bluuebunny/crossref_metadata_2025 huggingface dataset:
Development and Optimization of Andrographis paniculata Extract-Loaded Self-Microemulsifying Drug Delivery System Using Experimental Design Model
Authors: Pornpitchanarong Chaiyakarn , Akkaramongkolporn Prasert , Nattapulwat Nattawat , Opanasopit Praneet , Patrojanasophon Prasopchai
Published: January 2024

The objectives of this study were to develop an optimized formulation for an Andrographis paniculata extract (AGPE)-loaded self-microemulsifying drug delivery system (SMEDDS) using an experimental design and evaluate the characteristics of the developed SMEDDS. The solubility of andrographolide (AGP) in various solvents was investigated. The pseudo-ternary phase was constructed to provide an optimal range for each component to form microemulsions (MEs). The formulation was optimized using an I-optimal design mixture type, where the physical stability, droplet size, polydispersity index, and zeta potential were examined. Soft capsules of the optimized AGPE-loaded SMEDDS were manufactured. The dissolution and ex vivo membrane permeation were studied. Oleic acid, Tween® 80, and PEG 400 were the best solubilizers for AGP. The promising surfactant to co-surfactant ratio to generate ME was 3:1. The optimized SMEDDS contained 68.998% Tween® 80, with 13.257% oleic acid and 17.745% PEG 400. The assayed content of AGP, uniformity of dosage unit, and stability complied with the expected specifications. The dissolution and membrane permeability of AGPE-loaded SMEDDS was significantly improved from the A. paniculata extract (p < 0.05). All in all, the developed optimized AGPE-loaded SMEDDS was proven to contain optimal composition and AGP content where a stable ME could spontaneously be formed with enhanced delivery efficacy.
Digital Solutions Available to Be Used by Informal Caregivers, Contributing to Medication Adherence: A Scoping Review
Authors: Espírito-Santo Margarida , Santos Sancha , Estêvão Maria Dulce
Published: January 2024

Medication adherence is essential for managing chronic diseases and achieving optimal health outcomes. However, this process is often challenging, particularly for patients with complex care needs. Informal caregivers play a pivotal role in supporting medication management, but they may face resource limitations and a lack of necessary support. Digital health tools offer a promising avenue to enhance medication adherence by providing reminders, education, and remote monitoring capabilities. This scoping review aimed to identify and evaluate digital solutions available to informal caregivers for improving medication adherence. A systematic search of PubMed and Web of Science was conducted using relevant keywords. Four studies were included in the review, examining a variety of digital tools including mobile apps, SMS messaging, and wearable devices. These tools demonstrated efficacy in improving medication adherence, managing disease symptoms, and enhancing quality of life for patients and caregivers. Digital health interventions hold the potential to revolutionize medication adherence among chronic disease patients. By empowering informal caregivers, these tools can bridge the gaps in medication management and contribute to better health outcomes. Further research is warranted to optimize the design, implementation, and evaluation of digital interventions for medication adherence.
Impact of the COVID-19 Pandemic on the Use of Antidepressants by Young Adults in the ASL TO4 Regione Piemonte (Italy)
Authors: Armando Lucrezia Greta , Baroetto Parisi Raffaella , Rolando Cristina , Esiliato Mariangela , Vinciguerra Valeria , Bertiond Cecilia , Diarassouba Abdoulaye , Cena Clara , Miglio Gianluca
Published: January 2024

The association between younger age and poorer mental health during the COVID-19 pandemic has been documented. Whether these changes were associated with a change in antidepressant (AD) use is not well understood. This study aimed to estimate the impact of the COVID-19 pandemic on AD use by young adults in the ASL TO4 Regione Piemonte (Italy). The impact of the pandemic on the weekly prevalence of AD users was assessed using interrupted time-series analysis with autoregressive integrated moving average models. A total of 1071 subjects (18–22 years with ≥1 AD dispensation) were included in the study. The observed prevalence was lower than the predicted value for several weeks after the introduction of the lockdown. However, it was consistently higher than the predicted values from week 134. The maximum difference between observed and predicted values (25 subjects per 10,000 young adults) was found at week 170. Changes in AD use were observed in both genders and were more pronounced for selective serotonin reuptake inhibitors. In conclusion, the impact of the COVID-19 pandemic on the mental health of young adults is likely to be significant in the coming years, which may place a future burden on pharmaceutical public health and community health.
The Advances and Applications of Characterization Technique for Exosomes: From Dynamic Light Scattering to Super-Resolution Imaging Technology
Authors: Wu Shijia , Zhao Yalan , Zhang Zitong , Zuo Chao , Wu Hongjun , Liu Yongtao
Published: January 2024

Exosomes distributed by extracellular vesicles carry various information highly consistent with cells, becoming a new type of biomarker for tumor screening. However, although conventional characterization technologies can quantify size and morphology for exosomes, they are limited in related fields such as function tracing, protein quantification at unit point, and microstructural information. In this paper, firstly, different exosome characterization methods are systematically reviewed, such as dynamic light scattering, nanoparticle tracking analysis, flow cytometry, electron microscope, and emerging super-resolution imaging technologies. Then, advances in applications are described one by one. Last but not least, we compare the features of different technologies for exosomes and propose that super-resolution imaging technology can not only take into account the advantages of conventional characterization techniques but also provide accurate, real-time, and super-resolution quantitative analysis for exosomes. It provides a fine guide for exosome-related biomedical research, as well as application in liquid biopsy and analysis techniques.
Anatomical Mechanisms of Leaf Blade Morphogenesis in Sasaella kogasensis ‘Aureostriatus’
Authors: Zhao Wanqi , Lv Zhuo , Zhang Hanjiao , Yue Jiahui , Zhang Xu , Li Long , Huang Feiyi , Lin Shuyan
Published: January 2024

There are limited studies on the cytology of bamboo leaf development from primordium to maturity. This study delves into the leaf morphological characteristics and growth patterns of Sasaella kogasensis ‘Aureostriatus’ and provides a three-dimensional anatomical analysis of cell division, expansion, and degradation. Leaves on the same branch develop bottom-up, while individual leaves develop the other way around. Like bamboo shoots and culms, the leaves follow a “slow–fast–slow” growth pattern, with longitudinal growth being predominant during their development. The growth zones of individual leaves included division, elongation, and maturation zones based on the distribution of growth space. By measuring 13,303 epidermal long cells and 3293 mesophyll cells in longitudinal sections of rapidly elongating leaves, we observed that in the rapid elongation phase (S4–S5), the division zone was located in the 1–2 cm segment at the bottom of the leaf blade and maintained a constant size, continuously providing new cells for leaf elongation, whereas in the late rapid elongation phase (S6), when the length of the leaf blade was approaching that of a mature leaf, its cells at the bottom of the blade no longer divided and were replaced by the ability to elongate. Furthermore, to gain an insight into the dynamic changes in the growth of the S. kogasensis ‘Aureostriatus’ leaves in the lateral and periclinal directions, the width and thickness of 1459 epidermal and 2719 mesophyll cells were counted in the mid-cross section of leaves at different developmental stages. The results showed that during the early stages of development (S1–S3), young leaves maintained vigorous division in the lateral direction, while periplasmic division gradually expanded from the bottom to the top of the leaf blade and the number of cell layers stabilized at S4. The meristematic tissues on both sides of the leaf were still able to divide at S4 but the frequency of the division gradually decreased, while cell division and expansion occurred simultaneously between the veins. At S6, the cells at the leaf margins and between the veins were completely differentiated and the width of the leaf blade no longer expanded. These findings revealed changes in cell growth anisotropically during the leaf development of S. kogasensis ‘Aureostriatus’ and demonstrated that leaf elongation was closely related to the longitudinal expansion of epidermal cells and proliferative growth of mesophyll cells, whereas the cell division of meristematic tissues and expansion of post-divisional cells contributed to the increases in blade width and thickness. The presented framework will facilitate a further exploration of the molecular regulatory mechanisms of leaf development in S. kogasensis ‘Aureostriatus’ and provide relevant information for developmental and taxonomic studies of bamboo plants.
Application of Lavandula angustifolia Mill. Extracts for the Phytosynthesis of Silver Nanoparticles: Characterization and Biomedical Potential
Authors: Șuică-Bunghez Ioana Raluca , Senin Raluca Mădălina , Sorescu Ana Alexandra , Ganciarov Mihaela , Răut Iuliana , Firincă Cristina , Constantin Mariana , Gifu Ioana Cătălina , Stoica Rusăndica , Fierăscu Irina , Fierăscu Radu Claudiu
Published: January 2024

Nanotechnology can offer a series of new “green” and eco-friendly methods for developing different types of nanoparticles, among which the development of nanomaterials using plant extracts (phytosynthesis) represents one of the most promising areas of research. This present study details the use of lavender flowers (Lavandula angustifolia Mill., well-known for their use in homeopathic applications) for the biosynthesis of silver nanoparticles with enhanced antioxidant and antibacterial properties. Several qualitative and quantitative assays were carried out in order to offer an image of the extracts’ composition (the recorded total phenolics content varied between 21.0 to 40.9 mg GAE (gallic acid equivalents)/g dry weight (d.w.), while the total flavonoids content ranged between 3.57 and 16.8 mg CE (catechin equivalents)/g d.w.), alongside modern analytical methods (such as gas chromatography-mass spectrometry—GC-MS, quantifying 12 phytoconstituents present in the extracts). The formation of silver nanoparticles (AgNPs) using lavender extract was studied by UV-Vis spectroscopy, Fourier-transform infrared spectrometry (FTIR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and dynamic light scattering (DLS)/zeta potential, with the selected nanoparticles having crystallite sizes of approx. 14.55 nm (AgNP-L2) and 4.61 nm, respectively (for AgNP-L4), and hydrodynamic diameters of 392.4 nm (for AgNP-L2) and 391.6 nm (for AgNP-L4), determined by DLS. A zeta potential of around −6.4 mV was displayed for both samples while presenting as large aggregates, in which nanoparticle clusters with dimensions of around 130–200 nm can be observed. The biomedical applications of the extracts and the corresponding phytosynthesized nanoparticles were evaluated using antioxidant and antimicrobial assays. The obtained results confirmed the phytosynthesis of the silver nanoparticles using Lavandula angustifolia Mill. extracts, as well as their antioxidant and antimicrobial potential.
RETRACTED: Alminderej et al. Antimicrobial and Wound Healing Potential of a New Chemotype from Piper cubeba L. Essential Oil and In Silico Study on S. aureus tyrosyl-tRNA Synthetase Protein. Plants 2021, 10, 205
Authors: Alminderej Fahad , Bakari Sana , Almundarij Tariq I. , Snoussi Mejdi , Aouadi Kaïss , Kadri Adel
Published: January 2024

The journal retracts the article, ‘Antimicrobial and Wound Healing Potential of a New Chemotype from Piper cubeba L. Essential Oil and In Silico Study on S. aureus tyrosyl-tRNA Synthetase Protein’ [...]
Genetic Diversity within a Collection of Italian Maize Inbred Lines: A Resource for Maize Genomics and Breeding
Authors: Mastrangelo Anna Maria , Hartings Hans , Lanzanova Chiara , Balconi Carlotta , Locatelli Sabrina , Cassol Helga , Valoti Paolo , Petruzzino Giuseppe , Pecchioni Nicola
Published: January 2024

Genetic diversity is fundamental for studying the complex architecture of the traits of agronomic importance, controlled by major and minor loci. Moreover, well-characterized germplasm collections are essential tools for dissecting and analyzing genetic and phenotypic diversity in crops. A panel of 360 entries, a subset of a larger collection maintained within the GenBank at CREA Bergamo, which includes the inbreds derived from traditional Italian maize open-pollinated (OP) varieties and advanced breeding ones (Elite Inbreds), was analyzed to identify SNP markers using the tGBS® genotyping-by-sequencing technology. A total of 797,368 SNPs were found during the initial analysis. Imputation and filtering processes were carried out based on the percentage of missing data, redundant markers, and rarest allele frequencies, resulting in a final dataset of 15,872 SNP markers for which a physical map position was identified. Using this dataset, the inbred panel was characterized for linkage disequilibrium (LD), genetic diversity, population structure, and genetic relationships. LD decay at a genome-wide level indicates that the collection is a suitable resource for association mapping. Population structure analyses, which were carried out with different clustering methods, showed stable grouping statistics for four groups, broadly corresponding to ‘Insubria’, ‘Microsperma’, and ‘Scagliolino’ genotypes, with a fourth group composed prevalently of elite accessions derived from Italian and US breeding programs. Based on these results, the CREA Italian maize collection, genetically characterized in this study, can be considered an important tool for the mapping and characterization of useful traits and associated loci/alleles, to be used in maize breeding programs.
Phytochemical Elucidation and Effect of Maesa indica (Roxb.) Sweet on Alleviation of Potassium Dichromate-Induced Pulmonary Damage in Rats
Authors: Abdelgawad Fatma Alzahra M. , El-Hawary Seham S. , El-Kader Essam M. Abd , Alshehri Saad Ali , Rabeh Mohamed Abdelaaty , El-Mosallamy Aliaa E. M. K. , Salama Abeer , El Gedaily Rania A.
Published: January 2024

Maesa indica (Roxb.) Sweet is one of the well-known traditionally-used Indian plants. This plant is rich in secondary metabolites like phenolic acids, flavonoids, alkaloids, glycosides, saponins, and carbohydrates. It contains numerous therapeutically active compounds like palmitic acid, chrysophanol, glyceryl palmitate, stigmasterol, β-sitosterol, dodecane, maesaquinone, quercetin 3-rhaminoside, rutin, chlorogenic acid, catechin, quercetin, nitrendipine, 2,3-dihydroxypropyl octadeca-9,12-dienoate, kiritiquinon, and β-thujone. The Maesa indica plant has been reported to have many biological properties including antidiabetic, anticancer, anti-angiogenic, anti-leishmanial, antioxidant, radical scavenging, antibacterial, antiviral, and anti-coronavirus effects. One purpose of the current study was to investigate the leaves’ metabolome via Triple-Time-of-Flight-Liquid-Chromatography-Mass Spectrometry (T-TOF LC/MS/MS) to identify the chemical constituents of the Maesa indica ethanolic extract (ME). Another purpose of this study was to explore the protective effect of ME against potassium dichromate (PD)-induced pulmonary damage in rats. Rats were assigned randomly into four experimental groups. Two different doses of the plant extract, (25 and 50 mg/kg), were administered orally for seven consecutive days before PD instillation injection. Results of our study revealed that ME enhanced cellular redox status as it decreased lipid peroxidation marker, MDA and elevated reduced glutathione (GSH). In addition, ME upregulated the cytoprotective signaling pathway PI3K/AKT. Moreover, ME administration ameliorated histopathological anomalies induced by PD. Several identified metabolites, such as chlorogenic acid, quercetin, apigenin, kaempferol, luteolin, and rutin, had previously indicated lung-protective effects, possibly through an antioxidant effect and inhibition of oxidative stress and inflammatory mediators. In conclusion, our results indicated that ME possesses lung-protective effects, which may be the result of its antioxidant and anti-inflammatory properties.
Identification of the Maize PP2C Gene Family and Functional Studies on the Role of ZmPP2C15 in Drought Tolerance
Authors: Pang Yunyun , Cao Liru , Ye Feiyu , Ma Chenchen , Liang Xiaohan , Song Yinghui , Lu Xiaomin
Published: January 2024

The protein phosphatase PP2C plays an important role in plant responses to stress. Therefore, the identification of maize PP2C genes that respond to drought stress is particularly important for the improvement and creation of new drought-resistant assortments of maize. In this study, we identified 102 ZmPP2C genes in maize at the genome-wide level. We analyzed the physicochemical properties of 102 ZmPP2Cs and constructed a phylogenetic tree with Arabidopsis. By analyzing the gene structure, conserved protein motifs, and synteny, the ZmPP2Cs were found to be strongly conserved during evolution. Sixteen core genes involved in drought stress and rewatering were screened using gene co-expression network mapping and expression profiling. The qRT-PCR results showed 16 genes were induced by abscisic acid (ABA), drought, and NaCl treatments. Notably, ZmPP2C15 exhibited a substantial expression difference. Through genetic transformation, we overexpressed ZmPP2C15 and generated the CRISPR/Cas9 knockout maize mutant zmpp2c15. Overexpressing ZmPP2C15 in Arabidopsis under drought stress enhanced growth and survival compared with WT plants. The leaves exhibited heightened superoxide dismutase (SOD), peroxidase (POD), ascorbate peroxidase (APX), and catalase (CAT) activities, elevated proline (Pro) content, and reduced malondialdehyde (MDA) content. Conversely, zmpp2c15 mutant plants displayed severe leaf dryness, curling, and wilting under drought stress. Their leaf activities of SOD, POD, APX, and CAT were lower than those in B104, while MDA was higher. This suggests that ZmPP2C15 positively regulates drought tolerance in maize by affecting the antioxidant enzyme activity and osmoregulatory substance content. Subcellular localization revealed that ZmPP2C15 was localized in the nucleus and cytoplasm. Yeast two-hybrid (Y2H) and bimolecular fluorescence complementation (BiFC) experiments demonstrated ZmPP2C15’s interaction with ZmWIN1, ZmADT2, ZmsodC, Zmcab, and ZmLHC2. These findings establish a foundation for understanding maize PP2C gene functions, offering genetic resources and insights for molecular design breeding for drought tolerance.
Heat Treatment of Seeds to Control Invasive Common Ragweed (Ambrosia artemisiifolia), Narrow-Leaved Ragwort (Senecio inaequidens) and Giant Hogweed (Heracleum mantegazzianum)
Authors: Hall Rea Maria , Urban Bernhard , Durec Nora , Renner-Martin Katharina , Kaul Hans-Peter , Wagentristl Helmut , Karrer Gerhard
Published: January 2024

The intended or unintentional transport of soil material contaminated with weed seeds is one of the most important drivers in the spreading dynamics of invasive alien plants (IAPs). This phenomenon can be observed at any kind of construction site. Typical transfer of soil contaminated with IAP seeds can be observed along with road construction (soil translocation) or road maintenance services (deposit of mown plant biomass). Thus, an effective inactivation of these seeds by heating can avoid the spread of IAPs substantially. In the present study, the effects of various thermal control techniques (dry air heating and wet heating with hot steam, hot water, and hot foam) on seed survival of the widespread European IAPs common ragweed (Ambrosia artemisiifolia), narrow-leaved ragwort (Senecio inaequidens), and giant hogweed (Heracleum mantegazzianum) are discussed. Dry and wet seeds which were either uncovered or covered with soil were tested for survival at different treatment temperatures and different exposure times. Results revealed that particularly dry seeds of all three species could withstand temperatures of 100 °C for at least 6 h in climate chambers. Dry seeds of common ragweed and narrow-leaved ragwort survived exposure times of up to 48 h. Wet seeds were significantly more susceptible to heat treatments. Giant hogweed seeds were completely killed after 12 h at 70 °C. The exposure of IAP seeds to hot water was generally more effective than the treatment with hot steam. The treatment with hot foam was only effective when seeds were lying unprotected on the soil surface. Dry seeds of all the three species survived hot foam application in the field when they were covered by vegetation and leaf litter or soil. Due to the robustness of the seeds, a preventive management of IAPs by an efficient control before seeds formation is substantial to avoid their further dispersal.
Spatial Distribution Analyses of Axially Long Plasmas under a Multi-Cusp Magnetic Field Using a Kinetic Particle Simulation Code KEIO-MARC
Authors: Nishimura Ryota , Seino Tomohiro , Yoshimura Keigo , Takahashi Hiroyuki , Matsuyama Akinobu , Hoshino Kazuo , Oishi Tetsutarou , Tobita Kenji
Published: January 2024

To realize the development of a long plasma source with a uniform electron density distribution in the axial direction, the spatial distribution of plasma under a multi-cusp magnetic field was analyzed using a KEIO-MARC code. Considering a cylindrical plasma source with an axial length of 3000 mm and a cross-sectional diameter of 100 mm, in which the filament electrode was the electron source, the electron density distribution was calculated using the residual magnetic flux density, Bres, and the number of permanent magnets installed at different locations surrounding the device, Nmag, as design parameters. The results show that both Bres and Nmag improved the uniformity of the electron density distribution in the axial direction. The maximum axial electron density decreased with increasing Nmag and increased with increasing Bres. These trends can be explained by considering the nature of the multi-cusp field, where particles are mainly confined to the field-free region (FFR) near the center of the plasma column, and the loss of particles due to radial particle transport. The use of multiple filaments at intervals shorter than the plasma decay length dramatically improved axial uniformity. To further improve axial uniformity, the filament length and FFR must be properly set so that electrons are emitted inside the FFR.
Three-Dimensional-Printed Sodium Alginate and k-Carrageenan-Based Scaffolds with Potential Biomedical Applications
Authors: Stavarache Cristina , Gȃrea Sorina Alexandra , Serafim Andrada , Olăreț Elena , Vlăsceanu George Mihail , Marin Maria Minodora , Iovu Horia
Published: January 2024

This work reports the development of a marine-derived polysaccharide formulation based on k-Carrageenan and sodium alginate in order to produce a novel scaffold for engineering applications. The viscoelastic properties of the bicomponent inks were assessed via rheological tests prior to 3D printing. Compositions with different weight ratios between the two polymers, without any crosslinker, were subjected to 3D printing for the first time, to the best of our knowledge, and the fabrication parameters were optimized to ensure a controlled architecture. Crosslinking of the 3D-printed scaffolds was performed in the presence of a chloride mixture (CaCl2:KCl = 1:1; v/v) of different concentrations. The efficiency of the crosslinking protocol was evaluated in terms of swelling behavior and mechanical properties. The swelling behavior indicated a decrease in the swelling degree when the concentration of the crosslinking agent was increased. These results are consistent with the nanoindentation measurements and the results of the macro-scale tests. Moreover, morphology analysis was also used to determine the pore size of the samples upon freeze-drying and the uniformity and micro-architectural characteristics of the scaffolds. Overall, the registered results indicated that the bicomponent ink, Alg/kCG = 1:1 may exhibit potential for tissue-engineering applications.
Catalyst-Free Cardanol-Based Epoxy Vitrimers for Self-Healing, Shape Memory, and Recyclable Materials
Authors: Zhu Yu , Li Wenbin , He Zhouyu , Zhang Kun , Nie Xiaoan , Fu Renli , Chen Jie
Published: January 2024

Bio-based vitrimers present a promising solution to the issues associated with non-renewable and non-recyclable attributes of traditional thermosetting resins, showcasing extensive potential for diverse applications. However, their broader adoption has been hindered by the requirement for catalyst inclusion during the synthesis process. In this study, a cardanol-based curing agent with poly-hydroxy and tertiary amine structures was prepared by a clean synthetic method under the theory of click chemistry. The reaction of a cardanol-based curing agent with diglycidyl ether of bisphenol A formed catalyst-free, self-healing, and recyclable bio-based vitrimers. The poly-hydroxy and tertiary amine structures in the vitrimers promoted the curing of epoxy-carboxylic acid in the cross-linked network and served as internal catalysts of dynamic transesterification. In the absence of catalysts, the vitrimers network can achieve topological network rearrangement through dynamic transesterification, exhibiting excellent reprocessing performance. Moreover, the vitrimers exhibited faster stress relaxation (1500 s at 180 °C), lower activation energy (92.29 kJ·mol−1) and the tensile strength of the recycled material reached almost 100% of the original sample. This work offers a new method for preparing cardanol-based epoxy vitrimers that be used to make coatings, hydrogels, biomaterials, adhesives, and commodity plastics in the future.
Giant Response and Selectivity of Hansen Solubility Parameters-Based Graphene-SBS Co-Polymer Matrix Composite Room Temperature Sensor to Organic Vapours
Authors: Slobodian Rostislav , Olejnik Robert , Dmonte David John , Sevcik Jakub , Matyas Jiri , Jurca Marek , Pricilla R. Blessy , Hanulikova Barbora , Slobodian Petr , Kuritka Ivo
Published: January 2024

A styrene-butadiene-styrene co-polymer matrix nanocomposite filled with graphene nanoplatelets was studied to prepare chemiresistive volatile organic compounds (VOCs) room temperature sensors with considerable response and selectivity. Nanofiller concentration was estimated from the electrical conductivity percolation behaviour of the nanocomposite. Fabricated sensors provided selective relative responses to representative VOCs differing by orders of magnitude. Maximum observed average relative responses upon exposure to saturated vapours of the tested VOCs were ca. 23% for ethanol, 1600% for acetone, and the giant values were 9 × 106% for n-heptane and 10 × 106% for toluene. The insensitivity of the sensor to the direct saturated water vapour exposure was verified. Although high humidity decreases the sensor’s response, it paradoxically enhances the resolution between hydrocarbons and polar organics. The non-trivial sensing mechanism is explained using the Hansen solubility parameters (HSP), enabling a rational design of new sensors; thus, the HSP-based class of sensors is outlined.
Biocomposites of Cellulose Isolated from Coffee Processing By-Products and Incorporation in Poly(Butylene Adipate-Co-Terephthalate) (PBAT) Matrix: An Overview
Authors: Gondim Fernanda Fabbri , Rodrigues João Gabriel Passos , Aguiar Vinicius Oliveira , de Fátima Vieira Marques Maria , Monteiro Sergio Neves
Published: January 2024

With its extensive production and consumption, the coffee industry generates significant amounts of lignocellulosic waste. This waste, primarily comprising coffee biomasses, is a potential source of cellulose. This cellulose can be extracted and utilized as a reinforcing agent in various biocomposites with polymer matrices, thereby creating high-value products. One such biodegradable polymer, Poly(butylene adipate-co-terephthalate) (PBAT), is notable for its properties that are comparable with low-density polyethylene, making it an excellent candidate for packaging applications. However, the wider adoption of PBAT is hindered by its relatively high cost and lower thermomechanical properties compared with conventional, non-biodegradable polymers. By reinforcing PBAT-based biocomposites with cellulose, it is possible to enhance their thermomechanical strength, as well as improve their water vapor and oxygen barrier capabilities, surpassing those of pure PBAT. Consequently, this study aims to provide a comprehensive review of the latest processing techniques for deriving cellulose from the coffee industry’s lignocellulosic by-products and other coffee-related agro-industrial wastes. It also focuses on the preparation and characterization of cellulose-reinforced PBAT biocomposites.
Characterization of Lignocellulose Nanofibril from Desilicated Rice Hull with Carboxymethylation Pretreatment
Authors: Zahra Audrey , Lim Seo-Kyoung , Shin Soo-Jeong
Published: January 2024

Rice hulls have a high-value potential, and the lignocellulose components are underutilized compared to other biomass resources. Pretreatments such as carboxymethylation of the degree of substitutions (DS) are used to prepare lignocellulose nanofibril (LCNF) from desilicated rice hull (DSRH). High-pressure homogenization (HPH) and grinding are used to process nano fibrillation. The composition of LCNF DS of desilicated rice hull was identified using 1H NMR for polysaccharide composition and DS determination, acetone and hot water extraction to evaluate extractives, and Klason lignin for lignin content. LCNF was prepared using various DS from 0.2 until DS 0.4. The results showed that LCNF DS has a more than −30 mV zeta potential, suitable for stable nanoemulsion formulations. The particle size of LCNF DS decreases with an increasing carboxyl content in the hydrogel and an increasing number of passes through grinding and high-pressure homogenization, of which LCNF DS 0.4 had the smallest width and length. Mechanical processes further reduced the size.
Enhancing Hyperspectral Anomaly Detection with a Novel Differential Network Approach for Precision and Robust Background Suppression
Authors: Zhang Jiajia , Xiang Pei , Teng Xiang , Zhao Dong , Li Huan , Song Jiangluqi , Zhou Huixin , Tan Wei
Published: January 2024

The existing deep-learning-based hyperspectral anomaly detection methods detect anomalies by reconstructing a clean background. However, these methods model the background of the hyperspectral image (HSI) through global features, neglecting local features. In complex background scenarios, these methods struggle to obtain accurate background priors for training constraints, thereby limiting the anomaly detection performance. To enhance the capability of the network in extracting local features and improve anomaly detection performance, a hyperspectral anomaly detection method based on differential network is proposed. First, we posit that anomalous pixels are challenging to be reconstructed through the features of surrounding pixels. A differential convolution method is introduced to extract local punctured neighborhood features in the HSI. The differential convolution contains two types of kernels with different receptive fields. These kernels are adopted to obtain the outer window features and inner window features. Second, to improve the feature extraction capability of the network, a local detail attention and a local Transformer attention are proposed. These attention modules enhance the inner window features. Third, the obtained inner window features are subtracted from the outer window features to derive differential features, which encapsulate local punctured neighborhood characteristics. The obtained differential features are employed to reconstruct the background of the HSI. Finally, the anomaly detection results are extracted from the difference between the input HSI and the reconstructed background of the HSI. In the proposed method, for each receptive field kernel, the optimization objective is to reconstruct the input HSI rather than the background HSI. This way circumvents problems where the background constraint biases might affect detection performance. The proposed method offers researchers a new and effective approach for applying deep learning in a local area to the field of hyperspectral anomaly detection. The experiments are conducted with multiple metrics on five real-world datasets. The proposed method outperforms eight state-of-the-art methods in both subjective and objective evaluations.
Uncertainty Quantification of Soil Organic Carbon Estimation from Remote Sensing Data with Conformal Prediction
Authors: Kakhani Nafiseh , Alamdar Setareh , Kebonye Ndiye Michael , Amani Meisam , Scholten Thomas
Published: January 2024

Soil organic carbon (SOC) contents and stocks provide valuable insights into soil health, nutrient cycling, greenhouse gas emissions, and overall ecosystem productivity. Given this, remote sensing data coupled with advanced machine learning (ML) techniques have eased SOC level estimation while revealing its patterns across different ecosystems. However, despite these advances, the intricacies of training reliable and yet certain SOC models for specific end-users remain a great challenge. To address this, we need robust SOC uncertainty quantification techniques. Here, we introduce a methodology that leverages conformal prediction to address the uncertainty in estimating SOC contents while using remote sensing data. Conformal prediction generates statistically reliable uncertainty intervals for predictions made by ML models. Our analysis, performed on the LUCAS dataset in Europe and incorporating a suite of relevant environmental covariates, underscores the efficacy of integrating conformal prediction with another ML model, specifically random forest. In addition, we conducted a comparative assessment of our results against prevalent uncertainty quantification methods for SOC prediction, employing different evaluation metrics to assess both model uncertainty and accuracy. Our methodology showcases the utility of the generated prediction sets as informative indicators of uncertainty. These sets accurately identify samples that pose prediction challenges, providing valuable insights for end-users seeking reliable predictions in the complexities of SOC estimation.
Radar Echo Recognition of Gust Front Based on Deep Learning
Authors: Tian Hanyuan , Hu Zhiqun , Wang Fuzeng , Xie Peilong , Xu Fen , Leng Liang
Published: January 2024

Gust fronts (GFs) belong to the boundary layer convergence system. A strong GF can cause serious wind disasters, so its automatic monitoring and identification are very helpful but difficult in daily meteorological operations. By collecting convective weather processes in Hubei, Jiangsu, and other regions of China, 1422 GFs from 106 S-band new-generation weather radar (CINRAD/SA) volume scan data are labeled as positive samples by means of human–computer interaction, and the same number of negative samples are randomly tagged from no GF radar data. A deep learning dataset including 2844 labels with a positive and negative sample ratio of 1:1 is constructed, and 80%, 10%, and 10% of the dataset are separated as training, validation, and test sets, respectively. Then, the training dataset is expanded to 273,120 samples by data augmentation technology. Since the height of a GF is generally less than 1.5 km, three deep-learning-based models are trained for GF automatic recognition according to the distance from the radars. Three models (M1, M2, M3) are trained with the data at a 0.5° elevation angle from 65 to 180 km away from the radars, at 0.5° and 1.5° angles from 40 to 65 km, and at 0.5°, 1.5°, and 2.4° angles within 40 km, respectively. The precision, confusion matrix, and its derived indicators including receiver operating characteristic curve (ROC) and the area under ROC (AUC) are used to evaluate the three models by the test set. The results show that the identification precisions of the models are 97.66% (M1), 90% (M2), and 90.43% (M3), respectively. All the hit rates are over 89%, the false positive rates are less than 11%, and the critical success indexes (CSIs) surpass 82%. In addition, all the optimal critical points on the ROC curves are close to (0, 1), and the AUC values are above 0.93. These results suggest that the three models can effectively achieve the automatic discrimination of GFs. Finally, the models are demonstrated by three GF events detected with Qingpu, Nantong, and Cangzhou radars.
Machine-to-Machine Visual Dialoguing with ChatGPT for Enriched Textual Image Description
Authors: Ricci Riccardo , Bazi Yakoub , Melgani Farid
Published: January 2024

Image captioning is a technique that enables the automatic extraction of natural language descriptions about the contents of an image. On the one hand, information in the form of natural language can enhance accessibility by reducing the expertise required to process, analyze, and exploit remote sensing images, while on the other, it provides a direct and general form of communication. However, image captioning is usually restricted to a single sentence, which barely describes the rich semantic information that typically characterizes remote sensing (RS) images. In this paper, we aim to move one step forward by proposing a captioning system that, mimicking human behavior, adopts dialogue as a tool to explore and dig for information, leading to more detailed and comprehensive descriptions of RS scenes. The system relies on a questions–answers scheme fed by a query image and summarizes the dialogue content with ChatGPT. Experiments carried out on two benchmark remote sensing datasets confirm the potential of such an approach in the context of semantic information mining. Strengths and weaknesses are highlighted and discussed, as well as some possible future developments.
PU-CTG: A Point Cloud Upsampling Network Using Transformer Fusion and GRU Correction
Authors: Li Tianyu , Lin Yanghong , Cheng Bo , Ai Guo , Yang Jian , Fang Li
Published: January 2024

Point clouds are widely used in remote sensing applications, e.g., 3D object classification, semantic segmentation, and building reconstruction. Generating dense and uniformly distributed point clouds from low-density ones is beneficial to 3D point cloud applications. The traditional methods mainly focus on the global shape of 3D point clouds, thus ignoring detailed representations. The enhancement of detailed features is conducive to generating dense and uniform point clouds. In this paper, we propose a point cloud upsampling network to improve the detail construction ability, named PU-CTG. The proposed method is implemented by a cross-transformer-fused module and a GRU-corrected module. The aim of the cross-transformer module is to enable the interaction and effective fusion between different scales of features so that the network can capture finer features. The purpose of the gated recurrent unit (GRU) is to reconstruct fine-grained features by rectifying the feedback error. The experimental results demonstrate the effectiveness of our method. Furthermore, the ModelNet40 dataset is upsampled by PU-CTG, and the classification experiment is applied to PointNet to verify the promotion ability of this network.
A CFO-Assisted Algorithm for Wireless Time-Difference-of-Arrival Localization Networks: Analytical Study and Experimental Results
Authors: Hannotier Cédric , Horlin François , Quitin François
Published: January 2024

Localization of wireless transmitters is traditionally done using Radio Frequency (RF) sensors that measure the propagation delays between the transmitter and a set of anchor receivers. One of the major challenges of wireless localization systems is the need for anchor nodes to be time-synchronized to achieve accurate localization of a target node. Using a reference transmitter is an efficient way to synchronize the anchor nodes Over-The-Air (OTA), but such algorithms require multiple periodic messages to achieve tight synchronization. In this paper, we propose a new synchronization method that only requires a single message from a reference transmitter. The main idea is to use the Carrier Frequency Offset (CFO) from the reference node, alongside the Time of Arrival (ToA) of the reference node messages, to achieve tight synchronization. The ToA allows the anchor nodes to compensate for their absolute time offset, and the CFO allows the anchor nodes to compensate for their local oscillator drift. Additionally, using the CFO of the messages sent by the reference nodes and the target nodes also allow us to estimate the speed of the targets. The error of the proposed algorithm is derived analytically and is validated through controlled laboratory experiments. Finally, the algorithm is validated by realistic outdoor vehicular measurements with a software-defined radio testbed.
Real World Interstitial Glucose Profiles of a Large Cohort of Physically Active Men and Women
Authors: Skroce Kristina , Zignoli Andrea , Fontana Federico Y. , Maturana Felipe M. , Lipman David , Tryfonos Andrea , Riddell Michael C. , Zisser Howard C.
Published: January 2024

The use of continuous glucose monitors (CGMs) in individuals living without diabetes is increasing. The purpose of this study was to profile various CGM metrics around nutritional intake, sleep and exercise in a large cohort of physically active men and women living without any known metabolic disease diagnosis to better understand the normative glycemic response to these common stimuli. A total of 12,504 physically active adults (age 40 ± 11 years, BMI 23.8 ± 3.6 kg/m2; 23% self-identified as women) wore a real-time CGM (Abbott Libre Sense Sport Glucose Biosensor, Abbott, USA) and used a smartphone application (Supersapiens Inc., Atlanta, GA, USA) to log meals, sleep and exercise activities. A total of >1 M exercise events and 274,344 meal events were analyzed. A majority of participants (85%) presented an overall (24 h) average glucose profile between 90 and 110 mg/dL, with the highest glucose levels associated with meals and exercise and the lowest glucose levels associated with sleep. Men had higher mean 24 h glucose levels than women (24 h—men: 100 ± 11 mg/dL, women: 96 ± 10 mg/dL). During exercise, the % time above >140 mg/dL was 10.3 ± 16.7%, while the % time <70 mg/dL was 11.9 ± 11.6%, with the remaining % within the so-called glycemic tight target range (70–140 mg/dL). Average glycemia was also lower for females during exercise and sleep events (p < 0.001). Overall, we see small differences in glucose trends during activity and sleep in females as compared to males and higher levels of both TAR and TBR when these active individuals are undertaking or competing in endurance exercise training and/or competitive events.
SDN-Based Congestion Control and Bandwidth Allocation Scheme in 5G Networks
Authors: Yang Dong , Tsai Wei-Tek
Published: January 2024

5G cellular networks are already more than six times faster than 4G networks, and their packet loss rate, especially in the Internet of Vehicles (IoV), can reach 0.5% in many cases, such as when there is high-speed movement or obstacles nearby. In such high bandwidth and high packet loss network environments, traditional congestion control algorithms, such as CUBIC and bottleneck bandwidth and round-trip propagation time (BBR), have been unable to balance flow fairness and high performance, and their flow rate often takes a long time to converge. We propose a congestion control algorithm based on bottleneck routing feedback using an in-network control mode called bottleneck routing feedback (BRF). We use SDN technology (OpenFlow protocol) to collect network bandwidth information, and BRF controls the data transmission rate of the sender. By adding the bandwidth information of the bottleneck in the option field in the ACK packet, considering the flow fairness and the flow convergence rate, a bandwidth allocation scheme compatible with multiple congestion control algorithms is proposed to ensure the fairness of all flows and make them converge faster. The performance of BRF is evaluated via Mininet. The experimental results show that BRF provides higher bandwidth utilization, faster convergence rate, and fairer bandwidth allocation than existing congestion control algorithms in 5G cellular networks.
Smartphone-Controlled Aptasensor for Voltammetric Detection of Patulin in Apple Juice
Authors: Erdem Arzum , Senturk Huseyin
Published: January 2024

Patulin (PAT) is a mycotoxin that adversely affects the health of humans and animals. PAT can be particularly found in products such as apples and apple juice and can cause many health problems if consumed. Therefore, accurate and sensitive determination of PAT is very important for food quality and human and animal health. A voltammetric aptasensor was introduced in this study for PAT determination while measuring the changes at redox probe signal. The limit of detection (LOD) was found to be 0.18 pg/mL in the range of 1–104 pg/mL of PAT in buffer medium under optimum experimental conditions. The selectivity of the PAT aptasensor against ochratoxin A, fumonisin B1 and deoxynivalenol mycotoxins was examined and it was found that the aptasensor was very selective to PAT. PAT determination was performed in an apple juice medium for the first time by using a smartphone-integrated portable device, and accordingly, an LOD of 0.47 pg/mL was achieved in diluted apple juice medium. A recovery range of 91.24–93.47% was obtained for PAT detection.
Validation of a Zio XT Patch Accelerometer for the Objective Assessment of Physical Activity in the Atherosclerosis Risk in Communities (ARIC) Study
Authors: Davoudi Anis , Urbanek Jacek K. , Etzkorn Lacey , Parikh Romil , Soliman Elsayed Z. , Wanigatunga Amal A. , Gabriel Kelley Pettee , Coresh Josef , Schrack Jennifer A. , Chen Lin Yee
Published: January 2024

Background: Combination devices to monitor heart rate/rhythms and physical activity are becoming increasingly popular in research and clinical settings. The Zio XT Patch (iRhythm Technologies, San Francisco, CA, USA) is US Food and Drug Administration (FDA)-approved for monitoring heart rhythms, but the validity of its accelerometer for assessing physical activity is unknown. Objective: To validate the accelerometer in the Zio XT Patch for measuring physical activity against the widely-used ActiGraph GT3X. Methods: The Zio XT and ActiGraph wGT3X-BT (Actigraph, Pensacola, FL, USA) were worn simultaneously in two separately-funded ancillary studies to Visit 6 of the Atherosclerosis Risk in Communities (ARIC) Study (2016–2017). Zio XT was worn on the chest and ActiGraph was worn on the hip. Raw accelerometer data were summarized using mean absolute deviation (MAD) for six different epoch lengths (1-min, 5-min, 10-min, 30-min, 1-h, and 2-h). Participants who had ≥3 days of at least 10 h of valid data between 7 a.m–11 p.m were included. Agreement of epoch-level MAD between the two devices was evaluated using correlation and mean squared error (MSE). Results: Among 257 participants (average age: 78.5 ± 4.7 years; 59.1% female), there were strong correlations between MAD values from Zio XT and ActiGraph (average r: 1-min: 0.66, 5-min: 0.90, 10-min: 0.93, 30-min: 0.93, 1-h: 0.89, 2-h: 0.82), with relatively low error values (Average MSE × 106: 1-min: 349.37 g, 5-min: 86.25 g, 10-min: 56.80 g, 30-min: 45.46 g, 1-h: 52.56 g, 2-h: 54.58 g). Conclusions: These findings suggest that Zio XT accelerometry is valid for measuring duration, frequency, and intensity of physical activity within time epochs of 5-min to 2-h.