Surgical ASTM F139 stainless steel is used for temporary fixtures in the biomedical field. Tribocorrosion is a major concern in this application. The aim of the present work was to study the interplay between tribocorrosion behavior and the surface chemistry of the ASTM F139 stainless steel in phosphate-buffered saline solution (PBS). Sliding wear tests were conducted against alumina balls at different electrochemical potentials: open circuit potential (OCP), cathodic potential (−100 mV versus the OCP), and anodic potentials (+200 mV_Ag/AgCl and +700 mV_Ag/AgCl). The normal load was 20 N. The wear volume was estimated based on micrographs obtained from the wear tracks using confocal laser scanning microscopy. Moreover, the wear tracks were also examined by scanning electron microscopy (SEM). The surface chemistry of the ASTM F139 specimens was analyzed by X-ray photoelectron spectroscopy (XPS). The wear volume was dependent on the electrochemical potential, being maximized at +700 mVAg/AgCl. Delamination areas and grooves were observed in the wear tracks. Detailed assessment of the surface chemistry inside the wear tracks allowed identification of the main chemical species and their relative quantities, thus enabling correlation of the passive film composition with the observed tribocorrosion behavior. Full article

Background: The aim of the present study was to provide ocular biometry percentile values for Indian children between the ages of 6 and 12 and to validate the usefulness of centiles in predicting myopia development. Methods: The study was part of a longitudinal study—the Sankara Nethralaya Tamil Nadu Essilor Myopia Study (STEM), where objective refraction and ocular biometry were measured for children studying in grades 1, 4, and 6 at baseline (2019–2020). These data were used to generate ocular biometry percentile curves (both for axial length (AL) and AL/corneal curvature (AL/CR) ratios). The usefulness of percentile values in predicting myopia development was estimated from follow-up data (2022). Results: The total number of children in the three grades at baseline was 4514 (age range 6 to 12). Boys represented 54% (n = 2442) of the overall sample. The prevalence of myopia at baseline was 11.7% (95% CI from 10.8 to 12.7%) in these three grades. Both the AL and AL/CR ratio centiles showed a linear trend with an increase in AL and AL/CR with increasing grades (p < 0.001) for all percentiles (2, 5, 10, 25, 50, 75, 90, 95, 98, and 99) when stratified by sex. In the follow-up data (n = 377), the 75th and 50th percentiles of the AL/CR ratio had an area under the curve (AUC) of 0.79 and 0.72 to predict myopia onset for grade 4 and 6 children at baseline. Combining baseline AL with the centile shift in follow-up as a predictor increased the AUC to 0.83. Conclusions: The present study has provided centile values specific for Indian children between the ages of 6 and 12 to monitor and intervene where children are at a higher risk of myopia development. Full article

Bariatric surgery therapy (BST) is an effective treatment for obesity; however, little is known about its impacts on health-related quality of life (HRQoL) and related factors. This study aimed to evaluate changes in HRQoL and its relationship with weight loss, depression status, physical activity (PA), and nutritional habits after BST. Data were obtained before and 18 months postprocedure from 56 obese patients who underwent BST. We administered four questionnaires: Short Form-36 health survey for HRQoL, 14-item MedDiet adherence questionnaire, Rapid Assessment of PA (RAPA) questionnaire, and Beck’s Depression Inventory-II. Multivariable linear regression analysis was used to identify factors associated with improvement in HRQoL. After the surgery, MedDiet adherence and HRQoL improved significantly, especially in the physical component. No changes in PA were found. Patients without previous depression have better mental quality of life, and patients who lost more than 25% of %TBWL have better results in physical and mental quality of life. In the multivariable analysis, we found that %TBWL and initial PCS (inversely) were related to the improvement in PCS and initial MCS (inversely) with the MCS change. In conclusion, BST is an effective intervention for obesity, resulting in significant weight loss and improvements in HRQoL and nutritional habits. Full article

This study investigated the effect of 3 s light-curing with a high-power LED curing unit on the shear bond strength of bulk-fill composites. Four bulk-fill composites were bonded to dentin with a universal adhesive (Scotchbond Universal Plus): two materials designed for rapid curing (Tetric PowerFill and Tetric PowerFlow) and two controls (Filtek One Bulk Fill Restorative and SDR Plus Bulk Fill Flowable). The 4 mm composite layer was light-cured with Bluephase PowerCure for 20 s at 1000 mW/cm² (“20 s”) or for 3 s at 3000 mW/cm² (“3 s”). The samples were stored at 37 °C in distilled water and tested after 1, 6 and 12 months. The samples polymerised in the “3 s” mode had statistically similar or higher bond strength than the samples cured in “20 s” mode, except for the Tetric PowerFlow (1 month) and SDR+ (6 month). The flowable materials Tetric PowerFlow and SDR Plus initially showed the highest values in the “3 s” and “20 s” groups, which decreased after 12 months. The bond strength was statistically similar for all materials and curing protocols after 12 months, except for Tetric PowerFill cured with the “3 s” protocol (21.22 ± 5.0 MPa), which showed the highest value. Tetric PowerFill showed the highest long-term bond strength. While “3 s” curing resulted in equal or better shear bond strength, its use can only be recommended for a material with an AFCT agent such as Tetric PowerFill. Full article

It is well known that application of exogenous trehalose can enhance the heat resistance of plants. To investigate the underlying molecular mechanisms by which exogenous trehalose induces heat resistance in C. sinensis, a combination of physiological and transcriptome analyses was conducted. The findings revealed a significant increase in the activity of superoxide dismutase (SOD) and peroxidase (POD) upon treatment with 5.0 mM trehalose at different time points. Moreover, the contents of proline (PRO), endogenous trehalose, and soluble sugar exhibited a significant increase, while malondialdehyde (MDA) content decreased following treatment with 5.0 mM trehalose under 24 h high-temperature stress (38 °C/29 °C, 12 h/12 h). RNA-seq analysis demonstrated that the differentially expressed genes (DEGs) were significantly enriched in the MAPK pathway, plant hormone signal transduction, phenylpropanoid biosynthesis, flavone and flavonol biosynthesis, flavonoid biosynthesis, and the galactose metabolism pathway. The capability to scavenge free radicals was enhanced, and the expression of a heat shock factor gene (HSFB2B) and two heat shock protein genes (HSP18.1 and HSP26.5) were upregulated in the tea plant. Consequently, it was concluded that exogenous trehalose contributes to alleviating heat stress in C. sinensis. Furthermore, it regulates the expression of genes involved in diverse pathways crucial for C. sinensis under heat-stress conditions. These findings provide novel insights into the molecular mechanisms underlying the alleviation of heat stress in C. sinensis with trehalose. Full article

Software vulnerabilities present a significant cybersecurity threat, particularly as software code grows in size and complexity. Traditional vulnerability-mining techniques face challenges in keeping pace with this complexity. Fuzzing, a key automated vulnerability-mining approach, typically focuses on code branch coverage, overlooking syntactic and semantic elements of the code. In this paper, we introduce HotCFuzz, a novel vulnerability-mining model centered on the coverage of hot code blocks. Leveraging vulnerability syntactic features to identify these hot code blocks, we devise a seed selection algorithm based on their coverage and integrate it into the established fuzzing test framework AFL. Experimental results demonstrate that HotCFuzz surpasses AFL, AFLGo, Beacon, and FairFuzz in terms of efficiency and time savings. Full article

Skin is the primary and largest protective organ of the human body. It produces a number of highly evolved arsenal of factors to counter the continuous assault of foreign materials and pathogens from the environment. One such potent factor is the repertoire of Antimicrobial Peptides (AMPs) that not only directly destroys invading pathogens, but also optimally modulate the immune functions of the body to counter the establishment and spread of infections. The canonical direct antimicrobial functions of these AMPs have been in focus for a long time to design principles for enhanced therapeutics, especially against the multi-drug resistant pathogens. However, in recent times the immunomodulatory functions performed by these peptides at sub-microbicidal concentrations have been a point of major focus in the field of host-directed therapeutics. Such strategies have the added benefit of not having the pathogens develop resistance against the immunomodulatory pathways, since the pathogens exploit these signaling pathways to obtain and survive within the host. Thus, this review summarizes the potent immunomodulatory effect of these AMPs on, specifically, the different host immune cells with the view of providing a platform of information that might help in designing studies to exploit and formulate effective host-directed adjunct therapeutic strategies that would synergies with drug regimens to counter the current diversity of drug-resistant skin opportunistic pathogens. Full article

Progressive Multifocal Leukoencephalopathy (PML) is a possibly fatal demyelinating disease and John Cunningham Polyomavirus (JCPyV) is believed to cause this condition. The so-called JCPyV was initially reported in lymphoma and Human Immunodeficiency Virus (HIV) cases, whereas nowadays, its incidence is increasing in Multiple Sclerosis (MS) cases treated with natalizumab (Tysabri). However, there are conflicting literature data on its pathology and diagnosis, whereas some misdiagnosed reports exist, giving rise to further questions towards the topic. In reality, the so-called PML and the supposed JCPyV are not what they seem to be. In addition, novel and more frequent PML-like conditions may be reported, especially after the Coronavirus Disease 2019 (COVID-19) pandemic. Full article

The production of pure water plays a pivotal role in enabling sustainable green hydrogen production through electrolysis. The current industrial approach for generating pure water relies on energy-intensive techniques such as reverse osmosis. This study unveils a straightforward method to produce pure water, employing real-world units derived from previously simulated and developed laboratory devices. This demonstrated system is cost-effective and boasts low energy consumption, utilizing membrane distillation (MD) driven by the waste heat harnessed from photovoltaic (PV) panels. In a previous study, modeling simulations were conducted to optimize the multi-layered MD system, serving as a blueprint for the construction of prototype devices with a suitable selection of materials, enabling the construction of field-testable units. The most efficient PV-MD device, featuring evaporation and condensation zones constructed from steel sheets and polytetrafluoroethylene (PTFE) membranes, is capable of yielding high-purity water with conductivity levels below 145 μS with high flux rates. Full article

Nature-based solutions (NBSs), defined as actions that work with and enhance nature, providing environmental, social, and economic benefits, play a pivotal role in accomplishing multiple objectives within the Water–Ecosystem–Food Nexus domain. They contribute to facilitating the transition to more resilient agrifood systems and providing an evidence base for a broader Nexus policy dialogue. This paper describes the stepwise methodology developed in the EU-funded LENSES project to carry out a comprehensive analysis of NBSs in six pilot areas in five Mediterranean countries and presents the results of NBS implementation in four pilot areas, highlighting obstacles and opportunities. The methodology includes the development of an analytical evaluation framework and a comprehensive catalogue of Nexus-related NBSs, whose suitability needs to be assessed at the local level to achieve better use of protected/natural ecosystems, increase the sustainability and multifunctionality of managed ecosystems, and design and manage novel ecosystems. Subsequently, in a collective learning process that supported the operationalisation of the WEF Nexus, NBSs were identified that address specific contextual vulnerabilities, improve water distribution, and enhance food security while preserving ecosystems and supporting adaptation to climate change. The added value of the proposed methodology lies in the multi-stakeholder participatory approach to gain in-depth knowledge of local agri-food systems, including their main WEF-related challenges, and to facilitate overcoming barriers to NBS implementation. Finally, a final survey was conducted among a small group of purposively selected stakeholders to gain some insight into their perceptions of the impact of NBS and to gather some opinions on the main barriers and opportunities. Full article

Various methods for evaluating the visual quality of landscapes have been continuously studied. In the era of the rapid development of big data, methods to obtain evaluation data efficiently and accurately have received attention. However, few studies have been conducted to optimize the evaluation methods for landscape visual quality. Here, we aim to develop an evaluation model that is model fine-tuned using Scenic Beauty Evaluation (SBE) results. In elucidating the methodology, it is imperative to delve into the intricacies of refining the evaluation process. First, fine-tuning the model can be initiated with a scoring test on a small population, serving as an efficient starting point. Second, determining the optimal hyperparameter settings necessitates establishing intervals within a threshold range tailored to the characteristics of the dataset. Third, from the pool of fine-tuned models, selecting the one exhibiting optimal performance is crucial for accurately predicting the visual quality of the landscape within the study population. Lastly, through the interpolation process, discernible differences in landscape aesthetics within the core monitoring area can be visually distinguished, thereby reinforcing the reliability and practicality of the new method. In order to demonstrate the efficiency and practicality of the new method, we chose the core section of the famous Beijing–Hangzhou Grand Canal in Wujiang District, China, as a case study. The results show the following: (1) Fine-tuning the model can start with a scoring test on a small population. (2) The optimal hyperparameter setting intervals of the model need to be set in a threshold range according to different dataset characteristics. (3) The model with optimal performance is selected among the four fine-tuning models for predicting the visual quality of the landscape in the study population. (4) After the interpolation process, the differences in landscape aesthetics within the core monitoring area can be visually distinguished. We believe that the new method is efficient, accurate, and practically applicable for improving landscape visual quality evaluation. Full article

A deep learning-based Visual Inertial SLAM technique is proposed in this paper to ensure accurate autonomous localization of mobile robots in environments with dynamic objects. Addressing the limitations of real-time performance in deep learning algorithms and the poor robustness of pure visual geometry algorithms, this paper presents a deep learning-based Visual Inertial SLAM technique. Firstly, a non-blocking model is designed to extract semantic information from images. Then, a motion probability hierarchy model is proposed to obtain prior motion probabilities of feature points. For image frames without semantic information, a motion probability propagation model is designed to determine the prior motion probabilities of feature points. Furthermore, considering that the output of inertial measurements is unaffected by dynamic objects, this paper integrates inertial measurement information to improve the estimation accuracy of feature point motion probabilities. An adaptive threshold-based motion probability estimation method is proposed, and finally, the positioning accuracy is enhanced by eliminating feature points with excessively high motion probabilities. Experimental results demonstrate that the proposed algorithm achieves accurate localization in dynamic environments while maintaining real-time performance. Full article

Purpose: Given the emergence of PSMA-targeted diagnostic agents and therapeutics, we sought to investigate patterns of FOLH1 expression in RCC and their impacts on RCC outcomes. Methods: We conducted a pooled multi-institutional analysis of patients with RCC having undergone DNA and RNA next-generation sequencing. FOLH1-high/low expression was defined as the ≥75th/<25th percentile of RNA transcripts per million (TPM). Angiogenic, T-effector, and myeloid expression signatures were calculated using previously defined gene sets. Kaplan–Meier estimates were calculated from the time of tissue collection or therapy start. Results: We included 1,724 patients in the analysis. FOLH1 expression was significantly higher in clear cell (71%) compared to non-clear cell RCC tumors (19.0 versus 3.3 TPM, p < 0.001) and varied by specimen site (45% primary kidney/55% metastasis, 13.6 versus 9.9 TPM, p < 0.001). FOLH1 expression was correlated with angiogenic gene expression (Spearman = 0.76, p < 0.001) and endothelial cell abundance (Spearman = 0.76, p < 0.001). While OS was similar in patients with FOLH1-high versus -low ccRCC, patients with FOLH1-high clear cell tumors experienced a longer time on cabozantinib treatment (9.7 versus 4.6 months, respectively, HR 0.57, 95% CI 0.35–0.93, p < 0.05). Conclusions: We observed differential patterns of FOLH1 expression based on histology and tumor site in RCC. FOLH1 was correlated with angiogenic gene expression, increased OS, and a longer duration of cabozantinib treatment. Full article

In this study, spherical or hexagonal NaYF₄:Yb,Er nanoparticles (UCNPs) with sizes of 25 nm (S-UCNPs) and 120 nm (L-UCNPs) were synthesized by high-temperature coprecipitation and subsequently modified with three kinds of polymers. These included poly(ethylene glycol) (PEG) and poly(N,N-dimethylacrylamide-co-2-aminoethylacrylamide) [P(DMA-AEA)] terminated with an alendronate anchoring group, and poly(methyl vinyl ether-co-maleic acid) (PMVEMA). The internalization of nanoparticles by rat mesenchymal stem cells (rMSCs) and C6 cancer cells (rat glial tumor cell line) was visualized by electron microscopy and the cytotoxicity of the UCNPs and their leaches was measured by the real-time proliferation assay. The comet assay was used to determine the oxidative damage of the UCNPs. An in vivo study on mice determined the elimination route and potential accumulation of UCNPs in the body. The results showed that the L- and S-UCNPs were internalized into cells in the lumen of endosomes. The proliferation assay revealed that the L-UCNPs were less toxic than S-UCNPs. The viability of rMSCs incubated with particles decreased in the order S-UCNP@Ale-(PDMA-AEA) > S-UCNP@Ale-PEG > S-UCNPs > S-UCNP@PMVEMA. Similar results were obtained in C6 cells. The oxidative damage measured by the comet assay showed that neat L-UCNPs caused more oxidative damage to rMSCs than all coated UCNPs while no difference was observed in C6 cells. An in vivo study indicated that L-UCNPs were eliminated from the body via the hepatobiliary route; L-UCNP@Ale-PEG particles were almost eliminated from the liver 96 h after intravenous application. Pilot fluorescence imaging confirmed the limited in vivo detection capabilities of the nanoparticles. Full article

In this study, Fe₃O₄/Ag magnetite-silver (MSx) nanocomposites were investigated as catalysts for advanced oxidation processes by coupling the plasmonic effect of silver nanoparticles and the ferromagnetism of iron oxide species. A surfactant-free co-precipitation synthesis method yielded pure Fe₃O₄ magnetite and four types of MSx nanocomposites. Their characterisation included structural, compositional, morphological and optical analyses, revealing Fe₃O₄ magnetite and Ag silver phases with particle sizes ranging from 15 to 40 nm, increasing with the silver content. The heterostructures with silver reduced magnetite particle aggregation, as confirmed by dynamic light scattering. The UV–Vis spectra showed that the Fe:Ag ratio strongly influenced the absorbance, with a strong absorption band around 400 nm due to the silver phase. The oxidation kinetics of organic pollutants, monitored by in situ luminescence measurements using rhodamine B as a model system, demonstrated the higher performance of the developed catalysts with increasing Ag content. The specific surface area measurements highlighted the importance of active sites in the synergistic catalytic activity of Fe₃O₄/Ag nanocomposites in the photo-Fenton reaction. Finally, the straightforward fabrication of diverse Fe₃O₄/Ag heterostructures combining magnetism and plasmonic effects opens up promising possibilities for heterogeneous catalysis and environmental remediation. Full article

Background: Parents play a crucial role in the care of infants during their stay in the neonatal intensive care unit (NICU). Recent studies have reported a decrease in parental participation due to the coronavirus disease (COVID-19) pandemic, which has led to restricted access policies in hospitals. The aim of this study was to describe the barriers to good parental participation during their stay in the neonatal intensive care unit in the COVID-19 era. Methods: This was a quantitative, observational study. Results: A total of 270 parents participated in this study. Mothers’ participation in care was higher than that of fathers (p = 0.017). Parents who lived at the birth of their first child reported a better level of participation in care compared to those who lived at the birth of their second-born (p = 0.005). Parents of extremely preterm neonates reported a lower interaction with their infants than parents of term newborns (p < 0.001). Conclusions: Some disadvantaged categories reported lower scores for cultural and linguistic minorities, parents of multiple children, and fathers. The COVID-19 pandemic has made several family-centred care activities impossible, with a higher impact on those who benefited most of these facilities. This study was prospectively approved by the IRB-CRRM of the University “G. d’Annunzio” Chieti-Pescara on 23 January 2024 (approval number CRRM: 2023_12_07_01). Full article

The solutions to the radial Schrödinger equation for a pseudoharmonic potential and Kratzer potential have been studied separately in the past. Despite different reports on the Kratzer potential, the fundamental theoretical quantities such as Fisher information have not been reported. In this study, we obtain the solution to the radial Schrödinger equation for the combination of the pseudoharmonic and Kratzer potentials in the presence of a constant-dependent potential, utilizing the concepts and formalism of the supersymmetric and shape invariance approach. The position expectation value and momentum expectation value are calculated employing the Hellmann–Feynman Theory. These expectation values are then used to calculate the Fisher information for both position and momentum spaces in both the absence and presence of the constant-dependent potential. The results obtained revealed that the presence of the constant-dependent potential leads to an increase in the energy eigenvalue, as well as in the position and momentum expectation values. Additionally, the constant-dependent potential increases the Fisher information for both position and momentum spaces. Furthermore, the product of the position expectation value and the momentum expectation value, along with the product of the Fisher information, satisfies both Fisher’s inequality and Cramer–Rao’s inequality. Full article

Background: cardiovascular diseases, including acute myocardial infarction (AMI) and takotsubo cardiomyopathy (TTC), are significant causes of morbidity and mortality worldwide. Timely differentiation of these conditions is essential for effective patient management and improved outcomes. Methods: We conducted a review focusing on studies that applied artificial intelligence (AI) techniques to differentiate between acute myocardial infarction (AMI) and takotsubo cardiomyopathy (TTC). Inclusion criteria comprised studies utilizing various AI modalities, such as deep learning, ensemble methods, or other machine learning techniques, for discrimination between AMI and TTC. Additionally, studies employing imaging techniques, including echocardiography, cardiac magnetic resonance imaging, and coronary angiography, for cardiac disease diagnosis were considered. Publications included were limited to those available in peer-reviewed journals. Exclusion criteria were applied to studies not relevant to the discrimination between AMI and TTC, lacking detailed methodology or results pertinent to the AI application in cardiac disease diagnosis, not utilizing AI modalities or relying solely on invasive techniques for differentiation between AMI and TTC, and non-English publications. Results: The strengths and limitations of AI-based approaches are critically evaluated, including factors affecting performance, such as reliability and generalizability. The review delves into challenges associated with model interpretability, ethical implications, patient perspectives, and inconsistent image quality due to manual dependency, highlighting the need for further research. Conclusions: This review article highlights the promising advantages of AI technologies in distinguishing AMI from TTC, enabling early diagnosis and personalized treatments. However, extensive validation and real-world implementation are necessary before integrating AI tools into routine clinical practice. It is vital to emphasize that while AI can efficiently assist, it cannot entirely replace physicians. Collaborative efforts among clinicians, researchers, and AI experts are essential to unlock the potential of these transformative technologies fully. Full article

This paper pioneers a novel approach in electromagnetic (EM) system analysis by synergistically combining Bayesian Neural Networks (BNNs) informed by Latin Hypercube Sampling (LHS) with advanced thermal–mechanical surrogate modeling within COMSOL simulations for high-frequency low-pass filter modeling. Our methodology transcends traditional EM characterization by integrating physical dimension variability, thermal effects, mechanical deformation, and real-world operational conditions, thereby achieving a significant leap in predictive modeling fidelity. Through rigorous evaluation using Mean Squared Error (MSE), Maximum Learning Error (MLE), and Maximum Test Error (MTE) metrics, as well as comprehensive validation on unseen data, the model’s robustness and generalization capability is demonstrated. This research challenges conventional methods, offering a nuanced understanding of multiphysical phenomena to enhance reliability and resilience in electronic component design and optimization. The integration of thermal variables alongside dimensional parameters marks a novel paradigm in filter performance analysis, significantly improving simulation accuracy. Our findings not only contribute to the body of knowledge in EM diagnostics and complex-environment analysis but also pave the way for future investigations into the fusion of machine learning with computational physics, promising transformative impacts across various applications, from telecommunications to medical devices. Full article

The aim of this study was to evaluate the effect of local administration of melatonin (MLT) on molecular biomarkers and calvaria bone critical defects in female rats with or without osteoporosis, associated or not with a xenogeneic biomaterial. Forty-eight female rats were randomly divided into two groups: (O) ovariectomized and (S) placebo groups. After 45 days of osteoporosis induction, two critical-size defects (5 mm diameter) were created on the calvaria. The groups were subdivided according to the following treatment: (C) Clot, MLT, MLT associated with Bio-Oss^® (MLTBO), and Bio-Oss^® (BO). After 45 days, the defect samples were collected and processed for microtomography, histomorphometry, and biomolecular analysis (Col-I, BMP-2, and OPN). All animals had one femur harvested to confirm the osteoporosis. Microtomography analysis demonstrated a bone mineral density reduction in the O group. Regarding bone healing, the S group presented greater filling of the defects than the O group; however, in the O group, the defects treated with MLT showed higher mineral filling than the other treatments. There was no difference between the treatments performed in the S group (p = 0.05). Otherwise, O-MLT had neoformed bone higher than in the other groups (p = 0.05). The groups that did not receive biomaterial demonstrated lower levels of Col-I secretion; S-MLT and S-MLTBO presented higher levels of OPN, while O-C presented statistically lower results (p < 0.05); O-BO showed greater BMP-2 secretion (p < 0.05). In the presence of ovariectomy-induced osteoporosis, MLT treatment increased the newly formed bone area, regulated the inflammatory response, and increased OPN expression. Full article

Elastomers are made of chain-like molecules to form networks that can sustain large deformation. Rubbers are thermosetting elastomers that are obtained from irreversible curing reactions. Curing reactions create permanent bonds between the molecular chains. On the other hand, thermoplastic elastomers do not need curing reactions. Incorporation of appropriated filler particles, as has been practiced for decades, can significantly enhance mechanical properties of elastomers. However, there are fundamental questions about polymer matrix composites (PMCs) that still elude complete understanding. This is because the macroscopic properties of PMCs depend not only on the overall volume fraction ($\varphi$) of the filler particles, but also on their spatial distribution (i.e., primary, secondary, and tertiary structure). This work aims at reviewing how the mechanical properties of PMCs are related to the microstructure of filler particles and to the interaction between filler particles and polymer matrices. Overall, soft rubbery matrices dictate the elasticity/hyperelasticity of the PMCs while the reinforcement involves polymer–particle interactions that can significantly influence the mechanical properties of the polymer matrix interface. For $\varphi$ values higher than a threshold, percolation of the filler particles can lead to significant reinforcement. While viscoelastic behavior may be attributed to the soft rubbery component, inelastic behaviors like the Mullins and Payne effects are highly correlated to the microstructures of the polymer matrix and the filler particles, as well as that of the polymer–particle interface. Additionally, the incorporation of specific filler particles within intelligently designed polymer systems has been shown to yield a variety of functional and responsive materials, commonly termed smart materials. We review three types of smart PMCs, i.e., magnetoelastic (M-), shape-memory (SM-), and self-healing (SH-) PMCs, and discuss the constitutive models for these smart materials. Full article

The smart grid, as a crucial part of modern energy systems, handles extensive and diverse data, including inputs from various sensors, metering devices, and user interactions. Outsourcing data storage to remote cloud servers presents an economical solution for enhancing data management within the smart grid ecosystem. However, ensuring data privacy before transmitting it to the cloud is a critical consideration. Therefore, it is common practice to encrypt the data before uploading them to the cloud. While encryption provides data confidentiality, it may also introduce potential issues such as limiting data owners’ ability to query their data. The searchable attribute-based encryption (SABE) not only enables fine-grained access control in a dynamic large-scale environment but also allows for data searches on the ciphertext domain, making it an effective tool for cloud data sharing. Although SABE has become a research hotspot, existing schemes often have limitations in terms of computing efficiency on the client side, weak security of the ciphertext and the trapdoor. To address these issues, we propose an efficient server-aided ciphertext-policy searchable attribute-based encryption scheme (SA-CP-SABE). In SA-CP-SABE, the user’s data access authority is consistent with the search authority. During the search process, calculations are performed not only to determine whether the ciphertext matches the keyword in the trapdoor, but also to assist subsequent user ciphertext decryption by reducing computational complexity. Our scheme has been proven under the random oracle model to achieve the indistinguishability of the ciphertext and the trapdoor and to resist keyword-guessing attacks. Finally, the performance analysis and simulation of the proposed scheme are provided, and the results show that it performs with high efficiency. Full article