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Abstract To further raise the gas extraction efficiency of the tight sandstone, the liquid nitrogen (LN2) freezing-thawing cycles method can be employed to improve the permeability of the low-permeability reservoirs. Permeability is generally regarded as a macroscopic description of the pore structure and usually has functional relationship to pore structure properties. The permeability of the rock is closely related to the change of microscopic pore structure. The permeability of rock depends on how the subzero temperatures changed the microscopic pore structure of rock, but it has not yet been confirmed obviously. In this study, the nuclear magnetic resonance (NMR) technique was adopted to investigate the pore structure evolution law and permeability of the tight sandstone with different LN2 freezing-thawing cycles. The results demonstrate that the LN2 freezing-thawing cycles promotes pore development and micro-fracture connection, and enhances the pore connectivity. The proportion of meso-pores, macro-pores and micro-fractures in the sandstone samples increases significantly, which provides a channel for the sandstone gas flow and extraction. Total porosity and effective porosity of the samples present a trend of rapid increase as the number of LN2 freezing-thawing cycles increasing, while the residual porosity decreases as the number of LN2 freezing-thawing cycles increasing. Coates model, SDR model (mean T2 model) and PP model were used to calculate and evaluate the permeability of the samples subjected to different LN2 freezing-thawing cycles. Furthermore, PP model can provide a better permeability estimate than the classical Coates and SDR model.

Abstract Cardiopulmonary bypass (CPB) is often used in cardiothoracic surgery because its nonphysiological state causes pathophysiological changes in the body, causing multiorgan and multitissue damage to varying degrees. Postoperative cognitive dysfunction (POCD) is a common central nervous system complication after cardiac surgery. The etiology and mechanism of POCD are not clear. Neuroinflammation, brain mitochondrial dysfunction, cerebral embolism, ischemia, hypoxia, and other factors are related to the pathogenesis of POCD. There is a close relationship between CPB and POCD, as CPB can cause inflammation, hypoxia and reperfusion injury, and microemboli formation, all of which can trigger POCD. POCD increases medical costs, seriously affects patients' quality of life, and increases mortality. Currently, there is a lack of effective treatment methods for POCD. Commonly used methods include preoperative health management, reducing inflammation response during surgery, preventing microemboli formation, and implementing individualized rehabilitation programs after surgery. Strengthening preventive measures can minimize the occurrence of POCD and its adverse effects.

ObjectiveTo investigate the impact of different infusion media on the flow rate of infusion pumps. MethodsTen infusion pumps were randomly selected and tested for infusion rates using deionized water, saline solution, glucose solution, and parenteral nutrition solution. The infusion flow rate was set at 30 mL/h, and the testing methodology conformed to the standards for the calibration and quality control of syringe pumps and infusion pumps. ResultsFor infusion set A, the infusion rate was unaffected by the infusion media, remaining within the acceptable quality control standards. For infusion set B, when infused with deionized water, saline solution, and glucose solution, the infusion errors were within the quality control standards. However, when using parenteral nutrition solution as the infusion medium, the infusion error exceeded the acceptable quality control standards. ConclusionBoth the infusion set and the infusion medium can affect the flow rate of infusion pumps. It is crucial to calibrate the flow rate according to the specific infusion medium to reduce medical risks associated with infusion pumps during clinical use.

The fracture toughness of rocks is a critical fracturing parameter in geo-energy exploitation playing a significant role in fracture mechanics and hydraulic fracturing. The edge-notched disk bending (ENDB) specimens are employed to measure the entire range of mixed-mode I/III fracture toughness of Longmaxi shale. To theoretically interpret the fracture mechanisms, this research first introduces the detailed derivations of three established fracture criteria. By distinguishing the volumetric and distortional strain energy densities, an improved three-dimensional mean strain energy density (MSED) criterion is proposed. As the critical volumetric to distortional MSED ratio decreases, the transition from tension-dominated fracture to shear-dominated fracture is observed. Our results indicate that both peak load and applied energy increase significantly with the transition from pure mode I (i.e., tension) to pure mode III (i.e., torsion or tearing) since mode-III cracking happens in a twisted manner and mode-I cracking occurs in a coplanar manner. The macroscopic fracture signatures are consistent with those of triaxial hydraulic fracturing. The average ratio of pure mode-III fracture toughness to pure mode-I fracture toughness is 0.68, indicating that the obtained mode-III fracture resistance for a tension-based loading system is apparent rather than true. Compared to the three mainstream fracture criteria, the present fracture criterion exhibits greater competitiveness and can successfully evaluate and predict mixed-mode I/III fracture toughness of distinct materials and loading methods.

Endophytic fungi are a crucial microbial resource that can influence plant growth and development through their interactions with host plants. Gentiana straminea Maxim. is an important traditional Tibetan herb used to treat a range of diseases in the Qinghai-Tibetan region. However, the diversity and community structure of endophytic fungi in the species remain poorly understood. In this study, a total of 944 strains of endophytic fungi were isolated from the roots, stems, and leaves of G. straminea from four different altitudes. A total of 87 OTUs were identified through sequence alignment, comprising 6 classes, 15 orders, 25 families, and 44 genera. The colonization rate and diversity of endophytic fungi were affected by tissue type and altitude. With the exception of Xining, the endophytic fungi colonization rate of tissues was roots>leaves>stems. Moreover, the α-diversity of endophytic fungi among different tissues was leaves>stems>roots. Notably, the phylogenetic diversity index in leaves was significantly higher than that in roots. In addition, the colonization rate and diversity of endophytic fungi in leaves and stems demonstrated a decline with the increasing altitude. The β-diversity analysis revealed significant differences in the endophytic fungi of G. straminea at varying altitudes. In roots, geographical factors, such as latitude and longitude, were the primary drivers of variation, whereas environmental factors, including temperature and precipitation, had a greater influence on endophytes in leaves and stems. In addition, the results of the endophytic fungi association preference, linear discriminant analysis effect size (LEfSe), and co-network analysis indicated that these differential endophytic fungi may play a significant role in the authenticity and stress resistance of G. straminea.

Since ancient times, human beings have had the universal law of “living by water”, and the Yangtze River plays a crucial role in promoting socioeconomic development. Impervious surface area (ISA) is the key indicator of urban expansion and can effectively reflect human activities. Therefore, based on long time-series data of ISA, we used the combination of remote sensing, geographical information systems, and spatial statistics to quantify the ISA spatiotemporal evolution patterns at different distances from different sections of the Yangtze River from 1990 to 2020 and proposed the ISA layered development model along riverbanks. The results indicate that the expansion rate of most cities along the Yangtze River had variations and different temporal characteristics among cities of different levels. From the perspective along the Yangtze River, there are certain regularities in the ISA growth. Human dependence on rivers has been decreasing over time, but the closer to the river, the greater the ISA expansion intensity (EI). The fluctuation trends of expansion intensity within different distance ranges (10–50 km) are similar in different sections over time and approximate to “a short head S-shaped curve”, but the size of EI varies in different sections along the Yangtze River. Different sections along the Yangtze River show the pattern of “slow-fast-deceleration, with the highest intensity occurring around 2015”. In the process of urbanization, areas far away from rivers will eventually connect with areas close to rivers, and the regional spatial pattern differences will gradually weaken. Multiple regression analysis indicated that the economic, social, and geographical factors were strongly associated with spatiotemporal differences in ISA expansion. This study will deepen our understanding of human activity changes along the Yangtze River, which is of great significance for implementing the national major strategy of “to step up conservation of the Yangtze River and stop its over development” and achieving the sustainable development between humans and water.

The emotional variation can reflect shifts in mental and emotional states. It plays an important role in the field of intelligent education. Emotion recognition can be used as cues for teachers to evaluate the learning state, analyze learning motivation, interest, and efficiency. Although research on emotion recognition has been ongoing for a long time, there has been a restricted emphasis on analyzing the credibility of the recognized emotions. In this paper, the origin, development, and application of emotion recognition were introduced. Then, multiple signals captured from video that could reflect emotion changes were described in detail and their advantages and disadvantages were discussed. Moreover, a comprehensive summary of the pertinent applications and research endeavors of emotion recognition technology in the field of education was provided. Last, the trend of emotion recognition in the field of education was given.

Objective Exploring the relationship between sleep disorders and sarcopenia in terms of both sleep duration and sleep quality. Methods A survey was conducted on the elderly population who came to the main city and districts of Chongqing Municipality from March 2023 to August 2023 for medical checkups in a total of five community health centers.Sleep quality was assessed by the Pittsburgh sleep quality index(PSQI) scale.Sleep duration was categorized as short sleep(0.05).Logistic regression equations showed that the prevalence of sarcopenia in older women who slept longer than those with a normal sleep duration was 2.486 times higher when not adjusted for covariates.The prevalence of sarcopenia in older women who slept longer was 2.818 times that of those with normal sleep duration,after adjusting for age,body mass index,marital history,work status,education,hypertension,and diabetes mellitus.In contrast,there was no correlation between sleep duration and sarcopenia in older male subjects(P>0.05). Conclusion Elderly people who sleep longer are more likely to suffer from sarcopenia than those who sleep a normal amount of time,and this finding is more pronounced in women.

Facial expression recognition plays a crucial role in human-computer intelligent interaction. Due to the problem of missing facial information caused by face masks, the average accuracy of facial expression recognition algorithms in mask-obscured scenes is relatively low. At present, most deep learning-based facial expression recognition methods primarily focus on global facial features, thus they are less suitable for scenarios where facial expressions are obscured by masks. Therefore, this paper proposes a facial expression recognition method, TransformerKNN (TKNN), which integrates eyebrow and eye state information in mask-obscured scenes. The proposed method utilizes facial feature points in the eyebrow and eye regions to calculate various relative distances and angles, capturing the state information of eyebrows and eyes. Subsequently, the original face images with masks are used to train a Swin-transformer model, and the eyebrow and eye state information is used to train a k-Nearest Neighbor (KNN) model. These models are then fused at the decision layer to achieve automated emotion computation in situations when facial expressions are obscured by masks. The TKNN method offers a novel approach by leveraging both local and global facial features, thereby enhancing the performance of facial expression recognition in mask-obscured scenes. Experimental results demonstrate that the average accuracy of the TKNN method is 85.8% and 70.3%, respectively. This provides better support for facial expression recognition in scenarios when facial information is partially obscured.

Abstract Background Molecular subtyping is expected to enable precise treatment. However, reliable subtyping strategies for clinical application remains defective and controversial. Given the significance of tumor immune dysfunction and exclusion (TIDE), we aimed to develop a novel TIDE-based subtyping strategy to guide personalized immunotherapy in the bladder cancer (BC). Methods Transcriptome data of BC was used to evaluate the heterogeneity and the status of TIDE patterns. Subsequently, consensus clustering was applied to classify BC patients based on TIDE marker-genes. Patients’ clinicopathological, molecular features and signaling pathways of the different TIDE subtypes were well characterized. We also utilize the deconvolution algorithms to analyze the tumor microenvironment, and further explore the sensitivity and mechanisms of each subtype to immunotherapy. Furthermore, BC patient clinical information, real-world BC samples and urine samples were collected for the validation of our findings, which were used for RNA-seq analysis, H&E staining, immunohistochemistry and immunofluorescence staining, and enzyme-linked immunosorbent assay. Finally, we also explored the conservation of our novel TIDE subtypes in pan-cancers. Results We identified 69 TIDE biomarker genes and classified BC samples into three subtypes using consensus clustering. Subtype I showed the lowest TIDE status and malignancy with the best prognosis and highest sensitivity to immune checkpoint blockade (ICB) treatment, which was enriched of metabolic related signaling pathways. Subtype III represented the highest TIDE status and malignancy with the poorest prognosis and resistance to ICB treatment, resulting from its inhibitory immune microenvironment and T cell terminal exhaustion. Subtype II was in a transitional state with intermediate TIDE level, malignancy, and prognosis. We further confirmed the existence and characteristics of our novel TIDE subtypes using real-world BC samples and collected patient clinical data. This subtyping method was proved to be more efficient than previous known methods in identifying non-responders to immunotherapy. We also propose that combining our TIDE subtypes with known biomarkers can potentially improve the sensitivity and specificity of these biomarkers. Moreover, besides guiding ICB treatment, this classification approach can assist in selecting the frontline or recommended drugs. Finally, we confirmed that the TIDE subtypes are conserved across the pan-tumors. Conclusions Our novel TIDE-based subtyping method can serve as a powerful clinical tool for BC and pan-cancer patients, and potentially guiding personalized therapy decisions for selecting potential beneficiaries and excluding resistant patients of ICB therapy.

Objective Prostate hyperplasia and cancer are more prevalent in middle-aged and elderly men. Previous studies have linked both disorders to androgen receptors. Herein, efforts were made to identify factors associated with prostate cancer in patients ≥60 years, aiming to enhance their health management.Methods An analytical framework was established utilizing the “Prostate Cancer Early Warning Dataset” from the National Clinical Medical Science Data Center. Variables selection was conducted through LASSO regression, followed by multifactorial logistic stepwise regression to construct a predictive model.Results A total of 1,502 patients with BPH and 294 with combined PCa were hereby included. Multivariate regression delineated several independent predictors of PCa coexistence, including age (OR [95% CI]: 1.06 [1.04–1.09], p

A novel semi-organic combustion approach using orange and lemon juice as chelating agents is employed to synthesize the perovskite Sr0.8X0.2Co0.2Fe0.8O3-δ (x = La, Ce) cathode for IT-SOFCs. This approach has been found to exhibit lower toxicity compared to chemical routes and lower impurities compared to green routes. The structural analysis validated the successful synthesis of perovskite Sr0.8X0.2Co0.2Fe0.8O3-δ (La, Ce) cathode materials with no prominent secondary phase of impurities while surface morphology revealed a porous and well-connected network of particles. EDS confirmed the composition and thermo-gravimetric analysis showed weight losses related to the creation of vacancies. The functional groups were investigated through FTIR and the conductivity measurements revealed higher electrical conductivity for Sr0.8X0.2Co0.2Fe0.8O3-δ (x = La, Ce) synthesized with orange juice as a chelating agent with Sr0.8La0.2Co0.2Fe0.8O3-δ exhibiting slightly higher value compared to Sr0.8Ce0.2Co0.2Fe0.8O3-δ. The electrochemical performance showed the highest power density of 354 and 313 mW·cm−2 at 700 °C obtained for cells having Sr0.8X0.2Co0.2Fe0.8O3-δ (x = La, Ce) cathodes synthesized with orange juice which was attributed to better crystallinity and uniform lattice. This work shows that a novel semi-organic route is successfully employed to synthesize the perovskite cathode materials for IT-SOFCs.

ObjectiveTo select high-quality and cost-effective dural (spinal) membrane repair materials, in order to reduce the cost of consumables procurement, save medical insurance funds, and optimize hospital operation and management. MethodsTaking the BS06B disease group (spinal cord and spinal canal surgery without extremely severe or severe complications and comorbidities, mainly diagnosed as congenital tethered cord syndrome) as an example, a retrospective analysis was conducted on the relevant data of surgical treatment for congenital tethered cord syndrome conducted in our hospital from January 2021 to June 2023. Safety and efficacy indicators in clinical application (incidence of postoperative epidural hemorrhage, incidence of postoperative purulent cerebrospinal meningitis, incidence of cerebrospinal fluid leakage, surgical duration, and postoperative hospital stay) were compared. ResultsThere was no difference in safety and effectiveness between different brands of dura mater repair materials. Conclusion For the repair of small incisions in dura mater surgery, high-quality and cost-effective dura mater repair materials can be selected to reduce hospital costs and control expenses for the disease group.

In the freeze-thaw environments, the fracturing of bedding rock poses a significant threat to the stability of the projects in cold regions, leading to potential engineering accidents. In this paper, uniaxial compression and acoustic emission tests were carried out on parallel and vertical stratified sandstones after 0, 20, 40, and 60 freeze-thaw cycles. The mechanical properties of different stratified sandstones and the changes in acoustic emission characteristic parameters during rock deformation and failure were studied. The results show that with the intensification of freeze-thaw effects, both longitudinal wave velocities of the two sample groups gradually decrease, and the porosity increases gradually. The proportion of compressive strength decrease and strain increase of the parallel group of samples is greater than that of the vertical group, indicating a higher level of degradation in parallel group. The trend of acoustic emission ringing count evolution curve of the two groups of different stratified sandstones under freeze-thaw cycles is consistent and can be divided into three stages: a calm stage, a stepwise growth stage, and a sudden growth stage. Uniaxial failure modes of sandstones with different bedding directions are different. The change in acoustic emission b-values for parallel group samples presents an inverted “V” shape, while for vertical group samples, it shows a normal "V" shape. Based on the various characteristics of RA-AF values, it is suggested that the parallel stratified yellow sandstone primarily undergoes tensile failure, while the vertical stratified sandstone is mainly dominated by both tensile and shear failures in the untreated condition, and also mainly dominated by tensile failure after 60 freeze-thaw cycles. The research results provide a scientific basis for the safety assessment of geotechnical engineering in cold regions.

Abstract Although the acidic oxygen evolution reaction (OER) plays a crucial role in proton-exchange membrane water electrolysis (PEMWE) devices, challenges remain owing to the lack of efficient and acid-stable electrocatalysts. Herein, we present a low-iridium electrocatalyst in which tensile-strained iridium atoms are localized at manganese-oxide surface cation sites (TS-Ir/MnO2) for high and sustainable OER activity. In situ synchrotron characterizations reveal that the TS-Ir/MnO2 can trigger a continuous localized lattice oxygen-mediated (L-LOM) mechanism. In particular, the L-LOM process could substantially boost the adsorption and transformation of H2O molecules over the oxygen vacancies around the tensile-strained Ir sites and prevent further loss of lattice oxygen atoms in the inner MnO2 bulk to optimize the structural integrity of the catalyst. Importantly, the resultant PEMWE device fabricated using TS-Ir/MnO2 delivers a current density of 500 mA cm−2 and operates stably for 200 h.

Abstract Spintronic device is the fundamental platform for spin-related academic and practical studies. However, conventional techniques with energetic deposition or boorish transfer of ferromagnetic metal inevitably introduce uncontrollable damage and undesired contamination in various spin-transport-channel materials, leading to partially attenuated and widely distributed spintronic device performances. These issues will eventually confuse the conclusions of academic studies and limit the practical applications of spintronics. Here we propose a polymer-assistant strain-restricted transfer technique that allows perfectly transferring the pre-patterned ferromagnetic electrodes onto channel materials without any damage and change on the properties of magnetism, interface, and channel. This technique is found productive for pursuing superior-quality spintronic devices with high controllability and reproducibility. It can also apply to various-kind (organic, inorganic, organic-inorganic hybrid, or carbon-based) and diverse-morphology (smooth, rough, even discontinuous) channel materials. This technique can be very useful for reliable device construction and will facilitate the technological transition of spintronic study.

ObjectiveTo explore the effect of routine reusable pipeline and disposable pipeline on ventilator quality control results. Methods17 ventilators were randomly selected to conduct quality control using routine reusable pipeline and disposable pipeline respectively. Quality control data were recorded and then paired t-test method was used to analyze whether the difference between the two pipelines was significant or not. ResultsThere were no significant differences in respiratory rate, tidal volume and end airway pressure between the two types of pipes (P＞0.05). The airway peak pressure of routine reusable pipeline was significantly higher than disposable pipeline (P＜0.05), but the difference was very small, only about 0.2 mbar which would not affect the conclusion of quality control. ConclusionQuality control of ventilator is not affected by routine reusable pipeline and disposable pipeline, which can be replaced by each other.

Abstract Photocatalytic two-electron oxygen reduction to produce high-value hydrogen peroxide (H2O2) is gaining popularity as a promising avenue of research. However, structural evolution mechanisms of catalytically active sites in the entire photosynthetic H2O2 system remains unclear and seriously hinders the development of highly-active and stable H2O2 photocatalysts. Herein, we report a high-loading Ni single-atom photocatalyst for efficient H2O2 synthesis in pure water, achieving an apparent quantum yield of 10.9% at 420 nm and a solar-to-chemical conversion efficiency of 0.82%. Importantly, using in situ synchrotron X-ray absorption spectroscopy and Raman spectroscopy we directly observe that initial Ni-N3 sites dynamically transform into high-valent O1-Ni-N2 sites after O2 adsorption and further evolve to form a key *OOH intermediate before finally forming HOO-Ni-N2. Theoretical calculations and experiments further reveal that the evolution of the active sites structure reduces the formation energy barrier of *OOH and suppresses the O=O bond dissociation, leading to improved H2O2 production activity and selectivity.

Abstract Background Prostate cancer (PCA) is the fifth leading cause of cancer-related deaths worldwide, with limited treatment options in the advanced stages. The immunosuppressive tumor microenvironment (TME) of PCA results in lower sensitivity to immunotherapy. Although molecular subtyping is expected to offer important clues for precision treatment of PCA, there is currently a shortage of dependable and effective molecular typing methods available for clinical practice. Therefore, we aim to propose a novel stemness-based classification approach to guide personalized clinical treatments, including immunotherapy. Methods An integrative multi-omics analysis of PCA was performed to evaluate stemness-level heterogeneities. Unsupervised hierarchical clustering was used to classify PCAs based on stemness signature genes. To make stemness-based patient classification more clinically applicable, a stemness subtype predictor was jointly developed by using four PCA datasets and 76 machine learning algorithms. Results We identified stemness signatures of PCA comprising 18 signaling pathways, by which we classified PCA samples into three stemness subtypes via unsupervised hierarchical clustering: low stemness (LS), medium stemness (MS), and high stemness (HS) subtypes. HS patients are sensitive to androgen deprivation therapy, taxanes, and immunotherapy and have the highest stemness, malignancy, tumor mutation load (TMB) levels, worst prognosis, and immunosuppression. LS patients are sensitive to platinum-based chemotherapy but resistant to immunotherapy and have the lowest stemness, malignancy, and TMB levels, best prognosis, and the highest immune infiltration. MS patients represent an intermediate status of stemness, malignancy, and TMB levels with a moderate prognosis. We further demonstrated that these three stemness subtypes are conserved across pan-tumor. Additionally, the 9-gene stemness subtype predictor we developed has a comparable capability to 18 signaling pathways to make tumor diagnosis and to predict tumor recurrence, metastasis, progression, prognosis, and efficacy of different treatments. Conclusions The three stemness subtypes we identified have the potential to be a powerful tool for clinical tumor molecular classification in PCA and pan-cancer, and to guide the selection of immunotherapy or other sensitive treatments for tumor patients.

In recent years, the development of environmentally friendly, lead-free ferroelectric films with prominent electrostrictive effects have been a key area of focus due to their potential applications in micro-actuators, sensors, and transducers for advanced microelectromechanical systems (MEMS). This work investigated the enhanced electrostrictive effect in lead-free sodium bismuth titanate-based relaxor ferroelectric films. The films, composed of (Bi0.5Na0.5)0.8−xBaxSr0.2TiO3 (BNBST, x = 0.02, 0.06, and 0.11), with thickness around 1 μm, were prepared using a sol-gel method on Pt/TiO2/SiO2/Si substrates. By varying the Ba2+ content, the crystal structure, morphology, and electrical properties, including dielectric, ferroelectric, strain, and electromechanical performance, were investigated. The films exhibited a single pseudocubic structure without preferred orientation. A remarkable strain response (S > 0.24%) was obtained in the films (x = 0.02, 0.06) with the coexistence of nonergodic and ergodic relaxor phases. Further, in the x = 0.11 thick films with an ergodic relaxor state, an ultrahigh electrostrictive coefficient Q of 0.32 m4/C2 was achieved. These findings highlight the potential of BNBST films as high-performance, environmentally friendly electrostrictive films for advanced microelectromechanical systems (MEMS) and electronic devices.

Abstract The interfacial morphology of crystalline silicon/hydrogenated amorphous silicon (c-Si/a-Si:H) is a key success factor to approach the theoretical efficiency of Si-based solar cells, especially Si heterojunction technology. The unexpected crystalline silicon epitaxial growth and interfacial nanotwins formation remain a challenging issue for silicon heterojunction technology. Here, we design a hybrid interface by tuning pyramid apex-angle to improve c-Si/a-Si:H interfacial morphology in silicon solar cells. The pyramid apex-angle (slightly smaller than 70.53°) consists of hybrid (111)0.9/(011)0.1 c-Si planes, rather than pure (111) planes in conventional texture pyramid. Employing microsecond-long low-temperature (500 K) molecular dynamic simulations, the hybrid (111)/(011) plane prevents from both c-Si epitaxial growth and nanotwin formation. More importantly, given there is not any additional industrial preparation process, the hybrid c-Si plane could improve c-Si/a-Si:H interfacial morphology for a-Si passivated contacts technique, and wide-applied for all silicon-based solar cells as well.

Abstract Skeletal muscle makes up 30–40% of the total body mass. It is of great significance in maintaining digestion, inhaling and exhaling, sustaining body posture, exercising, protecting joints and many other aspects. Moreover, muscle is also an important metabolic organ that helps to maintain the balance of sugar and fat. Defective skeletal muscle function not only limits the daily activities of the elderly but also increases the risk of disability, hospitalization and death, placing a huge burden on society and the healthcare system. Sarcopenia is a progressive decline in muscle mass, muscle strength and muscle function with age caused by environmental and genetic factors, such as the abnormal regulation of protein post‐translational modifications (PTMs). To date, many studies have shown that numerous PTMs, such as phosphorylation, acetylation, ubiquitination, SUMOylation, glycosylation, glycation, methylation, S‐nitrosylation, carbonylation and S‐glutathionylation, are involved in the regulation of muscle health and diseases. This article systematically summarizes the post‐translational regulation of muscle growth and muscle atrophy and helps to understand the pathophysiology of muscle aging and develop effective strategies for diagnosing, preventing and treating sarcopenia.

Accidental falls pose a significant threat to the elderly population, and accurate fall detection from surveillance videos can significantly reduce the negative impact of falls. Although most fall detection algorithms based on video deep learning focus on training and detecting human posture or key points in pictures or videos, we have found that the human pose-based model and key points-based model can complement each other to improve fall detection accuracy. In this paper, we propose a preposed attention capture mechanism for images that will be fed into the training network, and a fall detection model based on this mechanism. We accomplish this by fusing the human dynamic key point information with the original human posture image. We first propose the concept of dynamic key points to account for incomplete pose key point information in the fall state. We then introduce an attention expectation that predicates the original attention mechanism of the depth model by automatically labeling dynamic key points. Finally, the depth model trained with human dynamic key points is used to correct the detection errors of the depth model with raw human pose images. Our experiments on the Fall Detection Dataset and the UP-Fall Detection Dataset demonstrate that our proposed fall detection algorithm can effectively improve the accuracy of fall detection and provide better support for elderly care.

Lead-free bismuth sodium titanate (Bi0.5Na0.5)TiO3 (BNT) and related solid solutions are potential piezoelectric materials for such applications as actuators and transducers if their excellent strain responses and piezoelectric properties can be optimized. In this work, a large strain response of 0.61% is achieved in lead-free (0.94-x%)(Bi0.5Na0.5)TiO3-0.06BaTiO3-x%NaNbO3 (x = 0 –6, BNT-6BT-xNN) ceramics with the composition of x = 3.5 in a pseudo-cubic structure. Coexistence of ferroelectric (FE) and relaxor (RE) domain structures is observed in all the unpoled ceramics and the enhanced strain response is believed to be related to the evolution of the ergodic relaxor (ER) and non-ergodic (NR) states thanks to the substitution of antiferroelectric NN. BNT-6BT-3.5NN is a critical composition near the FE/NR/ER phase boundary close to room temperature (RT) and its high strain response arises from a synergistic combination of a reversible electric-field-induced phase transition and an active domain switching in the mixed NR/ER state. This work provides new insights into the dynamic interplay between mesoscopic domains and macroscopic electrical properties in the BNT-based piezoceramics.

In order to realize the accurate and reliable fault diagnosis of hydraulic systems, a diagnostic model based on improved tuna swarm optimization (ITSO), optimized convolutional neural networks (CNNs), and bi-directional long short-term memory (BiLSTM) networks is proposed. Firstly, sensor selection is implemented using the random forest algorithm to select useful signals from six kinds of physical or virtual sensors including pressure, temperature, flow rate, vibration, motor power, and motor efficiency coefficient. After that, fused features are extracted by CNN, and then, BiLSTM is applied to learn the forward and backward information contained in the data. The ITSO algorithm is adopted to adaptively optimize the learning rate, regularization coefficient, and node number to obtain the optimal CNN-BiLSTM network. Improved Chebyshev chaotic mapping and the nonlinear reduction strategy are adopted to improve population initialization and individual position updating, further promoting the optimization effect of TSO. The experimental results show that the proposed method can automatically extract fusion features and effectively utilize multi-sensor information. The diagnostic accuracies of the plunger pump, cooler, throttle valve, and accumulator are 99.07%, 99.4%, 98.81%, and 98.51%, respectively. The diagnostic results of noisy data with 0 dB, 5 dB, and 10 dB signal-to-noise ratios (SNRs) show that the ITSO-CNN-BiLSTM model has good robustness to noise interference.

Recent works have illustrated that many facial privacy protection methods are effective in specific face recognition algorithms. However, the COVID-19 pandemic has promoted the rapid innovation of face recognition algorithms for face occlusion, especially for the face wearing a mask. It is tricky to avoid being tracked by artificial intelligence only through ordinary props because many facial feature extractors can determine the ID only through a tiny local feature. Therefore, the ubiquitous high-precision camera makes privacy protection worrying. In this paper, we establish an attack method directed against liveness detection. A mask printed with a textured pattern is proposed, which can resist the face extractor optimized for face occlusion. We focus on studying the attack efficiency in adversarial patches mapping from two-dimensional to three-dimensional space. Specifically, we investigate a projection network for the mask structure. It can convert the patches to fit perfectly on the mask. Even if it is deformed, rotated and the lighting changes, it will reduce the recognition ability of the face extractor. The experimental results show that the proposed method can integrate multiple types of face recognition algorithms without significantly reducing the training performance. If we combine it with the static protection method, people can prevent face data from being collected.

Abstract Histogram equalization (HE) is a classic and widely used image contrast enhancement algorithm for its good performance and high efficiency. However, over‐enhancement caused by high peak in the histogram affects the subjective quality of the image processed by HE to a large extent. In this paper, a detail weighted histogram equalization (DWHE) method is proposed based on a novel histogram modification (HM) model named partial statistic and global mapping (PSGM) to alleviate high peak and suppress over‐enhancement. Moreover, the authors implement a refined version of gamma correction (GC) named texture enhancement function (TEF) on high‐frequency images to reduce the noise amplification effect. At last, the authors propose a novel adaptively weighted pixel‐level image fusion method to further reduce the phenomenon of over‐enhancement and improve brightness distribution. Both subjective and quantitative evaluations are conducted on images containing a variety of scenes. Compared with several state‐of‐the‐art image enhancement methods, the proposed framework obtained generally the best performance in aspects of both subjective appearance and objective evaluation indices. Therefore, it is proved that the proposed methods can effectively alleviate the over‐enhancement, enrich image details, and efficiently improve the visual quality while preserving the brightness of the image.

Background: Sepsis is a serious condition with a high mortality rate, and septic patients often have organ dysfunction, low tissue perfusion and hypoxia, lactic acidosis, oliguria, or functional brain changes.Objective: To observe the number and the function of Vδ1T cells in peripheral blood of septic patients, to analyze the clinical significance of detecting Vδ1T cells, and to clarify the correlation of their presence with the prognosis of sepsis.Methods: The basic data of the septic patients were recorded at admission. The immunosuppressive function–related molecules on the surface of Vδ1T cells were detected, and the immunosuppressive function of Vδ1T cells was also evaluated.Results: Compared with the healthy controls, the proportion of Vδ1T cells in the blood of septic patients significantly decreased (P

Abstract As an implementation tool of data intensive scientific research methods, machine learning (ML) can effectively shorten the research and development (R&D) cycle of new materials by half or even more. ML shows great potential in the combination with other scientific research technologies, especially in the processing and classification of large amounts of material data from theoretical calculation and experimental characterization. It is very important to systematically understand the research ideas of material informatics to accelerate the exploration of new materials. Here, we provide a comprehensive introduction to the most commonly used ML modeling methods in material informatics with classic cases. Then, we review the latest progresses of prediction models, which focus on new processing–structure–properties–performance (PSPP) relationships in some popular material systems, such as perovskites, catalysts, alloys, two‐dimensional materials, and polymers. In addition, we summarize the recent pioneering researches in innovation of material research technology, such as inverse design, ML interatomic potentials, and microtopography characterization assistance, as new research directions of material informatics. Finally, we comprehensively provide the most significant challenges and outlooks related to the future innovation and development in the field of material informatics. This review provides a critical and concise appraisal for the applications of material informatics, and a systematic and coherent guidance for material scientists to choose modeling methods based on required materials and technologies.

BackgroundMost patients with high-grade serous ovarian cancer (HGSOC) experienced disease recurrence with cumulative chemoresistance, leading to treatment failure. However, few biomarkers are currently available in clinical practice that can accurately predict chemotherapy response. The tumor immune microenvironment is critical for cancer development, and its transcriptomic profile may be associated with treatment response and differential outcomes. The aim of this study was to develop a new predictive signature for chemotherapy in patients with HGSOC.MethodsTwo HGSOC single-cell RNA sequencing datasets from patients receiving chemotherapy were reinvestigated. The subtypes of endoplasmic reticulum stress-related XBP1+ B cells, invasive metastasis-related ACTB+ Tregs, and proinflammatory-related macrophage subtypes with good predictive power and associated with chemotherapy response were identified. These results were verified in an independent HGSOC bulk RNA-seq dataset for chemotherapy. Further validation in clinical cohorts used quantitative real-time PCR (qRT-PCR).ResultsBy combining cluster-specific genes for the aforementioned cell subtypes, we constructed a chemotherapy response prediction model containing 43 signature genes that achieved an area under the receiver operator curve (AUC) of 0.97 (p = 2.1e-07) for the GSE156699 cohort (88 samples). A huge improvement was achieved compared to existing prediction models with a maximum AUC of 0.74. In addition, its predictive capability was validated in multiple independent bulk RNA-seq datasets. The qRT-PCR results demonstrate that the expression of the six genes has the highest diagnostic value, consistent with the trend observed in the analysis of public data.ConclusionsThe developed chemotherapy response prediction model can be used as a valuable clinical decision tool to guide chemotherapy in HGSOC patients.

IntroductionRetinoic acid-induced 2 (RAI2) was initially related to cell differentiation and induced by retinoic acid. RAI2 has been identified as an emerging tumor suppressor in breast cancer and colorectal cancer.MethodsIn this study, we performed systematic analyses of RAI2 in breast cancer. Meta-analysis and Kaplan-Meier survival curves were applied to identify the survival prediction potential of RAI2. Moreover, the association between RAI2 expression and the abundance of six tumor-infiltrating immune cells was investigated by TIMER, including B cells, CD8+ T cells, CD4+ T cells, B cells, dendritic cells, neutrophils, and macrophages. The expression profiles of high and low RAI2 mRNA levels in GSE7390 were compared to identify differentially expressed genes (DEGs) and the biological function of these DEGs was analyzed by R software, which was further proved in GSE7390.ResultsOur results showed that the normal tissues had more RAI2 expression than breast cancer tissues. Patients with high RAI2 expression were related to a favorable prognosis and more immune infiltrates. A total of 209 DEGs and 182 DEGs were identified between the expression profiles of high and low RAI2 mRNA levels in the GSE7390 and GSE21653 databases, respectively. Furthermore, Gene Ontology (GO) enrichment indicated that these DEGs from two datasets were both mainly distributed in “biological processes” (BP), including “organelle fission” and “nuclear division”. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis demonstrated that these DEGs from two datasets were both significantly enriched in the “cell cycle”. Common hub genes between the DEGs in GSE7390 and GSE21653 were negatively associated with RAI2 expression, including CCNA2, MAD2L1, MELK, CDC20, and CCNB2.DiscussionsThese results above suggested that RAI2 might play a pivotal role in preventing the initiation and progression of breast cancer. The present study may contribute to understanding the molecular mechanisms of RAI2 and enriching biomarkers to predict patient prognosis in breast cancer.

Several biometric privacy-enhancing techniques have been appraised to protect face image privacy. However, a face privacy protection algorithm is usually designed for a specific face recognition algorithm. When the structure or threshold of the face recognition algorithm is fine-tuned, the protection algorithm may be invalid. It will cause the network bloated and make the image distortion target multiple FRAs through the existing technology simultaneously. To address this problem, a fusion technology is developed to cope with the changeable face recognition algorithms via an image perturbation method. The image perturbation is performed by using a GAN-improved algorithm including generator, nozzles and validator, referred to as the Adversarial Fusion algorithm. A nozzle structure is proposed to replace the discriminator. Paralleling multiple face recognition algorithms on the nozzle can improve the compatibility of the generated image. Next, a validator is added to the training network, which takes part in the inverse back coupling of the generator. This component can make the generated graphics have no impact on human vision. Furthermore, the group hunting theory is quoted to make the network stable and up to 4.8 times faster than other models in training. The experimental results show that the Adversarial Fusion algorithm can not only change the image feature distribution by over 42% but also deal with at least 5 commercial face recognition algorithms at the same time.

With the recent development of non-contact physiological signal detection methods based on videos, it is possible to obtain the physiological parameters through the ordinary video only, such as heart rate and its variability of an individual. Therefore, personal physiological information may be leaked unknowingly with the spread of videos, which may cause privacy or security problems. In this paper a new method is proposed, which can shield physiological information in the video without reducing the video quality significantly. Firstly, the principle of the most widely used physiological signal detection algorithm: remote photoplethysmography (rPPG) was analyzed. Then the region of interest (ROI) of face contain physiological information with high signal to noise ratio was selected. Two physiological information forgery operation: single-channel periodic noise addition with blur filtering and brightness fine-tuning are conducted on the ROIs. Finally, the processed ROI images are merged into video frames to obtain the processed video. Experiments were performed on the VIPL-HR video dataset. The interference efficiencies of the proposed method on two mainly used rPPG methods: Independent Component Analysis (ICA) and Chrominance-based Method (CHROM) are 82.9 % and 84.6 % respectively, which demonstrated the effectiveness of the proposed method.

BackgroundOsteosarcoma is the most common primary malignant bone tumor. The existing treatment regimens remained essentially unchanged over the past 30 years; hence the prognosis has plateaued at a poor level. Precise and personalized therapy is yet to be exploited.MethodsOne discovery cohort (n=98) and two validation cohorts (n=53 & n=48) were collected from public data sources. We performed a non-negative matrix factorization (NMF) method on the discovery cohort to stratify osteosarcoma. Survival analysis and transcriptomic profiling characterized each subtype. Then, a drug target was screened based on subtypes’ features and hazard ratios. We also used specific siRNAs and added a cholesterol pathway inhibitor to osteosarcoma cell lines (U2OS and Saos-2) to verify the target. Moreover, PermFIT and ProMS, two support vector machine (SVM) tools, and the least absolute shrinkage and selection operator (LASSO) method, were employed to establish predictive models.ResultsWe herein divided osteosarcoma patients into four subtypes (S-I ~ S-IV). Patients of S- I were found probable to live longer. S-II was characterized by the highest immune infiltration. Cancer cells proliferated most in S-III. Notably, S-IV held the most unfavorable outcome and active cholesterol metabolism. SQLE, a rate-limiting enzyme for cholesterol biosynthesis, was identified as a potential drug target for S-IV patients. This finding was further validated in two external independent osteosarcoma cohorts. The function of SQLE to promote proliferation and migration was confirmed by cell phenotypic assays after the specific gene knockdown or addition of terbinafine, an inhibitor of SQLE. We further employed two machine learning tools based on SVM algorithms to develop a subtype diagnostic model and used the LASSO method to establish a 4-gene model for predicting prognosis. These two models were also verified in a validation cohort.ConclusionThe molecular classification enhanced our understanding of osteosarcoma; the novel predicting models served as robust prognostic biomarkers; the therapeutic target SQLE opened a new way for treatment. Our results served as valuable hints for future biological studies and clinical trials of osteosarcoma.

Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) bring significant benefits to non-small cell lung cancer patients with EGFR mutations, which represent a breakthrough in lung cancer therapy. However, patients will ultimately develop the acquired resistance to the first- or second-generation EGFR-TKIs after a period of treatment, and EGFR T790M mutation is the most common resistant mechanism. The third-generation EGFR-TKIs target T790M mutation and show potent anti-tumor efficacy, especially in central neural system response. Unfortunately, patients inevitably get resistant to the third-generation EGFR-TKIs due to various mechanisms, which can be mainly divided into EGFR-dependent and -independent ones. EGFR-dependent mechanism refers to manifold EGFR mutations while EGFR-independent mechanisms include bypass signal activation, histologic transformation and so on. To precisely address this issue and improve clinical outcomes, various other therapies (e.g. chemotherapy, radiotherapy, etc.) in combination with the third-generation EGFR-TKIs are designed. However, the current results of combination therapies are insufficient and ambiguous, which remain further exploration. Herein, we provide an updated landscape of the third-generation EGFR-TKIs and elaborate on the complex resistant mechanisms. Notably, we summarize the combination therapies with third-generation EGFR-TKIs and discuss their limitations and future perspective, aiming at providing insights to clinicians from bench to bedside.

BackgroundTo investigate the clinical value of ultrasound (US)-guided intervention for frozen shoulder (FS) in the frozen stage.MethodsThis study included 40 patients who had primary FS in the frozen stage and were evaluated by US. These 40 patients have all received conservative treatment elsewhere, and no satisfactory results have been achieved, with no improvement in active and passive movement angles, and no improvement in scores within 3 months. Therefore, their previous treatment was set as comparison. All patients underwent US-guided shoulder joint capsule distension by injection of sterilized water. Of these participants, 22 patients with scapulohumeral periarthritis received a compound betamethasone injection, and 14 patients with thickened coracohumeral ligaments (CHLs) underwent acupotomy lysis, and the remaining 4 patients had no extra treatments. The Constant-Murley score (CMS) was evaluated before and after the operation and analysed for each patient.ResultsBefore treatment, the indices for the thickening of the subaxillary joint capsule, subacromial bursa (with or without effusion), long head of the biceps brachii tendon (LHBBT) and CHL were 40, 22, 16 and 14, respectively. After treatment, all the indices were significantly decreased (all P

Abstract Defects in the DNA damage response (DDR) can lead to genome instability, producing mutations or aberrations that promote the development and progression of cancer. But it also confers such cells vulnerable to cell death when they inhibit DNA damage repair. Poly (ADP-ribose) polymerase (PARP) plays a central role in many cellular processes, including DNA repair, replication, and transcription. PARP induces the occurrence of poly (ADP-ribosylation) (PARylation) when DNA single strand breaks (SSB) occur. PARP and various proteins can interact directly or indirectly through PARylation to regulate DNA repair. Inhibitors that directly target PARP have been found to block the SSB repair pathway, triggering homologous recombination deficiency (HRD) cancers to form synthetic lethal concepts that represent an anticancer strategy. It has therefore been investigated in many cancer types for more effective anti-cancer strategies, including gastric cancer (GC). This review describes the antitumor mechanisms of PARP inhibitors (PARPis), and the preclinical and clinical progress of PARPis as monotherapy and combination therapy in GC.

Breast cancer has overtaken lung cancer as the most frequently diagnosed cancer type and is the leading cause of death for women worldwide. It has been demonstrated in published studies that long non-coding RNAs (lncRNAs) involved in genomic stability are closely associated with the progression of breast cancer, and remarkably, genomic stability has been shown to predict the response to immune checkpoint inhibitors (ICIs) in cancer therapy, especially colorectal cancer. Therefore, it is of interest to explore somatic mutator-derived lncRNAs in predicting the prognosis and ICI efficacy in breast cancer patients. In this study, the lncRNA expression data and somatic mutation data of breast cancer patients from The Cancer Genome Atlas (TCGA) were downloaded and analyzed thoroughly. Univariate and multivariate Cox proportional hazards analyses were used to generate the genomic instability-related lncRNAs in a training set, which was subsequently used to analyze a testing set and combination of the two sets. The qRT-PCR was conducted in both normal mammary and breast cancer cell lines. Furthermore, the Kaplan–Meier and receiver operating characteristic (ROC) curves were applied to validate the predictive effect in the three sets. Finally, the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to evaluate the association between genomic instability-related lncRNAs and immune checkpoints. As a result, a six-genomic instability-related lncRNA signature (U62317.4, MAPT-AS1, AC115837.2, EGOT, SEMA3B-AS1, and HOTAIR) was identified as the independent prognostic risk model for breast cancer patients. Compared with the normal mammary cells, the qRT-PCR showed that HOTAIR was upregulated while MAPT-AS1, EGOT, and SEMA3B-AS1 were downregulated in breast cancer cells. The areas under the ROC curves at 3 and 5 years were 0.711 and 0.723, respectively. Moreover, the patients classified in the high-risk group by the prognostic model had abundant negative immune checkpoint molecules. In summary, this study suggested that the prognostic model comprising six genomic instability-related lncRNAs may provide survival prediction. It is necessary to identify patients who are suitable for ICIs to avoid severe immune-related adverse effects, especially autoimmune diseases. This model may predict the ICI efficacy, facilitating the identification of patients who may benefit from ICIs.

Most patients with clear cell renal cell carcinoma (ccRCC) have an impaired response to immune checkpoint blockade (ICB) therapy. Few biomarkers can predict responsiveness, and there is insufficient evidence to extend them to ccRCC clinical use. To explore subtypes and signatures of immunocytes with good predictive performance for ICB outcomes in the ccRCC context, we reanalyzed two ccRCC single-cell RNA sequencing (scRNA-seq) datasets from patients receiving ICB treatment. A subtype of proliferative CD4+ T cells and regulatory T cells and a subtype of antigen-presenting monocytes that have good predictive capability and are correlated with ICB outcomes were identified. These findings were corroborated in independent ccRCC ICB pretreatment bulk RNA-seq datasets. By incorporating the cluster-specific marker genes of these three immunocyte subtypes, we developed a prediction model, which reached an AUC of 93% for the CheckMate cohort (172 samples). Our study shows that the ICB response prediction model can serve as a valuable clinical decision-making tool for guiding ICB treatment of ccRCC patients.

BackgroundThis is a pilot study of radiomics based on 68Ga-NOTA-PRGD2 [NOTA-PEG4-E[c(RGDfK)]2)] and 18F-FDG PET/CT to (i) evaluate the diagnostic efficacy of radiomics features of 68Ga-NOTA-PRGD2 PET in the differential diagnosis of benign and malignant pulmonary space-occupying lesions and (ii) compare the diagnostic efficacy of multi-modality and multi-probe images.MethodsWe utilized a dataset of 48 patients who participated in 68Ga-NOTA-PRGD2 PET/CT and 18F-FDG PET/CT clinical trials to extract image features and evaluate their diagnostic efficacy in the differentiation of benign and malignant lesions by the Mann-Whitney U test. After feature selection with sequential forward selection, random forest models were developed with tenfold cross-validation. The diagnostic performance of models based on different image features was visualized by receiver operating characteristic (ROC) curves and compared by permutation tests.ResultsFourteen of the 68Ga-NOTA-PRGD2 PET features between benign and malignant pulmonary space-occupying lesions had significant differences (P

A major challenge of spintronics is achieving magnetic field free electrical control of magnetisation. Here, Xie et al. achieve perpendicular magnetisation switching in a CoPt alloy, breaking inversion symmetry by varying the composition of the alloy in the growth direction.

Ultrafine Polyvinyl alcohol (PVA) fibers have an outstanding potential in various applications, especially in absorbing fields. In this manuscript, an electrostatic-field-assisted centrifugal spinning system was designed to improve the production efficiency of ultrafine PVA fibers from PVA aqueous solution for NH3 adsorption. It was established that the fiber production efficiency using this self-designed system could be about 1000 times higher over traditional electrospinning system. The produced PVA fibers establish high morphology homogeneity. The impact of processing variables of the constructed spinning system including rotation speed, needle size, liquid feeding rate, and voltage on fiber morphology and diameter was systematically investigated by SEM studies. To acquire homogeneous ultrafine PVA fiber membranes, the orthogonal experiment was also conducted to optimize the spinning process parameters. The impact weight of different studied parameters on the spinning performance was thus provided. The experimental results showed that the morphology of micro/nano-fibers can be well controlled by adjusting the spinning process parameters. Ultrafine PVA fibers with the diameter of 2.55 μm were successfully obtained applying the parameters, including rotation speed (6500 rpm), needle size (0.51 mm), feeding rate (3000 mL h−1), and voltage (20 kV). Furthermore, the obtained ultrafine PVA fiber mat was demonstrated to be capable of selectively adsorbing NH3 gas relative to CO2, thus making it promising for NH3 storage and other environmental purification applications.

Nanodelivery systems combining photothermal therapy (PTT) and chemotherapy (CT), have been widely used to improve the efficacy and biosafety of chemotherapeutic agents in cancer. In this work, we constructed a self-assembled nanodelivery system, formed by the assembling of photosensitizer (IR820), rapamycin (RAPA), and curcumin (CUR) into IR820-RAPA/CUR NPs, to realize photothermal therapy and chemotherapy for breast cancer. The IR820-RAPA/CUR NPs displayed a regular sphere, with a narrow particle size distribution, a high drug loading capacity, and good stability and pH response. Compared with free RAPA or free CUR, the nanoparticles showed a superior inhibitory effect on 4T1 cells in vitro. The IR820-RAPA/CUR NP treatment displayed an enhanced inhibitory effect on tumor growth in 4T1 tumor-bearing mice, compared to free drugs in vivo. In addition, PTT could provide mild hyperthermia (46.0 °C) for 4T1 tumor-bearing mice, and basically achieve tumor ablation, which is beneficial to improving the efficacy of chemotherapeutic drugs and avoiding damage to the surrounding normal tissue. The self-assembled nanodelivery system provides a promising strategy for coordinating photothermal therapy and chemotherapy to treat breast cancer.

The effect of epitaxial strain on the electrical properties of ferroelectric films has been widely investigated. However, this kind of strain is generally attributed to the substrate clamping constraints and is easily relaxed when the thickness of films is over 100 nm. In this work, a vertically epitaxial strain was introduced into lead-free piezoelectric K0.5Na0.5NbO3 films to improve the electrical properties of ferroelectric films. Two-phase, vertically epitaxial composite KNN-ZnO thin films were grown on the (001) STO substrate using a pulsed laser deposition (PLD) method. The highly (001) preferentially oriented KNN phase and (112¯ 0)-oriented ZnO phase were orderly arranged. Two types of morphologies of “square-like” and “stripe-looking” grains were observed in the surface image. An asymmetric “square” out-of-plane phase hysteresis loop and a “butterfly” displacement loop were exhibited in the KNN phase, whereas the ZnO phase showed a closed phase hysteresis loop and a slim displacement-voltage loop. Two different kinds of polarization behaviors for domains were also observed under applied electric fields, in which the domain of the KNN phase is easily switched to the opposite state, whereas the ZnO phase keeps a stable domain state when applying a DC bias of ±50 V. the vertically epitaxial growth of the KNN-ZnO composited films in this work provides a new way to fabricate complex nanoscale materials.

The (001) plate-like BaTiO3 piezoelectric micromaterials are synthesized by topochemical microcrystal conversion technique. BaTiO3 plates with a length of 2~10 μm and thickness of 0.5~1.3 μm are obtained. The dependence of morphology on synthesis conditions is discussed in detail. The crystal symmetry and multiscale domain structures of BaTiO3 plates are systematically investigated by various characterizations. X-ray diffraction (XRD) and Raman spectra analyses demonstrate the tetragonal symmetry of the (001) oriented BaTiO3 plates at room temperature. The domain configurations of the micron BaTiO3 are investigated with a polarized light microscope (PLM) and piezoresponse force microscopy (PFM). The single-crystal-like quality and uniformity are supported by PLM observations. More importantly, the classical 90° banded ferroelectric domains of ~125 nm width are observed for the first time in such BaTiO3 plates. The domain features in the mesoscale BaTiO3 plate are discussed and compared with its bulk counterparts. The results may provide insights into understanding and designing the mesoscale BaTiO3 functional materials.

Aiming at the efficiency of cloud computing ciphertext retrieval scheme,a method of ciphertext retrieval in mobile edge computing based on block segmentations was proposed.Firstly,the edge server was introduced to calculate the document similarity score,thereby the computational cost of cloud server was reduced and the processing efficiency of cloud server was improved.Secondly,most keywords that are not related to the query were filtered out by a method of block segmentations based on the MRSE scheme,thereby the efficiency of calculating the document similarity score was improved.Theoretical analysis and experimental results show that the solution is safe under the known background threat model.Compared with the existing scheme,the proposed scheme has the same security and higher retrieval efficiency.

Background Although photodynamic therapy (PDT) has emerged as a potential alternative to conventional chemotherapy, the low reactive oxygen species (ROS) yield of the photosensitizer such as TiO2 nanoparticles has limited its application. In addition, it is difficult to achieve effective tumor treatment with a single tumor therapy. Methods We used TiOx nanocomposite (YSA‐PEG‐TiOX) instead of TiO2 as a photosensitizer to solve the problem of insufficient ROS generation in PDT. Benefiting from the desired mesoporous structure of TiOx, Cantharidin (CTD), one of the active components of mylabris, is loaded into TiOx for targeted combination of chemotherapy and PDT. The cellular uptake in human non‐small cell lung carcinoma cell line (A549) and human normal breast cell line (MCF 10A) was evaluated by confocal microscopy. in vitro cytotoxicity was evaluated using Cell Counting Kit‐8 assay. The ROS was detected via a chemical probe DCFH‐DA and the photodynamic treatment effect of YSA‐PEG‐TiOx was further evaluated by a living‐dead staining. The cell apoptosis was detected by the flow cytometry. Results Our findings showed that the modification of YSA peptide improved the cytotoxicity of YSA‐PEG‐TiOX/CTD to EphA2 overexpressing A549 non‐small cell lung cancer (NSCLC) than non‐YSA modified counterparts. In addition, TiOx generated adequate ROS under X‐ray irradiation to further kill cancer cells. Flow analysis results also proved the superiority of this combined treatment. Conclusions YSA‐PEG‐TiOX nanoparticles could significantly increase ROS production under X‐ray exposure and provide a new drug delivery nanocarrier for CTD in combination with PDT to achieve effective NSCLC treatment.

Among Aurivillius-phase ferroelectric ceramics, CaBi2Nb2O9 is considered as the best candidate with potential applications in ultrahigh-temperature piezoelectric devices due to the highest Tc (∼940 °C). This paper reports that BiMn co-substitution at A and B sites gives rise to dramatic enchantments in ferroelectricity, piezoelectricity, and electrical resistivity of CaBi2Nb2O9 ceramics. The optimum composition (Ca0.97Bi2.03Nb1.99Mn0.01O9) with a Tc of 953 ± 3°C shows a high ferroelectric remnant polarization (Pr), field-induced strain (S33), piezoelectric activity d33 and $d_{33}^\ast $ with values of ∼11.1 µC/cm2, 4.9 × 10−4, 20.8 and 26.1 pC/N, respectively, which are about two to three times those of CaBi2Nb2O9.

We present a variational autoencoder (VAE) learning framework with introspective training for conditional image synthesis, and explore conditional capsule encoder by class-wise mask label insertion for this framework. Our model only consists of encoder (E), generator (G) and classifier (C), where E and G can be adversarially optimized, and C helps to boost conditional generation, improve authenticity and provide generation measures for E and G. Discriminator is not necessary in our framework and its absence makes our model more concise with fewer artifacts and pattern collapse problems. To compensate for the blurry weakness of VAE-like models, feature matching is introduced into loss functions by means of C to offer more reasonable measures between real and synthesized images. Moreover, in consideration of the key role of E in autoencoders as well as the interesting characteristics of capsule structure, conditional capsule encoder is preliminary explored in the image synthesis model. Class labels participate conditional encoding by masking high-level capsules of other categories, and capsule loss for the encoder is added to facilitate conditional synthesis. Experiments on MNIST and Fashion-MNIST data sets show that our model achieves real conditional synthesis performances with better diversity and fewer artifacts. And conditional capsule encoder also reveals interesting synthesis effects.

The real visual attention areas of students during the learning process are vital data. They represent the students' visual concentration and provide strong support for the analysis of learning effects. It is necessary to use professional equipment to collect the visual attention areas of students on a screen but this equipment is expensive, so it cannot be solely depended upon. A binocular camera can directly obtain the depth information under static conditions; thus, detected pupil and iris sizes do not change as the user-to-screen distance changes. Robust pupil detection is an important prerequisite for gaze detection in a real-world setting. Hence, an accurate algorithm to calculate the position of pupils and the size of irises under natural light is proposed in this paper. It is based on the positive and negative oblique projection of relative linear density. The MPIIGaze dataset was used to test the algorithm, and the experimental results show that the algorithm is resistant to changes in illumination and the presence of glasses. Moreover, compared with a system based on a monocular camera, the error in the distance between label points and gaze location is decreased by 5 pixels and dispersion is decreased by 3 pixels. Finally, the line of sight is concentrated and the dispersion is low. With the `user-screen' distance between 60cm and 80cm, the accuracy can reach up to 1.5° to 2.2°.