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Abstract Near-infrared (NIR)-II fluorescence imaging-guided photodynamic therapy (PDT) has shown great potential for precise diagnosis and treatment of tumors in deep tissues; however, its performance is severely limited by the undesired aggregation of photosensitizers and the competitive relationship between fluorescence emission and reactive oxygen species (ROS) generation. Herein, we report an example of an anionic pentamethine cyanine (C5T) photosensitizer for high-performance NIR-II fluorescence imaging-guided PDT. Through the counterion engineering approach, a triphenylphosphine cation (Pco) modified with oligoethylene glycol chain is synthesized and adopted as the counterion of C5T, which can effectively suppress the excessive and disordered aggregation of the resulting C5T-Pco by optimizing the dye amphipathicity and enhancing the cyanine-counterion interactions. Dynamic tuning of fluorescence characteristics and ROS generation is achieved at the aggregate level, resulting in an impressive type I ROS generation under 760 nm light irradiation, accompanied by efficient NIR-II fluorescence emission excited at 808 nm. As a result, excitation wavelength selective NIR-II fluorescence imaging-guided PDT has been successfully demonstrated for tumor diagnosis and therapeutics of female mice.

BackgroundCardiovascular disease(CVD) remains a significant global challenge. Asthma, which is characterized by airway hyperresponsiveness and reversible and limited airflow, plays an important role in cardiovascular diseases. This study aimed to investigate the association between asthma and CVD.MethodsThis cross-sectional study included demographic, laboratory, and questionnaire data from the National Health and Nutrition Examination Survey (NHANES) 1999–2018. CVD included stroke, congestive heart failure, coronary heart disease, and angina. Multiple logistic regression models were used to detect the association between asthma and the prevalence of CVD, adjusting for age, gender, race, education level, body mass index, ratio of family income to poverty, smoking exposure, drinking exposure, diabetes history, hypertension history, chronic obstructive pulmonary disease (COPD) history, and chronic kidney disease (CKD) history. A subgroup analysis was performed to investigate the association between asthma and CVD in different populations.ResultsIn total, 16,807 participants were included in this study, including 2,446 who reported having asthma. Compared with participants without asthma, the prevalence of stroke in those with asthma was increased by 1.607 times; the prevalence of congestive heart failure was increased by 1.911 times. Asthma significantly increased the prevalence of stroke among participants aged 18–44 years old, with a BMI 18.50–29.99 kg/m2, with low education levels, and with a PIR

Abstract Two years following the extreme rainfall event in Henan Province in July 2021, North China was struck by another significant rainfall episode in late July and early August 2023 (the “23.7” event). This recent event, surpassed only by the August 1963 deluge in Henan province, precipitated extensive disasters across the Beijing‐Tianjin‐Hebei region (BTH) over the North China Plain. Understanding the mechanisms underlying such extreme precipitation events, including moisture sources and atmospheric circulation patterns, in the context of synoptic‐scale systems is crucial for accurate predictions and effective disaster mitigation in the future. To achieve this, this study utilized a vertically integrated water vapor transport method and a Water Accounting model to investigate the moisture sources and pathways of the “23.7” event. A systematic analysis of circulation patterns was also conducted based on the ERA5 reanalysis. The results showed that the western North Pacific and Indian Ocean contributed 38.1% and 18.6%, respectively, to the extreme rainfall over the BTH region. Additionally, terrestrial moisture sources contributed 16.59%, playing a significant role in the event. The stable and moisture‐laden air was transported to the BTH due to the influence of binary tropical cyclones “Doksuri” and “Khanun,” as well as the western Pacific subtropical high‐pressure system. Convergence and updraft dynamics trigger convective processes modulated by vortices and topography. The findings of this study help to build a deeper understanding of the formation processes and mechanisms behind such heavy rainfall, which provides insights for model predictions of similar high‐impact low‐frequency extreme rainfall events.

Background: The ketogenic diet (KD) is widely used for weight loss in obese individuals; however, its potential impact on hypertension risk remains uncertain. Methods: We used cross-sectional data from the 2007–2018 to National Health and Nutrition Examination Survey (NHANES) to investigate the association between the dietary ketogenic ratio (DKR) and hypertension prevalence. Dietary intake information was obtained through a comprehensive 24-h dietary recall interview. The DKR values were computed using a specialized formula. Multiple logistic regression analysis was employed to examine this association, whereas nonlinear relationships were assessed using restricted cubic splines. Inflection points were determined using two-piecewise linear regression analysis. Subgroup analyses based on age were also performed. Results: In a fully adjusted multivariate logistic regression model accounting for confounding variables, DKR was significantly associated with hypertension (OR, 1.24; 95 % CI: 1.00–1.53; P = 0.045). Moreover, individuals in the highest quartile of DKR exhibited a significantly elevated risk of hypertension compared with those in the lowest quartile (OR, 1.15; 95 % CI: 1.07–1.24; P

Multi-motion visual odometry (MVO) based on geometric features is widely used. However, the accuracy and efficiency of the MVO algorithm are limited to instance-level segmentation of landmarks with inconsistent motion. To address this challenge, this study proposes a two-stage landmark instance segmentation network, GMVO, based on geometric features. First, a supervised method is used to classify static trajectories for camera odometer calculations and dynamic trajectories for rigid body motion estimation. Next, the dynamic trajectories are clustered and the instance-level segmentation of their motion consistency is restricted within them. Finally, bundle adjustment is applied to optimize the observation of landmarks within a sliding window and complete the MVO calculation. Extensive experiments were conducted on the OMD and KITTI data sets to evaluate the performance of the GMVO algorithm in terms of its classification performance, camera odometer accuracy, and real-time performance. The related results were visualized, which verified that the GMVO algorithm is more effective than and superior to state-of-the-art approaches.

Background: Hypertension is often accompanied by anxiety and sleep disorders, which further complicate the disease. This study aimed to evaluate the feasibility and effectiveness of transcutaneous electrical acupoint stimulation (TEAS) in patients with hypertension and anxiety or sleep disorders. Methods: Eligible participants were randomly assigned to the 10 Hz TEAS, 2 Hz TEAS, or routine treatment groups in a 1:1:1 ratio. Participants continued their routine treatment during the trial, while those in the two TEAS groups received 12 sessions of 30-min TEAS treatment with different stimulation frequencies. The feasibility parameters were successful screening probability, enrollment rate, and dropout rate. The primary outcome was the change in office systolic blood pressure from baseline to week four. Secondary outcomes included changes in office diastolic blood pressure, heart rate, Pittsburgh Sleep Quality Index score, and Generalized Anxiety Disorder 7-item scale score from baseline to week four. Results: Eighty-eight participants (age 58.0 [51.0, 63.0] years; 49 women) were randomized. The successful screening probability was 56.1 %, the enrollment rate was 3.1 participants per week, and the dropout rate was 14.8 %. The change in office systolic blood pressure from baseline to week four was −2.8 ± 13.6 mm Hg, −6.4 ± 10.0 mm Hg, and −7.2 ± 11.2 mm Hg, respectively, in the 10 Hz TEAS, 2 Hz TEAS, and routine treatment groups (P = 0.332). No significant differences were noted, except for a change in the Pittsburgh Sleep Quality Index score (P = 0.014). Both 10 Hz (P = 0.024) and 2 Hz TEAS (P = 0.039) significantly improved sleep quality compared to routine treatment. Conclusions: In patients with hypertension having anxiety or sleep disorders, this study did not demonstrate the superiority of TEAS over routine treatment but did show an improvement in sleep quality and a downward trend in diastolic blood pressure. Therefore, a largescale trial is warranted.

Incorporating authentic tactile interactions into virtual environments presents a notable challenge for the emerging development of soft robotic metamaterials. In this study, a vision‐based approach is introduced to learning proprioceptive interactions by simultaneously reconstructing the shape and touch of a soft robotic metamaterial (SRM) during physical engagements. The SRM design is optimized to the size of a finger with enhanced adaptability in 3D interactions while incorporating a see‐through viewing field inside, which can be visually captured by a miniature camera underneath to provide a rich set of image features for touch digitization. Employing constrained geometric optimization, the proprioceptive process with aggregated multi‐handles is modeled. This approach facilitates real‐time, precise, and realistic estimations of the finger's mesh deformation within a virtual environment. Herein, a data‐driven learning model is also proposed to estimate touch positions, achieving reliable results with impressive R2 scores of 0.9681, 0.9415, and 0.9541 along the x, y, and z axes. Furthermore, the robust performance of the proposed methods in touch‐based human–cybernetic interfaces and human–robot collaborative grasping is demonstrated. In this study, the door is opened to future applications in touch‐based digital twin interactions through vision‐based soft proprioception.

Abstract Background Foot‐and‐mouth disease virus (FMDV) is an important pathogen of the MicroRNA virus family. Infection of livestock can cause physical weakness, weight loss, reduced milk production, and a significant reduction in productivity for an extended period. It also causes a high mortality rate in young animals, seriously affecting livestock production. The host range of FMDV is mainly limited to cloven‐hoofed animals such as cattle and sheep, while odd‐toed ungulates such as horses and donkeys have natural resistance to FMDV. The mechanism underlying this resistance in odd‐toed ungulates remains unclear. Objective This study aimed to analyze the differences between FMDV‐infected cattle and horses to provide valuable insights into the host‐FMDV interaction mechanisms, thereby contributing to the control of foot‐and‐mouth disease and promoting the development of the livestock industry. Methods We observed the distribution of integrins, which help FMDV enter host cells, in the nasopharyngeal tissues of cattle and horses using immunohistochemistry. Then, we employed high‐throughput RNA sequencing (RNA‐Seq) to study the changes in host gene expression in the nasopharyngeal epithelial tissues of cattle and horses after FMDV infection. We performed enrichment analysis of GO and KEGG pathways after FMDV infection and validated related genes through qPCR. Results The immunohistochemical results showed that both cattle and horses had four integrin receptors that could assist FMDV entry into host cells. The transcriptome analysis revealed that after FMDV infection, pro‐apoptotic genes such as caspase‐3 (CASP3) and cytochrome C (CYCS) were upregulated in cattle, while apoptosis‐inhibiting genes such as NAIP and BCL2A1 were downregulated. In contrast, the expression trend of related genes in horses was opposite to that in cattle. Additionally, autophagy‐related genes such as beclin 1, ATG101, ATG4B, ATG4A, ATG13, and BCL2A1 were downregulated in cattle after FMDV infection, indicating that cattle did not clear the virus through autophagy. However, key autophagy genes including ATG1, ATG3, ATG9, ATG12, and ATG16L1 were significantly upregulated in horses after viral infection. Conclusion Both water buffaloes and Mongolian horses express integrin receptors that allow FMDV entry into cells. Therefore, the resistance of Mongolian horses to FMDV may result from more changes in intracellular mechanisms, including processes such as autophagy and apoptosis. Significant differences were observed between water buffaloes and Mongolian horses in these processes, suggesting that these processes influence FMDV replication and synthesis.

The transformation of hydrogen metallurgy is a principal means of promoting the iron and steel industry (ISI) in reaching peak and deep emissions reduction. However, the environmental impact of different hydrogen production paths on hydrogen metallurgy has not been systemically discussed. To address this gap, based on Long-range Energy Alternatives Planning System (LEAP), this paper constructs a bottom-up energy system model that includes hydrogen production, iron and steel (IS) production, and power generation. By setting three hydrogen production structure development paths, namely the baseline scenario, business-as-usual (BAU) scenario, and clean power (CP) scenario, the carbon dioxide (CO2) emissions impact of different hydrogen production paths on hydrogen metallurgy is carefully evaluated from the perspective of the whole industry, and each IS production process. The results show that, under the baseline scenario, the hydrogen metallurgy transition will help the CO2 emissions of ISI peak at 2.19 billion tons in 2024, compared to 2.08 billion tons in 2020, and then gradually decrease to 0.78 billion tons in 2050. However, different hydrogen production paths will contribute to the reduction or inhibit the reduction. In 2050, the development of electrolysis hydrogen production with renewable electricity will reduce CO2 emissions by an additional 48.76 million tons (under the CP scenario), while the hydrogen production mainly based on coal gasification and methane reforming will increase the additional 50.04 million tons CO2 emissions (under the BAU scenario). Moreover, under the hydrogen production structure relying mainly on fossil and industrial by-products, the technological transformation of blast furnace ironmaking with hydrogen injections will leak carbon emissions to the upstream energy processing and conversion process. Furthermore, except for the 100% scrap based electric arc furnace (EAF) process, the IS production process on hydrogen-rich shaft furnace direct reduced iron (hydrogen-rich DRI) have lower CO2 emissions than other processes. Therefore, developing hydrogen-rich DRI will help the EAF steelmaking development to efficiently reduce CO2 emissions under scrap constraints.

Soil organic carbon (SOC) fractions are vital intrinsic indicators of SOC stability, and soil fungi are the key drivers of soil carbon cycling. However, variations in SOC fractions along an elevational gradient in mountain meadows and the role of the fungal community in regulating these variations are largely unknown, especially in subtropical areas. In this study, an elevation gradient experiment (with experimental sites at 1500, 1700, and 1900 m) was set up in a Miscanthus sinensis community in a meadow on Wugong Mountain, Southeast China, to clarify the effects of elevation on soil fungal community composition, microbial residue carbon, and SOC fractions. The results showed that the contribution of soil microbial residue carbon to SOC was only 16.1%, and the contribution of soil fungal residue carbon to SOC (15.3%) was far greater than that of bacterial residue carbon (0.3%). An increase in elevation changed the fungal community structure and diversity, especially in the topsoil (0–20 cm depth) compared with that in the subsoil (20–40 cm depth), but did not affect fungal residue carbon in the two soil layers. When separating SOC into the fractions mineral-associated organic carbon (MAOC) and particulate organic carbon (POC), we found that the contribution of MAOC (66.6%) to SOC was significantly higher than that of POC (20.6%). Although an increased elevation did not affect the SOC concentration, it significantly changed the SOC fractions in the topsoil and subsoil. The soil POC concentration and its contribution to SOC increased with an increasing elevation, whereas soil MAOC showed the opposite response. The elevational variations in SOC fractions and the POC/MAOC ratio were co-regulated by the fungal community structure and total nitrogen. Our results suggested that SOC stabilization in mountain meadows decreases with an increasing elevation and is driven by the fungal community structure, providing scientific guidance for SOC sequestration and stability in mountain meadows in subtropical areas.

Droughts in the Weihe River Basin are occurring more frequently and are becoming more intense. These events negatively affect industrial production, economic development, and ecosystems. Studying how vegetation changes in response to them is of practical significance. We report temporal and spatial trends in vegetation cover, use a copula function to analyze relationships between drought and vegetation cover, and assess the probability of vegetation loss in different drought scenarios. A vegetation index trends upwards from north to south in this basin; from 2001 to 2017, vegetation cover also trends upward in most areas, although it decreases in areas with high vegetation cover. An escalated susceptibility to drought has been observed in the southern and eastern sectors, where proximity to the riverbank correlates with heightened drought sensitivity, particularly in zones of intensified vegetation density. The probability of vegetation loss at the same vegetation loss preset point gradually increases with increased drought severity. These results will facilitate the formulation of countermeasures to prevent and combat the effects of drought on vegetation and land management.

Abstract Due to the impact of COVID-19, a significant influx of emergency patients inundated the intensive care unit (ICU), and as a result, the treatment of elective patients was postponed or even cancelled. This paper studies ICU bed allocation for three categories of patients (emergency, elective, and current ICU patients). A two-stage model and an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to obtain ICU bed allocation. In the first stage, bed allocation is examined under uncertainties regarding the number of emergency patients and their length of stay (LOS). In the second stage, in addition to including the emergency patients with uncertainties in the first stage, it also considers uncertainty in the LOS of elective and current ICU patients. The two-stage model aims to minimize the number of required ICU beds and maximize resource utilization while ensuring the admission of the maximum number of patients. To evaluate the effectiveness of the model and algorithm, the improved NSGA-II was compared with two other methods: multi-objective simulated annealing (MOSA) and multi-objective Tabu search (MOTS). Drawing on data from real cases at a hospital in Lyon, France, the NSGA-II, while catering to patient requirements, saves 9.8% and 5.1% of ICU beds compared to MOSA and MOTS. In five different scenarios, comparing these two algorithms, NSGA-II achieved average improvements of 0%, 49%, 11.4%, 9.5%, and 17.1% across the five objectives.

In order to expand the use of bubble green vegetables, bubble green freeze-dried powder was used as raw material to fabricate dried noodles in this study. The effects of adding the bubble green powder on the flour characteristics, dough tensile properties were discussed. The effects of the additions of green powder, water and salt on the cooking loss, texture and edible quality of the dried noodles were studied, and the processing of bubble green dried noodles was optimized. The results showed that, the dough formation time and stability in the flour characteristics decreased after adding bubble green vegetable powder. Meanwhile, the water absorption rate and weakening degree of the dough increased. The tensile energy, tensile resistance, ductility and maximum tensile resistance in the dough tensile characteristics decreased because of the addition of bubble green vegetables powder. Therefore, the bubble green powder was not conducive to the formation of dough gluten network structure. The processing technology of bubble green dried noodles was optimized. The sensory evaluation of bubble green noodles was 90.12 points when the addition of bubble green powder, water, and salt was 1.30%, 36.00%, and 1.90%, respectively. Blocking effect of bubble green powder on the formation of some gluten networks was observed by scanning electron microscopy and laser confocal microscopy, which preliminarily explained the change trend of decreasing hardness, decreasing chewiness and increasing cooking loss in the texture of dried noodles.

As environmental and human changes combine, water shortage and ecological fragility are becoming increasingly serious issues in the basin. The national “14th Five-Year Plan” proposes to build resilient basins to enhance disaster resilience. On the basis of clarifying the multi-link characteristics of water resources system resilience under the influence of meteorology-hydrology-ecology-society-economy, this paper reveals the interrelationship and chain reaction among the factors affecting the resilience of water resources system by clarifying the multi-link characteristics of water resources system resilience. Based on the interconnections among meteorology-hydrology-engineering-economic society-ecology in regional water resources systems, this study constructs a resilience evaluation index for the water resources system. The index considers different objectives, dimensions, and scales to provide a comprehensive assessment of the system’s resilience. Based on the multi-dimensional relationship of the evaluation index system, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method based on entropy weight method is employed to depict the resilience level of the water resources system at varying spatial and temporal scales. By focusing on Shanxi Province as the research subject, a multi-link evaluation framework for assessing the resilience of the water resources system is established, and a quantitative approach to evaluate its resilience is investigated. The results show that the level of water resources resilience in Shanxi Province has improved from 2017 to 2021, and there are certain spatial and temporal differences. In 2021, only Lvliang City and Yangquan City have low resilience level, and the resilience level of other cities has been improved. Among them, Taiyuan City has the highest resilience level of 0.56, which belongs to the high resilience level. The research results can improve the cognitive level of multi-link evolution mechanism of resilience to a certain extent, and provide scientific basis for multi-dimensional targeted regulation of water resources system resilience.

Abstract Background There is a recognized need for additional approaches to improve the accuracy of extrathyroidal extension (ETE) diagnosis in papillary thyroid carcinoma (PTC) before surgery. Up to now, multimodal ultrasound has been widely applied in disease diagnosis. We investigated the value of radiomic features extracted from multimodal ultrasound in the preoperative prediction of ETE. Methods We retrospectively pathologically confirmed PTC lesions in 235 patients from January 2019 to April 2022 in our hospital, including 45 ETE lesions and 205 non-ETE lesions. MaZda software was employed to obtain radiomics parameters in multimodal sonography. The most valuable radiomics features were selected by the Fisher coefficient, mutual information, probability of classification error and average correlation coefficient methods (F + MI + PA) in combination with the least absolute shrinkage and selection operator (LASSO) method. Finally, the multimodal model was developed by incorporating the clinical records and radiomics features through fivefold cross-validation with a linear support vector machine algorithm. The predictive performance was evaluated by sensitivity, specificity, accuracy, F1 scores and the area under the receiver operating characteristic curve (AUC) in the training and test sets. Results A total of 5972 radiomics features were extracted from multimodal sonography, and the 13 most valuable radiomics features were selected from the training set using the F + MI + PA method combined with LASSO regression. The multimodal prediction model yielded AUCs of 0.911 (95% CI 0.866–0.957) and 0.716 (95% CI 0.522–0.910) in the cross-validation and test sets, respectively. The multimodal model and radiomics model showed good discrimination between ETE and non-ETE lesions. Conclusion Radiomics features based on multimodal ultrasonography could play a promising role in detecting ETE before surgery.

Under the changing environment, the problems of the water cycle and water resources in the basin become extremely complex, and the coordination of water use efficiency and fairness is extremely difficult. This paper takes the Yellow River Basin as the key research area and creates a balanced allocation method and model of water resources that take into account the fairness and efficiency of water use. The dynamic equilibrium allocation of water resources increment brought by new water source projects and regulation projects is realized, and the fine-tuning optimization of the water distribution scheme is realized. The results show that the optimal adjustment strategy of the water diversion scheme is to increase the upstream water allocation, and the adjustment range is 2.13%. The water allocation in the middle reaches was slightly increased by 0.25% to reduce the downstream and Hebei Province, Tianjin water allocation, and the adjustment range is −3.81%. The optimization scheme reflects the principle of ecological priority, guarantees the basic ecological environment water use in the Yellow River, balances the fairness and efficiency of economic and social water use outside the river, and provides technical support for water resources security in water-shortage basins. HIGHLIGHTS The method and model of incremental dynamic equilibrium allocation of water resources in the Yellow River Basin were proposed in this study. The scenario analysis was carried out to study the strategies of water diversion schemes such as optimizing the direction and amplitude of adjustment, so as to improve the adaptability of the water distribution scheme to the changing environment.; From the perspective of fairness, the distribution of rigid water demand such as domestic and industrial water demand in each province of the basin is given priority, and then the efficiency factors of rigid elasticity and elastic water demand distribution in each province are considered.;

Electronic components are the main components of PCBs (printed circuit boards), so the detection and classification of ECs (electronic components) is an important aspect of recycling used PCBs. However, due to the variety and quantity of ECs, traditional target detection methods for EC classification still have problems such as slow detection speed and low performance, and the accuracy of the detection needs to be improved. To overcome these limitations, this study proposes an enhanced YOLO (you only look once) network (EC-YOLOv7) for detecting EC targets. The network uses ACmix (a mixed model that enjoys the benefits of both self-attention and convolution) as a substitute for the 3 × 3 convolutional modules in the E-ELAN (Extended ELAN) architecture and implements branch links and 1 × 1 convolutional arrays between the ACmix modules to improve the speed of feature retrieval and network inference. Furthermore, the ResNet-ACmix module is engineered to prevent the leakage of function data and to minimise calculation time. Subsequently, the SPPCSPS (spatial pyramid pooling connected spatial pyramid convolution) block has been improved by replacing the serial channels with concurrent channels, which improves the fusion speed of the image features. To effectively capture spatial information and improve detection accuracy, the DyHead (the dynamic head) is utilised to enhance the model’s size, mission, and sense of space, which effectively captures spatial information and improves the detection accuracy. A new bounding-box loss regression method, the WIoU-Soft-NMS method, is finally suggested to facilitate prediction regression and improve the localisation accuracy. The experimental results demonstrate that the enhanced YOLOv7 net surpasses the initial YOLOv7 model and other common EC detection methods. The proposed EC-YOLOv7 network reaches a mean accuracy (mAP@0.5) of 94.4% on the PCB dataset and exhibits higher FPS compared to the original YOLOv7 model. In conclusion, it can significantly enhance high-density EC target recognition.

Vascular aging is one of the reasons for the high incidence of cardiovascular diseases nowadays, as vascular cells age due to various internal and external factors. Among them, high fat is an important inducer. Canagliflozin (CAN) is one of the SGLT2 inhibitors that has been shown to have cardiovascular protective effects in addition to lowering blood sugar, but the specific mechanism is not clear. This study first established a vascular aging model using palmitic acid (PA), then tested the effect of CAN on PA-induced vascular aging, and finally examined the mechanism of CAN’s anti-vascular aging via ROS/ERK and ferroptosis pathways. We found that CAN alleviates PA-induced vascular cell aging by inhibiting the activation of ROS/ERK and ferroptosis signaling pathways. This study reveals new mechanisms of lipid-induced vascular aging and CAN inhibition of vascular aging from the perspectives of ROS/ERK and ferroptosis pathways, which is expected to provide new ideas for the development of related drugs in the future.

Robotic metamaterials represent an innovative approach to creating synthetic structures that combine desired material characteristics with embodied intelligence, blurring the boundaries between materials and machinery. Inspired by the functional qualities of biological skin, integrating tactile intelligence into these materials has gained significant interest for research and practical applications. This study introduces a Soft Robotic Metamaterial (SRM) design featuring omnidirectional adaptability and superior tactile sensing, combining vision-based motion tracking and machine learning. The study compares two sensory integration methods to a state-of-the-art motion tracking system and force/torque sensor baseline: an internal-vision design with high frame rates and an external-vision design offering cost-effectiveness. The results demonstrate the internal-vision SRM design achieving an impressive tactile accuracy of 98.96%, enabling soft and adaptive tactile interactions, especially beneficial for dexterous robotic grasping. The external-vision design offers similar performance at a reduced cost and can be adapted for portability, enhancing material science education and robotic learning. This research significantly advances tactile sensing using vision-based motion tracking in soft robotic metamaterials, and the open-source availability on GitHub fosters collaboration and further exploration of this innovative technology (https://github.com/bionicdl-sustech/SoftRoboticTongs).

Robots play a critical role as the physical agent of human operators in exploring the ocean. However, it remains challenging to grasp objects reliably while fully submerging under a highly pressurized aquatic environment with little visible light, mainly due to the fluidic interference on the tactile mechanics between the finger and object surfaces. This study investigates the transferability of grasping knowledge from on‐land to underwater via a vision‐based soft robotic finger that learns 6D forces and torques (FT) using a supervised variational autoencoder (SVAE). A high‐framerate camera captures the whole‐body deformations while a soft robotic finger interacts with physical objects on‐land and underwater. Results show that the trained SVAE model learns a series of latent representations of the soft mechanics transferable from land to water, presenting a superior adaptation to the changing environments against commercial FT sensors. Soft, delicate, and reactive grasping enabled by tactile intelligence enhances the gripper's underwater interaction with improved reliability and robustness at a much‐reduced cost, paving the path for learning‐based intelligent grasping to support fundamental scientific discoveries in environmental and ocean research.

Mountain torrent disaster prevention is the focus of flood control and disaster reduction in China. Critical rainfall is an important indicator to determine the success or failure of mountain torrent disaster early warning. In this paper, the M-Copula function is introduced, the multi-dimensional joint distribution of critical rainfall is constructed, and the joint distribution of rainfall and peak rainfall intensity is analyzed. Taking A village in Xinxian County as an example. The critical rainfall of the combined probability is calculated, and the critical rainfall of the flash flood disaster water level, the pre-shift warning and the sharp-shift warning is warned and analyzed. The results show that the flood peak modulus calculated by Yishangfan group is 8.89, which has certain rules for the flood peak modulus of rivers in hilly areas. The larger the basin area is, the smaller the flood peak modulus is, the smaller the area is, and the larger the flood peak modulus is. The calculation result of the design flow of 533 m3/s is reasonable. It is reasonable and reliable to select the M-Copula function as the connection function to fit the joint distribution of rainfall and peak rainfall intensity, which can provide theoretical support for flash flood disaster warning in other regions.

Studying the propagation law and response relationship between meteorological elements and hydrological drought is conducive to exploring the propagation mechanism and transmission time of drought, and providing a basis for reasonable and efficient drought relief work. In this paper, the area above Xiangtan station is taken as the research area, and the temperature and precipitation are selected as the meteorological elements. The standardized flow index (SDI) is used to characterize the hydrological drought. The linear regression method and Mann-Kendall trend test are used to analyze the evolution sequence of meteorological elements and hydrological drought at different scales. The characteristics and laws of drought propagation are revealed, and the hydrological drought is divided into stages by combining the ordered cluster analysis method and the sliding t-test method. The Pearson correlation analysis method is used to analyze the stage correlation degree between meteorological elements and hydrological drought, reflecting the response relationship between meteorological elements and hydrological drought under different types and different scales, and the response period of hydrological drought to meteorological elements at different time scales is obtained. Studying the development trend and evolution law of meteorological elements and hydrological drought, and deeply exploring the phased response relationship are conducive to improving the drought resistance ability and drought disaster reduction management ability of Xiangtan area.

This study presents the design of an underwater superlimb as a wearable robot, providing divers with mobility assistance and freeing their hands for manipulating tools underwater. The wearable design features a thrust vectoring system with two 3D‐printed, waterproofed modules. The module with adjustable connections and strapping holes is designed to enable reconfiguration for multiple purposes, including regular use as an underwater superlimb for divers, manually operated as a handheld glider for swimmers, combined with an amphibian, legged robot as a quadruped superlimb, and coupled as a dual‐unit autonomous underwater vehicle for underwater navigation. The kinematics and dynamics of the prototype and all of its reconfigured modes are developed. A sliding‐mode controller is also introduced to achieve stable simulation in PyBullet. Field tests further support the feasibility of the underwater superlimb when worn on a test diver in a swimming pool. As the first underwater superlimb presented in the literature, this study opens new doors for supernumerary robotic limbs in underwater scenarios with multifunctional reconfiguration.

To study the propagation law of meteorological droughts to hydrological droughts under variable time scales, and to reveal the synchronisation gap and lag time of hydrological droughts compared to meteorological droughts, and the lag degree of hydrological drought is quantitatively studied. In this paper, the Yellow River Water Supply Area in Henan is taken as the research area, and the propagation time of meteorological drought to hydrological drought under variable time scale is mainly studied. The calculation of drought propagation time is set as two states: interval scale and continuous scale. The Standardized Precipitation Index (SPI) sequence and Standardized Runoff Index (SRI) sequence (1)with interval and continuous scales were obtained by multi-scale standardization of precipitation and runoff, which were used to characterize meteorological drought and hydrological drought respectively. The Mann-Kendall (M−K) test method was used to analyze the evolution of SPI sequence and SRI sequence at monthly scale, and to study the lag time of hydrological drought in four seasons compared with meteorological drought. Combining the Grey Correlation Method and Pearson correlation coefficient methods, the time interval for the propagation of meteorological droughts to hydrological droughts was determined based on the strongest correlation of different combinations of sequences. Finally, the propagation time series is divided into sliding windows to analyse the M−K dynamic trend of propagation time from a seasonal scale perspective. It provides a strong basis for the study of drought propagation based on multi-scale.

In recent years, dibenzyl disulfide (DBDS) in transformer oils has caused many transformer failures around the world, and its removal has attracted more attention. In this work, nine imidazolium-based ionic liquids (ILs) were applied as effective, green desulfurization extractants for DBDS-containing transformer oil for the first time. The results show that the desulfurization ability of the ILs for DBDS followed the order of [BMIM]FeCl4 > [BMIM]N(CN)2 > [BMIM]SCN > [BMIM](C4H9O)2PO2 > [BMIM]MeSO4 > [BMIM]NTf2 > [BMIM]OTf > [BMIM]PF6 > [BMIM]BF4. Especially, [BMIM]FeCl4 ionic liquid had excellent removal efficiency for DBDS, with its S partition coefficient KN (S) being up to 2642, which was much higher than the other eight imidazolium-based ILs. Moreover, the extractive performance of [BMIM]FeCl4 increased with an increasing molar ratio of FeCl3 to [BMIM]Cl, which was attributed to its Lewis acidity and fluidity. [BMIM]FeCl4 ionic liquid could also avail in the desulfurization of diphenyl sulfide (DPS) from model oils. The experimental results demonstrate that π−π action, π-complexation, and Lewis acid−base interaction played important roles in the desulfurization process. Finally, the ([BMIM]FeCl4) ionic liquid could be recycled five times without a significant decrease in extractive ability.

Kiwi wine (KW) is tipically made by fermenting juice from peeled kiwifruit, resulting in the disposal of peel and pomace as by-products. However, the peel contains various beneficial compounds, like phenols and flavonoids. Since the peel is edible and rich in these compounds, incorporating it into the fermentation process of KW presents a potential solution to minimize by-product waste. This study compared the aroma and taste profiles of KW from peeled (PKW) and unpeeled (UKW) kiwifruits by combining intelligent sensory technology, GC-MS, and 1H-NMR. Focusing on aroma profiles, 75 volatile organic compounds (VOCs) were identified in KW fermented with peel, and 73 VOCs in KW without peel, with 62 VOCs common to both. Among these compounds, rose oxide, D-citronellol, and bornylene were more abundant in UKW, while hexyl acetate, isoamyl acetate, and 2,4,5-trichlorobenzene were significantly higher in PKW. For taste profiles, E-tongue analysis revealed differences in the taste profiles of KW from the two sources. A total of 74 molecules were characterized using 1H-NMR. UKW exhibited significantly higher levels of tartrate, galactarate, N-acetylserotonin, 4-hydroxy-3-methoxymandelate, fumarate, and N-acetylglycine, along with a significantly lower level of oxypurinol compared to PKW. This study seeks to develop the theoretical understanding of the fermentation of kiwifruit with peel in sight of the utilization of the whole fruit for KW production, to increase the economic value of kiwifruit production.

Abstract A high geological background can increase the ecological and health risks associated with crop production; therefore, it is essential to assess the heavy metals and their impact. In this study, ecological and health risk impacts of heavy metal contamination, in combination with positive matrix factorization was assessed for an area with high geological background with wheat–maize cropping system, to provide a quantitative understanding of the effects of heavy metals, enabling its prevention and control. This study revealed that the comprehensive ecological risk (RI wheat–maize ) is 56.21 (low), with industries being the biggest contributors (34.22%). Comprehensive health risk (non-carcinogenic) assessment showed that industrial (40.98–49.30%) and natural (23.96–37.64%) factors were the primary (particularly of Cd and Zn) and secondary (particularly of Cr and Ni) contributors, respectively in eastern China. Comprehensive health risk (HI wheat–maize ) for children and adults were 0.74 and 0.42, respectively, indicating that non-carcinogenic risks were at an acceptable level. Soil ingestion was the primary pathway for health risks (62.23–73.00%), especially for children. Based on soil heavy metal sources and crop systems, source-ecological risk assessment and source-health risk assessment were used to provided valuable insights on making strategies to protect human health in high geological background areas.

Abstract In computer vision, timely and accurate execution of object identification tasks is critical. However, present road damage detection approaches based on deep learning suffer from complex models and computationally time-consuming issues. To address these issues, we present a lightweight model for road damage identification by enhancing the YOLOv5s approach. The resulting algorithm, YOLO-LRDD, provides a good balance of detection precision and speed. First, we propose the novel backbone network Shuffle-ECANet by adding an ECA attention module into the lightweight model ShuffleNetV2. Second, to ensure reliable detection, we employ BiFPN rather than the original feature pyramid network since it improves the network's capacity to describe features. Moreover, in the model training phase, localization loss is modified to Focal-EIOU in order to get higher-quality anchor box. Lastly, we augment the well-known RDD2020 dataset with many samples of Chinese road scenes and compare YOLO-LRDD against several state-of-the-art object detection techniques. The smaller model of our YOLO-LRDD offers superior performance in terms of accuracy and efficiency, as determined by our experiments. Compared to YOLOv5s in particular, YOLO-LRDD improves single image recognition speed by 22.3% and reduces model size by 28.8% while maintaining comparable accuracy. In addition, it is easier to implant in mobile devices because its model is smaller and lighter than those of the other approaches.

Introduction: A new method is introduced to test the tensile strength of concrete: the cylinder transverse splitting test. Compared with the cylinder splitting (or Brazilian) test, the cylinder transverse splitting test involves different load positions and offers the advantages of doubling the data volume with the same number of specimens and improving the detection accuracy.Methods: Finite element analysis software was used to simulate the concrete cylinder transverse splitting test and the stress distribution on the failure surface was determined.Results and Discussion: The results show that the fracture of a cylinder is mainly determined by tensile stress. The splitting strength of normal concrete and crumb rubber concrete, a new environmentally friendly concrete material that has gathered considerable attention in recent years, was obtained by cylinder transverse and cube splitting tests. The cylinder transverse splitting test data show a stable correlation with the cube splitting test data and well characterize the concrete strength. The relationship between the cylinder nominal transverse splitting strength (f2) and cube splitting strength (f1) was established on the basis of linear analysis of the test data: f1 = 0.51f2. The calculated cube splitting strength is in good agreement with the test values.

Introduction: The North China Plain is an important production base of grain, cotton, and fruits in China. However, the climate is dry and rainless, and thus, water resources are scarce. The combination of water resources, population, and cultivated land is extremely unbalanced, making the region a serious water shortage area in China. In addition to long-term groundwater over-exploitation, water shortage has become an important bottleneck, restricting the economic and social development of the North China Plain and national food security. Therefore, making full use of unconventional water resources and reducing the proportion of conventional water resources will alleviate the shortage of water resources and improve the utilization of water resources.Methods: Taking Hengshui City as an example, this paper establishes an optimal allocation model of water resources with the minimum relative water shortage rate as the objective function, the coordinated allocation of water resources between conventional and unconventional water resources is studied, and various available water sources are effectively allocated between regions and water use departments. The genetic algorithm is used to study the model, by taking 2020 as the starting year, and optimize the allocation of water resources in Hengshui City between 2020 and 2025.Results and Discussion: The results show that the water demand of each county in Hengshui City will be guaranteed in 2025, and there will be no water shortage. In the 2025 level year, the total amount of unconventional water resources in Hengshui City will increase compared with that in 2020, with an increase of 21.9144 million m3. Among them, there will be an increase in brackish water consumption, 11.3244 million m3, and an increase in sewage reuse water consumption, 10.59 million m3, which will effectively alleviate the contradiction between supply and demand of water resources in Hengshui City.

Abstract Background Circadian disturbance is a common nonmotor complaint in Parkinson’s disease (PD). The molecular basis underlying circadian rhythm in PD is poorly understood. Neuroinflammation has been identified as a key contributor to PD pathology. In this study, we explored the potential link between the core clock molecule Rev-erbα and the microglia-mediated NLR family pyrin domain-containing 3 (NLRP3) inflammasome in PD pathogenesis. Methods We first examined the diurnal Rev-erbα rhythms and diurnal changes in microglia-mediated inflammatory cytokines expression in the SN of MPTP-induced PD mice. Further, we used BV2 cell to investigate the impacts of Rev-erbα on NLRP3 inflammasome and microglial polarization induced by 1-methyl-4-phenylpyridinium (MPP+) and αsyn pre-formed fibril. The role of Rev-erbα in regulating microglial activation via NF-κB and NLRP3 inflammasome pathway was then explored. Effects of SR9009 against NLRP3 inflammasome activation, microgliosis and nigrostriatal dopaminergic degeneration in the SN and striatum of MPTP-induced PD mice were studied in detail. Results BV2 cell-based experiments revealed the role of Rev-erbα in regulating microglial activation and polarization through the NF-κB and NLRP3 inflammasome pathways. Circadian oscillation of the core clock gene Rev-erbα in the substantia nigra (SN) disappeared in MPTP-induced PD mice, as well as diurnal changes in microglial morphology. The expression of inflammatory cytokines in SN of the MPTP-induced mice were significantly elevated. Furthermore, dopaminergic neurons loss in the nigrostriatal system were partially reversed by SR9009, a selective Rev-erbα agonist. In addition, SR9009 effectively reduced the MPTP-induced glial activation, microglial polarization and NLRP3 inflammasome activation in the nigrostriatal system. Conclusions These observations suggest that the circadian clock protein Rev-erbα plays an essential role in attenuating neuroinflammation in PD pathology, and provides a potential therapeutic target for PD treatment.

The assessment of heavy metal pollution is crucial for water conservation. This study determined the contents of heavy metals (Cd, Cr, Cu, Ni, Pb, Zn and As) from 39 soil samples surrounding a reservoir, and analyzed the corresponding source and enrichment using enrichment factors and partial least-squares regression. The concentration of Cr (54.06 mg/kg) was lower than the background value of the reservoir area, while the Cd concentration was higher (0.96 mg/kg). Moreover, Cd, Cr, Ni, Pb, Zn and As concentrations in the south exceeded those of the northeast in the Nanwan lake reservoir (NLR). Cd and As were the dominant contaminated elements in the NLR. The Cd enrichment factor value was 11.25, areas with moderate and higher levels of pollution of Cd occupied 89.0% of the total area, while As occupied 18.4%. The dominant sources of Zn, Ni, Cu, Pb and Cr were identified as natural inputs, those of As were agricultural production activities, and those of Cd were industrial production activities. This study provides insight into the heavy metal pollution and key factors of land-use types in watersheds with tea trees as the dominant vegetation cover, and aids in the planning of water pollution prevention and ecological protection. HIGHLIGHTS A novel technology partial least-squares regression model.; The principle sources were identified by calculating the variable importance for the projection (VIP).; The inherent defects of traditional regression algorithms in handling multicollinear and noisy data were overcome.;

With the rapid development of economy and society, the contradiction between supply and demand of water resources is increasing. Efficient utilization and allocation of limited water resources are one of the main means to solve the above contradictions. In this paper, the multidimensional joint distribution of natural streamflow series in reservoirs is constructed by introducing the mixed Copula function, and the probability of wet and dry encounters between natural streamflow is analyzed. Luan River is located in the northeastern part of Hebei Province, China, taking the group of Panjiakou Reservoir, Douhe Reservoir and Yuqiao Reservoir in the downstream of Luan River Basin as an example, the probabilities of synchronous and asynchronous abundance and depletion of inflow from the reservoirs are calculated. The results show that the probability of natural streamflow series between reservoirs is 61.14% for asynchronous wetness and dryness, which has certain mutual compensation ability. Therefore, it is necessary to minimize the risk of water supply security in Tianjin, Tangshan and other cities, and strengthen the optimal joint water supply scheduling of reservoirs. The research results are reasonable and reliable, which can provide reference for water supply operation of other basins. HIGHLIGHTS The mixed Copula function can more flexibly describe the correlation between variables of a hydrological system.; The M-Copula function is selected as the connection function to fit the joint distribution of runoff between reservoirs.; The results of the study can be used as a reference for the optimal scheduling of water resources in other basins.;

In-hand object pose estimation is challenging for humans and robots due to occlusion caused by the hand and object. This paper proposes a soft finger that integrates inner vision with kinesthetic sensing to estimate object pose inspired by human fingers. The soft finger has a flexible skeleton and skin that adapts to different objects, and the skeleton deformations during interaction provide contact information obtained by the image from the inner camera. The proposed framework is an end-to-end method that uses raw images from soft fingers to estimate in-hand object pose. It consists of an encoder for kinesthetic information processing and an object pose and category estimator. The framework was tested on seven objects, achieving an impressive error of 2.02 mm and 11.34 degrees for pose error and 99.05% for classification.

Abstract This study explored the role of MTDH in regulating the sensitivity of breast cancer cell lines to gemcitabine (Gem) and the potential miRNAs targeting MTDH. The expression of MTDH in cancer tissues and cells was detected by immunohistochemical staining or qRT-PCR. The target genes for MTDH were predicted by bioinformatics and further confirmed by dual-luciferase reporter assay and qRT-PCR. Cancer cells were transfected with siMTDH, MTDH, miR-9-3p inhibitor, or mimics and treated by Gem, then CCK-8, colony formation assay, tube formation assay, flow cytometry, wound healing assay, and Transwell were performed to explore the effects of MTDH, miR-9-3p, and Gem on cancer cell growth, apoptosis, migration, and invasion. Expressions of VEGF, p53, cleaved caspase-3, MMP-2, MMP-9, E-Cadherin, N-Cadherin, and Vimentin were determined by Western blot. MTDH was high-expressed in cancer tissues and cells, and the cells with high-expressed MTDH were less sensitive to Gem, while silencing MTDH expression significantly promoted the effect of Gem on inducing apoptosis, inhibiting cell migration, invasion, and growth, and on regulating protein expressions of cancer cells. Moreover, miR-9-3p had a targeted binding relationship with MTDH, and overexpressed miR-9-3p greatly promoted the toxic effects of Gem on cancer cells and expressions of apoptosis-related proteins, whereas overexpressed MTDH partially reversed such effects of overexpressed miR-9-3p. The study proved that miR-9-3p regulates biological functions, drug resistance, and the growth of Gem-treated breast cancer cells through targeting MTDH.

BackgroundSeveral markers of inflammation have been associated with oncologic outcomes. Prognostic markers are not well-defined for renal cell carcinoma (RCC). We sought to investigate the association of preoperative neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and De Ritis ratio with mortality in RCC.MethodsMulti-center retrospective analysis of patients undergoing surgery for RCC. Primary outcome of interest was all-cause mortality (ACM). Secondary outcomes were non-cancer mortality (NCM) and cancer-specific mortality (CSM). Elevated NLR was defined as ≥2.27, elevated PLR as ≥165, and elevated De Ritis ratio as ≥ 2.72. Multivariable cox regression analysis (MVA) was conducted to elucidate risk factors for primary and secondary outcomes, and Kaplan-Meier analysis (KMA) was used to evaluate survival outcomes comparing elevated and non-elevated NLR, PLR, and De Ritis ratio.Results2656 patients were analyzed (874 patients had elevated NLR; 480 patients had elevated PLR and 932 patients had elevated De Ritis). Elevated NLR was a significant predictor of ACM (HR 1.32, 95% CI: 1.07-1.64, p=0.003) and NCM (HR 1.79, 95% CI: 1.30-2.46, p

Dongping Lake area, located in the lower reaches of Yellow River, is an ideal place to study the changes of modern river and lake sedimentary environment. The sediment samples of Dawen River, Yellow River, and Dongping Lake were collected, and the major elements, trace elements and organic matter geochemical composition of the samples were analyzed. Cluster analysis, characteristic element ratio method and graphic method were used to explore the geochemical characteristics of sediments and their environmental implication. The results show that the contents of SiO2, Na2O, TiO2 and Zr in sediments of Dawen River and Yellow River are relatively high, and the contents of iron and manganese oxides, organic matter, CaO, P2O5 and Sr in lake sediments are relatively high. That reveals the differences of sedimentary environments between the rivers and the lake. The contents of Sr and Zr in Dawen River are affected by the rapid migration of clastic materials in the upstream carbonate source area during the flood season; the δCe, ΣREE and REE’s ratios in the sediments of the Yellow River reflect the influence of the Loess source; and the distribution of elements changes along the flow direction during the flood season. The characteristics of pH, element composition and LREE & HREE fractionation of the lake sediments indicate that the sediment source is complex, and the lake environment is affected by the flood season. The study shows that the geochemical content and its variation characteristics of sediments effectively reveal the sedimentary environment, material composition and characteristics of flood season of rivers and the lake in the study area.

Locomotion and manipulation are two essential skills in robotics but are often divided or decoupled into two separate problems. It is widely accepted that the topological duality between multi-legged locomotion and multi-fingered manipulation shares an intrinsic model. However, a lack of research remains to identify the data-driven evidence for further research. This paper explores a unified formulation of the loco-manipulation problem using reinforcement learning (RL) by reconfiguring robotic limbs with an overconstrained design into multi-legged and multi-fingered robots. Such design reconfiguration allows for adopting a co-training architecture for reinforcement learning towards a unified loco-manipulation policy. As a result, we find data-driven evidence to support the transferability between locomotion and manipulation skills using a single RL policy with a multilayer perceptron or graph neural network. We also demonstrate the Sim2Real transfer of the learned loco-manipulation skills in a robotic prototype. This work expands the knowledge frontiers on loco-manipulation transferability with learning-based evidence applied in a novel platform with overconstrained robotic limbs.

Observations that hearing loss is a substantial risk factor for dementia may be accounted for by a common pathology. Mitochondrial oxidative stress and alterations in α-synuclein pathology may be common pathology candidates. Crucially, these candidate pathologies are implicated in Parkinson’s disease (PD). Consequently, hearing loss may be a risk factor for PD. Subsequently, this prospective cohort study of the English Longitudinal Study of Ageing examines whether hearing loss is a risk factor for PD longitudinally. Participants reporting self-reported hearing capabilities and no PD diagnosis prior to entry (n = 14,340) were used. A joint longitudinal and survival model showed that during a median follow up of 10 years (SD = 4.67 years) increased PD risk (p < 0.001), but not self-reported hearing capability (p = 0.402). Additionally, an exploratory binary logistic regression modelling the influence of hearing loss identified using a screening test (n = 4812) on incident PD indicated that neither moderate (p = 0.794), nor moderately severe/severe hearing loss (p = 0.5210), increased PD risk, compared with normal hearing. Whilst discrepancies with prior literature may suggest a neurological link between hearing loss and PD, further large-scale analyses using clinically derived hearing loss are needed.

With the advancement of living standards in modern society and the emergence of an aging population, an increasing number of people are becoming interested in the topic of aging and anti-aging. An important feature of aging is skin aging, and women are particularly concerned about skin aging. In the field of cosmetics, the market share of anti-aging products is increasing year by year. This article reviews the research and development progress of skin aging and related active compounds both domestically and internationally in recent years. The results show that, in terms of the research on skin aging, the popular theories mainly include free radicals and oxidative stress theory, inflammation theory, photoaging theory, and nonenzymatic glycosyl chemistry theory. In terms of research on the active ingredients with anti-aging activities in the skin, there are numerous reports on related products in clinical studies on human subjects, animal experiments, and experimental studies on cell cultures, with a variety of types. Most of the compounds against skin aging are sourced from natural products and their action mechanisms are mainly related to scavenging oxygen free radicals and enhancing antioxidant defenses. This review provides important references for the future research of skin aging and the development of related products. Although there is a great progress in skin aging including related active ingredients, ideal compounds or products are still lacking and need to be further validated. New mechanisms of skin aging, new active ingredients sourced from natural and artificial products, and new pharmaceutical forms including further clinical validations should be further investigated in the future.

In the field of metallurgy, the timely and accurate detection of surface defects on metallic materials is a crucial quality control task. However, current defect detection approaches face challenges with large model parameters and low detection rates. To address these issues, this paper proposes a lightweight recognition model for surface damage on steel strips, named LSD-YOLOv5. First, we design a shallow feature enhancement module to replace the first Conv structure in the backbone network. Second, the Coordinate Attention mechanism is introduced into the MobileNetV2 bottleneck structure to maintain the lightweight nature of the model. Then, we propose a smaller bidirectional feature pyramid network (BiFPN-S) and combine it with Concat operation for efficient bidirectional cross-scale connectivity and weighted feature fusion. Finally, the Soft-DIoU-NMS algorithm is employed to enhance the recognition efficiency in scenarios where targets overlap. Compared with the original YOLOv5s, the LSD-YOLOv5 model achieves a reduction of 61.5% in model parameters and a 28.7% improvement in detection speed, while improving recognition accuracy by 2.4%. This demonstrates that the model achieves an optimal balance between detection accuracy and speed, while maintaining a lightweight structure.

Diabetic foot infection (DFI) is a common complication in diabetes patients, with foot infections being the leading cause of amputations. Staphylococcus aureus is frequently found in diabetic foot infections, of which methicillin-resistant Staphylococcus aureus (MRSA) has become a major clinical and epidemiological challenge. Since MRSA strains are resistant to most β-lactam antibiotics, and also partially resistant to other antibiotics, treatment is difficult and costly. The emergence of drug-resistant bacteria often arises from overuse or misuse of antibiotics. Clinically, canagliflozin is commonly used for the treatment of type 2 diabetes. On this basis, we investigated the antibacterial activity and mechanism of canagliflozin against MRSA, with the aim to discover novel functions of canagliflozin and provide new insights for the treatment of MRSA. Using the microbroth dilution method to determine the half maximal inhibitory concentration of drugs, we found that canagliflozin not only can inhibit the growth of methicillin-sensitive Staphylococcus aureus (MSSA) but also exhibits antibacterial activity against MRSA. The IC50 values, at approximately 56.01 μM and 57.60 μM, were almost the same. At 12 h, canagliflozin showed a significant antibacterial effect against MRSA at and above 30 μM. In addition, its combined use with penicillin achieved better antibacterial effects, which were increased by about three times. Additive antibacterial activity (FICI = 0.69) was found between penicillin and canagliflozin, which was better than that of doxycycline and canagliflozin (FICI = 0.95). Canagliflozin also affected bacterial metabolic markers, such as glucose, ATP, and lactic acid. The results of crystal violet staining indicate that canagliflozin disrupted the formation of bacterial biofilm. Our electron microscopy results showed that canagliflozin distorted the bacterial cell wall. The results of RT-PCR suggest that canagliflozin down-regulated the expressions of biofilm-related gene (clfA, cna, agrC, mgrA, hld) and methicillin-resistance gene (mecA), which was related to MRSA. Molecular docking also indicated that canagliflozin affected some interesting targets of MRSA, such as the sarA, crtM and fnbA proteins. In conclusion, canagliflozin exhibits antibacterial activity against MRSA by affecting bacterial metabolism, inhibiting its biofilm formation, distorting the bacterial cell wall, and altering the gene expression of biofilm formation and its virulence. Our study reveals the antibacterial activity of canagliflozin against MRSA, providing a new reference for treating diabetic foot infections.

Abstract The recent boom in flexible and wearable electronics requires their power sources not only to be adequately compact but also could undergo extreme deformation without significant degradation in performance. Here, flexible and tailorable quasi‐solid‐state microsized Ag/Zn batteries (micro‐AZBs) were designed by combining mask‐assisted spray printing and electrochemical deposition strategies. The micro‐AZBs display ultrastable output voltage, excellent energy, and power densities, as well as stable cycling performance. Furthermore, the micro‐AZBs with desired shapes can be designed in series or in parallel on a flexible chip to output improved voltage or current with the internal connection. More importantly, the microelectrodes could be sprayed on various substrates. Flexible micro‐AZBs could be achieved on flexible substrates and tailorable micro‐AZBs are obtained when they are fabricated on clothes. They exhibit stable electrochemical performance even under bending or cutting states. The novel design of such quasi‐solid‐state micro‐AZBs would pave a way for the miniaturization and integration of energy storage devices.

BackgroundThis study aimed to investigate the hypothesis that specific pattern of myocardial work (MW) distribution in patients with acute anterior ST-segment elevation myocardial infarction (STEMI) could provide prognostic value for predicting left ventricular (LV) remodeling.MethodsA total of 98 first anterior wall STEMI patients treated with primary percutaneous coronary intervention [85 men (86.7%), mean age: 58 ± 12 years] were enrolled. Transthoracic echocardiography was performed 24–72 h after angioplasty and during 3-month follow-up. MW was estimated from the left ventricular pressure–strain loop derived from speckle tracking echocardiography and simultaneous noninvasive brachial artery cuff pressure. The primary endpoint was early LV remodeling, defined as an increase in LV end-diastolic volume ≥20% compared with baseline at 3 months after STEMI. Major adverse cardiac events and combined clinical outcomes were recorded.ResultsLV remodeling was present in 32 patients (33%), who exhibited lower global and culprit-regional work index (WI), constructive work (CW), work efficiency (WE), and specifically, greater differences of WE (delta-WE) and CW (delta-CW) between the culprit and non-culprit region than those without LV remodeling both at the acute phase and follow-up (all P < 0.0125). During follow-up, all global and regional WI, CW, and WE were improved (P < 0.0125 compared with baseline), with less improvement in patients with LV remodeling. In multivariate analysis, baseline delta-WE (odds ratio: 2.304; 95% CI: 1.093–4.856, P = 0.028) and peak troponin I level (odds ratio: 1.035; 95%CI: 1.008–1.063, P = 0.010) were independently associated with early LV remodeling. Patients with greater delta-WE at baseline were associated with a higher incidence of heart failure and combined clinical outcomes during follow-up.ConclusionAfter reperfused acute anterior STEMI, patients with LV remodeling presented with more inhomogeneous MW distribution. The absolute difference of WE between culprit and non-culprit territory at the acute phase is an independent predictor for early LV remodeling.Clinical Trial Registrationwww.ClinicalTrials.gov, identifier: NCT05107102.

With the development of convolutional neural network, video super-resolution algorithm has achieved remarkable success. Because the dependence between frames is complex, traditional methods lack the ability to model the complex dependence, and it is difficult to estimate and compensate the motion accurately in the process of video super-resolution reconstruction. Therefore, a reconstruction network based on optical flow residuals is proposed. In low resolution space, the dense residual network is used to obtain the complementary information of adjacent video frames, and then the optical flow of high-resolution video frames is predicted through the pyramid structure, and then the low resolution video frames are transformed into high-resolution video frames through the sub-pixel convolution layer, The high-resolution video frame is compensated with the predicted high-resolution optical flow. Finally, it is input into the super-resolution fusion network to get better effect. A new loss function training network is proposed to better constrain the network. Experimental results on public data sets show that the reconstruction effect is improved in PSNR, structural similarity and subjective visual effect.

Rechargeable aqueous batteries are promising for potential large-scale energy storage due to their high safety and low cost. Here the authors analyse a zinc chloride based low-temperature electrolyte for improving practicability of the aqueous batteries.

Abstract Background The original version of Victorian Institute of Sport Assessment-Patella Questionnaire (VISA-P) is developed in English, and aimed to assess the severity of patellar tendinopathy symptoms. Before used in China, it should be translated to Chinese version. Objectives Our aim is to make a translation/cross-culturally adaption for the VISA-P into simplified Chinese version (VISA-PC). And primarily validate the VISA-PC in Chinese speaking population. Methods The translation process of VISA-P questionnaire into simplified Chinese version (VISP-PC) followed the International recognized guideline. Cross-cultural adaptation was carried out with a clinical measurement study. A total of 128 projects which consisted 33 healthy students, 39 patients with patellar tendinopathy and 56 military students (receive military training as at-risk population) were included into this study. Internal consistency was evaluated with Cronbach’s alpha, and test-retest reliability was assessed with intraclass correlation coefficients (ICCs). Construct validity and floor and ceiling effects were also tested. Results The scores were 95.84 ± 5.97 of healthy group, 91.87 ± 9.03 of at-risk group, 62.49 ± 11.39 of pathological group. There is no ceiling and floor effect of VISA-PC. The Cronbach’s alpha (0.895) and ICC (0.986) values showed good internal consistency and reliability. There were high correlations between VISA-PC and Kujala patellofemoral score (r = 0.721). VISA-PC score also had good correlation with the relevant SF-36 items. Conclusion The VISA-PC was well translated into simplified Chinese version (VISA-PC), which is reliable and valid for Chinese-speaking patients with patellar tendinopathy. Level of evidence II.

Abstract Background Breast cancer (BC) is one of the malignant solid tumors with the highest morbidity in the world. Currently, the therapeutic outcome of different types of treatment can be unsatisfactory. Novel lncRNA biomarkers in BC remains to be further explored. Methods Different expression of lncRNAs among BC tissues and adjacent normal tissues were identified with microarray analyses. A series of in vivo and in vitro gain-of-function laboratory procedures were conducted to study the biological functions of IGBP1-AS1. The prognostic effects on IGBP1-AS1 survival were evaluated by using in situ hybridization and survival analysis. In addition, other experiments including RNA pull down analysis, RNA immunoprecipitation, luciferase reporter assays, and chromatin immunoprecipitation as well as validating assays conducted in vivo were applied to identify the target and regulatory mechanisms of IGBP1-AS1. Results Significant down-regulation of IGBP1-AS1 was discovered in the cell lines and tissues of BC. With respect to its biological function, overexpression of IGBP1-AS1 had inhibitory effects on the invasion and proliferation of BC cells in vivo as well as in vitro. Analysis of the samples obtained from BC patients indicated a positive effect of IGBP1-AS1 on survival outcomes. LncRNA IGBP1-AS1/miR-24-1/ZIC3 axis as a loop can regulate the proliferation and invasion of BC cells. Conclusions IGBP1-AS1 could have inhibitory impact on the invasion and proliferation of BC and may serve as a promising biomarker for BC.

Self-charging power systems integrating energy generation and storage are receiving consideration attention. Here the authors report an aqueous Zn-ion battery that can be self-recharged by the spontaneous redox reaction between cathode and oxygen from ambient environment without external power supply.