Abstract: Existing unmanned aerial vehicle (UAV) urban logistics planning follows a sequential paradigm—depot siting first, routing second—that embeds a structural information loss. Straight-line distance screening systematically overestimates the feasible service radius of candidate depots, creating a blindzone of depot–demand pairs that appear reachable but prove operationally infeasible under road-network distances. We term this range-feasibility blindness and derive its analytical radius Δ=Rmax(α−1)/(2α), where α is the road-to-straight-line distance ratio. Empirical measurement across three Chinese urban districts confirms α∈[1.40,1.52] and blindzone radii exceeding 2.8 km, establishing the phenomenon as a systemic property of high-density urban road geometry. To eliminate this failure by construction, we formulate a feasibility-embedded location–routing mixed-integer linear programme (MILP) that enforces road-network range constraints simultaneously with depot-opening decisions, making blindzone configurations implicitly inadmissible. A structure-aware Adaptive Large Neighbourhood Search (ALNS) solves the model at practical scales. Benchmark experiments across all three cities show consistent cost reductions of 20.6–28.2% over sequential baselines, with gains increasing monotonically with instance scale. These results position joint optimisation as a necessary methodological shift for city-scale UAV infrastructure planning.

Abstract: The rapid advancement of Machine Learning (ML) has significantly transformed polymer science by enabling efficient prediction and design of polymer properties through high‑throughput screening. However, current methods still struggle with nonlinear Structure–Property Relationships (SPRs), limited dataset standardization, and computational inefficiency, which restrict prediction accuracy and interpretability. This study proposes a comprehensive ML‑based framework for predicting polymer properties and identifying SPRs. The approach integrates data preprocessing, molecular descriptor and topological index–based feature extraction, iterative feature selection, and XGBoost predictive modeling. Model hyperparameters are optimized using the Starfish Optimization Algorithm (SOA) to enhance performance and efficiency. Model interpretability is achieved through SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME), providing both global and local insights into the influence of molecular features on polymer properties. Experimental evaluation on the PolyOne dataset demonstrates strong predictive performance, with R² values exceeding 0.92, mean absolute error (MAE) below 0.08, and root mean square error (RMSE) under 0.12 for key physical and optical polymer properties. Overall, the proposed framework effectively balances accuracy, computational efficiency, and interpretability, offering a robust and practical tool for accelerating polymer design while enhancing understanding of molecular structure–property relationships.

Abstract: With the large-scale commercialization of 5G and rapid evolution of 6G wireless systems, planar interdigital bandpass filters (BPFs) have become the core passive components for low-power RF front-ends. However, state-of-the-art filter design methods either rely heavily on empirical trial-and-error with 8–10 simulation iterations, or fail to resolve the inherent trade-off between center frequency tuning and stopband performance degradation, which cannot meet the demands of rapid customized design for 5G/6G multi-band scenarios. In this paper, a symmetric five-resonator three-segment patch-type interdigital BPF is taken as the research object. Through theoretical derivation, full-wave electromagnetic simulation, parametric scanning and orthogonal experiments, the quantitative mapping between structural parameters and filter performance is established. Notably, the directional tuning mechanism of the resonator’s narrow segment width on the first stopband is first revealed, which realizes lossless stopband optimization without disturbing the center frequency. On this basis, a three-stage standardized design procedure is proposed, which reduces design iterations from 8–10 to 3, shortens the design cycle by over 70%, and achieves 100% compliance of core design indexes. This work provides an implementable, low-threshold engineering method for rapid customized design of planar interdigital BPFs for 5G/6G RF front-ends.

Abstract: This study aimed to analyze the temporal trends and spatial distribution of mortality from malignant central nervous system (CNS) neoplasms in Brazil from 2000 to 2023. An ecological, time-series study using Joinpoint regression for temporal analysis and Global and Local Moran’s I for spatial patterns. Data were retrieved from the Mortality Information System (SIM). A total of 187,551 deaths were recorded. The Average Annual Percent Change (AAPC) showed a significant growth of +2.1% (95% CI: 1.8 – 2.4). However, a significant inflection point was identified in 2013; between 2000–2013, the APC was +4.1% (p < 0.05), becoming non-significant (+0.8%) thereafter, likely reflecting methodological data inconsistencies in the national system. Spatially, high-high clusters were concentrated in the South and Southeast regions (Moran’s I p < 0.05), while the North and Northeast presented low-low clusters, suggesting significant underreporting. While mortality trends appear to increase, they are heavily influenced by regional diagnostic disparities and information system transitions. This is the first nationwide study to integrate spatio-temporal dynamics to highlight these inequities in Brazil.

Abstract: Background: Transthyretin amyloidosis (ATTR) is a rare, often underdiagnosed and undertreated, autosomal dominantly inherited, progressive disease that affects multiple systems of the body. It results from the extracellular accumulation of misfolded transthyretin (TTR) protein as insoluble amyloid fibrils, predominantly causing cardiomyopathy, polyneuropathy or mixed phenotypes. It can occur in a hereditary form (ATTRv) and in a wild-type form (ATTRwt), with over 150 different pathogenic mutations having been identified worldwide. The clinical presentation is highly variable, leading to a diagnostic delay of 2–5 years. Transthyretin (TTR) amyloidosis is an inherited disease for which recent advances in pathogenesis, diagnosis and treatment have revolutionized its management. Objectives: The aims of this review are to provide an update on the epidemiology and genotype-phenotype correlation, on current diagnostic techniques and on emerging and individualized treatments for this rare hereditary disease. Particular attention will be given to the early diagnosis Methods: A systematic literature search was conducted across major databases to identify studies addressing clinical characteristics, diagnostic modalities, and treatment outcomes in hereditary and wild-type ATTR amyloidosis. Registry data from THAOS and other multinational cohorts were analyzed to evaluate phenotypic variability across genotypes and geographic regions. Results: Clinical presentation of TTR related amyloidosis (h-Amyloid) can range from early onset to late onset with late onset having worse neurological and cardiac involvement at time of diagnosis. The Val30Met mutation is the most common TTR mutation worldwide, however patients with non-V30M mutations can have very different presentations of h-amyloidosis. Identifying “red flag” symptoms in a patient with suspicious clinical presentation can initiate correct diagnostic pathway. Non-invasive imaging, especially bone scintigraphy, has greatly facilitated the diagnosis of patients with Transthyretin related cardiac amyloidosis (ATTR-CM). First generation h-amyloid treatments or TTR stabilizers such as tafamidis have been shown to significantly improve survival in patients with h-amyloidosis. The second generation treatments such as RNA silencers (patisiran, vutrisiran, inotersen, eplontersen) have been shown to halt the disease progression. Present data from small to moderate-sized patient cohorts demonstrate that TTR-targeting therapy is associated with reduction of cardiovascular events and improvement in survival compared with current standard of care. Early recognition of key clinical features and application of a diverse diagnostic strategy, in conjunction with timely initiation of disease-modifying therapy, are critical to optimal management of patients with hereditary transthyretin (ATTR) amyloidosis. Conclusions: The therapeutic options have evolved and improved in recent years, and with current diagnostic tools, the opportunity to alter the natural history of a disease that was once invariably fatal is better than ever. Because the disease is systemic, a thorough, multidisciplinary approach to patient management is ideal.

Abstract: C-reactive protein (CRP) was discovered in 1930 by Tillett and Francis as a protein that reacts with C-polysaccharides to form precipitates in the serum of patients with pneumococcal infection. Subsequently, it was found to increase in the serum of patients with bacterial infections and rheumatic diseases, and it has since been widely recognized as a nonspecific biomarker of acute inflammation and utilized in clinical medicine. Meanwhile, CRP-like proteins are also present in the hemolymph of horseshoe crabs, and it has become clear that these proteins have long played a crucial role in the humoral innate immune response against foreign microorganisms. In recent years, advances in molecular analysis have revealed the details of the complex biological functions performed by CRP. Furthermore, with the development of highly sensitive CRP measurement methods, its importance as a biomarker is gaining attention not only in acute inflammatory diseases but also in chronic inflammatory diseases such as cardiovascular disease, diabetes, cancer and neurological disorders. New treatment strategies targeting CRP, based on recent findings, are also being explored.

Abstract: Mechanistic models in radiobiology have proliferated across FLASH ultra-high dose-rate radiotherapy, spatially fractionated radiation therapy (SFRT), and stereotactic body radiotherapy (SBRT), yet the field has not converged on unified mechanistic explanations despite decades of model development. We propose that this proliferation partly reflects a structural property of the model-observation pairing itself: clinically accessible measurements may be insufficient to uniquely recover the parameters governing the underlying biological dynamics. Using generating-series structural identifiability analysis, we examine four representative models spanning the temporal, spatial, magnitude, and adaptive-state dimensions of radiobiological response: the Pratx-Kapp radiolytic oxygen depletion model (FLASH), the McMahon kinetic-bystander model (SFRT), the LQ-L extension (SBRT), and the Gupta phenotypic-plasticity model of adaptive resistance. The Pratx-Kapp and McMahon models exhibit intrinsic non-identifiability under conventional surviving-fraction observation, while the LQ-L and Gupta models exhibit observation-dependent identifiability conditional on dose-range coverage and marker-panel richness. These findings suggest that increasing radiobiological complexity progressively exposes the limitations of fixed-parameter mechanistic descriptions under partial observability. As a constructive response, we propose, as a hypothesis, that adaptive latent-state inference frameworks operating over a coupled multi-layer organizational state may provide a complementary operational paradigm for radiobiology under uncertainty.

Abstract: Background and Objectives: Controlled hypotension during functional endoscopic sinus surgery (FESS) improves surgical field visibility but may pose a risk of subclinical cerebral hypoperfusion. Serum S100Β and neuron‑specific enolase (NSE) are established biomarkers of glial and neuronal injury and may reflect perioperative neuroprotection associated with different anesthetic regimens. This study evaluated the effect of four anesthetic protocols on perioperative brain biomarker release during FESS. Materials and Methods: In this single‑center, randomized, controlled trial, 88 adult patients (ASA I–III) undergoing FESS under moderately controlled hypotension (mean arterial pressure <55 mmHg) were allocated to one of four groups: propofol–remifentanil, propofol–remifentanil with ketamine–magnesium, sevoflurane–remifentanil, or sevoflurane–remifentanil with ketamine–magnesium. Serum S100Β and NSE concentrations were measured at three timepoints: early intraoperatively, during hypotension, and at the end of surgery. Biomarker data were analyzed using nested ANOVA and linear mixed‑effects models adjusted for relevant covariates. Secondary outcomes included recovery characteristics, surgical field quality, bleeding scores, and perioperative hemodynamics. Results: Baseline demographic and perioperative characteristics were comparable across groups. The group receiving sevoflurane–remifentanil combined with ketamine–magnesium showed the lowest S100B levels (p=0.01 compared to the propofol–remifentanil group; p=0.04 compared to the sevoflurane–remifentanil group). Additionally, NSE concentrations were markedly lower in both sevoflurane groups (sevoflurane–remifentanil and sevoflurane–remifentanil plus ketamine–magnesium) compared to the propofol–remifentanil group (p=0.003 and p=0.007, respectively). No intergroup differences were observed at baseline and surgical field quality, bleeding, and hemodynamic parameters did not differ significantly among groups. Recovery and extubation times were shortest with propofol–remifentanil, whereas ketamine–magnesium prolonged emergence. Conclusions: Anesthetic technique significantly influences perioperative brain biomarker release during FESS. Sevoflurane‑based regimens, with or without ketamine–magnesium, demonstrate more favorable neurobiological profiles under controlled hypotension, although propofol‑based anesthesia offers faster recovery.

Abstract: The emergence of vancomycin-intermediate Staphylococcus aureus (VISA) threatens the efficacy of this last-line antibiotic. The GraSR two component system is frequently mutated in VISA strains. Here, we demonstrate that the GraS(T136I) point mutation, identified in the clinical VISA isolate XN108, is a key determinant of reduced vancomycin susceptibility. Introducing this mutation into the susceptible strain Newman increased the vancomycin MIC from 1.5 to 4 mg/L, while its reversion in XN108 decreased the MIC from 12 to 8 mg/L. The mutation conferred common phenotypes, including thickened cell wall, decreased autolysis, and reduced cell surface negative charge via upregulation of the dltABCD operon and mprF. Notably, GraS(T136I) mutation also upregulated virulence genes (efb, hlb, sbi, hld) and enhanced hemolytic activity. Interestingly, despite this hypervirulence profile, the mutant showed impaired long term survival within macrophages. Our study reveals that a single GraSR mutation can co-regulate vancomycin resistance and virulence, offering new insights into the adaptation of S. aureus to antibiotic pressure.

Abstract: Background: Chronic low back pain (CLBP) is the leading cause of years lived with disability globally, affecting over 600 million individuals. Intervertebral disc degeneration (IVDD) is a principal structural contributor, yet conventional treatments, including pharmacotherapy, physical therapy, and surgical intervention, do not reverse the underlying degenerative pathology. Regenerative medicine has introduced a spectrum of biological therapies, ranging from cell-based mesenchymal stromal cells (MSCs) transplantation to cell-free modalities, including platelet-rich plasma (PRP), platelet lysate, MSC-derived extracellular vesicles (EVs), and MSC-derived secretomes. However, these approaches have largely been studied in isolation, without a unified framework to compare their respective advantages and limitations in CLBP secondary to IVDD. Accordingly, this narrative review aims to provide an integrated and comparative evaluation of these regenerative strategies within a single translational and clinical context. Methods: For this narrative review, PubMed, Scopus, and Web of Science were searched from January 2000 to January 2026 using terms combining regenerative modalities with intervertebral disc degeneration, and chronic low back pain. Randomized controlled trials (RCTs), prospective cohort studies, systematic reviews, and preclinical studies with translational relevance were included. Results: Intradiscal MSC therapy has demonstrated safety across multiple phase I–III trials, but two recent landmark RCTs (RESPINE and the Mesoblast phase III trial) failed to meet primary efficacy endpoints, highlighting the gap between preclinical promise and clinical outcomes. PRP has the largest clinical evidence base, with level II evidence supporting short- to medium-term pain relief for discogenic pain, although standardization remains a critical barrier. Platelet lysate, MSC-derived EVs, and MSC-derived secretomes show compelling preclinical data, including extracellular matrix restoration, anti-inflammatory modulation, and attenuation of nucleus pulposus cell apoptosis, but remain at early translational stages for spinal applications, with no completed RCTs. The hostile disc microenvironment (avascular, hypoxic, acidic, and nutrient-poor) poses unique challenges for all regenerative modalities, differing fundamentally from other musculoskeletal applications. Conclusions: The studies included in this narrative review suggest that no single regenerative modality has yet shown consistent and unequivocal efficacy for CLBP secondary to IVDD across clinical trials. Cell-free approaches offer manufacturing, scalability, and safety advantages over cell-based therapies, but lack clinical validation. Future progress requires standardized preparation protocols, disc-specific delivery systems, patient phenotyping strategies, and rigorously designed comparative clinical trials. This narrative review provides a framework for researchers and clinicians to evaluate these therapies in context rather than isolation.

Abstract: Avian metapneumovirus (aMPV) represents a serious respiratory pathogen of poultry and is associated with considerable economic losses in breeder flocks worldwide. Although horizontal transmission is well established, the contribution of vertical transmission remains poorly understood, especially under field conditions in chickens. In this study, we aimed to assess whether aMPV could be transmitted vertically in unvaccinated broiler breeder flocks that tested positive by PCR in Egypt. Therefore, 10 broiler breeder flocks (≥30 weeks) from seven Egyptian governorates were screened for aMPV subtypes A and B. From each flock, tracheal swabs were collected from breeder hens, along with 20 fertile eggs and 20 newly hatched chicks. All samples, including tracheal swabs, chicken tissues (trachea, lungs, reproductive tract, and spleen), eggshells, internal egg contents, and embryonic tissues were analyzed for aMPV RNA using subtype-specific RT-qPCR. All breeder flocks tested positive for aMPV subtype B, but not subtype A. No aMPV RNA was found in eggshells, internal egg contents, embryonic tissues, or tissues from newly hatched chicks. In conclusion, Despite PCR detection of aMPV in breeder hens, the absence of viral RNA in eggs and their progeny provides field evidence that vertical transmission of subtype B is unlikely to play a significant role in virus spread in commercial broiler breeder flocks. These results support horizontal transmission as the primary route of aMPV spread and highlight the need for further longitudinal and genomic studies to better elucidate aMPV transmission dynamics.

Abstract: Although SARS-CoV-2 has been extensively studied from clinical, virological, and diagnostic perspectives, the problem of accurate automatic semantic segmentation of SARS-CoV-2 particles in electron microscopy images remains inadequately explored. Existing studies have largely focused on virus detection, classification, morphometry, or conventional image analysis, while comparatively little attention has been paid to pixel-level delineation of viral structures using specialised deep learning segmentation frameworks. To address this gap, we propose here a deep learning system based on convolutional neural networks (CNNs) combined with image processing techniques to establish semantic segmentation tools for the automatic identification of SARS-CoV-2. Our approach utilises the super-Euclidean pixels method as an intermediate layer within the CNN for semantic segmentation. We then compare its performance against the gradient vector flow (GVF) and Poisson inverse gradient (PIG) segmenters. The proposed CNN model surpassed the traditional GVF and PIG segmentation models, achieving the following metrics (mean ± variance): Dice similarity coefficient (DSC) = 0.9345 ± 0.0006; intersection over union (IoU) = 0.8782 ± 0.0018; sensitivity/true positive rate (TPR) = 0.9373 ± 0.0018; specificity/true negative rate (SPC) = 0.9517 ± 0.0012; accuracy = 0.9449 ± 0.0004; area under the ROC curve (AUC) = 0.9446 ± 0.0431; and Cohen’s Kappa = 0.9137 ± 0.0011. This method enables virologists to employ an automatic CNN-based segmentation tool for detecting SARS-CoV-2 and demonstrates superiority over GVF and PIG.

Abstract: Background: The prognostic value of serial coronary artery calcium (CAC) progression remains uncertain in Asian populations, particularly among patients receiving statin therapy. We evaluated whether CAC progression predicts major adverse cardiovascular events (MACE) in a Taiwanese cohort and whether this association differs by statin use. Methods: We retrospectively studied 1,942 individuals who underwent two cardiac computed tomography scans for CAC scoring at a tertiary medical center in Taiwan between 2006 and 2021. CAC progression was defined as an annualized Agatston score increase of ≥20 units/year. The primary outcome was MACE, defined as acute myocardial infarction, stroke, or cardiovascular death. Predictors of CAC progression were assessed using logistic regression. Associations between CAC progression and MACE were evaluated using Cox models with propensity score–based inverse probability weighting; 1,621 participants with complete covariate data were included in weighted analyses. Results: CAC progression occurred in 397 participants (20.4%). Independent predictors included male sex, hypertension, fasting glucose, lipid parameters, and baseline CAC score. CAC progression was associated with a higher risk of MACE, with increasing event rates across higher categories of annualized CAC change (p for trend < 0.0001). This association was consistent across clinical subgroups and was observed in both statin and non-statin users, without a significant CAC progression × statin interaction (p = 0.163). Conclusions: In this Asian serial CAC cohort, CAC progression was strongly associated with future MACE and may serve as a marker of residual cardiovascular risk, including among statin-treated patients. Serial CAC assessment may support dynamic risk stratification, but prospective studies are needed to determine whether progression-guided management improves outcomes.

Abstract: Against the backdrop of escalating global climate risks, this study systematically investigates the effects, boundary conditions, and interactive mechanisms of two core policy instruments—green finance and environmental regulation—on agricultural supply chain resilience. Using panel data of China’s Shanghai and Shenzhen A-share listed agribusiness firms from 2010 to 2025 and a two-way fixed effects model, we find: First, climate risk serves as a critical external pressure driving resilience building, yet its positive impact is conditional on a “capacity threshold”—only significant for firms with high resilience and large scale. Second, the two policy instruments exhibit heterogeneous structural thresholds: green finance demonstrates a “supporting-the-weak” effect, enhancing resilience primarily in small and medium-sized enterprises (SMEs) with low resilience, but is constrained by an “institutional–technological” double threshold. In contrast, environmental regulation displays a “scale bias”, with its statistically significant positive effect limited to large firms. Third, climate risk negatively moderates the effectiveness of green finance: under high-risk conditions, firms tend to divert green funds toward short-term relief, eroding long-term resilience investment, and this “policy failure” risk is particularly pronounced among SMEs. Fourth, mechanism tests rule out the traditional mediation channel of alleviating financing constraints; moreover, the two policy instruments have not yet formed significant synergistic effects under the current institutional framework. This study extends the application boundaries of the resource-based view and dynamic capabilities theory in high-risk contexts, provides micro-level empirical evidence on policy instrument implementation biases in heterogeneous market structures, and offers theoretical support and practical references for developing climate-smart agricultural supply chain policies.

Abstract: We derive a penalty strength criterion for ridge regression using stochastic complexity, which is a refined variant of the minimum description length principle. Since stochastic complexity doesn’t typically account for the effect of regularisation on complexity, despite its ability to simplify models, we are required to make a slight modification to the un- derlying coding scheme. Our scheme makes use of a weighted ensemble of regularised model fits rather than a mixture of maximum likelihood estimates. Under this modification, regularisation is interpreted as reducing model complexity by constraining flexibility. In the case of ridge regression, the complexity penalty term that we derive can be expressed analytically as the log determinant of the residual operator. We demonstrate the effect of this complexity penalty by fitting a linear readout to a reservoir computer.

Abstract: We study the effects of weak magnetic fields (around 2 mT) on the growth of Staphylococcus aureus (S. aureus) in the presence of a few sweeteners (monosaccharides, disaccharides, sugar alcohols, and consumer-grade sweeteners). Bacterial growth rates were compared in various magnetic fields at room temperature. Bacterial growth was estimated using optical absorbance measurements at various wavelengths, and pH values were manually estimated using pH strips. Absorbance was measured at 492 nm and 630 nm, which are wavelengths comparable to the size of a cell of S. aureus after division. This comparability plays a vital role in the scale of measured absorbance values. The results imply that bacterial growth may be reduced due to acidic byproducts formed by metabolizing sugars or sugar alcohols, as an increasingly acidic solution is less ideal for bacterial growth. Magnetic fields were also found to have a minor effect on pH estimates. These results reveal potential effects on microorganisms in the presence of sugars and sugar alcohols in addition to weak magnetic fields, demonstrating the contribution of various environmental conditions with increasing prevalence in the modern day.

Abstract: Background: An estimated 28,900 deaths around the world in 2021 were attributed to unintentional CO poisoning. Following inhalation, CO binds to hemoglobin with an affinity 220–240 times greater than that of oxygen to form carboxyhemoglobin (COHb). While the constituents of CO exposure are known to determine CO uptake in the blood, much less is understood regarding individual variability of the response to a given CO stimulus. Thus, the purpose of this paper was to explore the relationship between hemoglobin mass (HbM, a proxy for blood hemoglobin content) and the magnitude of the ensuing carboxyhemoglobinemia. Methods: This is a theoretical work based solely on considerations and published data. Discussion: Currently considered the gold standard for HbM assessment, the CO-rebreathing technique relies on the dilution principle i.e. the lower the HbM values the higher the ΔCOHb following a standardized CO bolus administration or an outdoors exposure. Accordingly, previously published prediction equations with HbM and ΔCOHb as the predictor and outcome variables, respectively, are reviewed with particular reference to the (confounding) factor of pulmonary ventilation. As far as treatment to CO poisoning is concerned, dynamic exercise emerges as a supplement to oxygen therapy to facilitate CO removal from human body. Screening procedures aiming to identify individuals susceptible to CO poisoning should henceforth include HbM assessments.

Abstract: Benefiting from tunable emission from ultraviolet to near-infrared windows, long luminescence lifetimes, and exceptional photostability, rare-earth-doped nanomaterials overcome the limitations of conventional dyes and quantum dots, enabling deep-tissue, high-resolution, and low-background imaging. As multifunctional fluorescent probes, rare-earth-doped nanomaterials are driving the development of next-generation biomedical imaging. This review summarizes recent advances in the structural design of rare earth-doped nanomaterials, surface engineering for biocompatibility, and targeting strategies for improved performance, and highlights their integration into advanced imaging modalities, including NIR-I/II fluorescence, FLIM, PAI, super-resolution STED, multimodal FL/MRI/CT, X-ray-excited luminescence, and persistent luminescence. Meanwhile, mechanistic insights, material innovations, and comparative advantages are discussed. Furthermore, challenges related to quantum yield, scalable synthesis, imaging resolution, and clinical translation are considered, while future directions—centered on multifunctional probe design, NIR-II imaging, and AI-assisted data analysis—are proposed, offering a versatile platform for precise multimodal imaging with significant potential to advance early diagnosis, personalized therapy, and clinical applications.

Abstract: Hysteresis is normally unavoidable in hydrogels under complex external loading conditions due to the intermolecular friction, which usually leads to fatigue. Here, we develop a sarcomere-inspired double-network hydrogel made from polyacrylamide, alginate and phytic acid, whose hysteresis can be precisely modulated by preloading. Particularly, due to the synergy of micellization, fibrillation and micro-lubrication, the as-prepared hydrogel displays an ultra-low hysteresis (≤ 0.02 %) after it experiences a pre-tensile process at a specific amplitude and strain rate, or even possesses negative hysteresis in the case of low tensile amplitudes or high strain rates. Interestingly, smart responses of the developed hydrogel to cyclic tensile loadingare similar to the mechanical behaviors of sarcomeres in vivo. Likewise, the derived hydrogel with ultra-low hysteresis performs reliably even at temperatures as low as -20 ℃. The ultra-low hysteresis presented by the biomimetic hydrogel with ultra-low hysteresis makes it suitable for many engineering fields like electrical sensing with superior reliability (the corresponding electrical signal (ΔR/R0) is stable even after 1000 stretching-unstretching cycles). Moreover, the design strategy of hydrogels with programmable hysteresis provides an innovative methodology for the future development of smart high-performance hydrogels.

Abstract: Technology plays a vital role in the way teacher’s work, communicate, and share their knowledge particularly after COVID pandemic. Thus, it is a matter of great importance both from theoretical and practical point of view to understand the factors that govern knowledge sharing through technologies. This study integrates Teo’s composite model of Technology Acceptance(TA) and Knowledge Sharing(KS) construct of Van den Hooff & Van Weenen, to empirically examine the relationship between technology acceptance and knowledge sharing among teachers. A study used a descriptive-correlational cross-sectional research approach. 225 participants responded to the survey. The study used Technology Acceptance Questionnaire, Teo( 2011) with 20 items(α=0.84) and Knowledge Sharing Questionnaire by Van den Hooff and Van Weenen ( 2004), with 12 items(α=0.96). One- sample t-test was used to find out the degree to which Technology Acceptance and Knowledge Sharing is practised by teachers. Pearson’s correlation was used to identify if there is any positive relationship between Technology Acceptance components and Knowledge Sharing elements. Structural equation modelling (SEM) was used to study whether any of the factors of Technology Acceptance can significantly predict the two types of Knowledge Sharing.Perceived Usefulness (PU) and Facilitating Conditions (FC) emerged as the most influential factors of Technology Acceptance in driving teachers’ Knowledge Sharing.