bluuebunny/crossref_metadata_2025 huggingface dataset:
VO2-Based Spacecraft Smart Radiator with High Emissivity Tunability and Protective Layer
Authors: Xu Qingjie , Ji Haining , Ren Yang , Ou Yangyong , Liu Bin , Wang Yi , Chen Yongxing , Long Peng , Deng Cong , Wang Jingting
Published: August 2024

In the extreme space environment, spacecraft endure dramatic temperature variations that can impair their functionality. A VO2-based smart radiator device (SRD) offers an effective solution by adaptively adjusting its radiative properties. However, current research on VO2-based thermochromic films mainly focuses on optimizing the emissivity tunability (Δε) of single-cycle sandwich structures. Although multi-cycle structures have shown increased Δε compared to single-cycle sandwich structures, there have been few systematic studies to find the optimal cycle structure. This paper theoretically discusses the influence of material properties and cyclic structure on SRD performance using Finite-Difference Time-Domain (FDTD) software, which is a rigorous and powerful tool for modeling nano-scale optical devices. An optimal structural model with maximum emissivity tunability is proposed. The BaF2 obtained through optimization is used as the dielectric material to further optimize the cyclic resonator. The results indicate that the tunability of emissivity can reach as high as 0.7917 when the BaF2/VO2 structure is arranged in three periods. Furthermore, to ensure a longer lifespan for SRD under harsh space conditions, the effects of HfO2 and TiO2 protective layers on the optical performance of composite films are investigated. The results show that when TiO2 is used as the protective layer with a thickness of 0.1 µm, the maximum emissivity tunability reaches 0.7932. Finally, electric field analysis is conducted to prove that the physical mechanism of the smart radiator device is the combination of stacked Fabry–Perot resonance and multiple solar reflections. This work not only validates the effectiveness of the proposed structure in enhancing spacecraft thermal control performance but also provides theoretical guidance for the design and optimization of SRDs for space applications.
Relationship between Markers of Gut Barrier Function and Erythrocyte Membrane PUFAs in Diarrhea-Predominant IBS Patients Undergoing a Low-FODMAP Diet
Authors: Linsalata Michele , Ignazzi Antonia , D’Attoma Benedetta , Riezzo Giuseppe , Mallardi Domenica , Orlando Antonella , Prospero Laura , Notarnicola Maria , De Nunzio Valentina , Pinto Giuliano , Russo Francesco
Published: August 2024

Many patients with irritable bowel syndrome (IBS) have a compromised intestinal barrier associated with low-grade inflammation. Polyunsaturated fatty acids (PUFAs) are potential mediators of inflammation: omega-6 PUFAs are pro-inflammatory, while omega-3 PUFAs are antioxidant and anti-inflammatory. Zonulin is a potential biomarker for small intestinal permeability (s-IP). This study investigated the relationship between PUFAs and gastrointestinal (GI) barrier integrity in IBS patients with predominant diarrhea (IBS-D). We evaluated GI barrier function indicators in the urine and bloodstream and erythrocyte membrane PUFA composition in 38 IBS-D patients (5 men, 33 women, 44.11 ± 1.64 years), categorized at baseline by fecal zonulin levels into high (≥107 ng/mL, H-FZ) and normal (<107 ng/mL N-FZ) groups. Evaluations were conducted prior to and following a 12-week diet low in FODMAPs (LFD). At baseline, H-FZ patients had s-IP significantly higher than the reference value, lower n-3 PUFAs levels, and higher n-6/n-3 PUFAs and arachidonic acid (AA) to eicosapentaenoic acid (EPA) ratios than N-FZ. After LFD, H-FZ patients showed significant increases in n-3 PUFAs levels; decreases in n-6 PUFAs, n-6/n-3 PUFAs and AA/EPA ratios; and improved s-IP. The n-6/n-3 PUFAs ratio positively correlated with fecal zonulin levels in all subjects. These findings highlight the relationship between PUFAs and the intestinal barrier, suggesting their role in IBS-D pathophysiology and confirming the positive effects of LFD in managing IBS-D.
Dietary and Lifestyle Strategies for Obesity
Authors: Barber Thomas M. , Kabisch Stefan , Pfeiffer Andreas F. H. , Weickert Martin O.
Published: August 2024

The prevalence of obesity globally has tripled over the last half century, and currently affects around 650 million adults and 340 million children and adolescents (ages 5–19 years). Obesity contributes towards >50 co-morbidities and premature mortality. Obesity is a highly stigmatised condition that is associated with much mental and emotional distress and dysfunction. Thus, obesity is a major contributor to healthcare expenditure globally. Traditionally, the management of obesity stratifies into three major groups that include metabolic (bariatric) surgery, pharmacotherapies, and lifestyle (primarily dietary) strategies. Although listed as a separate category, dietary strategies for obesity remain a central component of any management plan, and often complement other surgical and pharmacotherapeutic options. Indeed, the effectiveness of any management approach for obesity relies upon successful behavioural changes, particularly relating to eating behaviours. In this concise review, we explore the foundational pillars of dietary strategies for obesity: sleep, listening, routine, de-stressing and optimisation of social conditions. We then discuss the importance of balancing dietary macronutrients (including dietary fibre, carbohydrates, protein and ultra-processed foods [UPFs]) as a key dietary strategy for obesity. Although we focus on general principles, we should provide bespoke dietary strategies for our patients, tailored to their individual needs. Rather than judging the utility of a diet based simply on its associated magnitude of weight loss, we should adopt a more holistic perspective in which a dietary strategy is valued for its overall health benefits, including the nurturing of our gut microbiota, to enable them to nurture and protect us.
Beneficial Effects of Ginger Extract on Eye Fatigue and Shoulder Stiffness: A Randomized, Double-Blind, and Placebo-Controlled Parallel Study
Authors: Higashikawa Fumiko , Nakaniida Yuta , Li Hongyang , Liang Lian , Kanno Keishi , Ogawa-Ochiai Keiko , Kiuchi Yoshiaki
Published: August 2024

This study aimed to assess ginger extract’s impact on ocular and peripheral blood flow and its potential to alleviate eye fatigue and shoulder stiffness. This study included 100 healthy individuals aged 20–73 years with eye fatigue and shoulder stiffness. Participants were randomly assigned to receive either placebo capsules or ginger extract capsules daily for eight weeks. Ocular blood flow, peripheral blood flow, eye fatigue (visual analog scale [VAS]), shoulder stiffness (VAS), body warmth (VAS), and shoulder muscle stiffness were assessed at weeks 0, 4, and 8, respectively. No improvement in ocular blood flow was observed under the study conditions. Conversely, peripheral blood flow in deep areas was enhanced in females (p = 0.033). Subgroup analysis by age (≥51 or <51 years) revealed that ginger’s effect on enhancing peripheral blood flow in deep vessels was restricted in females under 51 (p = 0.017). Similarly, subjective complaints of eye fatigue and shoulder stiffness were improved by ginger consumption in females under 51. Body warmth was favorably changed significantly in males ≥51 years due to ginger consumption. The muscle stiffness showed no statistically significant changes. In conclusion, ginger consumption reduces eye fatigue and shoulder stiffness by enhancing peripheral blood flow in relatively young females.
Extracellular Vesicles of the Probiotic Escherichia coli Nissle 1917 Reduce PepT1 Levels in IL-1β-Treated Caco-2 Cells via Upregulation of miR-193a-3p
Authors: Olivo-Martínez Yenifer , Martínez-Ruiz Sergio , Cordero Cecilia , Badia Josefa , Baldoma Laura
Published: August 2024

PepT1, a proton-coupled oligopeptide transporter, is crucial for intestinal homeostasis. It is mainly expressed in small intestine enterocytes, facilitating the absorption of di/tri-peptides from dietary proteins. In the colon, PepT1 expression is minimal to prevent excessive responses to proinflammatory peptides from the gut microbiota. However, increased colonic PepT1 is linked to chronic inflammatory diseases and colitis-associated cancer. Despite promising results from animal studies on the benefits of extracellular vesicles (EVs) from beneficial gut commensals in treating IBD, applying probiotic EVs as a postbiotic strategy in humans requires a thorough understanding of their mechanisms. Here, we investigate the potential of EVs of the probiotic Nissle 1917 (EcN) and the commensal EcoR12 in preventing altered PepT1 expression under inflammatory conditions, using an interleukin (IL)-1-induced inflammation model in Caco-2 cells. The effects are evaluated by analyzing the expression of PepT1 (mRNA and protein) and miR-193a-3p and miR-92b, which regulate, respectively, PepT1 mRNA translation and degradation. The influence of microbiota EVs on PepT1 expression is also analyzed in the presence of bacterial peptides that are natural substrates of colonic PepT1 to clarify how the regulatory mechanisms function under both physiological and pathological conditions. The main finding is that EcN EVs significantly decreases PepT1 protein via upregulation of miR-193a-3p. Importantly, this regulatory effect is strain-specific and only activates in cells exposed to IL-1β, suggesting that EcN EVs does not control PepT1 expression under basal conditions but can play a pivotal role in response to inflammation as a stressor. By this mechanism, EcN EVs may reduce inflammation in response to microbiota in chronic intestinal disorders by limiting the uptake of bacterial proinflammatory peptides.
Umbrella Review on the Relationship between Vitamin D Levels and Cancer
Authors: Schömann-Finck Matthias , Reichrath Jörg
Published: August 2024

Background: Cancer is a growing public health problem and cancer is linked to vitamin D via several mechanisms. Recent umbrella reviews on the extra-skeletal effects of vitamin D did not turn their attention to cancer. Accordingly, an overview of the current state of research is needed. Materials and methods: An umbrella review was conducted to provide an overview of systematic reviews on the association between vitamin D and incidence or mortality of breast cancer, colorectal cancer, lung cancer, pancreatic cancer, and prostate cancer. Results: Inverse correlations were found between the vitamin D level (measured by circulating 25(OH)D) and mortality for all five types of cancer. For breast cancer, colorectal cancer, lung cancer, and pancreatic cancer, there are also hints of a lower incidence due to higher 25(OH)D levels. Conclusion: As most reviews include observational studies, conclusions on causality cannot be made. Methodological differences between the included reviews and different study designs in the individual studies lead to methodological problems. Despite these problems, the review shows inverse correlations between 25(OH)D levels and mortality, and mostly inverse correlations between 25(OH)D levels and incidence.
Establishment of Dissolution Test Method for Multi-Components in Traditional Chinese Medicine Preparations Based on In Vitro–In Vivo Correlation
Authors: Guo Pengcheng , Wang Qizheng , Xiang Xiaoqiang , Zhang Yufeng , Pan Yue , Zuo Zhong , Wang Jianxin
Published: August 2024

In this study, a multi-component integrated dissolution evaluation system of Yuanhu Zhitong tablets (YZTs) was established based on in vitro and in vivo correlation (IVIVC). The dissolution tests of five quality markers (Q-markers), including tetrahydropalmatine, α-allocryptopine, protopine, corydaline, and byakangelicin, in YZTs were conducted under different dissolution conditions, and pharmacokinetic studies were performed in beagle dogs to construct a correlation model using numerical deconvolution. The data of the five ingredients were integrated in vitro and in vivo according to the biopharmaceutical classification system (BCS) to establish an IVIVC integrating multiple Q-markers. The dissolution media with the best correlation of components were obtained and validated. The results showed that all five components were classified as BCS I compounds, and α-allocryptopine, byakangelicin, tetrahydropalmatine, and corydaline showed good correlation in the paddle method, 75 rpm, with dissolution media of artificial gastric fluid, acetate buffer, acetate buffer and 0.1 M HCl, respectively. Protopine showed good correlation in the paddle method, 100 rpm, with dissolution media of 0.1 M HCl. The integrated BCS I Q-markers showed the best correlation in the medium of acetate buffer. The multi-component integrated dissolution evaluation system established in this experiment accurately predicted the pharmacokinetic data of YZTs by verifying the media, which can be used for the quality control of YZTs. The present study provides an effective and promising strategy for the dissolution evaluation for traditional Chinese medicine preparations.
Revitalizing Bacillus Calmette–Guérin Immunotherapy for Bladder Cancer: Nanotechnology and Bioengineering Approaches
Authors: Lv Maoxin , Shang Shihao , Liu Kepu , Wang Yuliang , Xu Peng , Song Hao , Zhang Jie , Sun Zelong , Yan Yuhao , Zhu Zheng , Wu Hao , Li Hao
Published: August 2024

Bacillus Calmette–Guérin (BCG) immunotherapy has been a cornerstone treatment for non-muscle-invasive bladder cancer for decades and still faces challenges, such as severe immune adverse reactions, which reduce its use as a first-line treatment. This review examines BCG therapy’s history, mechanisms, and current status, highlighting how nanotechnology and bioengineering are revitalizing its application. We discuss novel nanocarrier systems aimed at enhancing BCG’s efficacy while mitigating specific side effects. These approaches promise improved tumor targeting, better drug loading, and an enhanced stimulation of anti-tumor immune responses. Key strategies involve using materials such as liposomes, polymers, and magnetic particles to encapsulate BCG or functional BCG cell wall components. Additionally, co-delivering BCG with chemotherapeutics enhances drug targeting and tumor-killing effects while reducing drug toxicity, with some studies even achieving synergistic effects. While most studies remain experimental, this research direction offers hope for overcoming BCG’s limitations and advancing bladder cancer immunotherapy. Further elucidation of BCG’s mechanisms and rigorous safety evaluations of new delivery systems will be crucial for translating these innovations into clinical practice.
The Antinociceptive Role of Nrf2 in Neuropathic Pain: From Mechanisms to Clinical Perspectives
Authors: Petrikonis Kestutis , Bernatoniene Jurga , Kopustinskiene Dalia M. , Casale Roberto , Davinelli Sergio , Saso Luciano
Published: August 2024

Neuropathic pain, a chronic condition resulting from nerve injury or dysfunction, presents significant therapeutic challenges and is closely associated with oxidative stress and inflammation, both of which can lead to mitochondrial dysfunction. The nuclear factor erythroid 2-related factor 2 (Nrf2) pathway, a critical cellular defense mechanism against oxidative stress, has emerged as a promising target for neuropathic pain management. Nrf2 modulators enhance the expression of antioxidant and cytoprotective genes, thereby reducing oxidative damage, inflammation, and mitochondrial impairment. This review explores the antinociceptive effects of Nrf2, highlighting how pharmacological agents and natural compounds may be used as potential therapeutic strategies against neuropathic pain. Although preclinical studies demonstrate significant pain reduction and improved nerve function through Nrf2 activation, several clinical challenges need to be addressed. However, emerging clinical evidence suggests potential benefits of Nrf2 modulators in several conditions, such as diabetic neuropathy and multiple sclerosis. Future research should focus on further elucidating the molecular role of Nrf2 in neuropathic pain to optimize its modulation efficacy and maximize clinical utility.
Three-Dimensional Printing of PVA Capsular Devices for Applications in Compounding Pharmacy: Effect of Design Parameters on Pharmaceutical Performance
Authors: Peña Juan Francisco , Cotabarren Ivana , Gallo Loreana
Published: August 2024

The creation of products with personalized or innovative features in the pharmaceutical sector by using innovative technologies such as three-dimensional (3D) printing is particularly noteworthy, especially in the realm of compounding pharmacies. In this work, 3D printed capsule devices (CDs) with different wall thicknesses (0.2, 0.3, 0.4, 0.6, and 0.9 mm) and sizes were designed and successfully fabricated varying printing parameters such as extrusion temperature, printing speed, material flow percent, and nozzle diameter. The physicochemical, pharmaceutical, and biopharmaceutical performance of these CDs was evaluated with the aim of achieving an immediate drug release profile comparable to hard gelatin capsules (HGC) for use in magistral compounding. It was observed that the disintegration time of the CDs increased with wall thickness, which correlated with a slower drug release rate. CDs with configurations presenting 0.4 mm wall thickness and sizes comparable to HGC n° 0, 1, and 2 demonstrated satisfactory weight uniformity, short disintegration times, and immediate drug release, indicating their potential as effective devices in future compounding pharmacy applications. In addition, a modified Weibull-type model was proposed that incorporates wall thickness as a new variable in predicting dissolution profiles. This model improves the process of selecting a specific wall thickness to achieve the desired dissolution rate within a specified time frame.
First Peek into the Transcriptomic Response in Heat-Stressed Tomato Inoculated with Septoglomus constrictum
Authors: Szentpéteri Viktor , Virág Eszter , Mayer Zoltán , Duc Nguyen Hong , Hegedűs Géza , Posta Katalin
Published: August 2024

In this study, we report the interaction between an arbuscular mycorrhizal fungus, Septoglomus constrictum, and tomato plants under heat stress. For the first time, this interaction was studied by Illumina RNA-seq, followed by a comprehensive bioinformatic analysis that investigated root and leaf tissue samples. The genome-wide transcriptional profiling displayed fewer transcriptomic changes in the root under heat-stress conditions caused by S. constrictum. The top 50 DEGs suggested significant changes in the expression of genes encoding heat-shock proteins, transporter proteins, and genes of phytohormone metabolism involving jasmonic acid signalling. S. constrictum induced the upregulation of genes associated with pathways such as ‘drought-responsive’ and the ‘development of root hair’ in the root, as well as ‘glycolipid desaturation’, ‘intracellular auxin transport’, and ‘ethylene biosynthesis’ in the leaf. The pathways ‘biotin biosynthesis’ and ‘threonine degradation’ were found in both investigated tissue types. Expression analysis of transcription factors showed 2 and 11 upregulated transcription factors in heat-stressed root and leaf tissues, respectively. However, we did not find shared transcription factors. Heat-stressed arbuscular mycorrhizal plants suffered less oxidative stress when exposed to high temperatures. Colorimetric tests demonstrated less accumulation of H2O2 and MDA in heat-stressed mycorrhizal plants. This phenomenon was accompanied by the higher expression of six stress genes that encode peroxidases, glutathione S-transferase and ubiquitin carboxyl-terminal hydrolase in roots and leaves. Our findings provide a new perspective on elucidating the functional metabolic processes of tomato plants under mycorrhizal-heat stressed conditions.
Revolutionizing Tomato Cultivation: CRISPR/Cas9 Mediated Biotic Stress Resistance
Authors: Shawky Abdelrahman , Hatawsh Abdulrahman , Al-Saadi Nabil , Farzan Raed , Eltawy Nour , Francis Mariz , Abousamra Sara , Ismail Yomna Y. , Attia Kotb , Fakhouri Abdulaziz S. , Abdelrahman Mohamed
Published: August 2024

Tomato (Solanum lycopersicon L.) is one of the most widely consumed and produced vegetable crops worldwide. It offers numerous health benefits due to its rich content of many therapeutic elements such as vitamins, carotenoids, and phenolic compounds. Biotic stressors such as bacteria, viruses, fungi, nematodes, and insects cause severe yield losses as well as decreasing fruit quality. Conventional breeding strategies have succeeded in developing resistant genotypes, but these approaches require significant time and effort. The advent of state-of-the-art genome editing technologies, particularly CRISPR/Cas9, provides a rapid and straightforward method for developing high-quality biotic stress-resistant tomato lines. The advantage of genome editing over other approaches is the ability to make precise, minute adjustments without leaving foreign DNA inside the transformed plant. The tomato genome has been precisely modified via CRISPR/Cas9 to induce resistance genes or knock out susceptibility genes, resulting in lines resistant to common bacterial, fungal, and viral diseases. This review provides the recent advances and application of CRISPR/Cas9 in developing tomato lines with resistance to biotic stress.
Morphology and Inheritance of Wavy Flower Form in Periwinkle (Catharanthus roseus (L.) G. Don)
Authors: Huang Ting-Hsuan , Lu Yi-Chien , Chen Yu-Huan , Shen Rong-Show
Published: August 2024

Periwinkle (Catharanthus roseus (L.) G. Don) is renowned for its diverse colors and resilience to harsh climates. Still, most commercial cultivars predominantly display flat petals. Using cultivars representing non-wavy, medium-wavy, and extreme-wavy flower forms, we examined morphological differences in both their mature leaves and floral organs. Phenotypes of self-pollinated (S1) and cross-pollinated (F1, F2) populations further underscored their morphological distinctions. Specifically, the extreme-wavy type displayed elliptical leaves, broader than the non-wavy type, with a pronounced acute apex and a notably wrinkled blade surface. The non-wavy type also bore intensely wavy petal margins and exhibited a smaller flower diameter, with a notable absence of a functional pistil, indicating female sterility. The insights gained allowed for early differentiation during the seedling period. This study suggests that the inheritance of these flower forms is regulated by an allele WAVY (Wv), which exhibits incomplete dominance. Concretely, the non-wavy form arises from a recessive homozygous expression (wvwv), the extreme-wavy from a dominant homozygous expression (WvWv), and the medium-wavy from a heterozygous expression (Wvwv). This study provides clarity on morphological descriptions and inheritance patterns of wavy flower forms, facilitating strategic breeding of diverse flower forms in periwinkle.
An Integrated Strategy for Analyzing the Complete Complex Integrated Structure of Maize MON810 and Identification of an SNP in External Insertion Sequences
Authors: Huang Chunmeng , Zhang Yongjun , Yu Huilin , Chen Xiuping , Xie Jiajian
Published: August 2024

Genetically modified maize (Zea mays L.) MON810 was approved for importation into China for feed use in 2004; however, the localization data concerning exogenous insertion sequences, which confer insect resistance, have been questionable. MON810 maize plants discovered in northeastern China were used to analyze the molecular characteristics of the exogenous insertion. Using PacBio-HiFi sequencing and PCR assays, we found the insertion was located in chromosome 8, and there was a CaMV35S promoter, hsp70 intron, and insecticide gene cry1Ab, except for genome sequence insertion in the MON810 event. Importantly, the 5′ and 3′ flanking sequences were located in the region of 55869747–55879326 and 68416240–68419152 on chromosome 5, respectively. The results of this study correct previous results on the genomic localization of the insertion structure for the MON810 event. We also found a single-nucleotide polymorphism (SNP) in the hsp70 intron, which is most likely the first SNP found in a transgenic insertion sequence. PCR amplification in conjunction with Sanger sequencing, allele-specific PCR (AS-PCR), and blocker displacement amplification (BDA) assays were all effective at detecting the base variance. The integrated strategy used in this study can serve as a model for other cases when facing similar challenges involving partially characterized genetic modification events or SNPs.
Experimental Investigations on Shear Thickening Fluids as “Liquid Body Armors”: Non-Conventional Formulations for Ballistic Protection
Authors: Alexe Florentina , Sau Ciprian , Iorga Ovidiu , Toader Gabriela , Diacon Aurel , Rusen Edina , Lazaroaie Claudiu , Ginghina Raluca Elena , Tiganescu Tudor Viorel , Teodorescu Mircea , Sobetkii Arcadie
Published: August 2024

Shear thickening fluids (STFs) have garnered attention as potential enhancers of protective capabilities and for the optimization of Kevlar® armor design. To assess the possible shear thickening properties and potential application in ballistic protection, ten formulations were developed by employing polyethylene glycol (PEG) or polypropylene glycol (PPG), along with fumed silica or Aerosil HDK®. Rheological characterization facilitated the identification of formulations displaying shear thickening behavior. The potential integration of the selected shear thickening fluids (STFs) into Kevlar®-based composites was investigated by studying the impact resistance of Kevlar® soft armor structures. Also, high-velocity impact testing revealed that the distance between aramid layers plays a crucial role in the impact resistance effectiveness of Kevlar®–STF composite structures and that there is a very narrow domain between optimal and undesired scenarios in which STF could facilitate the penetration of Kevlar. The introduction of STF between the Kevlar sheets disrupted this packing and the energy absorption capacity of the material was not improved. Only one formulation (PEG400, Aerosil 27 wt.%) led to a less profound traumatic imprint and stopped the bullet when it was placed between layers no.1 and no.2 from a total of 11 layers of Kevlar XP. These experimental findings align with the modeling and simulation of Kevlar®–STF composites using Ansys simulation software (Ansys® AutoDyn 2022 R2).
Improving the Tribological Performance of POM through the Incorporation of Bio-Based Materials
Authors: Kneissl Lucas M. , Joffe Roberts , Kalin Mitjan , Emami Nazanin
Published: August 2024

Polyoxymethylene (POM), an engineering polymer commonly used in tribological applications, is often reinforced with fossil-based fibers such as carbon and/or glass fibers to improve its properties. To find more sustainable solutions, in this study, the tribological performance of POM/short cellulose fiber composites at different sliding conditions is investigated. An improvement in the wear coefficient of roughly 69% is observed at the harshest conditions of 5 MPa and 1 m · s−1 with only 10 wt.% cellulose fibers. The friction behavior is furthermore stabilized through fiber addition, as the unfilled polymer did not show a steady state. No signs of thermo-oxidative degradation are found after tribological testing. This study presents promising results for sustainable wear-resistant polymer materials in tribological applications.
Sodium-Alginate-Doped Lignin Nanoparticles for PBAT Composite Films to Dually Enhance Tensile Strength and Elongation Performance with Functionality
Authors: Guo Qiyue , He Yuan , Wu Jianyu , Ye Haichuan , You Tingting , Xu Feng
Published: August 2024

It is a formidable challenge in thermoplastic/lignin composites to simultaneously boost tensile strength and elongation performance due to the rigidity of lignin. To address this issue, sodium-alginate-doped lignin nanoparticles (SLNPs) were prepared by combining solvent exchange and a coprecipitation method and used as an eco-friendly filler for poly(butylene adipate-co-terephthalate) (PBAT). The results indicated that the 1% polyanionic sodium alginate solution contributed to the formation of SLNP in lignin/THF solution. SLNP with a mean hydrodynamic diameter of ~500 nm and a Zeta potential value of −19.2 mV was obtained, indicating more hydrophobic lignin nanoparticles and a smaller number of agglomerates in SLNP suspension. Only 0.5 wt% SLNP addition improved the yield strength, tensile strength, and elongation at break by 32.4%, 31.8%, and 35.1% of the PBAT/SLNP composite films, respectively. The reinforcing effect resulted from the rigid aromatic structure of SLNP, whereas the enhanced elongation was attributed to the nanostructural feature of SLNP, which may promote boundary cracking. Additionally, the PBAT/SLNP composite films displayed excellent ultraviolet (UV) resistance with a UV shielding percentage near 100% for UVB and more than 75% for UVA, respectively. The addition of SLNP hindered water vapor, enhancing the moisture barrier properties. Overall, this study provides an effective strategy to eliminate the decrement in elongation performance for PBAT/lignin composites and suggest they are good candidates to be extensively utilized.
Psychological Needs in Sports, Spirituality Index of Well-Being, and Motivation in Sports
Authors: Eryücel Mehmet Emre , Ceyhun Serdar , Eryücel Sema , Şahan Hasan , Turna Bülent , Yıldırım Sibel , Erdoğan İbrahim Halil
Published: August 2024

The aim of this study is to examine the relationship between the psychological needs of athletes who attend gyms, the spirituality index of well-being, and motivation in sports, and to determine the mediating role of the spirituality index of well-being between psychological needs in sports and motivation in sports. Although sports spirituality is rapidly developing in the international literature, sports and spirituality have not been studied together in the national literature before. Therefore, this study holds the distinction of being one of the pioneering research efforts on the subject of spirituality in athletes in Türkiye. In this context, the data of 422 athletes, 176 women and 246 men, who have been attending gym facilities in Antalya for at least one year, were included in the research. Participants were administered a personal information form, Psychological Need States. It was found that the spirituality index of well-being is positively related to all satisfaction subscales and negatively related to all frustration subscales of psychological needs and that the life scheme is related to many subscales of sport motivation. Furthermore, it was also found that the spirituality index of well-being is a mediating variable between psychological needs in sports and motivation in sports. The data draw attention to the importance of sports spirituality. It is recommended to integrate spirituality into healthcare for athletes.
Straw-Saint, Martyr, Most-Barbarous Archtraitor: Anti-Hagiographies of Henry Garnet in Seventeenth-Century London
Authors: Barraco Caroline K.
Published: August 2024

In 1606 Henry Garnet, provincial of the English Jesuits and purported co-conspirator in the Gunpowder Plot against James I, was executed at St. Paul’s Cathedral in London. Following his death, accounts of miracles occurring at his execution began to spread throughout England, including an account of a relic bearing his miraculous image. While Catholic writers promoted these accounts as evidence of Garnet’s innocence, Protestant contemporaries argued that Garnet was an illegitimate martyr and that his commemoration was evidence of Catholic support for regicide. This article demonstrates how London Protestant writers and publishers utilized anti-hagiographical arguments to intervene in attempts to promote Garnet’s sainthood, counter claims about the veracity of his relic, and shape his legacy in the decades following his execution.
Few-Shot Hyperspectral Remote Sensing Image Classification via an Ensemble of Meta-Optimizers with Update Integration
Authors: Hao Tao , Zhang Zhihua , Crabbe M. James C.
Published: August 2024

Hyperspectral images (HSIs) with abundant spectra and high spatial resolution can satisfy the demand for the classification of adjacent homogeneous regions and accurately determine their specific land-cover classes. Due to the potentially large variance within the same class in hyperspectral images, classifying HSIs with limited training samples (i.e., few-shot HSI classification) has become especially difficult. To solve this issue without adding training costs, we propose an ensemble of meta-optimizers that were generated one by one through utilizing periodic annealing on the learning rate during the meta-training process. Such a combination of meta-learning and ensemble learning demonstrates a powerful ability to optimize the deep network on few-shot HSI training. In order to further improve the classification performance, we introduced a novel update integration process to determine the most appropriate update for network parameters during the model training process. Compared with popular human-designed optimizers (Adam, AdaGrad, RMSprop, SGD, etc.), our proposed model performed better in convergence speed, final loss value, overall accuracy, average accuracy, and Kappa coefficient on five HSI benchmarks in a few-shot learning setting.
Enhanced Dual-Channel Model-Based with Improved Unet++ Network for Landslide Monitoring and Region Extraction in Remote Sensing Images
Authors: Wang Junxin , Zhang Qintong , Xie Hao , Chen Yingying , Sun Rui
Published: August 2024

Landslide disasters pose significant threats to human life and property; therefore, accurate and effective detection and area extraction methods are crucial in environmental monitoring and disaster management. In our study, we address the critical tasks of landslide detection and area extraction in remote sensing images using advanced deep learning techniques. For landslide detection, we propose an enhanced dual-channel model that leverages EfficientNetB7 for feature extraction and incorporates spatial attention mechanisms (SAMs) to enhance important features. Additionally, we utilize a deep separable convolutional neural network with a Transformers module for feature extraction from digital elevation data (DEM). The extracted features are then fused using a variational autoencoder (VAE) to mine potential features and produce final classification results. Experimental results demonstrate impressive accuracy rates of 98.92% on the Bijie City landslide dataset and 94.70% on the Landslide4Sense dataset. For landslide area extraction, we enhance the traditional Unet++ architecture by incorporating Dilated Convolution to expand the receptive field and enable multi-scale feature extraction. We further integrate the Transformer and Convolutional Block Attention Module to enhance feature focus and introduce multi-task learning, including segmentation and edge detection tasks, to efficiently extract and refine landslide areas. Additionally, conditional random fields (CRFs) are applied for post-processing to refine segmentation boundaries. Comparative analysis demonstrates the superior performance of our proposed model over traditional segmentation models such as Unet, Fully Convolutional Network (FCN), and Segnet, as evidenced by improved metrics: IoU of 0.8631, Dice coefficient of 0.9265, overall accuracy (OA) of 91.53%, and Cohen’s kappa coefficient of 0.9185 on the Bijie City landslide dataset; and IoU of 0.8217, Dice coefficient of 0.9021, overall accuracy (OA) of 96.68%, and Cohen’s kappa coefficient of 0.8835 on the Landslide4Sense dataset. These findings highlight the effectiveness and robustness of our proposed methodologies in addressing critical challenges in landslide detection and area extraction tasks, with significant implications for enhancing disaster management and risk assessment efforts in remote sensing applications.
Temporal Dynamics of Fractional Vegetation Cover in the Yellow River Basin: A Comprehensive Analysis
Authors: Zhang Kaiwen , Zhang Qiang , Singh Vijay P.
Published: August 2024

The spatiotemporal evolution of vegetation and its influencing factors is crucial for understanding the relationship between vegetation and climate change, which helps guide the management of regional ecosystems effectively. Utilizing the Fractional Vegetation Cover (FVC) data and various meteorological elements from 1982 to 2021, this research employed methodologies, such as grey relational analysis, path analysis, and the time-lag effect, to examine the impact of climate change on FVC fluctuations. It introduced a comprehensive qualitative and quantitative analysis of the multi-factor climate–vegetation relationship, enhancing the understanding of the interaction between the climate and vegetation growth. The findings indicate that 77.41% of the wetland vegetation cover in the Yellow River Basin (YRB) has significantly decreased. Precipitation and evapotranspiration emerged as the primary factors affecting FVC, with soil moisture and temperature having a lesser impact. Given the crucial influence of climate factors’ time lag on vegetation dynamics, especially the notable cumulative lag effects observed in arid regions, such as precipitation accumulating over approximately 1.963 months (on average) and evapotranspiration lagging by about 1.727 months (on average), this study offers valuable theoretical insights on vegetation restoration efforts amidst the challenges posed by climate change.
ASIPNet: Orientation-Aware Learning Object Detection for Remote Sensing Images
Authors: Dong Ruchan , Yin Shunyao , Jiao Licheng , An Jungang , Wu Wenjing
Published: August 2024

Remote sensing imagery poses significant challenges for object detection due to the presence of objects at multiple scales, dense target overlap, and the complexity of extracting features from small targets. This paper introduces an innovative Adaptive Spatial Information Perception Network (ASIPNet), designed to address the problem of detecting objects in complex remote sensing image scenes and significantly enhance detection accuracy. We first designed the core component of ASIPNet, an Adaptable Spatial Information Perception Module (ASIPM), which strengthens the feature extraction of multi-scale objects in remote sensing images by dynamically perceiving contextual background information. Secondly, To further refine the model’s accuracy in predicting oriented bounding boxes, we integrated the Skew Intersection over Union based on Kalman Filtering (KFIoU), which serves as an advanced loss function, surpassing the capabilities of the baseline model’s traditional loss function. Finally, we designed detailed experiments on the DOTAv1 and DIOR-R datasets, which are annotated with rotation, to comprehensively evaluate the performance of ASIPNet. The experimental results demonstrate that ASIPNet achieved mAP50 scores of 76.0% and 80.1%, respectively. These results not only validate the model’s effectiveness but also indicate that this method is significantly ahead of other most current state-of-the-art approaches.
Sensorizing a Beehive: A Study on Potential Embedded Solutions for Internal Contactless Monitoring of Bees Activity
Authors: Micheli Massimiliano , Papa Giulia , Negri Ilaria , Lancini Matteo , Nuzzi Cristina , Pasinetti Simone
Published: August 2024

Winter is the season of main concern for beekeepers since the temperature, humidity, and potential infection from mites and other diseases may lead the colony to death. As a consequence, beekeepers perform invasive checks on the colonies, exposing them to further harm. This paper proposes a novel design of an instrumented beehive involving color cameras placed inside the beehive and at the bottom of it, paving the way for new frontiers in beehive monitoring. The overall acquisition system is described focusing on design choices towards an effective solution for internal, contactless, and stress-free beehive monitoring. To validate our approach, we conducted an experimental campaign in 2023 and analyzed the collected images with YOLOv8 to understand if the proposed solution can be useful for beekeepers and what kind of information can be derived from this kind of monitoring, including the presence of Varroa destructor mites inside the beehive. We experimentally found that the observation point inside the beehive is the most challenging due to the frequent movements of the bees and the difficulties related to obtaining in-focus images. However, from these images, it is possible to find Varroa destructor mites. On the other hand, the observation point at the bottom of the beehive showed great potential for understanding the overall activity of the colony.
Correction: Golovko et al. Ambient Dose and Dose Rate Measurement in SNOLAB Underground Laboratory at Sudbury, Ontario, Canada. Sensors 2023, 23, 1945
Authors: Golovko Victor V. , Kamaev Oleg , Sun Jiansheng , Jillings Chris J. , Gorel Pierre , Vázquez-Jáuregui Eric
Published: August 2024

We have found a discrepancy in the reported exposure time for passive sensors, specifically TLDs, in the original manuscript entitled “Ambient Dose and Dose Rate Measurement in SNOLAB Underground Laboratory at Sudbury, Ontario, Canada” [...]
Mechanomyography-Based Metric Scale for Spasticity: A Pilot Descriptive Observational Study
Authors: dos Santos Elgison L. , Scheeren Eduardo M. , Nogueira-Neto Guilherme N. , Krueger Eddy , Peixoto Nathalia , Nohama Percy
Published: August 2024

(1) Background: The Modified Ashworth Scale (MAS) is commonly used clinically to evaluate spasticity, but its qualitative nature introduces subjectivity. We propose a novel metric scale to quantitatively measure spasticity using mechanomyography (MMG) to mitigate these subjective effects. (2) Methods: The flexor and extensor muscles of knee and elbow joints were assessed with the Modified Ashworth Scale (MAS) during the acquisition of mechanomyography (MMG) data. The median absolute amplitude of the MMG signals was utilized as a key descriptor. An algorithm was developed to normalize the MMG signals to a universal gravitational (G) acceleration scale, aligning them with the limits and range of MAS. (3) Results: We evaluated 34 lower and upper limbs from 22 volunteers (average age 39.91 ± 13.77 years) of both genders. Polynomial regression provided the best fit (R2 = 0.987), with negligible differences (mean of 0.001 G) between the MAS and MMG. We established three numerical sets for the median, minimum, and maximum MMG(G) values corresponding to each MAS range, ensuring consistent alignment of the Modified Ashworth levels with our proposed scale. (4) Conclusions: Muscle spasticity can now be quantitatively and semi-automatically evaluated using our algorithm and instrumentation, enhancing the objectivity and reliability of spasticity assessments.
Wearable Multi-Sensor Positioning Prototype for Rowing Technique Evaluation
Authors: Rodriguez Mendoza Luis , O’Keefe Kyle
Published: August 2024

The goal of this study is to determine the feasibility of a wearable multi-sensor positioning prototype to be used as a training tool to evaluate rowing technique and to determine the positioning accuracy using multiple mathematical models and estimation methods. The wearable device consists of an inertial measurement unit (IMU), an ultra-wideband (UWB) transceiver, and a global navigation satellite system (GNSS) receiver. An experiment on a rowing shell was conducted to evaluate the performance of the system on a rower’s wrist, against a centimeter-level GNSS reference trajectory. This experiment analyzed the rowing motion in multiple navigation frames and with various positioning methods. The results show that the wearable device prototype is a viable option for rowing technique analysis; the system was able to provide the position, velocity, and attitude of a rower’s wrist, with a positioning accuracy ranging between ±0.185 m and ±1.656 m depending on the estimation method.
Deep Reinforcement Learning-Based Adaptive Scheduling for Wireless Time-Sensitive Networking
Authors: Kim Hanjin , Kim Young-Jin , Kim Won-Tae
Published: August 2024

Time-sensitive networking (TSN) technologies have garnered attention for supporting time-sensitive communication services, with recent interest extending to the wireless domain. However, adapting TSN to wireless areas faces challenges due to the competitive channel utilization in IEEE 802.11, necessitating exclusive channels for low-latency services. Additionally, traditional TSN scheduling algorithms may cause significant transmission delays due to dynamic wireless characteristics, which must be addressed. This paper proposes a wireless TSN model of IEEE 802.11 networks for the exclusive channel access and a novel time-sensitive traffic scheduler, named the wireless intelligent scheduler (WISE), based on deep reinforcement learning. We designed a deep reinforcement learning (DRL) framework to learn the repetitive transmission patterns of time-sensitive traffic and address potential latency issues from changing wireless conditions. Within this framework, we identified the most suitable DRL model, presenting the WISE algorithm with the best performance. Experimental results indicate that the proposed mechanisms meet up to 99.9% under the various wireless communication scenarios. In addition, they show that the processing delay is successfully limited within the specific time requirements and the scalability of TSN streams is guaranteed by the proposed mechanisms.
Presenting the COGNIFOG Framework: Architecture, Building Blocks and Road toward Cognitive Connectivity
Authors: Adame Toni , Amri Emna , Antonopoulos Grigoris , Azaiez Selma , Berne Alexandre , Camargo Juan Sebastian , Kakoulidis Harry , Kleisarchaki Sofia , Llamedo Alberto , Prasinos Marios , Psara Kyriaki , Shumaiev Klym
Published: August 2024

In the era of ubiquitous computing, the challenges imposed by the increasing demand for real-time data processing, security, and energy efficiency call for innovative solutions. The emergence of fog computing has provided a promising paradigm to address these challenges by bringing computational resources closer to data sources. Despite its advantages, the fog computing characteristics pose challenges in heterogeneous environments in terms of resource allocation and management, provisioning, security, and connectivity, among others. This paper introduces COGNIFOG, a novel cognitive fog framework currently under development, which was designed to leverage intelligent, decentralized decision-making processes, machine learning algorithms, and distributed computing principles to enable the autonomous operation, adaptability, and scalability across the IoT–edge–cloud continuum. By integrating cognitive capabilities, COGNIFOG is expected to increase the efficiency and reliability of next-generation computing environments, potentially providing a seamless bridge between the physical and digital worlds. Preliminary experimental results with a limited set of connectivity-related COGNIFOG building blocks show promising improvements in network resource utilization in a real-world-based IoT scenario. Overall, this work paves the way for further developments on the framework, which are aimed at making it more intelligent, resilient, and aligned with the ever-evolving demands of next-generation computing environments.