 2023

Cellular delivery of plasmid DNA (pDNA) specifically into dendritic cells (DCs) has provoked wide attention in various applications. However, delivery tools that achieve effective pDNA transfection in DCs are rare. Herein, we report that tetrasulphide bridged mesoporous organosilica nanoparticles (MONs) have enhanced pDNA transfection performance in DC cell lines compared to conventional mesoporous silica nanoparticles (MSNs). The mechanism of enhanced pDNA delivery efficacy is attributed to the glutathione (GSH) depletion capability of MONs. Reduction of initially high GSH levels in DCs further increases the mammalian target of rapamycin complex 1 (mTORc1) pathway activation, enhancing translation and protein expression. The mechanism was further validated by showing that the increased transfection efficiency was apparent in high GSH cell lines but not in low GSH ones. Our findings may provide a new design principle of nano delivery systems where the pDNA delivery to DCs is important.
Sinonasal Stent Coated with Sustained-Release Varnish of Mometasone Furoate Inhibits Pro-Inflammatory Cytokine Release from Macrophages: An In Vitro Study
Authors: Cataldo Russomando Alessandra , Steinberg Doron , Gati Irith , Vogt Sionov Ronit , Eliashar Ron , Friedman Michael , Gross Menachem
Published: March 2023

The aim of the study was to develop a sustained-release varnish (SRV) containing mometasone furoate (MMF) for sinonasal stents (SNS) to reduce mucosa inflammation in the sinonasal cavity. The SNS’ segments coated with SRV-MMF or an SRV-placebo were incubated daily in a fresh DMEM at 37 °C for 20 days. The immunosuppressive activity of the collected DMEM supernatants was tested on the ability of mouse RAW 264.7 macrophages to secrete the cytokines’ tumor necrosis factor α (TNFα) and interleukin (IL)-10 and IL-6 in response to lipopolysaccharide (LPS). The cytokine levels were determined by respective Enzyme-Linked Immunosorbent Assays (ELISAs). We found that the daily amount of MMF released from the coated SNS was sufficient to significantly inhibit LPS-induced IL-6 and IL-10 secretion from the macrophages up to days 14 and 17, respectively. SRV-MMF had, however, only a mild inhibitory effect on LPS-induced TNFα secretion as compared to the SRV-placebo-coated SNS. In conclusion, the coating of SNS with SRV-MMF provides a sustained delivery of MMF for at least 2 weeks, maintaining a level sufficient for inhibiting pro-inflammatory cytokine release. This technological platform is, therefore, expected to provide anti-inflammatory benefits during the postoperative healing period and may play a significant role in the future treatment of chronic rhinosinusitis.
Caveolin-Mediated Internalization of Fmoc-FF Nanogels in Breast Cancer Cell Lines
Authors: Smaldone Giovanni , Rosa Elisabetta , Gallo Enrico , Diaferia Carlo , Morelli Giancarlo , Stornaiuolo Mariano , Accardo Antonella
Published: March 2023

Introduction: Hydrogel nanoparticles, also known as nanogels (NGs), have been recently proposed as alternative supramolecular vehicles for the delivery of biologically relevant molecules like anticancer drugs and contrast agents. The inner compartment of peptide based NGs can be opportunely modified according to the chemical features of the cargo, thus improving its loading and release. A full understanding of the intracellular mechanism involved in nanogel uptake by cancer cells and tissues would further contribute to the potential diagnostic and clinical applications of these nanocarriers, allowing the fine tuning of their selectivity, potency, and activity. The structural characterization of nanogels were assessed by Dynamic Light Scattering (DLS) and Nanoparticles Tracking Analysis (NTA) analysis. Cells viability of Fmoc-FF nanogels was evaluated by MTT assay on six breast cancer cell lines at different incubation times (24, 48, and 72 h) and peptide concentrations (in the range 6.25 × 10−4 ÷ 5·10−3 × wt%). The cell cycle and mechanisms involved in Fmoc-FF nanogels intracellular uptake were evaluated using flow cytometry and confocal analysis, respectively. Fmoc-FF nanogels, endowed with a diameter of ~130 nm and a zeta potential of ~−20.0/−25.0 mV, enter cancer cells via caveolae, mostly those responsible for albumin uptake. The specificity of the machinery used by Fmoc-FF nanogels confers a selectivity toward cancer cell lines overexpressing the protein caveolin1 and efficiently performing caveolae-mediated endocytosis.
Macroalgae Biorefinery for the Cosmetic Industry: Basic Concept, Green Technology, and Safety Guidelines
Authors: Hempel Mariana de Sousa Santos , Colepicolo Pio , Zambotti-Villela Leonardo
Published: March 2023

With the growth in the number of people searching for ways to improve personal care, the consumer finds the solution in cosmetic products. However, this demand is currently made concomitantly with the demand for products of natural origin, including seaweed. Algae, in their composition, are full of bioactive compounds with several applications. Therefore, their insertion in cosmetics is evidenced in the high number of scientific studies, which makes this natural resource potentially useful for the cosmetic industry. From this, a review was conducted with the aim of highlighting some of these active compounds and the latent applicability and versatility of others. In addition, the best way to add to the production of these substances while staying in alignment with green consumption, the design of biorefineries, and the promising production of macroalgae on a large scale using green technologies was sought.
Small Talk: On the Possible Role of Trans-Kingdom Small RNAs during Plant–Virus–Vector Tritrophic Communication
Authors: Matsumura Emilyn E. , Kormelink Richard
Published: March 2023

Small RNAs (sRNAs) are the hallmark and main effectors of RNA silencing and therefore are involved in major biological processes in plants, such as regulation of gene expression, antiviral defense, and plant genome integrity. The mechanisms of sRNA amplification as well as their mobile nature and rapid generation suggest sRNAs as potential key modulators of intercellular and interspecies communication in plant-pathogen–pest interactions. Plant endogenous sRNAs can act in cis to regulate plant innate immunity against pathogens, or in trans to silence pathogens’ messenger RNAs (mRNAs) and impair virulence. Likewise, pathogen-derived sRNAs can act in cis to regulate expression of their own genes and increase virulence towards a plant host, or in trans to silence plant mRNAs and interfere with host defense. In plant viral diseases, virus infection alters the composition and abundance of sRNAs in plant cells, not only by triggering and interfering with the plant RNA silencing antiviral response, which accumulates virus-derived small interfering RNAs (vsiRNAs), but also by modulating plant endogenous sRNAs. Here, we review the current knowledge on the nature and activity of virus-responsive sRNAs during virus–plant interactions and discuss their role in trans-kingdom modulation of virus vectors for the benefit of virus dissemination.
Biodegradable Polymer Electrospinning for Tendon Repairment
Authors: Zhang Yiming , Xue Yueguang , Ren Yan , Li Xin , Liu Ying
Published: March 2023

With the degradation after aging and the destruction of high-intensity exercise, the frequency of tendon injury is also increasing, which will lead to serious pain and disability. Due to the structural specificity of the tendon tissue, the traditional treatment of tendon injury repair has certain limitations. Biodegradable polymer electrospinning technology with good biocompatibility and degradability can effectively repair tendons, and its mechanical properties can be achieved by adjusting the fiber diameter and fiber spacing. Here, this review first briefly introduces the structure and function of the tendon and the repair process after injury. Then, different kinds of biodegradable natural polymers for tendon repair are summarized. Then, the advantages and disadvantages of three-dimensional (3D) electrospun products in tendon repair and regeneration are summarized, as well as the optimization of electrospun fiber scaffolds with different bioactive materials and the latest application in tendon regeneration engineering. Bioactive molecules can optimize the structure of these products and improve their repair performance. Importantly, we discuss the application of the 3D electrospinning scaffold’s superior structure in different stages of tendon repair. Meanwhile, the combination of other advanced technologies has greater potential in tendon repair. Finally, the relevant patents of biodegradable electrospun scaffolds for repairing damaged tendons, as well as their clinical applications, problems in current development, and future directions are summarized. In general, the use of biodegradable electrospun fibers for tendon repair is a promising and exciting research field, but further research is needed to fully understand its potential and optimize its application in tissue engineering.
Influence of Injection Molding Parameters on the Peel Strength between Plasma-Treated Fluoropolymer Films and Polycarbonate
Authors: Hubmann Martin , Groten Jonas , Pletz Martin , Grießer Thomas , Plevová Kateřina , Nemitz Wolfgang , Stadlober Barbara
Published: March 2023

Light guiding is used to direct light from an emitting source to a different location. It is frequently realized through a clad–core structure with a difference in the refractive index of the materials. This paper explores the possibility of combining a fluoropolymer (THV) film of low refractive index, serving as a cladding layer, with a polycarbonate (PC) core, via injection molding. Pristine THV lacks adherence to the PC. However, when treated with O2 plasma prior to overmolding, bonding can be established that was quantified in peel tests. The effect of this surface treatment was further investigated by adjusting the plasma treatment duration and time to overmolding. Furthermore, parameter studies comprising the four molding parameters, namely packing pressure, injection speed, melt temperature, and mold temperature, were performed. Numerical injection molding simulations assessed the prevailing temperatures at the PC–THV boundary. Consequently, the temperature–time integral could be calculated and linked with the measured peel strengths by fitting a proportionality constant. While the plasma treatment duration showed minor influence, the activation diminished with time, halving the measured peel loads within 24 h. The adhesion was experimentally found to increase with a lower packing pressure, faster injection speed, and higher melt and mold temperature. Those same molding relations influencing the peel loads were also found with the temperature–time integral when scaled by the proportionality constant in the simulations (R2=85%). Apparently, adhesion is added by molding settings which promote higher interface temperatures that prevail for longer. Hereby, the faster injection speed increases the melt temperature through shear heating. A higher packing pressure, in contrast, presumably increases the heat transfer at the PC–THV interface, accelerating the cooling. The measured peel loads were 0.3–1.6 N/mm for plasma-treated samples and nearly zero for pristine THV.
Effect of Nanometric Particles of Bentonite on the Mechanical Properties of a Thermoset Polymeric Matrix Reinforced with Hemp Fibers
Authors: Fernández Meylí Valin , González María José Ahumada , Oyanadel Rolando Briones , Rivera José Luis Valin , Soto Angel Rodríguez , Ortega Alvaro González , Ketterer Cristobal Galleguillos , Alvarez Alexander Alfonso , Diaz Francisco Rolando Valenzuela , García del Pino Gilberto
Published: March 2023

The influence of the addition of bentonite nanoparticles on the tensile and flexural strength of a thermosetting polymer matrix composite material reinforced with hemp fibers was de-terminated. All composites were manufactured with 5% of bentonite in the polymer mass–weight ratios and 10 to 45 wt% of fibers with a step of 5%. For mechanical characterization, tensile and flexural tests were performed: scanning electron microscopy and energy-dispersive X-ray spectroscopy analyses were carried out. The tensile strength of the samples containing bentonite compared to the polymer samples with the fiber addition was affected for all fiber addition percentages, except for 35% while the flexural resistance improved with the addition of bentonite in the percentages of 20, 30, 35, and 45% of fiber addition. With the addition of bentonite, the maximum values of tensile and flexural strength were both obtained for the 35% addition of fibers, with values of 34.28 MPa and 98.04 MPa, respectively. The presence of bentonite favored the rigidity of the material to traction and bending, which was reflected through an increase in the elastic modulus compared to the composite that only had fiber. The maximum values obtained were 9065 MPa in tension and 8453 MPa in flexion for the 40% and 35% of addition of fiber, respectively. Microscopy showed a good distribution of fibers in the matrix, the absence of internal porosities, and a good interaction between matrix and reinforcement.
Electrical Heaters for Anti/De-Icing of Polymer Structures
Authors: Shiverskii Aleksei V. , Owais Mohammad , Mahato Biltu , Abaimov Sergey G.
Published: March 2023

The problem of icing for surfaces of engineering structures requires attention more and more every year. Active industrialization in permafrost zones is currently underway; marine transport in Arctic areas targets new goals; the requirements for aerodynamically critical surfaces of wind generators and aerospace products, serving at low temperatures, are increasing; and fiber-reinforced polymer composites find wide applicability in these structural applications demanding the problem of anti/de-icing to be addressed. The traditional manufacturing approaches are superimposed with the new technologies, such as 3D printers and robotics for laying heat wires or cheap and high-performance Thermal Sprayed methods for metallic cover manufacturing. Another next step in developing heaters for polymer structures is nano and micro additives to create electrically conductive heating networks within. In our study, we review and comparatively analyze the modern technologies of structure heating, based on resistive heating composites.
A Thermo-Catalytic Pyrolysis of Polystyrene Waste Review: A Systematic, Statistical, and Bibliometric Approach
Authors: Gonzalez-Aguilar Arantxa M. , Pérez-García Vicente , Riesco-Ávila José M.
Published: March 2023

Global polystyrene (PS) production has been influenced by the lightness and heat resistance this material offers in different applications, such as construction and packaging. However, population growth and the lack of PS recycling lead to a large waste generation, affecting the environment. Pyrolysis has been recognized as an effective recycling method, converting PS waste into valuable products in the chemical industry. The present work addresses a systematic, bibliometric, and statistical analysis of results carried out from 2015 to 2022, making an extensive critique of the most influential operation parameters in the thermo-catalytic pyrolysis of PS and its waste. The systematic study showed that the conversion of PS into a liquid with high aromatic content (84.75% of styrene) can be achieved by pyrolysis. Discussion of PS as fuel is described compared to commercial fuels. In addition, PS favors the production of liquid fuel when subjected to co-pyrolysis with biomass, improving its properties such as viscosity and energy content. A statistical analysis of the data compilation was also discussed, evaluating the influence of temperature, reactor design, and catalysts on product yield.
The Effect of Various Fillers on the Properties of Methyl Vinyl Silicone Rubber
Authors: Chen Yun , Wang Kun , Zhang Chong , Yang Wei , Qiao Bo , Yin Li
Published: March 2023

Silicone rubber (SIR) has been widely used in electrical insulation fields, and the introduction of new materials is very important for the performance improvement of SIR composites. In this work, four different fillers, including aluminium hydroxide (ATH), yimonite (YMT), boron nitride (BN) and mica-filled SIR composites were prepared, and the vulcanization behavior, mechanical properties, insulation performance and hydrophobicity of the SIR composites were investigated and compared. Both BN- and mica-filled SIR composites showed excellent insulation performance, while the ATH-filled SIR composite exhibited the best mechanical properties with an elongation at break of 230% and a tensile strength of 2.9 MPa. The SIR/BN composite showed a breakdown strength of 29.2 kV/mm with a 5% failure rate. The addition of YMT deteriorated the insulation performance of SIR but improved the elongation at break and hydrophobicity, with an elongation at break increasing from 115% to 410% and the static contact angle improving from 109.8° to 115.6°.
Effect of Heat–Moisture Treatment on Crystallinity, Digestibility Properties, Bioactive Compounds, and Antioxidant Activity of Purple Rice (Oryza sativa L. indica) Flour
Authors: Chuwech Methus , Rakariyatham Nuansri , Tinoi Jidapha , Suwitchayanon Prapaipit , Chandet Nopakarn
Published: March 2023

Purple rice flour was modified using heat–moisture treatment (HMT) in three cycles using an oven (OHMT) and autoclave (AHMT) at temperatures of 100 °C and 120 °C, and with moisture levels of 20%, 25%, and 30%. X-ray diffraction was used to analyze the changes in the molecular structure. The swelling capacity, solubility, and starch digestibility, including rapidly digestible starch (RDS), slowly digestible starch (SDS), and resistant starch (RS), were studied in both native and modified purple rice flour. the bioactive compounds and antioxidant activities were also evaluated. Both OHMT and AHMT resulted in a decrease in swelling capacity, solubility, and RDS, but an increase in RS and SDS values compared to the native purple rice flour. All samples showed an increase in relative crystallinity. Both treatments also had an impact on the bioactive compounds and antioxidant activities, leading to a decrease in total phenolic content, total anthocyanin content, and the scavenging activity of DPPH and ABTS radicals compared to the native purple rice flour. The findings suggest that HMT can both improve the functional properties of purple rice flour and hold potential for use in various food industries.
A Transfer Learning Methodology for Recognizing Unsafe Behavior during Lifting Operations in a Chemical Plant
Authors: Li Hua , Xue Xicheng , Wang Yanbin , Wu Lizhou , Li Xinhong
Published: March 2023

Large lifting equipment is used regularly in the maintenance operations of chemical plant installations, where safety controls must be carried out to ensure the safety of lifting operations. This paper presents a convolutional neural network (CNN) methodology, based on the PyTorch framework, to identify unsafe behavior among lifting operation drivers, specifically, by collecting 22,352 images of equipment lifting operations over a certain time period in a chemical plant. The lifting drivers’ behavior was divided into eight categories, and a ResNet50 network model was selected to identify the drivers’ behavior in the pictures. The results show that the proposed ResNet50 network model based on transfer learning achieves a 99.6% accuracy rate, a 99% recall rate and a 99% F1 value for the expected behaviors of eight lifting operation drivers. This knowledge regarding unsafe behavior in the chemical industry provides a new perspective for preventing safety accidents caused by the dangerous behaviors of lifting operation drivers.
In God We Trust: Community and Immunity in American Religions during COVID-19
Authors: Brown Julia
Published: March 2023

From the systemic issues of race and class division to political partisanship and religious identity, the pandemic has affected many aspects of American social and political life. I interrogate the role that religions have played in communal identity-making during the pandemic, and how such identities shaped ideological responses, particularly in the US, stymying public health efforts to stop, or at least significantly slow, the spread of COVID-19. Drawing from Gabriel Garcia Marquez’s Love in the Time of Cholera as a historical case study, I use Garcia Marquez’s depiction of religion’s identity-making power during the cholera pandemic depicted in the novel as a comparison by which to understand current experiences of white Evangelical Christians in America during the current COVID-19 pandemic, particularly those who reject risk-minimizing practices such as mask wearing, quarantining, and vaccination. Drawing both from representations of Roberto Esposito’s theory of immunity and community, and from Lauren Berlant’s concept of “cruel optimism”, as well as sociological understandings of religion and identity, I argue that the boundary-making practices of religion and of communal and national identity are related to the complex and often contradictory set of moral practices that led many white Evangelicals to disregard public health policies surrounding COVID-19. A concurrent analysis of Garcia Marquez’s novel and of current events will allow me to explore this phenomenon, as Lauren Berlant would put it, both through the historically affective aesthetic and through the affective present.
The Impacts of Quality-Oriented Dataset Labeling on Tree Cover Segmentation Using U-Net: A Case Study in WorldView-3 Imagery
Authors: Jiang Tao , Freudenberg Maximilian , Kleinn Christoph , Ecker Alexander , Nölke Nils
Published: March 2023

Deep learning has emerged as a prominent technique for extracting vegetation information from high-resolution satellite imagery. However, less attention has been paid to the quality of dataset labeling as compared to research into networks and models, despite data quality consistently having a high impact on final accuracies. In this work, we trained a U-Net model for tree cover segmentation in 30 cm WorldView-3 imagery and assessed the impact of training data quality on segmentation accuracy. We produced two reference tree cover masks of different qualities by labeling images accurately or roughly and trained the model on a combination of both, with varying proportions. Our results show that models trained with accurately delineated masks achieved higher accuracy (88.06%) than models trained on masks that were only roughly delineated (81.13%). When combining the accurately and roughly delineated masks at varying proportions, we found that the segmentation accuracy increased with the proportion of accurately delineated masks. Furthermore, we applied semisupervised active learning techniques to identify an efficient strategy for selecting images for labeling. This showed that semisupervised active learning saved nearly 50% of the labeling cost when applied to accurate masks, while maintaining high accuracy (88.07%). Our study suggests that accurate mask delineation and semisupervised active learning are essential for efficiently generating training datasets in the context of tree cover segmentation from high-resolution satellite imagery.
Daily Sea Ice Concentration Product over Polar Regions Based on Brightness Temperature Data from the HY-2B SMR Sensor
Authors: Wu Suhui , Shi Lijian , Zou Bin , Zeng Tao , Dong Zhaoqing , Lu Dunwang
Published: March 2023

Polar sea ice profoundly affects atmospheric and oceanic circulation and plays a significant role in climate change. Sea ice concentration (SIC) is a key geophysical parameter used to quantify these changes. In this study, we determined SIC products for the Arctic and Antarctic from 2019 to 2021 using data from the Chinese marine satellite Haiyang 2B (HY-2B) with an improved bootstrap algorithm. Then the results were compared with similar operational SIC products and ship-based data. Our findings demonstrate the effectiveness of the improved algorithm for accurately determining SIC in polar regions. Additionally, the results of the study demonstrate that the SIC product obtained through the improved bootstrap algorithm has a high correlation with other similar SIC products. The daily average SIC of the different products showed similar inter-annual trends for both the Arctic and Antarctic regions. Comparison of the different SIC products showed that the Arctic BT-SMR SIC was slightly lower than the BT-SSMIS and BT-AMSR2 SIC products, while the difference between Antarctic SIC products was more pronounced. The lowest MAE was between the BT-SSMIS SIC and BT-SMR SIC in both regions, while the largest MAE was between the NT-SMR and BT-SMR in the Arctic, and between the NT-SSMIS and BT-SMR in the Antarctic. The SIE and SIA time series showed consistent trends, with a greater difference in SIA than SIC and a slight difference in SIA between the BT-AMSR2 and BT-SMR in the Arctic. Evaluation of the different SIC products using ship-based observation data showed a high correlation between the BT-SMR SIC and the ship-based SIC of approximately 0.85 in the Arctic and 0.88 in the Antarctic. The time series of dynamic tie-points better reflected the seasonal variation in sea ice radiation characteristics. This study lays the foundation for the release of long-term SIC product series from the Chinese autonomous HY-2B satellite, which will ensure the continuity of polar sea ice records over the past 40 years despite potential interruptions.
A Modified NLCS Algorithm for High-Speed Bistatic Forward-Looking SAR Focusing with Spaceborne Illuminator
Authors: Liu Yuzhou , Li Yachao , Song Xuan , Wang Xuanqi
Published: March 2023

The coupling and spatial variation of range and azimuth parameters is the biggest challenge for bistatic forward-looking SAR (BFSAR) imaging. In contrast with the monostatic SAR and translational invariant bistatic SAR (TI-BSAR), the range cell migration (RCM), and Doppler parameters of high-speed bistatic forward-looking SAR (HS-BFSAR) have two-dimensional spatial variation characteristics, which makes it difficult to obtain SAR images with satisfactory global focusing. Firstly, based on the configuration of the spaceborne illuminator and high-speed forward-looking receiving platform, the accurate range-Doppler domain expression of the echo signal is derived in this paper. Secondly, using this analytical expression, a range nonlinear chirp scaling (NLCS) is proposed to equalize the RCM and equivalent range frequency modulation (FM) rate so that they can be uniformly processed in the two-dimensional frequency domain. Next, in the azimuth processing, the proposed method decomposes the Doppler contribution of the transmitter and receiver, respectively. Then, an azimuth NLCS is used to eliminate the spatial variation of the azimuth FM rate. Finally, a range-dependent azimuth filter is constructed to achieve azimuth compression. Simulation results validate the efficiency and effectiveness of the proposed algorithm.
Convolutional Neural Network-Driven Improvements in Global Cloud Detection for Landsat 8 and Transfer Learning on Sentinel-2 Imagery
Authors: Pang Shulin , Sun Lin , Tian Yanan , Ma Yutiao , Wei Jing
Published: March 2023

A stable and reliable cloud detection algorithm is an important step of optical satellite data preprocessing. Existing threshold methods are mostly based on classifying spectral features of isolated individual pixels and do not contain or incorporate the spatial information. This often leads to misclassifications of bright surfaces, such as human-made structures or snow/ice. Multi-temporal methods can alleviate this problem, but cloud-free images of the scene are difficult to obtain. To deal with this issue, we extended four deep-learning Convolutional Neural Network (CNN) models to improve the global cloud detection accuracy for Landsat imagery. The inputs are simplified as all discrete spectral channels from visible to short wave infrared wavelengths through radiometric calibration, and the United States Geological Survey (USGS) global Landsat 8 Biome cloud-cover assessment dataset is randomly divided for model training and validation independently. Experiments demonstrate that the cloud mask of the extended U-net model (i.e., UNmask) yields the best performance among all the models in estimating the cloud amounts (cloud amount difference, CAD = −0.35%) and capturing the cloud distributions (overall accuracy = 94.9%) for Landsat 8 imagery compared with the real validation masks; in particular, it runs fast and only takes about 41 ± 5.5 s for each scene. Our model can also actually detect broken and thin clouds over both dark and bright surfaces (e.g., urban and barren). Last, the UNmask model trained for Landsat 8 imagery is successfully applied in cloud detections for the Sentinel-2 imagery (overall accuracy = 90.1%) via transfer learning. These prove the great potential of our model in future applications such as remote sensing satellite data preprocessing.
Remote Seismoacoustic Monitoring of Tropical Cyclones in the Sea of Japan
Authors: Dolgikh Grigory , Dolgikh Stanislav , Chupin Vladimir , Davydov Aleksandr , Mishakov Aleksandr
Published: March 2023

In the course of processing and analysing data from a two-coordinate laser strainmeter, obtained during the propagation of the Hagupit typhoon over the Sea of Japan, we researched the possibility of sensing the direction of tropical cyclones/typhoons and also tracking their movements. We tackled the set of problems on the basis of further development of the technology for sensing the direction of primary and secondary microseisms’ generation zones, the “voice of the sea” microseisms, and clarifying the connection between their formation zones and movement of tropical cyclones. In our work, we identified the formation zones of primary and secondary microseisms, which were registered by the two-coordinate laser strainmeter. We established that, from the registered microseisms, we could determine the main characteristics of wind waves generated by a typhoon, but we could not identify its location. By processing the two-coordinate laser strainmeter data in the range of the “voice of the sea” microseisms, we established the possibility of sensing the direction of the “voice of the sea” microseisms’ formation zones, which are associated with zones of the highest energy capacity of typhoons, and this allowed us to tracking the direction of the typhoons’ movement.
A Data Assimilation Method Combined with Machine Learning and Its Application to Anthropogenic Emission Adjustment in CMAQ
Authors: Huang Congwu , Niu Tao , Wu Hao , Qu Yawei , Wang Tijian , Li Mengmeng , Li Rong , Liu Hongli
Published: March 2023

Anthropogenic emissions play an important role in air quality forecasting. To improve the forecasting accuracy, the use of nudging as the data assimilation method, combined with extremely randomized trees (ExRT) as the machine learning method, was developed and applied to adjust the anthropogenic emissions in the Community Multiscale Air Quality modeling system (CMAQ). This nudging–ExRT method can iterate with the forecast and is suitable for linear and nonlinear emissions. For example, an episode between 15 and 30 January 2019 was simulated for China’s Beijing–Tianjin–Hebei (BTH) region. For PM2.5, the correlation coefficient of the site averaged concentration (Ra) increased from 0.85 to 0.94, and the root mean square error (RMSEa) decreased from 24.41 to 9.97 µg/m3. For O3, the Ra increased from 0.75 to 0.81, and the RMSEa decreased from 13.91 to 12.07 µg/m3. These results showed that nudging–ExRT can significantly improve forecasting skills and can be applied to routine air quality forecasting in the future.
Nearest Neighboring Self-Supervised Learning for Hyperspectral Image Classification
Authors: Qin Yao , Ye Yuanxin , Zhao Yue , Wu Junzheng , Zhang Han , Cheng Kenan , Li Kun
Published: March 2023

Recently, state-of-the-art classification performance of natural images has been obtained by self-supervised learning (S2L) as it can generate latent features through learning between different views of the same images. However, the latent semantic information of similar images has hardly been exploited by these S2L-based methods. Consequently, to explore the potential of S2L between similar samples in hyperspectral image classification (HSIC), we propose the nearest neighboring self-supervised learning (N2SSL) method, by interacting between different augmentations of reliable nearest neighboring pairs (RN2Ps) of HSI samples in the framework of bootstrap your own latent (BYOL). Specifically, there are four main steps: pretraining of spectral spatial residual network (SSRN)-based BYOL, generation of nearest neighboring pairs (N2Ps), training of BYOL based on RN2P, final classification. Experimental results of three benchmark HSIs validated that S2L on similar samples can facilitate subsequent classification. Moreover, we found that BYOL trained on an un-related HSI can be fine-tuned for classification of other HSIs with less computational cost and higher accuracy than training from scratch. Beyond the methodology, we present a comprehensive review of HSI-related data augmentation (DA), which is meaningful to future research of S2L on HSIs.
Trajectory Clustering-Based Anomaly Detection in Indoor Human Movement
Authors: Lan Doi Thi , Yoon Seokhoon
Published: March 2023

Human movement anomalies in indoor spaces commonly involve urgent situations, such as security threats, accidents, and fires. This paper proposes a two-phase framework for detecting indoor human trajectory anomalies based on density-based spatial clustering of applications with noise (DBSCAN). The first phase of the framework groups datasets into clusters. In the second phase, the abnormality of a new trajectory is checked. A new metric called the longest common sub-sequence using indoor walking distance and semantic label (LCSS_IS) is proposed to calculate the similarity between trajectories, extending from the longest common sub-sequence (LCSS). Moreover, a DBSCAN cluster validity index (DCVI) is proposed to improve the trajectory clustering performance. The DCVI is used to choose the epsilon parameter for DBSCAN. The proposed method is evaluated using two real trajectory datasets: MIT Badge and sCREEN. The experimental results show that the proposed method effectively detects human trajectory anomalies in indoor spaces. With the MIT Badge dataset, the proposed method achieves 89.03% in terms of F1-score for hypothesized anomalies and above 93% for all synthesized anomalies. In the sCREEN dataset, the proposed method also achieves impressive results in F1-score on synthesized anomalies: 89.92% for rare location visit anomalies (τ = 0.5) and 93.63% for other anomalies.
ABANICCO: A New Color Space for Multi-Label Pixel Classification and Color Analysis
Authors: Nicolás-Sáenz Laura , Ledezma Agapito , Pascau Javier , Muñoz-Barrutia Arrate
Published: March 2023

Classifying pixels according to color, and segmenting the respective areas, are necessary steps in any computer vision task that involves color images. The gap between human color perception, linguistic color terminology, and digital representation are the main challenges for developing methods that properly classify pixels based on color. To address these challenges, we propose a novel method combining geometric analysis, color theory, fuzzy color theory, and multi-label systems for the automatic classification of pixels into 12 conventional color categories, and the subsequent accurate description of each of the detected colors. This method presents a robust, unsupervised, and unbiased strategy for color naming, based on statistics and color theory. The proposed model, “ABANICCO” (AB ANgular Illustrative Classification of COlor), was evaluated through different experiments: its color detection, classification, and naming performance were assessed against the standardized ISCC–NBS color system; its usefulness for image segmentation was tested against state-of-the-art methods. This empirical evaluation provided evidence of ABANICCO’s accuracy in color analysis, showing how our proposed model offers a standardized, reliable, and understandable alternative for color naming that is recognizable by both humans and machines. Hence, ABANICCO can serve as a foundation for successfully addressing a myriad of challenges in various areas of computer vision, such as region characterization, histopathology analysis, fire detection, product quality prediction, object description, and hyperspectral imaging.
A Cost-Effective Lightning Current Measuring Instrument with Wide Current Range Detection Using Dual Signal Conditioning Circuits
Authors: Lee Youngjun , Lee Young Sam
Published: March 2023

Lightning strikes can cause significant damage to critical infrastructure and pose a serious threat to public safety. To ensure the safety of facilities and investigate the causes of lightning accidents, we propose a cost-effective design method for a lightning current measuring instrument that uses a Rogowski coil and dual signal conditioning circuits to detect a wide range of lightning currents, ranging from hundreds of A to hundreds of kA. To implement the proposed lightning current measuring instrument, we design signal conditioning circuits and software capable of detecting and analyzing lightning currents from ±500 A to ±100 kA. By employing dual signal conditioning circuits, it offers the advantage of detecting a wide range of lightning currents compared to existing lightning current measuring instruments. The proposed instrument has the following features: First, the peak current, polarity, T1 (front time), T2 (time to half value), and Q (amount of energy of the lightning current) can be analyzed and measured with a fast sampling time of 380 ns. Second, it can distinguish whether a lightning current is induced or direct. Third, a built-in SD card is provided to save the detected lightning data. Finally, it provides Ethernet communication capability for remote monitoring. The performance of the proposed instrument is evaluated and validated by applying induced and direct lightning using a lightning current generator.
The Story of Futures Studies: An Interdisciplinary Field Rooted in Social Sciences
Authors: Kristóf Tamás , Nováky Erzsébet
Published: March 2023

This article presents the almost century-long history of the development of futures studies in a comprehensive review. Futures studies, rooted in sociology and policy sciences, had become an academic discipline by the 1960s. One of the major global communities representing the discipline, the World Futures Studies Federation (WFSF), celebrates its 50th anniversary in 2023. In the 1970s, the focus was placed on discourses on global problems and preferred futures. Futures studies then developed a global institutional community and become a mature discipline by the 1980s and 1990s. Futurists by then had already mutually shared theoretical perspectives, objectives, ethics, and methods, and had produced empirical results. A wide range of comprehensive publications at that time synthesized the foundations and preceding results of futures studies. From the turn of the millennium, active discourse took place on the forthcoming role of futures studies. By that time, the theoretical, methodological, and practical knowledge foundations of the discipline had also appeared in internationally well-documented curricula. Since around 2010, the discipline has been characterized by the development of practical foresight projects. Based on notable trends and identified research gaps, this article formulates up-to-date expectations and research directions within which futures studies might develop in the future.