High-speed railway suspension bridges (HSRSBs) have been constructed with the new advancements in technology. The deformation prediction for HSRSBs is essential to their safety and maintenance. The conventional prediction methods are developed for bridges without high-speed railway. Different factors, including temperature (TEMP), time delay compensation (TDC), train live load (TLL), are considered in these methods. However, the train side (TS) and train instantaneous position (TIP) have a significant impact on deformation for HSRSBs, and they are not used in the prediction. More importantly, the coupling issue among different factors is so significant that it cannot be neglected. In this study, we propose a deformation prediction model based on a backpropagation (BP) neural network. This model uses different factors as model input, including TEMP, TDC, TLL, TS, and TIP. The coupling issue is addressed by using the new model. The new model was evaluated using a dataset of 10-day field measurements. It achieves a mean absolute error (MAE) of 8.81 mm, a mean relative error (MRE) of 9.82%, and coefficient of determination (R²) of 0.94. The new model will provide high-precision prediction for deformation and will be used in the development of an early warning system. Full article

The application of deep learning algorithms to predict the molecular profiles of various cancers from digital images of hematoxylin and eosin (H&E)-stained slides has been reported in recent years, mainly for gastric and colon cancers. In this study, we investigated the potential use of H&E-stained endometrial cancer slide images to predict the associated mismatch repair (MMR) status. H&E-stained slide images were collected from 127 cases of the primary lesion of endometrial cancer. After digitization using a Nanozoomer virtual slide scanner (Hamamatsu Photonics), we segmented the scanned images into 5397 tiles of 512 × 512 pixels. The MMR proteins (PMS2, MSH6) were immunohistochemically stained, classified into MMR proficient/deficient, and annotated for each case and tile. We trained several neural networks, including convolutional and attention-based networks, using tiles annotated with the MMR status. Among the tested networks, ResNet50 exhibited the highest area under the receiver operating characteristic curve (AUROC) of 0.91 for predicting the MMR status. The constructed prediction algorithm may be applicable to other molecular profiles and useful for pre-screening before implementing other, more costly genetic profiling tests. Full article

Titanium alloys are commonly used for implants, but the naturally forming oxides are bioinert and not ideal for bacterial resistance or osseointegration. Anodization processes are a modification technique that can crystallize the oxides, alter oxide surface topography, and introduce beneficial chemistries. Crystalline titanium oxides are known to exhibit photocatalytic activity (PCA) under UVA light. Anodization was used to create mixed-phase oxides on six titanium alloys including commercially pure titanium (CPTi), Ti-6Al-4V (TAV), Ti-6Al-7Nb (TAN), two forms of Ti-15Mo (TiMo-β and TiMo-αβ), and Ti-35Nb-7Zr-5Ta (TNZT). Combined EDS and XPS analyses showed uptake of the electrolyte and substrate alloying elements into the oxides. The relative oxide PCA was measured using methylene blue degradation assays. CPTi and TAN oxides exhibited increased PCA compared to other alloys. Combined XRD and EBSD oxide phase analyses revealed an unfavorable arrangement of anatase and rutile phases near the outermost surfaces, which may have reduced PCA for other oxides. The relative Staphylococcus aureus attachment to each oxide was also assessed. The CPTi and TiMo-αβ oxides showed significantly reduced S. aureus attachment after 1 h of UVA compared to un-anodized CPTi. Cell culture results verified that the UVA irradiation did not negatively influence the MC3T3-E1 attachment or proliferation on the mixed-phase oxides. Full article

In this study, digital light processing (DLP) was utilized to generate 3D-printed blends composed of photosensitive acrylate-modified polylactic acid (PLA) resin mixed with varying weight ratios of lignin extracted from softwood, typically ranging from 5 wt% to 30 wt%. The microstructure of these 3D-printed blends was examined through X-ray microtomography. Additionally, the tensile mechanical properties of all blends were assessed in relation to the weight ratio and post-curing treatment. The results suggest that post-curing significantly influences the tensile properties of the 3D-printed composites, especially in modulating the brittleness of the prints. Furthermore, an optimal weight ratio was identified to be around 5 wt%, beyond which UV light photopolymerization experiences compromises. These findings regarding acrylate-modified PLA/lignin blends offer a cost-effective alternative for producing 3D-printed bio-sourced components, maintaining technical performance in reasonable-cost, low-temperature 3D printing, and with a low environmental footprint. Full article

The diagnosis of MS relies on a combination of imaging, clinical examinations, and biological analyses, including blood and cerebrospinal fluid (CSF) assessments. G-Oligoclonal bands (OCBs) are considered a “gold standard” for MS diagnosis due to their high sensitivity and specificity. Recent advancements have involved the introduced of kappa free light chain (k-FLC) assay into cerebrospinal fluid (CSF) and serum (S), along with the albumin quotient, leading to the development of a novel biomarker known as the “K-index” or “k-FLC index”. The use of the K-index has been recommended to decrease costs, increase laboratory efficiency, and to skip potential subjective operator-dependent risk that could happen during the identification of OCBs profiles. This review aims to provide a comprehensive overview and analysis of recent scientific articles, focusing on updated methods for MS diagnosis with an emphasis on the utility of the K-index. Numerous studies indicate that the K-index demonstrates high sensitivity and specificity, often comparable to or surpassing the diagnostic accuracy of OCBs evaluation. The integration of the measure of the K-index with OCBs assessment emerges as a more precise method for MS diagnosis. This combined approach not only enhances diagnostic accuracy, but also offers a more efficient and cost-effective alternative. Full article

In rotating detonation engines the turbine inlet conditions may be transonic with unprecedented unsteady fluctuations. To ensure an acceptable engine performance, the turbine passages must be suited to these conditions. This article focuses on designing and characterizing highly diffusive turbine vanes to operate at any inlet Mach number up to Mach 1. First, the effect of pressure loss on the starting limit is presented. Afterward, a multi-objective optimization with steady RANS simulations, including the endwall and 3D vane design is performed. Compared to previous research, significant reductions in pressure loss and stator-induced rotor forcing are obtained, with an extended operating range and preserving high flow turning. Finally, the influence of the inlet boundary layer thickness on the vane performance is evaluated, inducing remarkable increases in pressure loss and downstream pressure distortion. Employing an optimization with a thicker inlet boundary layer, specific endwall design recommendations are found, providing a notable improvement in both objective functions. Full article

Earthquake-triggered landslides (ETLs) feature large quantities, extensive distributions, and enormous losses to human lives and critical infrastructures. Near-real spatial prediction of ETLs can rapidly predict the locations of coseismic landslides just after a violent earthquake and is a vital technical support for emergency response. However, near-real prediction of ETLs has always been a great challenge with relatively low accuracy. This work proposes an ensemble prediction model of EnPr by integrating machine learning tree models and a deep learning convolutional neural network. EnPr exhibits relatively strong prediction and generalization performance and achieves relatively accurate prediction of ETLs. Six great seismic events occurring from 2008 to 2022 on the southeastern margin of the Tibetan Plateau are selected to conduct ETL prediction. In a chronological order, the 2008 M_s 8.0 Wenchuan, 2010 M_s 7.1 Yushu, 2013 M_s 7.0 Lushan, and 2014 M_s 6.5 Ludian earthquakes are employed for model training and learning. The 2017 M_s 7.0 Jiuzhaigou and 2022 M_s 6.1 Lushan earthquakes are adopted for ETL prediction. The prediction accuracy merits of ACC and AUC attain 91.28% and 0.85, respectively, for the Jiuzhaigou earthquake. The values of ACC and AUC achieve 93.78% and 0.88, respectively, for the Lushan earthquake. The proposed EnPr algorithm outperforms the algorithms of XGBoost, random forest (RF), extremely randomized trees (ET), convolutional neural network (CNN), and Transformer. Moreover, this work reveals that seismic intensity, high and steep relief, pre-seismic fault tectonics, and pre-earthquake road construction have played significant roles in coseismic landslide occurrence and distribution. The EnPr model uses globally accessible open datasets and can therefore be used worldwide for new large seismic events in the future. Full article

Efficiently determining crop water stress is vital for optimising irrigation practices and enhancing agricultural productivity. In this realm, the synergy of deep learning with remote sensing technologies offers a significant opportunity. This study introduces an innovative end-to-end deep learning pipeline for within-field crop water determination. This involves the following: (1) creating an annotated dataset for crop water stress using Landsat 8 imagery, (2) deploying a standalone vision transformer model ViT, and (3) the implementation of a proposed CNN-ViT model. This approach allows for a comparative analysis between the two architectures, ViT and CNN-ViT, in accurately determining crop water stress. The results of our study demonstrate the effectiveness of the CNN-ViT framework compared to the standalone vision transformer model. The CNN-ViT approach exhibits superior performance, highlighting its enhanced accuracy and generalisation capabilities. The findings underscore the significance of an integrated deep learning pipeline combined with remote sensing data in the determination of crop water stress, providing a reliable and scalable tool for real-time monitoring and resource management contributing to sustainable agricultural practices. Full article

The interplay between two paradigms, artificial intelligence (AI) and optical metasurfaces, nowadays appears obvious and unavoidable. AI is permeating literally all facets of human activity, from science and arts to everyday life. On the other hand, optical metasurfaces offer diverse and sophisticated multifunctionalities, many of which appeared impossible only a short time ago. The use of AI for optimization is a general approach that has become ubiquitous. However, here we are witnessing a two-way process—AI is improving metasurfaces but some metasurfaces are also improving AI. AI helps design, analyze and utilize metasurfaces, while metasurfaces ensure the creation of all-optical AI chips. This ensures positive feedback where each of the two enhances the other one: this may well be a revolution in the making. A vast number of publications already cover either the first or the second direction; only a modest number includes both. This is an attempt to make a reader-friendly critical overview of this emerging synergy. It first succinctly reviews the research trends, stressing the most recent findings. Then, it considers possible future developments and challenges. The author hopes that this broad interdisciplinary overview will be useful both to dedicated experts and a general scholarly audience. Full article

Subjective well-being presents a societal challenge for vulnerable older adults. This study aims to investigate the mediating role of place attachment in the relationship between attitudes toward aging and subjective well-being among community-dwelling older adults in Taiwan. Two waves of investigations were conducted to examine the interplay between attitudes toward aging, subjective well-being, and place attachment among older adults. In Wave I, 1190 participants were enrolled, revealing predominantly younger cohorts with substantial educational levels. The subsequent Wave II involved 483 participants, maintaining continuity in characteristics. Subjective well-being remained moderate across waves, with prevalent positive attitudes toward aging. Place attachment scores indicated moderate to high associations. After controlling for demographics, structural equation modeling (SEM) in both waves revealed significant positive associations: attitudes toward aging influenced well-being, attitudes toward aging were positively associated with place attachment, and place attachment was positively related to well-being. Mediation testing confirmed the mediating role of place attachment in the relationship between attitudes toward aging and well-being. These findings underscore the important role of place attachment. It is evident that improving attitudes toward aging is an effective intervention which can lead to a better sense of well-being by enhancing place attachment to empower civil society. Full article

Patients with rheumatoid arthritis (RA) are prone to develop infections. Methods: Accordingly, 195 untreated early (e)RA patients and 398 healthy controls were selected from women in Tatarstan’s cohort to study infectious history in the anamnesis (four criteria) and in the previous year (16 criteria). Information about annual infections was collected face-to-face from year to year by a qualified rheumatologist/ general practitioner and included the active use of information from medical records. Results: In the anamnesis, tuberculosis, and pneumonia, and in the previous year, respiratory tract infections, skin infections, and herpes simplex virus reactivation incidence were reported to be increased in eRA patients, as well as the event number and duration of acute and chronic tonsillitis. Moreover, more bacterial-suspected upper respiratory infections and urinary tract infections were retrieved in sporadic eRA patients as compared to familial eRA patients. An elevated immunization against CCP prevented respiratory tract infection in those with HSV exacerbation. Finally, associations were retrieved between infection (event number/delay) and RA indices: (i) chronic tonsillitis exacerbations with disease activity and health assessment (HAQ) in familial eRA; (ii) bacterial-suspected upper respiratory infections with the number of swollen and tender joints in sporadic eRA; and (iii) HSV exacerbation with inflammation in eRA patients with negative/low response against CCP. Here, we demonstrate the complex nature of the interplay of RA with specific infections. Conclusions: For the first time, differences in the patterns of annual trivial infections and their links with RA indices were found in cohorts of familial and sporadic cases of the disease. Additionally, for the first time, we identified a remarkable relationship between early RA and exacerbations of chronic tonsillitis, as well as tuberculosis in the patient’s history. Altogether, this study supports the existence of a complex interplay between infections and RA at onset driven by familial status and the presence of anti-CCP Ab at elevated levels. Full article

The utilization of a reverberant shear-wave field in shear-wave elastography has emerged as a promising technique for achieving robust shear-wave speed (SWS) estimation. However, many types of estimators cannot accurately measure SWS within such a complicated 3D wave field. This study introduces an advanced autocorrelation estimator based on angular integration known as the angular integral autocorrelation (AIA) approach to address this issue. The AIA approach incorporates all the autocorrelation data from various angles during measurements, resulting in enhanced robustness to both noise and imperfect distributions in SWS estimation. The effectiveness of the AIA estimator for SWS estimation is first validated using a k-Wave simulation of a stiff branching tube in a uniform background. Furthermore, the AIA estimator is applied to ultrasound elastography experiments, magnetic resonance imaging (MRI) experiments, and optical coherence tomography (OCT) studies across a range of different excitation frequencies on tissues and phantoms, including in vivo scans. The results verify the capacity of the AIA approach to enhance the accuracy of SWS estimation and the signal-to-noise ratio (SNR), even within an imperfect reverberant shear-wave field. Compared to simple autocorrelation approaches, the AIA approach can also successfully visualize and define lesions while significantly improving the estimated SWS and SNR in homogeneous background materials and providing improved elastic contrast between structures within the scans. These findings demonstrate the robustness and effectiveness of the AIA approach across a wide range of applications, including ultrasound elastography, magnetic resonance elastography (MRE), and optical coherence elastography (OCE), for accurately identifying the elastic properties of biological tissues in diverse excitation scenarios. Full article

Grape seeds (GS), wine lees (WL), and grape pomace (GP) are common winery by-products, used as bio-fillers in this research with two distinct biopolymer matrices—poly(butylene adipate-co-terephthalate) (PBAT) and polybutylene succinate (PBS)—to create fully bio-based composite materials. Each composite included at least 30 v% bio-filler, with a sample reaching 40 v%, as we sought to determine a composition that could be economically and environmentally effective as a substitute for a pure biopolymer matrix. The compounding process employed a twin-screw extruder followed by an injection molding procedure to fabricate the specimens. An acetylation treatment assessed the specimen’s efficacy in enhancing matrix–bio-filler affinity, particularly for WL and GS. The fabricated bio-composites underwent an accurate characterization, revealing no alteration in thermal properties after compounding with bio-fillers. Moreover, hygroscopic measurements indicated increased water-affinity in bio-composites compared to neat biopolymer, most significantly with GP, which exhibited a 7-fold increase. Both tensile and dynamic mechanical tests demonstrated that bio-fillers not only preserved, but significantly enhanced, the stiffness of the neat biopolymer across all samples. In this regard, the most promising results were achieved with the PBAT and acetylated GS sample, showing a 162% relative increase in Young’s modulus, and the PBS and WL sample, which exhibited the highest absolute values of Young’s modulus and storage modulus, even at high temperatures. These findings underscore the scientific importance of exploring the interaction between bio-fillers derived from winery by-products and three different biopolymer matrices, showcasing their potential for sustainable material development, and advancing polymer science and bio-sourced material processing. From a practical standpoint, the study highlighted the tangible benefits of using by-product bio-fillers, including cost savings, waste reduction, and environmental advantages, thus paving the way for greener and more economically viable material production practices. Full article

Nanoparticles (NPs) are extremely important tools to overcome the limitations imposed by therapeutic agents and effectively overcome biological barriers. Smart designed/tuned nanostructures can be extremely effective for cancer treatment. The selection and design of nanostructures and the adjustment of size and surface properties are extremely important, especially for some precision treatments and drug delivery (DD). By designing specific methods, an important era can be opened in the biomedical field for personalized and precise treatment. Here, we focus on advances in the selection and design of nanostructures, as well as on how the structure and shape, size, charge, and surface properties of nanostructures in biological fluids (BFs) can be affected. We discussed the applications of specialized nanostructures in the therapy of head and neck cancer (HNC), which is a difficult and aggressive type of cancer to treat, to give an impetus for novel treatment approaches in this field. We also comprehensively touched on the shortcomings, current trends, and future perspectives when using nanostructures in the treatment of cancer. Full article

Background: Erectile dysfunction (ED) stands out as one of the most prevalent sexual disorders in men, with its incidence progressively escalating with age. As delineated by the International Consultation Committee for Sexual Medicine on Definitions/Epidemiology/Risk Factors for Sexual Dysfunction, the prevalence of ED among men under 40 years is estimated to be within the range of 1–10%. The aim of this study was to determine the relationship between the concentration of bioelements (Zn, Cu, Fe, Cr, Mg, and Mn) in the serum and bone tissue and the concentration of selected hormones in men with and without erectile dysfunction. Materials and methods: The retrospective cohort study included 152 men who underwent total hip arthroplasty for hip osteoarthritis at the Department of Orthopaedic Traumatology and Musculoskeletal Oncology at the Pomeranian Medical University in Szczecin. Certain exclusion criteria were applied to ensure the integrity of the study. These included individuals with diabetes, a history of cancer, alcohol abuse, liver or kidney failure, New York Heart Association (NYHA) class III or IV heart failure, and those taking medications that affect bone metabolism, such as mineral supplements, neuroleptics, chemotherapeutic agents, immunosuppressants, corticosteroids, or antidepressants. Patients with hypogonadism or infertility were excluded from the study. Results: The study showed an association between bioT concentrations and Cu concentrations in both patients with and without erectile dysfunction. A correlation between bioactive testosterone and Cr concentrations was also observed in both groups. Patients with erectile dysfunction showed a relationship between bioT concentration and Zn concentration, TT concentration and Mn concentration, FT concentration and Zn concentration, and E2 concentration and Cr concentration. An analysis of elemental concentrations in bone tissue showed an association between FT and Mg and Mn concentrations, but only in patients with erectile dysfunction. In patients without erectile dysfunction, a correlation was observed between FT and Cu concentrations. A correlation was also observed between bioT concentrations and Mg, Mn, and Zn concentrations, but only in patients with erectile dysfunction. In patients without erectile dysfunction, a correlation was observed between bioT and Cu concentrations. Conclusions: Studying the relationship between the concentration of bioelements (Zn, Cu, Fe, Cr, Mg, and Mn) in the serum and bone tissue and the concentration of selected hormones in men may be important in explaining the etiology of the problem. The study of the concentration of Zn and Cu in bone tissue and serum showed that these two elements, regardless of the place of accumulation, may be related to the concentration of androgens in men. Full article

Auxins are chemical compounds of wide interest, mostly due to their role in plant metabolism and development. Synthetic auxins have been used as herbicides for more than 75 years and low toxicity in humans is one of their most advantageous features. Extensive studies of natural and synthetic auxins have been made in an effort to understand their role in plant growth. However, molecular details of the binding and recognition process are still an open question. Herein, we present a comprehensive in silico pipeline for the assessment of TIR1 ligands using several structure-based methods. Our results suggest that subtle dynamics within the binding pocket arise from water–ligand interactions. We also show that this trait distinguishes effective binders. Finally, we construct a database of putative ligands and decoy compounds, which can aid further studies focusing on synthetic auxin design. To the best of our knowledge, this study is the first of its kind focusing on TIR1. Full article

The Sick Body Writing: Towards an Affective Genetic Criticism examines the idea that manuscripts can be affected by illness as much as their authors’ bodies are. This article aims to highlight a critical gap in the methodology of literary genetic criticism by introducing a new lens of affective genetic criticism. Genetic criticism looks at the archive of drafts and notes related to a literary work-in-progress. The application of affect theory brings focus to the impacts of the author’s bodily experience during writing while in different states of un/healthiness. The effects of authors’ health on their writing, especially textual non/production and the representations of un/healthiness, can be found in their archive in a variety of forms, whether represented in the narrative or responsible for elements of the narrative’s structure. Using two case studies from different literary canons, James Joyce (modernist) and Aidan Chambers (children’s and Young Adult), the article concludes that this lens can be productively applied to understand better the embodiment of writing processes and adaptations of writing environments as a result of affective needs. Full article

Aquatic plants play a key role in the structuring and functioning of shallow lake ecosystems. However, eutrophication often triggers shifts in plant communities and species diversity, especially in the early stages when the water is still clear. Additionally, water depth is an important factor regulating aquatic plant communities. We conducted a 50-day mesocosm study to investigate how water depth (50 cm and 100 cm) affected the functional traits (vertical expansion versus horizontal colonisation) of 20 aquatic plants under eutrophic clear-water conditions. Among the selected species, the submerged plants Hydrocotyle vulgaris and Limnophila indica exhibited higher plant height or biomass in deeper water, while the emergent plants Myriophyllum aquaticum showed the opposite trend. Additionally, Ludwigia peploides subsp. stipulacea exhibited better vertical growth than the remaining species, and the submerged species Vallisneria denseserrulata had better horizontal colonisation. There was a positive correlation between plant height and rhizome length, indicating the absence of a trade-off between vertical growth and horizontal expansion. Our findings suggest an overall resilience of aquatic plants to varying water depths within our study range and highlight the importance of analysing functional traits when selecting appropriate species in freshwater ecosystem restoration, particularly in the face of climate change-induced water depth fluctuations. Full article

Hemp, commonly known as Cannabis sativa L., is a medicinal plant species of the Cannabaceae family. For the efficient extraction of C. sativa leaves using the conventional stirring process with water as the solvent, three crucial extraction parameters (i.e., extraction duration, liquid–solid ratio, and temperature) were investigated through the response surface methodology (RSM). The concentrations of the extracted bioactive compounds (polyphenols, ascorbic acid, and carotenoids) showed significant variations in the RSM design points, suggesting the importance of finding the optimal extraction conditions in which liquid–solid ratio and extraction temperature were found to have the highest impact. Further analysis was conducted on the optimal extract employing several assays to determine their polyphenol content, total carotenoid content, color evaluation, anti-inflammatory activity, and antioxidant capacity through FRAP, DPPH, and H₂O₂ assays. Α low extraction time (30 min) at 50 °C and a high liquid–solid ratio (50:1) were required for the highest possible yield of polyphenols. The total polyphenol content was determined to be 9.76 mg gallic acid equivalents/g under optimum conditions, with pelargonin being the most abundant polyphenol (1.51 mg/g) in C. sativa extracts. Ascorbic acid was measured at 282.23 μg/g and total carotenoids at 356.98 μg/g. Correlation analyses revealed that anti-inflammatory activity was negatively correlated with specific polyphenols. As determined by DPPH (27.43 μmol ascorbic acid equivalents (AAE)/g), FRAP (49.79 μmol AAE/g), and H₂O₂ (230.95 μmol AAE/g) assays, the optimized aqueous extract showed a high antioxidant capacity. Furthermore, it demonstrated considerable anti-inflammatory activity at 17.89%, with the potential to increase to 75.12% under particular extraction conditions. Given the high added-value of the aqueous extracts, the results of this study highlight the potential utility of C. sativa leaves as a source of health-improving antioxidant compounds in the pharmaceutical and food industries. Full article

Adequate vitamin D (VD) intake during pregnancy is needed for fetal development and maternal health maintenance. However, while there is no doubt regarding its importance, there is not a unified recommendation regarding adequate intake. The main aim of our study was to measure the VD serum level of studied women, together with its potential influencing factors: demographic (i.e., age, level of education, relationship status and type of residence), conception and pregnancy related factors. Results are based on secondary data analyses of a retrospective case–control study of 100 preterm and 200 term pregnancies, where case and control groups were analyzed together. Data collection was based on a self-administered questionnaire, health documentation, and maternal serum VD laboratory tests. VD intake was evaluated by diet and dietary supplement consumption. According to our results, 68.1% of women took some kind of prenatal vitamin, and only 25.9% of them knew about its VD content. Only 12.1% of included women reached the optimal, 75 nmol/L serum VD level. Higher maternal serum levels were associated with early pregnancy care visits (p = 0.001), assisted reproductive therapy (p = 0.028) and advice from gynecologists (p = 0.049). A correlation was found between VD intake and serum levels (p < 0.001). Despite the compulsory pregnancy counselling in Hungary, health consciousness, VD intake and serum levels remain below the recommendations. The role of healthcare professionals is crucial during pregnancy regarding micronutrients intake and the appropriate supplementation dose. Full article

A hyperspectral image (HSI) is often corrupted by various types of noise during image acquisition, e.g., Gaussian noise, impulse noise, stripes, deadlines, and more. Thus, as a preprocessing step, HSI denoising plays a vital role in many subsequent tasks. Recently, a variety of mixed noise removal approaches have been developed for HSI, and the methods based on spatial–spectral double factor and total variation (DFTV) regularization have achieved comparable performance. Additionally, the nonlocal low-rank tensor model (NLR) is often employed to characterize spatial nonlocal self-similarity (NSS). Generally, fully exploring prior knowledge can improve the denoising performance, but it significantly increases the computational cost when the NSS prior is employed. To solve this problem, this article proposes a novel DFTV-based NLR regularization (DFTVNLR) model for HSI mixed noise removal. The proposed model employs low-rank tensor factorization (LRTF) to characterize the spectral global low-rankness (LR), introduces 2-D and 1-D TV constraints on double-factor to characterize the spatial and spectral local smoothness (LS), respectively. Meanwhile, the NLR is applied to the spatial factor to characterize the NSS. Then, we developed an algorithm based on proximal alternating minimization (PAM) to solve the proposed model effectively. Particularly, we effectively controlled the computational cost from two aspects, namely taking small-sized double factor as regularization object and putting the time-consuming NLR model before the main loop with fewer iterations to solve it independently. Finally, considerable experiments on simulated and real noisy HSI substantiate that the proposed method is superior to the related state-of-the-art methods in balancing the denoising effect and speed. Full article

Antibacterial hydrogel wound dressings hold great potential in eliminating bacteria and accelerating the healing process. However, it remains a challenge to fabricate hydrogel wound dressings that simultaneously exhibit excellent mechanical and photothermal antibacterial properties. Here we report the development of polydopamine-functionalized graphene oxide (rGO@PDA)/calcium alginate (CA)/Polypyrrole (PPy) cotton fabric-reinforced hydrogels (abbreviated as rGO@PDA/CA/PPy FHs) for tackling bacterial infections. The mechanical properties of hydrogels were greatly enhanced by cotton fabric reinforcement and an interpenetrating structure, while excellent broad-spectrum photothermal antibacterial properties based on the photothermal effect were obtained by incorporating PPy and rGO@PDA. Results indicated that rGO@PDA/CA/PPy FHs exhibited superior tensile strength in both the warp (289 ± 62.1 N) and weft directions (142 ± 23.0 N), similarly to cotton fabric. By incorporating PPy and rGO@PDA, the swelling ratio was significantly decreased from 673.5% to 236.6%, while photothermal conversion performance was significantly enhanced with a temperature elevated to 45.0 °C. Due to the synergistic photothermal properties of rGO@PDA and PPy, rGO@PDA/CA/PPy FHs exhibited excellent bacteria-eliminating efficiency for S. aureus (0.57%) and E. coli (3.58%) after exposure to NIR for 20 min. We believe that the design of fabric-reinforced hydrogels could serve as a guideline for developing hydrogel wound dressings with improved mechanical properties and broad-spectrum photothermal antibacterial properties for infected-wound treatment. Full article