Search

With the rapid growth of China's space industry, long-term manned space missions face challenges from the complex space environment, posing risks to human health. Aerospace medicine, a key field, addresses these risks by researching the impacts of space on biochemical changes, cognitive abilities, and immune systems. This article reviews China's aerospace medicine research, summarizing efforts from various institutions and offering insights for future developments in the field. [ABSTRACT FROM AUTHOR]

An object’s six-degree-of-freedom (6DoF) pose information has great importance in various fields. Existing methods of pose estimation usually detect two-dimensional (2D)-three-dimensional (3D) feature point pairs, and directly estimates the pose information through Perspective-n-Point (PnP) algorithms. However, this approach ignores the spatial association between pixels, making it difficult to obtain high-precision results. In order to apply pose estimation based on deep learning methods to real-world scenarios, we hope to design a method that is robust enough in more complex scenarios. Therefore, we introduce a method for 3D object pose estimation from color images based on farthest point sampling (FPS) and object 3D bounding box. This method detects the 2D projection of 3D feature points through a convolutional neural network, matches it with the 3D model of the object, and then uses the PnP algorithm to restore the feature point pair to the object pose. Due to the global nature of the bounding box, this approach can be considered effective even in partially occluded or complex environments. In addition, we propose a heatmap suppression method based on weighted coordinates to further improve the prediction accuracy of feature points and the accuracy of the PnP algorithm in solving the pose position. Compared with other algorithms, this method has higher accuracy and better robustness. Our method yielded 93.8% of the ADD(-s) metrics on the Linemod dataset and 47.7% of the ADD(-s) metrics on the Occlusion Linemod dataset. These results show that our method is more effective than existing methods in pose estimation of large objects. [ABSTRACT FROM AUTHOR]

Background and Aim: Early whitish gastric neoplasms can be easily misdiagnosed; differential diagnosis of gastric whitish lesions remains a challenge. We aim to build a deep learning (DL) model to diagnose whitish gastric neoplasms and explore the effect of adding domain knowledge in model construction. Methods: We collected 4558 images from two institutions to train and test models. We first developed two sole DL models (1 and 2) using supervised and semi‐supervised algorithms. Then we selected diagnosis‐related features through literature research and developed feature‐extraction models to determine features including boundary, surface, roundness, depression, and location. Then predictions of the five feature‐extraction models and sole DL model were combined and inputted into seven machine‐learning (ML) based fitting‐diagnosis models. The optimal model was selected as ENDOANGEL‐WD (whitish‐diagnosis) and compared with endoscopists. Results: Sole DL 2 had higher sensitivity (83.12% vs 68.67%, Bonferroni adjusted P = 0.024) than sole DL 1. Adding domain knowledge, the decision tree performed best among the seven ML models, achieving higher specificity than DL 1 (84.38% vs 72.27%, Bonferroni adjusted P < 0.05) and higher accuracy than DL 2 (80.47%, Bonferroni adjusted P < 0.001) and was selected as ENDOANGEL‐WD. ENDOANGEL‐WD showed better accuracy compared with 10 endoscopists (75.70%, P < 0.001). Conclusions: We developed a novel system ENDOANGEL‐WD combining domain knowledge and traditional DL to detect gastric whitish neoplasms. Adding domain knowledge improved the performance of traditional DL, which provided a novel solution for establishing diagnostic models for other rare diseases potentially. [ABSTRACT FROM AUTHOR]

Keypoint detector has achieved satisfactory performance in facial recognition and computer vision-related fields. However, convolutional neural network are somewhat limited for capturing global information, which greatly affects the performance of the detector. This paper proposes an efficient solution which obtains additional global information at a minimal costs. The framework is built upon a representative one-stage keypoint-based detector named CenterNet. The global keypoint network(GKPNet) approach forms a larger receptive field by using non-local modules to obtain more information than stacking multiple convolution modules. Feature pyramid network(FPN) was improved to extract multi-scale information and fuse low-level detail information to enhance the detection of small objects. The proposed approach is efficient and achieve 80.3% average precision on the Pascal VOC validation dataset, thus outperforms the CenterNet detector at least 1.6%. With a higher inference speed, GKPNet demonstrates performance comparable to that of the two-stage detectors and thereby provides a further avenue for anchor-free object detection. [ABSTRACT FROM AUTHOR]

As the largest terrestrial organic carbon pool, soil organic carbon (SOC) plays an important role in the global carbon cycle, but it is easily affected by land use and climate change. The Huang-Huai-Hai Plain (HHHP) in China, which is dominated by dry farming, is experiencing rapid farmland loss and gain (farmland use transition), which may cause drastic changes in SOC storage. To clarify the effects of farmland use transition on SOC in dry farming areas, this study adopted a land use transition matrix and spatial analyst tool to explore the characteristics of farmland use transition and its effects on SOC content and stocks in the 200 cm soil layer in the HHHP from 2000 to 2020. The results showed that the farmland use transition in this area during that time period resulted in a net decrease of 16.06 × 103 km2 of farmland, of which urban built-up land and rural settlements led to a net reduction of farmland by 9.74 × 103 km2 and 6.43 × 103 km2, respectively, which was mainly affected by climate, topography, and economic factors. In addition, the farmland use transition resulted in a net increase in SOC storage of 6.13 Tg C, contributing 44.32% of the net increase. This is likely because the change in land use type led to a change in soil bulk density and soil gravel content while altering the SOC content, which in turn affected the SOC stock. This study has important implications for addressing global climate change and maintaining sustainable agricultural resources. [ABSTRACT FROM AUTHOR]

The sustainable utilization of regional cultivated land systems in the Yangtze River Delta (YRD) region over the past 40 years has been severely impacted by rapid urbanization processes. Improving the eco-efficiency of cultivated land use (ECLU) plays a significant role in achieving the sustainable utilization of farmland and high-quality development of agriculture and rural areas. In this study, the spatial–temporal features and influencing factors of the ECLU in the YRD are investigated by various methods, such as a super-efficient SBM model, hot spot analysis, Dagum Gini coefficient, and panel tobit model. The findings indicate the following: the ECLU showed an overall high level from 2000 to 2020; the ECLU varied significantly over time and space in the YRD. The ECLU presented obvious spatial agglomeration in the YRD: southern regions exhibited a concentration of cold spots, while hot spots were primarily found in the east and north of the YRD. The trend of regional differences in ECLU during the research period fluctuated upwards in the YRD, and the density difference super-variable was the main source of regional differences. Increases in urbanization level and GDP per capita contributed to ECLU enhancement in the YRD, and agricultural intensity levels and agricultural industrial structures played a negative role in ECLU improvement. Finally, we suggest that different regions should adapt to local conditions, scientifically and reasonably allocate cultivated land production resources, and promote the coordinated improvement of ECLU. This study could provide a reference for policymakers to formulate better decisions on cultivated land utilization and management. [ABSTRACT FROM AUTHOR]

The recycling of dyes from dye wastewater is one of the most challenging problems in wastewater treatment. In this study, a pseudo‐polyrotaxane cyclodextrin based PVA/poly (acrylamide‐co‐acrylic acid) hydrogel was prepared by UV‐initiated polymerization. The network structure of the hydrogel and the performance on the dye absorption were adjusted by controlling the content of cyclodextrin. The study was mainly focused on the absorption of methylene blue (MB) in different environments, selectivity of absorption in mixed solutions and the cyclic absorption behavior. At room temperature, the absorption efficiency of this hydrogel for MB and methylene green reached 91.37% and 94.23%, respectively. In addition, the hydrogel exhibited highly selective absorption towards MB in mixed dye solutions. In the absorption‐desorption cyclic experiments, a more cost‐effective and environmental friendly solvent, a mixture of ethanol and water, was used, and after ten cycles, the highest absorption efficiency was basically maintained. Hence, the hydrogel is expected to be a candidate for more efficient and economical absorbent material in dye wastewater treatment. [ABSTRACT FROM AUTHOR]

Purpose: The numerous first-line treatment regimens for human epidermal growth factor receptor 2 (HER2)-positive advanced breast cancer (ABC) necessitate a comprehensive evaluation to inform clinical decision-making. We conducted a Bayesian network meta-analysis (NMA) to compare the efficacy and safety of different interventions. Methods: We systematically searched for relevant randomized controlled trials (RCTs) in Pubmed, Embase, Cochrane Library and online abstracts from inception to June 1, 2023. NMA was performed to calculate and analyze progression-free survival (PFS), overall survival (OS), objective response rate (ORR), and adverse events of grade 3 or higher (≥ 3 AEs). Results: Out of the 10,313 manuscripts retrieved, we included 28 RCTs involving 11,680 patients. Regarding PFS and ORR, the combination of trastuzumab with tyrosine kinase inhibitors (TKIs) was more favorable than dual-targeted therapy. If only using trastuzumab, combination chemotherapy is superior to monochemotherapy in terms of PFS. It is important to note that the addition of anthracycline did not result in improved PFS. For patients with hormone receptor-positive HER2-positive diseases, dual-targeted combined with endocrine therapy showed better benefit in terms of PFS compared to dual-targeted alone, but it did not reach statistical significance. The comprehensive analysis of PFS and ≥ 3 AEs indicates that monochemotherapy combined with dual-targeted therapy still has the optimal balance between efficacy and safety. Conclusion: Monochemotherapy (Docetaxel) plus dual-target (Trastuzumab and Pertuzumab) therapy remains the optimal choice among all first-line treatment options for ABC. The combination of trastuzumab with TKIs (Pyrotinib) demonstrated a significant improvement in PFS and ORR, but further data are warranted to confirm the survival benefit. [ABSTRACT FROM AUTHOR]

Background: Double-balloon enteroscopy (DBE) is a standard method for diagnosing and treating small bowel disease. However, DBE may yield false-negative results due to oversight or inexperience. We aim to develop a computer-aided diagnostic (CAD) system for the automatic detection and classification of small bowel abnormalities in DBE. Design and methods: A total of 5201 images were collected from Renmin Hospital of Wuhan University to construct a detection model for localizing lesions during DBE, and 3021 images were collected to construct a classification model for classifying lesions into four classes, protruding lesion, diverticulum, erosion & ulcer and angioectasia. The performance of the two models was evaluated using 1318 normal images and 915 abnormal images and 65 videos from independent patients and then compared with that of 8 endoscopists. The standard answer was the expert consensus. Results: For the image test set, the detection model achieved a sensitivity of 92% (843/915) and an area under the curve (AUC) of 0.947, and the classification model achieved an accuracy of 86%. For the video test set, the accuracy of the system was significantly better than that of the endoscopists (85% vs. 77 ± 6%, p < 0.01). For the video test set, the proposed system was superior to novices and comparable to experts. Conclusions: We established a real-time CAD system for detecting and classifying small bowel lesions in DBE with favourable performance. ENDOANGEL-DBE has the potential to help endoscopists, especially novices, in clinical practice and may reduce the miss rate of small bowel lesions. [ABSTRACT FROM AUTHOR]

Analysis of T‐cell receptor (TCR) repertoires in different stages of hepatocellular carcinoma (HCC) might help to elucidate its pathogenesis and progression. This study aimed to investigate TCR profiles in liver biopsies and peripheral blood mononuclear cells (PBMCs) in different Barcelona Clinic liver cancer (BCLC) stages of HCC. Ten patients in early stage (BCLC_A), 10 patients in middle stage (BCLC_B), and 10 patients in late stage (BCLC_C) cancer were prospectively enrolled. The liver tumor tissues, adjacent tissues, and PBMCs of each patient were collected and examined by TCR β sequencing. Based on the ImMunoGeneTics (IMGT) database, we aligned the V, D, J, and C gene segments and identified the frequency of CDR3 sequences and amino acids sequence. Diversity of TCR in PBMCs was higher than in both tumor tissues and adjacent tissues, regardless of BCLC stage and postoperative recurrence. TCR clonality was increased in T cells from peripheral blood in advanced HCC, compared with the early and middle stages. No statistical differences were observed between different BCLC stages, either in tumors or adjacent tissues. TCR clonality revealed no significant difference between recurrent tumor and non‐recurrent tumor, therefore PBMCs was better to be representative of TCR characteristics in different stages of HCC compared to tumor tissues. Clonal expansion of T cells was associated with low risk of recurrence in HCC patients. [ABSTRACT FROM AUTHOR]

Objective: The effectiveness and security of radiofrequency ablation (RFA) in combination with toripalimab (anti‐PD‐1) for the treatment of recurrent hepatocellular carcinoma (HCC) was studied in this article. Methods: Total of 40 patients were enrolled in the study between September 2019 and November 2021. Data follow‐up ends in April 2022. The study's main focus is on recurrence free survival (RFS), while the secondary objectives was safety. Chi‐square tests, Kaplan‐Meier, and Cox proportional hazards models were utilized to analyze the data. Results: The median follow‐up period was 21.40 months, and the median RFS was 15.40 months in the group that received combination therapy, which was statistically significantly different (HR: 0.44, p = 0.04) compared with the RFA group (8.2 months). RFS rates (RFSr) at 6, 12 and 18 months in the combination therapy groups and RFA groups were 80% vs 65%, 62.7% vs 35% and 48.7% vs 18.8%, respectively. Between the two groups, significant difference of RFSr was found at 18 months (p = 0.04). No statistical differences were observed between the two groups in terms of safeness (p > 0.05). The subgroup analysis indicated that the combination of RFA and anti‐PD‐1 led to better RFS than RFA alone. Moreover, patients benefited more from combination therapy in the groups younger than 60 years (HR: 0.26, p = 0.018), male (HR: 0.32, p = 0.028) and Child‐Pugh grade A (HR: 0.38, p = 0.032). Conclusions: Combining RFA with anti‐PD‐1 showed improved RFS and was deemed safe for patients with recurrent HCC who had previously undergone RFA treatment alone. [ABSTRACT FROM AUTHOR]

Polyaniline is the most famous conducting polymer and also a promising organic cathode material for rechargeable batteries, however, it has demonstrated poor utilization of its theoretical capacity (294 mAh g−1) and inferior cycling stability in previous studies. Herein, for the first time, its fully reduced form, i.e., leucoemeraldine base (LB), is studied as an alternative to the commonly used emeraldine salt and base (ES and EB). For the three different forms, the precise structures are carefully determined, and the electrochemical performance are systematically investigated. Within 2.0−4.3 V, LB realizes almost full capacity utilization (92%) that is much superior to those of ES and EB. Within 2.0−4.2 V, it shows both high reversible capacity (277 mAh g−1) and cycling stability (84% capacity retention after 1000 cycles). The combination of electrochemical analysis, density functional theory calculation, and ex situ characterization reveals that the capacity utilization is positively associated with the pristine proportion of ─NH─ groups, and the capacity fading is caused by the irreversible electrochemical deprotonation at high charge potential. This work promotes both the electrochemical performance and mechanistic understanding of polyaniline to a new stage, towards practical application in energy storage devices as a low‐cost, high‐performance, sustainable, and green cathode material. [ABSTRACT FROM AUTHOR]

Effects of lake evaporation (EW) on basin evapotranspiration (ETB) and lake water storage change (LWSC) at lake‐basin scale have never been reported for most basins on the inner Tibetan Plateau (IB). In this study, EW of 118 large lakes in 95 closed lake‐basins were estimated, and its effects on ETB and LWSC over 2001–2018 were examined using a derivative‐guided framework from the aspects of EW amount, rate, trend slope and inter‐annual variability. We found that EW amount has a high effect (17%) on regional ETB amount compared to the average lake area ratio (α) (∼5%), and the effect has increased significantly (2%/10 a). The spatial pattern of the effect is mainly controlled by α, and the increasing trend of α (0.6%/10 a) also dominated the increasing trend in regional ETB rate (0.30 mm/a) though with large spatial heterogeneity. Variance in α and EW rate have a minor effect (∼3%) on ETB variance, especially for the basins with lower α. The combination of quasi lake inflow (RL, 41%) and lake surface precipitation (PW, 16%) offset the depletion of EW (−43%), resulting in the surplus of regional lake water (LWSC > 0). The increase in EW mount, which is mainly from lake area expansion (90%), caused a decreasing trend in LWSC (i.e., slower growth rate) with a contribution of −59%. This suggests a negative feedback between lake area expansion and EW amount in the IB, and the feedback may continue with the predicted area increases. Key Points: Amount of evaporation for 118 lakes was estimated using two open water evaporation algorithms with annual lake areaA new derivative‐guided framework was presented to examine lake effects on basin evapotranspiration and lake water storage changeBasin scale lake inflow of 95 ungauged lake‐basins was estimated based on lake water balance [ABSTRACT FROM AUTHOR]

Background: Artificial intelligence (AI) performed variously among test sets with different diversity due to sample selection bias, which can be stumbling block for AI applications. We previously tested AI named ENDOANGEL, diagnosing early gastric cancer (EGC) on single-center videos in man–machine competition. We aimed to re-test ENDOANGEL on multi-center videos to explore challenges applying AI in multiple centers, then upgrade ENDOANGEL and explore solutions to the challenge. Methods: ENDOANGEL was re-tested on multi-center videos retrospectively collected from 12 institutions and compared with performance in previously reported single-center videos. We then upgraded ENDOANGEL to ENDOANGEL-2022 with more training samples and novel algorithms and conducted competition between ENDOANGEL-2022 and endoscopists. ENDOANGEL-2022 was then tested on single-center videos and compared with performance in multi-center videos; the two AI systems were also compared with each other and endoscopists. Results: Forty-six EGCs and 54 non-cancers were included in multi-center video cohort. On diagnosing EGCs, compared with single-center videos, ENDOANGEL showed stable sensitivity (97.83% vs. 100.00%) while sharply decreased specificity (61.11% vs. 82.54%); ENDOANGEL-2022 showed similar tendency while achieving significantly higher specificity (79.63%, p < 0.01) making fewer mistakes on typical lesions than ENDOANGEL. On detecting gastric neoplasms, both AI showed stable sensitivity while sharply decreased specificity. Nevertheless, both AI outperformed endoscopists in the two competitions. Conclusions: Great increase of false positives is a prominent challenge for applying EGC diagnostic AI in multiple centers due to high heterogeneity of negative cases. Optimizing AI by adding samples and using novel algorithms is promising to overcome this challenge. [ABSTRACT FROM AUTHOR]

The advent of self-powered arrays of tribological nanogenerators (TENGs) that harvest mechanical energy for data collection has ushered in a promising avenue for human motion monitoring. This emerging trend is poised to shape the future landscape of biomechanical study. However, when we try to monitor various regions of the foot across disparate environments simultaneously, it poses a number of problems, such as the lack of satisfactory waterproofing, suboptimal heat resistance, inaccurate monitoring capacity, and the inability to transmit data wirelessly. To overcome these issues, we have developed an array of sensors affixed to the insole's surface to adeptly monitor movement gait patterns and alert users to falls using self-powered triboelectric nanogenerators (TENGs). Each sensor cell on this sensor works as an individual air gap TENG (FWF-TENG), namely flexible, waterproof, and fast response, composed of an Ecoflex single-electrode array. Each FWF-TENG boasts a fast response time of 28 ms, which is sufficient to quickly monitor pressure changes during various badminton activities. Importantly, these sensors can persistently generate electrical signals at 70%RH humidity. Data obtained from these sensors can be transmitted to an upper computer intelligent terminal wirelessly through multi-grouped FHW-ENG sensing terminals in real time to achieve human–computer interaction applications, including motion technical determinations, feedback, and fall alerts. As a result, the interconnected TENG arrays have broad potential applications, including gait rehabilitation monitoring, motion technique identification, and fall alarm applications. [ABSTRACT FROM AUTHOR]

Background: This protocol is for a multi-centre randomised controlled trial to determine whether the computer-aided system ENDOANGEL-GC improves the detection rates of gastric neoplasms and early gastric cancer (EGC) in routine oesophagogastroduodenoscopy (EGD). Methods: Study design: Prospective, single-blind, parallel-group, multi-centre randomised controlled trial. Settings: The computer-aided system ENDOANGEL-GC was used to monitor blind spots, detect gastric abnormalities, and identify gastric neoplasms during EGD. Participants: Adults who underwent screening, diagnosis, or surveillance EGD. Randomisation groups: 1. Experiment group, EGD examinations with the assistance of the ENDOANGEL-GC; 2. Control group, EGD examinations without the assistance of the ENDOANGEL-GC. Randomisation: Block randomisation, stratified by centre. Primary outcomes: Detection rates of gastric neoplasms and EGC. Secondary outcomes: Detection rate of premalignant gastric lesions, biopsy rate, observation time, and number of blind spots on EGD. Blinding: Outcomes are undertaken by blinded assessors. Sample size: Based on the previously published findings and our pilot study, the detection rate of gastric neoplasms in the control group is estimated to be 2.5%, and that of the experimental group is expected to be 4.0%. With a two-sided α level of 0.05 and power of 80%, allowing for a 10% drop-out rate, the sample size is calculated as 4858. The detection rate of EGC in the control group is estimated to be 20%, and that of the experiment group is expected to be 35%. With a two-sided α level of 0.05 and power of 80%, a total of 270 cases of gastric cancer are needed. Assuming the proportion of gastric cancer to be 1% in patients undergoing EGD and allowing for a 10% dropout rate, the sample size is calculated as 30,000. Considering the larger sample size calculated from the two primary endpoints, the required sample size is determined to be 30,000. Discussion: The results of this trial will help determine the effectiveness of the ENDOANGEL-GC in clinical settings. Trial registration: ChiCTR (Chinese Clinical Trial Registry), ChiCTR2100054449, registered 17 December 2021. [ABSTRACT FROM AUTHOR]

Organic cathode materials (OCMs) have been widely applied in aqueous rechargeable zinc batteries (ARZBs), but there are still many novel structures to be explored for better electrochemical performance and clearer mechanism. Herein, we have studied an organic biological dye, namely thionin (Thn‐CH3COO), as a bipolar‐type OCM for ARZBs based on its electroactive phenothiazine unit. In the optimal electrolyte of 2 M Zn(CF3SO3)2, Thn‐CH3COO exhibited the lowest solubility and thus the highest cycling stability (94 % capacity retention after 100 cycles), with a reversible capacity of 162 mAh g−1 (the theoretical value is 186 mAh g−1) and a discharge plateau at ∼0.8 V vs. Zn2+/Zn. Various characterization and DFT calculations have revealed that both CH3COO− and CF3SO3− anions and H+ cations participated the p‐type and n‐type reactions, respectively. In brief, the novel structure, competitive performance, and exhaustive mechanism investigation will facilitate the further development of ARZBs based on OCMs. [ABSTRACT FROM AUTHOR]

White light endoscopy is the most pivotal tool for detecting early gastric neoplasms. Previous artificial intelligence (AI) systems were primarily unexplainable, affecting their clinical credibility and acceptability. We aimed to develop an explainable AI named ENDOANGEL-ED (explainable diagnosis) to solve this problem. A total of 4482 images and 296 videos with focal lesions from 3279 patients from eight hospitals were used for training, validating, and testing ENDOANGEL-ED. A traditional sole deep learning (DL) model was trained using the same dataset. The performance of ENDOANGEL-ED and sole DL was evaluated on six levels: internal and external images, internal and external videos, consecutive videos, and man–machine comparison with 77 endoscopists in videos. Furthermore, a multi-reader, multi-case study was conducted to evaluate the ENDOANGEL-ED's effectiveness. A scale was used to compare the overall acceptance of endoscopists to traditional and explainable AI systems. The ENDOANGEL-ED showed high performance in the image and video tests. In man–machine comparison, the accuracy of ENDOANGEL-ED was significantly higher than that of all endoscopists in internal (81.10% vs. 70.61%, p < 0.001) and external videos (88.24% vs. 78.49%, p < 0.001). With ENDOANGEL-ED's assistance, the accuracy of endoscopists significantly improved (70.61% vs. 79.63%, p < 0.001). Compared with the traditional AI, the explainable AI increased the endoscopists' trust and acceptance (4.42 vs. 3.74, p < 0.001; 4.52 vs. 4.00, p < 0.001). In conclusion, we developed a real-time explainable AI that showed high performance, higher clinical credibility, and acceptance than traditional DL models and greatly improved the diagnostic ability of endoscopists. [ABSTRACT FROM AUTHOR]

Background: White light (WL) and weak-magnifying (WM) endoscopy are both important methods for diagnosing gastric neoplasms. This study constructed a deep-learning system named ENDOANGEL-MM (multi-modal) aimed at real-time diagnosing gastric neoplasms using WL and WM data. Methods: WL and WM images of a same lesion were combined into image-pairs. A total of 4201 images, 7436 image-pairs, and 162 videos were used for model construction and validation. Models 1–5 including two single-modal models (WL, WM) and three multi-modal models (data fusion on task-level, feature-level, and input-level) were constructed. The models were tested on three levels including images, videos, and prospective patients. The best model was selected for constructing ENDOANGEL-MM. We compared the performance between the models and endoscopists and conducted a diagnostic study to explore the ENDOANGEL-MM's assistance ability. Results: Model 4 (ENDOANGEL-MM) showed the best performance among five models. Model 2 performed better in single-modal models. The accuracy of ENDOANGEL-MM was higher than that of Model 2 in still images, real-time videos, and prospective patients. (86.54 vs 78.85%, P = 0.134; 90.00 vs 85.00%, P = 0.179; 93.55 vs 70.97%, P < 0.001). Model 2 and ENDOANGEL-MM outperformed endoscopists on WM data (85.00 vs 71.67%, P = 0.002) and multi-modal data (90.00 vs 76.17%, P = 0.002), significantly. With the assistance of ENDOANGEL-MM, the accuracy of non-experts improved significantly (85.75 vs 70.75%, P = 0.020), and performed no significant difference from experts (85.75 vs 89.00%, P = 0.159). Conclusions: The multi-modal model constructed by feature-level fusion showed the best performance. ENDOANGEL-MM identified gastric neoplasms with good accuracy and has a potential role in real-clinic. [ABSTRACT FROM AUTHOR]

Farmland is the cornerstone of agriculture and is important for food security and social production. Farmland assessment is essential but traditional methods are usually expensive and slow. Deep learning methods have been developed and widely applied recently in image recognition, semantic understanding, and many other application domains. In this research, we used fully convolutional networks (FCN) as the deep learning model to evaluate farmland grades. Normalized difference vegetation index (NDVI) derived from Landsat images was used as the input data, and the China National Cultivated Land Grade Database within Jiangsu Province was used to train the model on cloud computing. We also applied an image segmentation method to improve the original results from the FCN and compared the results with classical machine learning (ML) methods. Our research found that the FCN can predict farmland grades with an overall F1 score (the harmonic mean of precision and recall) of 0.719 and F1 score of 0.909, 0.590, 0.740, 0.642, and 0.023 for non-farmland, level I, II, III, and IV farmland, respectively. Combining the FCN and image segmentation method can further improve prediction accuracy with results of fewer noise pixels and more realistic edges. Compared with conventional ML, at least in farmland evaluation, FCN provides better results with higher precision, recall, and F1 score. Our research indicates that by using remote sensing NDVI data, the deep learning method can provide acceptable farmland assessment without fieldwork and can be used as a novel supplement to traditional methods. The method used in this research will save a lot of time and cost compared with traditional means. [ABSTRACT FROM AUTHOR]

Background: Scarless endoscopic thyroidectomy (ET) is increasingly accepted by the growing amount of surgeons. The target of this study is to assess the efficacy and summarise the experiences of total areola approach for ET (TAAET). Subjects and Methods: TAAET was performed on 529 patients between January 2016 and October 2021. All operated patients were divided into two groups according to the chronological order. Demographic data, perioperative data and post-operative complications were collected to assess the effectiveness of TAAET. Results: Five hundred and twenty-eight patients were successfully treated with TAAET, while 1 case was converted to open surgery due to bleeding. The surgical approach consists of lobectomy or total thyroidectomy with or without central lymph node dissection. The post-operative pathology of 433 (81.9%) patients was diagnosed with T1 ~2N0M0. The average number of unilateral lymph node dissection was 7.72 ± 2.44 while the bilateral lymph node was 10.70 ± 3.72. In terms of complications, 38 cases had transient hoarseness, 28 cases had tetany and numbness, 3 cases had post-operative bleeding, 1 case had infection and 33 cases had subcutaneous fluid. There were statistically significant differences between the two groups with respect to transient hoarseness (P < 0.001), tetany and numbness (P = 0.005), intraoperative blood loss (P = 0.003) and operation time for malignant tumour (P < 0.001) because of the accumulation of surgical experience and the maturation of technology. Conclusions: TAAET which conforms to the anatomical pathway of open thyroidectomy is a safe, effective and feasible technique and is highly suitable for novices. [ABSTRACT FROM AUTHOR]

Stimuli-responsive fluorescent materials are ideal materials for paper anti-counterfeiting applications. However, the single responsiveness and the lacking of dynamics present the risk of being deciphered. Herein, we designed a series of cyanostilbene derivatives (ACNs) with fluorescence responses to acid or base. ACN1 with pyridine and hydroxyl groups exhibit dually responsive fluorescence "ON" in the solid state due to the ionization-enhanced intramolecular charge transfer (ICT) effect. Other ACNs with either pyridine or hydroxyl unit show only single responsiveness. Fluorescence papers (FPs) prepared by a simple dipping into the solutions of ACNs maintain the responsive fluorescence performance. FP1H with high ACN1 content exhibits time-dependent dynamic fluorescent colour changes by hydrogen chloride (HCl) vapour fumigation. The applications of paper anti-counterfeiting and information encryption are developed by combining ACN1 with other single-responsive ACNs. Moreover, a four-dimensional (4D) code with time-dependent information changes is designed. Our work provides new materials for the field of paper fluorescent anti-counterfeiting encryption. [ABSTRACT FROM AUTHOR]

Lake storage change serves as a unique indicator of natural climate change on the Tibetan Plateau (TP). However, comprehensive lake storage data, especially for lakes smaller than 10 km2, are still lacking in the region. In this dataset, we completed a census of annual relative lake volume (RLV) for 976 lakes, which are larger than 1 km2, on the endorheic basin of the Tibetan Plateau (EBTP) during 1989–2019 using Landsat imagery and digital terrain models. Our method first identifies individual lakes, determines their analysis extents and calculates annual lake area from Landsat imagery. It then derives lake area-elevation relationship, estimates lake surface elevation, and calculates RLV. Validation and comparison with several existing datasets indicate our data are more reliable and comprehensive. Our study complements existing lake datasets by providing a complete and long-term lake water volume change data for the region. Measurement(s) Relative lake volume Technology Type(s) Remote sensing image and DEM data Sample Characteristic - Environment endorheic lake Sample Characteristic - Location Tibetan Plateau [ABSTRACT FROM AUTHOR]

The Right to be Forgotten gives a data owner the right to revoke their data from an entity storing it. In the context of federated learning, the Right to be Forgotten requires that, in addition to the data itself, any influence of the data on the FL model must disappear, a process we call “federated unlearning.” The most straightforward and legitimate way to implement federated unlearning is to remove the revoked data and retrain the FL model from scratch. Yet the computational and time overhead associated with fully retraining FL models can be prohibitively expensive. In this article, we take the first step to comprehensively investigate the way to settle the unlearning paradigm in the context of federated learning. First, we define the problem of efficient federated unlearning, including its challenges and goals, and we identify three common types of federated unlearning requests: class unlearning, client unlearning, and sample unlearning. Based on those challenges and goals, a general pipeline is proposed for federated unlearning for the above three types of requests. We revisit how the training data affects the final FL model performance and thereby empowers the proposed framework with the reverse stochastic gradient ascent (SGA) and elastic weight consolidation (EWC). Various experiments are conducted to verify effectiveness of the proposed method in both aspects of unlearning efficacy and efficiency. We believe the proposed method will perform as an essential component for future machine unlearning systems. [ABSTRACT FROM AUTHOR]

In this article, a low-cost multistep finite control set model predictive current control (FCS-MPCC) using a dc link single current sensor is proposed for permanent magnet synchronous motor (PMSM). In order to reduce the system cost, the single dc link current sensor is used to reconstruct the three-phase current. Different from the current reconstruction technology of field-orientated control strategy, there are some problems of the existed current reconstruction technology applied for finite control set model predictive control (FCS-MPC). First, the optimal switching state of FCS-MPC in each cycle is not fixed, and only contains at most one phase current information for reconstruction, which will cause the reconstruction failure. Therefore, a multiperiod sampling method is proposed to obtain the different two-phase current information to reconstruction. Second, the uncertainty of the two-phase reconstruction current interval will lead to current error, so this article proposes a variable period compensation method to solve this problem. Moreover, in order to improve the system closed-loop performance without significantly increasing the computational cost and enhance the system reliability, a low-cost multistep FCS-MPCC strategy based on the reconstructed three-phase current is proposed for PMSM. Finally, simulation and experimental results validate the effectiveness of the low-cost multistep FCS-MPCC method using a dc link single current sensor reconstruction for PMSM. [ABSTRACT FROM AUTHOR]

Purpose: This retrospective study evaluated the efficacy, safety, and factors affecting the prognosis of transarterial chemoembolisation with irinotecan-eluting beads with CalliSpheres (DEB-TACE) for intrahepatic cholangiocarcinoma (ICC). Materials and Methods: We retrospectively collected data on 39 patients with unresectable ICC who received DEB-TACE therapy. We assessed the indicators of tumour response, progression-free survival (PFS), overall survival (OS), and the incidence of adverse events. PFS and OS were analysed using Kaplan–Meier curves, while Cox analysis was used to identify factors affecting the prognosis. Results: The 3-month objective response rate (ORR) and disease control rate (DCR) of the 39 patients with unresectable ICC were 35.9% and 56.4%, respectively, while the 6-month ORR and DCR were 23.0% and 40.9%, respectively. The median OS and PFS were 11.0 months and 8.0 months, respectively. Cox analysis demonstrated that combined therapy (adjuvant sorafenib after DEB-TACE) and a low cancer antigen (CA) 125 level (≤ 35 U/ml) were independent favourable prognostic factors. Transient elevation of the aminotransferase level, nausea, vomiting, abdominal pain, fever, and hyper-bilirubinaemia were common adverse events in patients with unresectable ICC treated with DEB-TACE with CalliSphere beads (CBs). Hepatic abscess was the most serious complication, observed in one patient. Conclusions: DEB-TACE with CBs is a safe and well-tolerated therapy in patients with unresectable ICC with a low incidence of adverse events and relatively prolonged survival. Combined therapy and low CA125 are prognostic factors associated with longer survival. [ABSTRACT FROM AUTHOR]

The double pulse technology increases the energy transmission between the plasma plume and the target by coupling the laser beam, which greatly enhances the signal, reduces the detection limit of laser-induced breakdown spectroscopy (LIBS) and improves the ability of trace elemental analysis. In this paper, the emission characteristics of plasma in orthogonal double-pulse LIBS (DP-LIBS) are studied theoretically by using the hydrodynamics model, including the effects of pulse interval and spot position of the second laser pulse on the emission intensity of various species in the reheating mode. The results show that in the reheating mode, the pulse interval corresponding to the maximum intensity ratio of double pulse to single pulse occurs at 0.2–0.5 μs, while in the pre-ablation mode, it increases with the increase of pulse interval. According to the decrease of the number density of the background gas above the sample before the ablation pulse in the pre-ablation mode, the enhancement mechanism of spectral line intensity is explained from two aspects: plasma–plasma coupling effect and pressure effect. In addition, the spatial distribution and raising mechanism of plasma temperature in these modes are also explored. It shows that in the reheating mode, the plasma temperature is increased by directly absorbing laser energy, while in the pre-ablation mode, it is increased by reducing the energy loss between vapor plasma and gas plasma and weakening the shielding effect. The theoretical analysis of double pulse plasma provides a theoretical basis for the experimental research and application of DP-LIBS. [ABSTRACT FROM AUTHOR]

A few long noncoding RNAs (long ncRNAs, lncRNAs) exhibit trophoblast cell type-specific expression patterns and functional roles in mouse placenta. However, the cell- and stage-specific expression patterns and functions of most placenta-derived lncRNAs remain unclear. In this study, we explored mouse placenta-associated lncRNAs using a combined bioinformatic and experimental approach. We used the FANTOM5 database to survey lncRNA expression in mouse placenta and found that 1600012P17Rik (MGI: 1919275, designated P17Rik), a long intergenic ncRNA, was the most highly expressed lncRNA at gestational day 17. Polymerase chain reaction analysis confirmed that P17Rik was exclusively expressed in placenta and not in any of the adult organs examined in this study. In situ hybridization analysis revealed that it was highly expressed in spongiotrophoblast cells and to a lesser extent in glycogen trophoblast cells, including migratory glycogen trophoblast cells invading the decidua. Moreover, we found that it is a polyadenylated lncRNA localized mainly to the cytoplasm of these trophoblast cells. As these trophoblast cells also expressed the neighboring protein-coding gene, pappalysin 2 (Pappa2), we investigated the effects of P17Rik on Pappa2 expression using Pappa2-expressing MC3T3-E1 cells and found that P17Rik transfection increased the messenger RNA (mRNA) and protein levels of Pappa2. These results indicate that mouse placenta-specific lncRNA P17Rik modulates the expression of the neighboring protein-coding gene Pappa2 in spongiotrophoblast and glycogen trophoblast cells of mouse placenta during late gestation. [ABSTRACT FROM AUTHOR]

This article presents an improved equivalent input disturbance observer-based model predictive control (IEIDO-based MPC) scheme for position tracking control of a magnetic levitation system. It overcomes the problem of the position tracking performance degradation for the magnetic levitation system in the presence of time-varying disturbances. To enhance the accuracy of estimation, an IEIDO is first proposed to estimate both the system states and the time-varying equivalent input disturbance. The estimations of IEIDO are then integrated into the MPC design for output position prediction. Afterward, an explicit analytical form of the optimal predictive controller is obtained to achieve the optimized tracking performance, as well as the fine robustness against lumped time-varying equivalent input disturbance. Rigorous stability analysis shows that the closed-loop system is stable. Simulation and experimental results demonstrate the effectiveness of the proposed method as compared with the conventional EID and Luenberger observer-based integral MPC approaches. [ABSTRACT FROM AUTHOR]

The tyrosine kinase inhibitors (TKIs), including sorafenib, remain one first-line antitumor treatment strategy for advanced hepatocellular carcinoma (HCC). However, many problems exist with the current orally administered TKIs, creating a heavy medical burden and causing severe side effects. In this work, we prepared a novel microcrystalline formulation of sorafenib that not only achieved sustainable release and long action in HCC tumors but also relieved side effects, as demonstrated by fundus microcirculation imaging. The larger the size of the microcrystalline formulation of sorafenib particle, the slower the release rates of sorafenib from the tumor tissues. The microcrystalline formulation of sorafenib with the largest particle size was named as Sor-MS. One intratumor injection (once administration) of Sor-MS, but not Sor-Sol (the solution formulation of sorafenib as a control), could slow the release of sorafenib in HCC tumor tissues and in turn inhibited the in vivo proliferation of HCC or the expression of EMT/pro-survival–related factors in a long-acting manner. Moreover, compared with oral administration, one intratumor injection of Sor-MS not only facilitated a long-acting antitumor effect but also relieved side effects of sorafenib, avoiding damage to the capillary network of the eye fundus, as evidenced by fundus microcirculation imaging. Therefore, preparing sorafenib as a novel microcrystal formulation could facilitate a long-acting antitumor effect and relieve drug-related side effects. [ABSTRACT FROM AUTHOR]

Aiming to reduce the influence of system model parameter uncertainties for the DC‐DC buck converter control system with high performance requirement, a reduced‐order extended state observer based event‐triggered sliding mode control method (RESO‐ESMC) is proposed in this paper. First, a reduced‐order extended state observer is designed to estimate the system state and total disturbances, including load resistance disturbance and input voltage variation. Then, based on the estimation, the novel event triggered sliding mode controller is constructed for the DC‐DC buck converter system, aiming for the event triggered mechanism to avoid unnecessary computation. In addition, it should be noted that, unlike the extended state observer based sliding mode control method (ESO‐SMC) presented in [1], the proposed method in this paper uses a reduced‐order extended state observer, that is simple to implement and does not require the current sensor, which reduces the cost in practical applications. The stability of the closed‐loop system is also analyzed using Lyapunov stability theorem. Compared with re‐designed ESO‐SMC, which is also in current sensor‐less mode, simulation and experimental results show that the proposed control method performs better in transient and disturbance rejection, but the steady state performance is sacrificed. [ABSTRACT FROM AUTHOR]

A Click-based network function (NF) has significant advantages for pipeline development, including modularity, extensibility, and programmability. Despite these features, its internal architecture has unfortunately not kept up with some specific problems of the software upgrade. To motivate our article, we analyzed a series of use cases to identify the limitations of native Click. These limitations include the inefficiencies in modifying modules, integrating modules, and recovering states. To bridge the gap, we present three novel enhancements in our Click upgrade (Click-UP) system: 1) modular state abstraction refines each type of stateful operations as an atom operation and decouples it from the pipeline, letting separately managing logics for stateless operations and stateful operations become practical; 2) essential module integration manages dependencies between modules, avoiding shipping unnecessary modules with neutral functionalities to the target NF; and 3) local state migration migrates needed states seamlessly from the old NF to the target NF at local memory. Our evaluation demonstrates that Click-UP reduces the context code required for module modification by 12–81%, cutting down the NF integration time by 78–96% and the service disruption time by 76–93%, as compared to the software upgrade performance represented by native Click. [ABSTRACT FROM AUTHOR]

In order to reduce the influence of time-varying disturbances for magnetic levitation system, we propose a reduced-order generalized proportional integral observer (RGPIO) based continuous dynamic sliding mode control scheme for magnetic levitation system in this paper. Unlike the popular extended state observer (ESO), it could deal with constant or slowing varying disturbances from theoretical point of view, the reduced-order generalized proportional integral observer (RGPIO) is designed to estimate the time-varying disturbances and system states, then the dynamic sliding mode surface is developed and deduce a continuous sliding mode controller (CSMC) for magnetic levitation system. Compared with ESO based continuous sliding mode controller, the proposed method not only ensures the position tracking accuracy, but also obtain better time-varying disturbance reject ability. Simulation and experimental results are also given to verify the effectiveness. [ABSTRACT FROM AUTHOR]

For improving the convergence rate and time-varying disturbance rejection ability, an adaptive nonsingular terminal sliding mode controller based on disturbance compensation technique is proposed to control the position of magnetic levitation system in this article. First, the dynamical model of the magnetic levitation system is deduced, then a nonsingular terminal sliding mode control (NTSMC) is constructed. For reducing the chattering phenomenon, the time-varying disturbance estimation and compensation is cooperated into NTSMC controller using generalized proportional integral observer, the switching gain value could be chosen smaller, it could improve the system disturbance rejection, but the dynamic response is sacrificed to some extent. Thus, the adaptive NTSMC method is proposed for ensuring the dynamic and steady-state performance, the switching gain value could be tuned adaptively depending on the system states. When the system states are far away from the sliding mode surface, the gain value is large, else if the system states convergence to sliding mode surface, the value is small. Simulation and experimental results confirm the closed-loop performance both in dynamic response and disturbance attenuation, corresponding quantitative comparison could also show the advantages of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Although polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) are abundant around cities, few researchers have studied the complex concentrations and joint risks of these pollutants in urban surface soils containing diverse land uses. We collected 69 urban surface soil samples from roadside districts, green belts, public green space, commercial districts, and residential district in urban areas of Nanjing, China to determine the concentrations, distributions, deposition patterns, and joint risks of PAH and HM contaminants. No significant differences were found among the five studied land uses, but a wide range of PAH levels were found in these land uses, as these diverse land uses have similar PAH pollution sources. As these areas persistently generate high PAH levels by gasoline/diesel engine or coal combustion, the PAH distribution characteristics indicated that commercial centers or city centers are the most heavily contaminated sites. The distributions of black carbon and HMs, except for Pb, were found to be significantly correlated. Except for Cd and As, HM levels among diverse land uses also showed no significant differences, possibly stemming from the non‐point source pollution of these metals in the study areas. Factor analysis showed that 46.2% of the elevated pollutant concentrations resulted from combustion processes, 24.3% were caused by natural background fluctuations, and 11.9% resulted from non‐combustion processes. The studied PAHs and As presented low carcinogenic risks. Cd, Cu, Pb, and Zn depicted acceptable total non‐carcinogenic risks in all land uses; however, the risks associated with these HMs possessed detailed differences. [ABSTRACT FROM AUTHOR]

A Luenberger disturbance observer based control scheme for surface mounted permanent magnet synchronous motor (SPMSM) is proposed in this paper. First, an extended SPMSM model is given by considering the external disturbances and parameter mismatches. Second, a Luenberger observer is introduced to estimate the lumped disturbances in the speed and current loops, respectively. Third, based on the observed disturbances, a speed controller is designed, which is proved to be stable. Finally, an improved deadbeat-based predictive current control (DPCC) based on the estimated disturbances and the new SPMSM model is designed to control the current loop. The proposed method is implemented on a Xilinx Zynq SoC XC7Z020-CLG484-1 and field programmable gate array (FPGA) implementations of the improved DPCC and conventional DPCC are compared and analyzed in detail in terms of area utilization and time consumption. Although the execution time of both methods is very short, the improved DPCC takes less time than the conventional DPCC due to the parallel processing capabilities of FPGAs. The experimental results verify that the proposed method has good dynamic performance, load disturbance suppression performance, and parameter robustness. [ABSTRACT FROM AUTHOR]

Currently, parallel data transmissions in large-scale datacenter networks are becoming increasingly crucial to application performance. Despite fine-grained control by SDN-enabled networks, some transmission errors, such as misconfigurations, will inevitably occur, resulting in high-level forwarding policies that cannot be conformed to at the data plane. Therefore, flow trajectory detection is very important for allowing datacenter network operators to troubleshoot problems and ensure that all traffic flows are running on the correct paths. However, existing solutions detect flow trajectories by recording the entire path of each packet. These methods are prone to imposing significant overheads in terms of both the number of switch entries and the amount of packet header space required. To considerably reduce this overhead, we present FlowTracer, an efficient flow trajectory detection solution, which can sample a path one link at a time instead of recording the entire path. FlowTracer consists of a method of probabilistic packet tagging and a method of trajectory reconstruction. In this paper, we first introduce the method of probabilistic packet tagging, which is performed in OpenFlow-enabled switches with very few switch entries and limited packet header space by means of double VLAN tags. Then, we explore the topological structure of datacenter networks and propose our method of trajectory reconstruction, which is performed at end hosts and achieves rapid convergence. Finally, we evaluate FlowTracer on a 48-ary fat-tree topology. The results show that FlowTracer can detect trajectories quickly while placing far smaller demands on both switch entries and packet header space than state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

Avobenzone (AB) is one of the most widely used UVA sunscreens, and it is viewed as a model compound for studying the photoisomerization process. In recent years, Miranda and co-workers studied photophysical and photochemical reactions of several AB derivatives. However, there is still a gap in the data of these compounds in the ultrafast time region. To get a better understanding of the photophysical and photochemical reaction mechanisms, selected AB derivatives of AB-Me, AB-Pr, AB-Br and AB-Cl were studied using ultrafast transient absorption spectroscopy and density functional theory calculations in the present study. It is unravelled that alkylated substituted AB compounds of AB-Me and AB-Pr exhibit an efficient intersystem crossing with the generation of the corresponding triplet state species, which further leads to the Norrish type II reaction for AB-Pr. On the other hand, AB-Br and AB-Cl prefer photochemical reactions via the singlet state surface. Based on the DFT calculations, the spin–orbit coupling constant between the singlet and triplet states, the energy difference between the singlet and triplet states and the natural transition orbital separations of the studied AB compounds were found to be the leading reasons accounting for their corresponding photochemical activities via singlet and triplet states. [ABSTRACT FROM AUTHOR]

As cascaded proportional-integral controllers involve complicated tuning work, many efforts have been focused on direct controllers. Direct torque control and predictive torque control are both feasible solutions. However, bigger ripples or weighting factor designs are not easily solved. In this paper, a direct current controller that uses an extended high-gain state observer is proposed. The integral controller is removed from the system by using a disturbance estimation technique, which improves the system's performance with a variety of loads. A direct current controller without weighting factors is proposed as the inner controller. Unlike existing direct control methods, all phase currents are considered equally in the controller, which ensures a high current control quality. The simulation and experimental results verify that the proposed method performs well both in steady and transient states. [ABSTRACT FROM AUTHOR]

During the past few years, finite control set predictive current control (PCC) method has attracted more and more attention in research and industry applications. However, PCC method could be improved by considering two points. First, the current reference used in the cost function of PCC control scheme is usually produced by a proportional and integration speed controller. Confront with load torque and time-varying system parameters, it is a better solution to design a disturbance estimation based feed-forward compensated controller. In this way, the current reference could be generated faster and more accurate. Second, the PCC method is model-based method which means the accuracy of the model parameters are essential. In real system, time-varying parameters existed almost always. This paper investigates a generalized proportional integral observer based PCC approach for dealing with load torque disturbance, time-varying parameter uncertainties. The effectiveness of the proposed method has also been confirmed by simulation and a lab-constructed experimental prototype. [ABSTRACT FROM AUTHOR]