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This paper proposes a new concept of Aviation-to-Grid (A2G) that utilizes electric aircraft (EA) charging to provide flexibility to the power grid. Smart EA charging system with battery swap method is developed using PV, gas turbine, and grid electricity. Hourly energy dispatch strategy is produced based on the mixed integer linear programming method to meet electrified aviation and provide A2G frequency response. Case studies are conducted in 8 major UK airports considering seasonal flight schedules and power system scenarios. Results show that the EA charging system can provide effective primary and secondary frequency response to improve the frequency nadir by 0.2 - 0.3 Hz under grid disturbance. The total A2G frequency response capacity across the 8 UK airport can reach up to 1,300 MW overnight and up to 900 MW daytime. Annual A2G frequency response revenue is 46.58 million pounds, which can cover 19.8% to 30% of EA charging costs.

Smart passenger-seeking strategies employed by taxi drivers contribute not only to drivers’ incomes, but also higher quality of service passengers received. Therefore, understanding taxi drivers’ behaviors and learning the good passenger-seeking strategies are crucial to boost taxi drivers’ well-being and public transportation quality of service. However, we observe that drivers’ preferences of choosing which area to find the next passenger are diverse and dynamic across locations and drivers. It is hard to learn the location-dependent preferences given the partial data (i.e., an individual driver's trajectory may not cover all locations). In this paper, we make the first attempt to develop conditional generative adversarial imitation learning (cGAIL) model, as a unifying collective inverse reinforcement learning framework that learns the driver's decision-making preferences and policies by transferring knowledge across taxi driver agents and across locations. Our evaluation results on three months of taxi GPS trajectory data in Shenzhen, China, demonstrate that the driver's preferences and policies learned from cGAIL are on average 34.7% more accurate than those learned from other state-of-the-art baseline approaches.

Reconstructing an esthetic interimplant papilla remains challenging with implant-supported restorations, especially for patients with a thin gingival biotype. This technique report describes a modified approach to rebuilding an interimplant papilla by joining 2 elevated connective tissue flaps at the second-stage surgery.

The safe and efficient operation of the shearer is the key to coal mining. However, the walking wheel with wear and short fatigue life seriously restrict the improvement of the shearer’s reliability. And the failure effect of torsion deformation is mostly ignored. Therefore, to reveal the failure mechanism of the walking wheel and improve the haulage reliability of the shearer, the meshing model of the walking wheel and pin track considering torsional deformation was established. The meshing characteristics of the walking wheel and the damage mechanism of the tooth surface caused by the axial unbalanced load were analyzed, and the effects of the roll angle, the velocity, and the traction force were discussed. The results show that the peak force is close to the meshing-in area, the stress concentration on the tooth profile of the walking wheel is significant, but the stress distribution in the axial direction of the pin track is uniform; although the roll angle can restrain the meshing impact of the walking wheel, the axial unbalanced load and the wear on the load-bearing side increases with the appearance of the torsional deformation; with the velocity increasing, the stability of the walking wheel with roll angle decreases, the axial unbalanced load intensifies while the safety factor decreases; with the traction load increasing, the load distribution improves, but the bending fatigue strength of the tooth root and the safety factor decrease, and the plastic deformation and wear on the bearing-load side increase. The results provide a reference for exploring the meshing characteristics and failure mechanism of the walking wheel and improving the traction reliability of the shearer.

Due to the attractive potential in avoiding the elaborate definition of anchor attributes, anchor-free-based deep learning approaches are promising for object detection in remote sensing imagery. CornerNet is one of the most representative methods in anchor-free-based deep learning approaches. However, it can be observed distinctly from the visual inspection that the CornerNet is limited in grouping keypoints, which significantly impacts the detection performance. To address the above problem, a novel and effective approach, called GroupNet, is presented in this paper, which adaptively groups corner specific to the objects based on corner embedding vector and corner grouping network. Compared with the CornerNet, the proposed approach is more effective in learning the semantic relationship between corners and improving remarkably the detection performance. On NWPU dataset, experiments demonstrate that our GroupNet not only outperforms the CornerNet with an AP of 12.8%, but also achieves comparable performance to considerable approaches with 83.4% AP.

BACKGROUND: To explore the development of central nervous system (CNS) symptoms and clinical application in predicting the clinical outcomes of SARS-COV-2 patients. METHODS: A retrospective cohort study was performed on the hospitalized patients with SARS-COV-2 recruited from four hospitals in Hubei Province, China from 18 January to 10 March 2020. The patients with CNS symptoms were determined. Data regarding clinical symptoms and laboratory tests were collected from medical records. RESULTS: Of 1268 patients studied, 162 (12.8%) had CNS symptoms, manifested as unconsciousness (71, 5.6%), coma (69, 5.4%), dysphoria (50, 3.9%), somnolence (34, 2.7%) and convulsion (3, 0.2%), which were observed at median of 14 (interquartile range 9-18) days after symptom onset and significantly associated with older age (OR = 5.71, 95% confidence interval [CI] 2.78-11.73), male (OR = 1.73, 95% CI 1.22-2.47) and preexisting hypertension (OR = 1.78, 95% CI 1.23-2.57). The presence of CNS symptoms could be predicted by abnormal laboratory tests across various clinical stages, including by lymphocyte counts of

Click-Through Rate (CTR) prediction is the core task in an online advertising system. How to capture the users' dynamic interests through the behavior sequences to predict CTR is a challenging problem in the real-world applications. To address this challenge, we propose a deep dynamic interest learning by learning the local sessions and global sessions within sequences for CTR prediction. The local sessions and global sessions are used to capture the short-term dynamic interests and the long-term interests of users respectively. To explore the heterogeneous behaviors within the global session efficiently, the interests in global sessions are forced to be consistent with that in local sessions. Then the Bi-LSTM network is adopted to capture the dynamic interests with the behaviors cross global sessions effectively. Experimental results on various datasets show that the proposed method outperforms several state-of-the-art CTR prediction methods.

Many big data applications such as smart transportation, healthcare, and e-commerce need to store and query large collections of small XML documents, which has become a fundamental problem. However, existing solutions are inadequate to deliver satisfactory query performance in such circumstances. In this paper, we propose a framework named XML2HBase to address this problem using HBase, a widely deployed NoSQL database. Within this framework, we design a novel encoding scheme called Pathed-Dewey Order and a two-layer mapping method to store XML documents in HBase tables. XML queries, which are represented as XPath expressions, are evaluated through their translation into queries over HBase tables. Based on an in-depth analysis of the characteristics of the proposed approach, we design and integrate four optimization strategies to reduce storage space and query response time. Extensive experiments on two well-known XML benchmarks demonstrate the superior performance of XML2HBase over three state-of-the-art methods.

In wireless power transfer (WPT) systems, the relative position between the transmitting and receiving coils could change suddenly, which is one of the most significant distinctions between wireless and wired power transfer systems. To the best of the authors knowledge, no theoretical analysis has been reported on the dynamic behavior of the WPT systems under the relative position transient (RPT). This paper proposes the concept of coupling-coefficient susceptibility to describe this dynamic behavior. The extended describing function method is applied to extract the mathematical model of the coupling-coefficient susceptibility. Finally, an RPT testing platform, composed of a series-series compensated WPT system and a coil motion mechanism is designed and fabricated to verify the theoretical analysis. The experimental results exhibit a good agreement with the proposed model.

Owing to its superior performance, the Transformer model, based on the 'Encoder- Decoder' paradigm, has become the mainstream model in natural language processing. However, bioinformatics has embraced machine learning and has led to remarkable progress in drug design and protein property prediction. Cell-penetrating peptides (CPPs) are a type of permeable protein that is a convenient 'postman' in drug penetration tasks. However, only a few CPPs have been discovered, limiting their practical applications in drug permeability. CPPs have led to a new approach that enables the uptake of only macromolecules into cells (i.e., without other potentially harmful materials found in the drug). Most previous studies have utilized trivial machine learning techniques and hand-crafted features to construct a simple classifier. CPPFormer was constructed by implementing the attention structure of the Transformer, rebuilding the network based on the characteristics of CPPs according to their short length, and using an automatic feature extractor with a few manually engineered features to co-direct the predicted results. Compared to all previous methods and other classic text classification models, the empirical results show that our proposed deep model-based method achieves the best performance, with an accuracy of 92.16% in the CPP924 dataset, and passes various index tests.

BACKGROUND: It remains unclear if plyometric training as a single component could improve landing mechanics that are potentially associated with lower risk of ACL injury in the long term OBJECTIVE: The purpose of this study was to investigate the influence of experience undertaking plyometrics on landing biomechanics in female athletes. METHODS: Non-jumpers with little experience in plyometric training (12 female college swimmers) and jumpers with five years of experience in plyometric training (12 female college long jumpers and high jumpers) were recruited to participate in two testing sessions: an isokinetic muscle force test for the dominant leg at 120∘/s and a 40-cm drop landing test. An independent t test was applied to detect any significant effects between cohorts for selected muscle force, kinematic, kinetic, and electromyography variables. RESULTS: While female jumpers exhibited greater quadriceps eccentric strength (P= 0.013) and hamstring concentric strength (P= 0.023) during isokinetic testing than female swimmers, no significant differences were observed in kinematics, kinetics, and muscle activities during both drop landing and drop jumping. CONCLUSIONS: The results suggest that the female jumpers did not present any training-induced modification in landing mechanics regarding reducing injury risks compared with the swimmers. The current study revealed that plyometric training as a single component may not guarantee the development of low-risk landing mechanics for young female athletes.

Objective To observe the effect of the combined therapy of electroacupuncture (EA) and ginger-isolated moxibustion on endometrial receptivity in the patients with polycystic ovarian syndrome (PCOS). Methods A total of 70 subjects of PCOS were randomized into two groups, 35 cases in each one. In the western medication group, letrozole and human chorionic gonadotropin (HCG) were administered. In the combined therapy group, on the base of the treatment as the western medication group, the artificial cycle therapy with EA and ginger-isolated moxibustion was provided. The treatment duration was 3 menstrual cycles in two groups. After treated for 3 menstrual cycles, the symptom score of traditional Chinese medicine (TCM), endometrial thickness, the number of ovulation cycle, endometrial morphology, bilateral uterine artery pulsatility index (PI), resistance index (RI), the sum of peak systolic velocity/end diastolic velocity (S/D) and pregnancy were compared in the patients between two groups. Results (1) After treatment, the endometrial thickness was better (0.21 ± ± 0.13 vs 0.14 ± 0.08, P Conclusion The combined treatment of electroacupuncture and ginger-isolated moxibustion with western medication effectively improves endometrial receptivity, increases clinical pregnancy rate and reduces early abortion rate in the patients with PCOS.

Synthetic aperture radar (SAR) plays an essential role in earth observation and projection due to its capability to penetrate clouds, which makes it possible to monitor terrestrial surfaces under all weather conditions. Multiplicative noise often occurs in the SAR signal, hampering the retrieval of information from SAR imagery. Convolutional neural networks (CNNs) have been used in many computer vision tasks and are helpful in image denoising. However, current CNN-based denoising approaches inevitably lead to a ``washed out'' effect that loses spatial details. Another limitation is that most typical CNN-based denoising models require a noise-free image for training. To address these issues, we propose a novel end-to-end self-supervised SAR denoising model: Enhanced Noise2Noise (EN2N), which can be trained without a noise-free image. To enhance the quality of the result images, the perceptual features from a pre-learned CNN are introduced to restore the spatial details by a hybrid loss function. Experiments show that our proposed method outperforms the typical denoising methods in terms of noise reduction and feature preservation based on image quality metrics. Also, the new hybrid loss could enhance the spatial details significantly. The good performance maintains the robustness throughout time, which reduces the uncertainty in time-series SAR caused by random noise. Benefiting from optimization of graphics processing unit (GPU) and multi-threading, the proposed method has higher computation efficiency than traditional methods. This study demonstrates the great potential of using our self-supervised deep learning approaches for SAR image denoising in the future.

Reduced precision computation is a key enabling factor for energy-efficient acceleration of deep learning (DL) applications. This article presents a 7-nm four-core mixed-precision artificial intelligence (AI) chip that supports four compute precisions--FP16, Hybrid-FP8 (HFP8), INT4, and INT2--to support diverse application demands for training and inference. The chip leverages cutting-edge algorithmic advances to demonstrate leading-edge power efficiency for 8-bit floating-point (FP8) training and INT4 inference without model accuracy degradation. A new HFP8 format combined with separation of the floating- and fixed-point pipelines and aggressive circuit/architecture optimization enables performance improvements while maintaining high compute utilization. A high-bandwidth ring protocol enables efficient data communication, while power management using workload-aware clock throttling maximizes performance within a given power budget. The AI chip demonstrates 3.58-TFLOPS/W peak energy efficiency and 26.2-TFLOPS peak performance for HFP8 iso-accuracy training, and 16.9-TOPS/W peak energy efficiency and 104.9-TOPS peak performance for INT4 iso-accuracy inference.

As the most classical unsupervised dimension reduction algorithm, principal component analysis (PCA) has been widely used in hyperspectral images (HSIs) preprocessing and analysis tasks. Recently proposed superpixelwise PCA (SuperPCA) has shown promising accuracy where superpixels segmentation technique was first used to segment an HSI to various homogeneous regions and then PCA was adopted in each superpixel block to extract the local features. However, the local features could be ineffective due to the neglect of global information especially in some small homogeneous regions and/or in some large homogeneous regions with mixed ground truth objects. In this article, a novel spectral-spatial and SuperPCA (S³-PCA) is proposed to learn the effective and low-dimensional features of HSIs. Inspired by SuperPCA we further adopt superpixels-based local reconstruction to filter the HSIs and use the PCA-based global features as the supplement of local features. It turns out that the global-local and spectral-spatial features can be well exploited. Specifically, each pixel of an HSI is reconstructed by the nearest neighbors' pixels in the same superpixel block, which could eliminate the noise and enhance the spatial information adaptively. After the local reconstruction-based data preprocessing, PCA is performed on each region and the entire HSI to obtain local and global features, respectively. Then we simply concatenate them to get the global-local and spectral-spatial features for HSIs classification. The experimental results on two HSIs data sets demonstrate the superiority of the proposed method over the state-of-the-art methods. The source code of the proposed model is available at https://github.com/XinweiJiang/S3-PCA.

With the development of synthetic aperture radar (SAR) imaging and deep learning, SAR ship detection based on convolutional neural networks (CNNs) has been extensively applied in the last few years. Nevertheless, there are two main obstacles in SAR ship detection. 1) The SAR images have too much noise, such as the interference from land area, making it difficult to distinguish ship objects from the surrounding background. 2) Due to the multiscale characteristics of ship objects, there are numerous false negatives in the detection results, especially for small objects. To alleviate the above problems, we propose a one-stage ship detector with strong robustness against scale changes and various interferences. Firstly, to mitigate the disturbance from complex background, coordinate attention module is introduced for obtaining more representative semantic features to accurately locate and distinguish ship objects. Secondly, receptive field increased module is devised to capture multiscale contextual information to improve the detection performance for ships with diverse scales. Finally, we verify the robustness of our method on several public SAR datasets, i.e., SAR-Ship-Dataset, HRSID and SSDD. The experimental results demonstrate that the proposed method has a competitive performance, exceeding other state-of-the-art methods by at least 2.6% AP50 on HRSID.

Most of the malignant melanomas are already in the middle and advanced stages when they are diagnosed, which is often accompanied by the metastasis and spread of other organs.Besides, the prognosis of patients is bleak. The characteristics of the local immune microenvironment in metastatic melanoma have important implications for both tumor progression and tumor treatment. In this study, data on patients with metastatic melanoma from the TCGA and GEO datasets were selected for immune, stromal, and estimate scores, and overlapping differentially expressed genes (DEGs) were screened. A nine-IRGs prognostic model (ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22) was established by univariate COX regression, LASSO and multivariate COX regression. Receiver operating characteristic (ROC) curves were used to test the predictive accuracy of the model. Immune infiltration was analyzed by using CIBERSORT, Xcell and ssGSEA in high-risk and low-risk groups. The immune infiltration of the high-risk group was significantly lower than that of the low-risk group. Immune checkpoint analysis revealed that the expression of PDCD1, CTLA4, TIGIT, CD274, HAVR2 and LAG3 were significantly different in groups with different levels of risk scores. WGCNA analysis found that the yellow-green module contained seven genes (ALOX5AP, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22) from the nine-IRG prognostic model, of which the yellow-green module had the highest correlation with risk scores. The results of GO and KEGG suggested that the genes in the yellow-green module were mainly enriched in immune-related biological processes. Finally, we analyzed the prognostic ability and expression characteristics of ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22 in metastatic melanoma. Overall, a prognostic model for metastatic melanoma based on the characteristics of the tumor immune microenvironment was established, which was helpful for further studies.It could function well in helping people to understand the characteristics of the immune microenvironment in metastatic melanoma and to find possible therapeutic targets.

Possessing the capability to handle high voltage, the bidirectional input-series–output-series (ISOS) modular dc–dc converter is suitable for use in dc grids. Regarding topology selection of the constituent modules, the open-loop controlled series-resonant dual active bridge (SR-DAB) converter exhibits superior efficiency performance and the advantage of simple control. However, it has no regulation capability. Aimed to reap the advantages of SR-DAB and achieve flexible control, this article presents a hybrid ISOS converter composed of SR-DAB and nonresonant phase-shift controlled dual active bridge (PS-DAB) modules. The SR-DAB modules process most of the power to ensure high-efficiency conversion, whereas the PS-DAB is responsible for flexible control. At the output stage of the ISOS system, embedded nonisolated resonant dual active half-bridge (NR-DAHB) converters are integrated between every two adjacent modules without adding any switches. The transformer property of the open-loop controlled SR-DAB and NR-DAHB circuits facilitates natural voltage sharing at both the input and output sides. The hardware experiment has been conducted to verify the operating principles and performance of the proposed ISOS system.

Multi-view object detection is challenging due to the influence of the different view-angles on intra-class similarity. The uniformed feature representation of traditional detectors couples the object’s perspective attribute and semantic feature, and the variances of perspective will cause intra-class differences. In this paper, a robust perspective-sensitive network (PSNet) is proposed to overcome the above problem. The uniformed feature is replaced by the perspective-specific structural feature, which makes the network perspective sensitive. Its essence is to learn multiple perspective spaces. In each perspective space, the semantic feature is decoupled from the perspective attribute and is robust to perspective variances. Perspective-sensitive RoI pooling and loss function are proposed for perspective-sensitive learning. Experiments on Pascal3D + and SpaceNet MOVI show the effectiveness and superiority of the PSNet.

Inclusive green growth and dependence on import trade are domestic and international issues that need to be considered in the process of high-quality development of China's tourism industry. Under the complex international environment, it is necessary to explore the regulating effect of import dependence on the impact of inclusive green growth on the high-quality development of the tourism industry. From the perspective of import dependence, this study uses the panel data of 30 Chinese provinces (excluding the Tibet Autonomous Region, Hong Kong, Macao, and Taiwan) from 2010 to 2019, and constructs the mechanism of inclusive green growth on the high-quality development of the tourism industry based on the theory of spatial production. The purpose of this study is to examine the moderating effect of import dependence on the mechanism of the inclusive green growth index on the high-quality development of the tourism industry. It is found that inclusive green growth can significantly promote the high quality of the tourism industry. The threshold test results show that import dependence has a significant negative threshold effect in the mechanism of inclusive green growth on the high-quality development of the tourism industry. When import dependence exceeds a single threshold (38.65), the contribution of inclusive green growth to the improvement of high-quality development level of the tourism industry first decreases and then increases. The results show that even if there are favourable conditions such as inclusive green growth, if there is dependence on imported goods, it will have a negative impact on the high-quality development of the tourism industry. This paper enriches the research on the evaluation of high-quality development level of the tourism industry and the interaction between international trade and tourism industry. Moreover, it provides a reference for developing countries such as China under the impact of COVID-19 and the anti-globalisation.

In Alzheimer's disease and ischemic stroke, intranasal insulin can act as a neuroprotective agent. However, whether intranasal insulin has a neuroprotective effect in intracerebral hemorrhage and its potential mechanisms remain poorly understood. In this study, a mouse model of autologous blood-induced intracerebral hemorrhage was treated with 0.5, 1, or 2 IU insulin via intranasal delivery, twice per day, until 24 or 72 hours after surgery. Compared with saline treatment, 1 IU intranasal insulin treatment significantly reduced hematoma volume and brain edema after cerebral hemorrhage, decreased blood-brain barrier permeability and neuronal degeneration damage, reduced neurobehavioral deficits, and improved the survival rate of mice. Expression levels of p-AKT and p-GSK3β were significantly increased in the perihematoma tissues after intranasal insulin therapy. Our findings suggest that intranasal insulin therapy can protect the neurological function of mice after intracerebral hemorrhage through the AKT/GSK3β signaling pathway. The study was approved by the Ethics Committee of the North Sichuan Medical College of China (approval No. NSMC(A)2019(01)) on January 7, 2019.

This paper aimed to study the clinical characteristics of patients with pulmonary embolism (PE) with syncope (PE + S) based on the three-dimensional (3D) reconstruction algorithm in computed tomography (CT) pulmonary angiography (CTPA). In this study, 857 patients with acute PE (APE) who were treated in hospital were selected as the research objects and divided into syncope group (group S) and nonsyncope group (group NS). The 3D reconstruction marching cubes (3DR-MC) algorithm was compared with the traditional MC (T-MC) algorithm and the mesh simplification MC (MMS-MC) algorithm, and the results proved that the running time of the 3DR-MC algorithm on the platform was shorter than that of the other two algorithms. The incidence of syncope in group S in women was higher than that in group NS (51.7% vs. 38.2%). The incidence of syncope classified as high risk in group S was higher than that in group NS, and the mortality rate of pulmonary embolism patients with syncope was higher, and the difference was statistically significant (χ2 = 113.332, P < 0.05 ). The incidence of syncope in group S was higher than that in group NS (χ2 = 4.074, P < 0.05 ). In short, hypertension was an independent risk factor for syncope. PE + S patients could be diagnosed and treated as early as possible based on the clinical characteristics, so as to reduce the adverse consequences of misdiagnosis.

The study aimed to investigate clinical impact of the flattening filter free (FFF) irradiation in fixed-field intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) for...

The development of deep learning has brought new prospects into the field of hyperspectral classification, and the classification ability of this method for the classification of hyperspectral images (HSIs) has been continuously improved. However, there are still some problems that must be solved; for example, the spectral-spatial features of HSIs are not effectively extracted, the labeled samples in the data set are limited, and the number of samples in different categories is imbalanced. To facilitate the progress of hyperspectral classification, a spectral-spatial fractal residual convolutional neural network with data balance augmentation is proposed here. In this network, a data balance augmentation approach that can solve the problems of limited labeled data and imbalanced categories is proposed. In addition, the spectral-spatial residual module is proposed to learn the spectral-spatial information and alleviate the problem of model degradation effectively. In addition, the spectral-spatial focal structure, which can guarantee the integrity of the information, is introduced. Moreover, the spectral-spatial dimensional transformation module, which can reduce the size and number of hyperspectral feature maps without losing the fine features, is presented. In particular, the proposed network has a strong ability to classify the categories that have a small number of samples and reaches the state-of-the-art level for three benchmark data sets.

The ever-increasing need for sustainable development requires advanced battery techniques beyond the current generation of lithium ion batteries. Among all candidates being explored, lithium-sulfur batteries are a very promising system to be commercialized in the near future. Towards this end, the development of lithium sulfide (Li2S) nanocrystal-based cathodes has received tremendous effort and witnessed multiple reviews. Differentiated from the focus on performance improvement in previous reviews, this review summarizes the research progress in line with the approaches of materials synthesis and electrode fabrication. The key chemistry, operation procedure, materials characterizations and performance assessments are all given a balanced description. Moreover, all approaches are collectively analyzed along the lines of six criteria towards practical applications, i.e., electrode performance, materials quality, resources sustainability, production cost, operation procedure, and consumed energy. Finally, some perspective viewpoints on the future research directions are offered.

Air balancing is an important technique in heating, ventilation, and air conditioning (HVAC) applications to achieve accurate air supply for satisfactory indoor air quality and better energy saving performance. The existing air balancing methods are usually based on a hybrid duct system model, which includes a data-driven duct system model between terminal flow and static pressure, and an American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) damper model between static pressure and terminal damper angle. Most of the existing methods just focus on how to improve the accuracy of the former part (i.e., the data-driven duct system model), whereas neglecting the latter. However, it is found that the ASHRAE damper model cannot exactly reflect the characteristics of the actual dampers in practice and may lead to unavoidable modeling errors. To fix this issue, this article develops a full data-driven duct system (FD3S) model to directly reveal the relationship between the terminal flow and terminal damper angle in the whole duct system. As a result, the desired terminal damper angle under the design flow conditions can be more accurately predicted. Besides, since the proposed method directly models the relationship between terminal flow and terminal damper angle, it avoids installing extra pressure sensors and reduces the operating cost. Besides, the proposed FD3S model greatly reduces the model complexity compared with the previous hybrid model. The proposed FD3S model-based air balancing method is fully tested on three real duct systems, and the results proved the effectiveness and generality of the proposed FD3S model-based air balancing method.

Background: This study aimed to investigate clinical involvement of ITGA7 in Philadelphia-chromosome-negative acute lymphoblastic leukemia (Ph- ALL). Methods: We sampled bone marrow (BM) from 91 Ph- ALL patients and 20 healthy donors (HDs), detecting ITGA7 expression in BM. Results: ITGA7 was highly expressed in Ph- ALL patients at differentiating values between Ph- ALL patients and HDs. Elevated ITGA7 expression was associated with CNS leukemia (CNSL) occurrence and increased percentage of BM blasts in Ph- ALL patients. Elevated ITGA7 expression was linked with lower complete remission rate (CR), worse event-free survival, and worse overall survival in Ph- ALL patients. Conclusion: ITGA7 highly expressed, correlated with CNSL occurrence and higher BM blasts, furthermore predicts lower CR rate and worse prognosis.

Aim: We investigated the efficacy and safety of hepatic artery infusion chemotherapy (HAIC) combined with anti-PD-1 immunotherapy and tyrosine kinase inhibitors (TKIs) for advanced hepatocellular carcinoma (HCC). Method: This retrospective study included HCC patients treated with HAIC, TKIs and anti-PD-1 antibodies between May 2019 and November 2020 in our hospital. Primary end points were progression-free survival and safety. Results: Twenty-seven advanced HCC patients were analyzed. The median follow-up was 12.9 months (range: 4.0–24.0 months) and the median progression-free survival was 10.6 months. The objective response rate and disease control rate were 63.0 and 92.6%, respectively. No treatment-related deaths occurred. Conclusion: In patients with advanced HCC, treatment with HAIC, anti-PD-1 antibodies and oral TKIs was effective and safe.

In this study, a fully biodegradable ultra-light poly(lactic acid)/silicon dioxide (PLA/SiO2) aerogel nanocomposite with ultra-low thermal conductivity was successfully fabricated. PLA used was a produced from lactic acid, where the lactic acid has been produced from carbohydrates. The rheological properties of PLA were enhanced by diphenylmethane diisocyanate (MDI). The foaming properties, cell density, cell size uniformity, mechanical properties and thermal conductivity and thermal diffusivity of PLA were further improved by SiO2 aerogel, and finally the ultra-low density foamed material was prepared by supercritical CO2. The density of PLA foam can be as low as 0.02 g/cm3 and the thermal conductivity as low as 0.02628 W/m·K. The PLA-based composites can be used in many fields such as thermal insulation, vibration damping and packaging, and can be fully biodegradable and sustainable throughout their life cycle, which meets the global trend of energy saving and emission reduction.

BSPIF-S-7.5A, a kind of open cell and low-density polyimide foam was developed for Chinese satellite. The polyimide foam is thermal isolation material with low thermal conductivity and high glass transition temperature. Basic physical properties, thermal physical properties, mechanical properties have been studied. For validating space environment resistance of polyimide foam, outgassing in vacuum, thermal cycle, total dose radiation, thermal vacuum and atomic oxygen tests have been performed. The apparent core density of this foam is as low as 7.5 ± 0.5 kg m−3. Its volume percentage of open cells is over 98%, which is beneficial to outgas in orbit. Coefficient of thermal expansion is less than 40 × 10–6 K−1 in the temperature range from − 170 to 135 ℃. Thermal conductivity in vacuum increases from 2.7 to 42.3 mW (m K)−1 with temperature rising from – 130 to 135 ℃. After severe space environment tests, thermal conductivity becomes even lower, compressive strength raises slightly, but shear property declines apparently. Covered with polyimide film, polyimide foam can resist atomic oxygen erosion effectively. Therefore, the polyimide foam is superior thermal insulation material for space application, which is ideal for satellite structure.

PURPOSE To compare outcomes after arthroscopy in FAIS patients with preoperative asymptomatic gluteal tendinosis (GT) to a control group with no gluteal tendinosis. METHODS A retrospective analysis was performed using data from FAIS patients who had arthroscopy between 2016 and 2018. Asymptomatic GT was diagnosed using hip MRI without clinical symptoms. Patients with asymptomatic GT were 1:1 propensity-score matched to patients without GT. Patient-reported outcomes (HOS-ADL, iHOT-12, mHHS), VAS scores, radiographic measures, performed procedures, complications, and revision surgery were compared and analyzed for both groups. RESULTS A total of 105 asymptomatic GT hips and 105 hips without GT were found using propensity-score matching. When compared to preoperative levels, both groups demonstrated significant improvements in PROs and VAS scores at the final follow-up. Besides, there were no significant differences in preoperative scores, final outcome scores, or score improvements between the groups. Patients in the GT group were significantly less likely to achieve the MCID for the VAS score (72.4% vs 83.8%, p = 0.045). However, there were no other differences in the rate of meeting the PASS and MCID between the study and the control groups. CONCLUSION It was demonstrated in this study that FAIS patients with asymptomatic gluteal tendinosis can expect to experience similar good short-term patients-reported outcomes as compared with patients without gluteal tendinosis. LEVEL OF EVIDENCE III.

Mining-induced stress will cause the change of coal seam pore structure. However, most coal seam infusion simulation studies do not consider the change of pore with mining-induced stress. In order to study the impact of mining-induced stress on coal seam infusion, this paper used the triaxial compression test of coal as the basis to establish the relationship equation between volume strain and stress loading by the volume deformation table, and then introduced the relationship equation into FLUENT through Fluent Custom Function (UDF). Taking the mining time and water injection time as the axis, this paper compared and analyzed the variation law of coal seam infusion seepage parameters with coal seams with pore changes caused by mining-induced stress (model I) and traditional fixed porosity (model II). The results show that in the elastic deformation stage, the mining-induced stress makes the original pores of the coal seam compact, so that the water injection seepage pressure, seepage velocity, and water content volume of model I are lower than those of model II. In the plastic deformation and post-peak deformation stages, mining-induced stress promotes the development of coal seam pores, and the water injection seepage pressure, seepage velocity, and water content of model I gradually exceed the seepage field parameters of model II. It can be seen that mining-induced stress has an important impact on water injection seepage. The simulation method proposed in this paper can more truly reflect the impact of actual mining process on coal seam infusion seepage.

INTRODUCTION Immediate early response 3 (IER3) has association with hematological malignancies' risk and prognosis, such as myelodysplastic syndrome, while its relation to acute myeloid leukemia (AML) is not clear. This study aimed to explore the correlation of IER3 with AML risk, clinical characteristics, complete remission (CR), event-free survival (EFS), and overall survival (OS). METHODS A total of 93 de novo AML patients were included in this study. In addition, 30 patients with non-hyperplasia hematologic malignancies requiring bone marrow testing (as disease controls) and 30 health donors (as health controls) were also recruited. Bone morrow samples of AML patients (before treatment), disease controls (before treatment), and health controls (at donation) were collected. IER3 in bone marrow mononuclear cells was detected by reverse transcription-quantitative polymerase chain reaction. RESULTS IER3 was increased in AML patients compared with disease controls and health donors (both P

The performance of object detection is closely related to the quality of input images. However, the current image acquisition is purely guided by human visual perception, and such camera imaging process ignores the subsequent application. In this context, detection performance is impacted by imaging configuration and dynamic camera motion. To address the above problems, an active object detection framework is proposed in this paper, which aims to build the bridge between imaging configuration and object detection task. Within the proposed framework, a dynamic camera configuration learning approach is presented based on deep reinforcement learning, where the camera is actively controlled to maximize the detection performance. Through iterated interactions between imaging, control and object detection, the deep gap between perception and cognition in the object detection system is eliminated, and the transformation from physical imaging to purposeful imaging is realized. The effectiveness and advantages of the proposed framework are demonstrated in three dynamic environments.

The temperature-dependent (T-dependent) linewidth (ΓG) and frequency shift (ΔωG) of the G mode provide valuable information on the phonon anharmonicity of graphene-based materials. In contrast to the negligible contribution from electron-phonon coupling (EPC) to the linewidth of a Raman mode in semiconductors, ΓG in pristine graphene is dominated by EPC contribution at room temperature due to its semimetallic characteristics. This leads to difficulty in resolving intrinsic contribution from phonon anharmonicity to ΓG. Here, we probed the intrinsic phonon anharmonicity of heavily-doped graphene by T-dependent Raman spectra based on FeCl3-based stage-1 graphite intercalation compound (GIC), in which the EPC contribution is negligible due to the large Fermi level (EF) shift. The ΔωG and ΓG exhibit a nonlinear decrease and noticeable broadening with increasing temperature, respectively, which are both dominated by phonon anharmonicity processes. The contribution of phonon anharmonicity to ΓG of heavily-doped graphene decreases as the EF approaches to the Dirac point. However, the T dependence of ΔωG is almost independent on EF and qualitatively agrees with the theoretical result of pristine graphene. These results provide a deeper understanding of the role of phonon anharmonicity on the Raman spectra of heavily doped graphene.

Objective Helicobacter pyloriinfection is mostly a family-based infectious disease. To facilitate its prevention and management, a national consensus meeting was held to review current evidence and propose strategies for population-wide and family-basedH. pyloriinfection control and management to reduce the related disease burden. Methods Fifty-seven experts from 41 major universities and institutions in 20 provinces/regions of mainland China were invited to review evidence and modify statements using Delphi process and grading of recommendations assessment, development and evaluation system. The consensus level was defined as ≥80% for agreement on the proposed statements. Results Experts discussed and modified the original 23 statements on family-basedH. pyloriinfection transmission, control and management, and reached consensus on 16 statements. The final report consists of three parts: (1)H. pyloriinfection and transmission among family members, (2) prevention and management ofH. pyloriinfection in children and elderly people within households, and (3) strategies for prevention and management ofH. pyloriinfection for family members. In addition to the ‘test-and-treat’ and ‘screen-and-treat’ strategies, this consensus also introduced a novel third ‘family-basedH. pyloriinfection control and management’ strategy to prevent its intrafamilial transmission and development of related diseases. Conclusion H. pyloriis transmissible from person to person, and among family members. A family-basedH. pyloriprevention and eradication strategy would be a suitable approach to prevent its intra-familial transmission and related diseases. The notion and practice would be beneficial not only for Chinese residents but also valuable as a reference for other highly infected areas.

The resonant modes and their coupling effect of metamaterials is a rapidly growing research topic with potential for applications in optoelectronics. In this work, a strong absorption coupling between the spoof surface plasmon polariton (SSPP) modes and the intrinsic modes has been investigated in a novel terahertz metamaterial. The anticrossing effects of the absorption-mode coupling show a splitting frequency difference that can be described based on a Rabi-splitting-like model. The theoretical and experimental results demonstrate that the splitting phenomenon is induced by an energy exchange between the intrinsic mode and the SSPP mode. This coupling process is mediated by the SSPP mode and can be controlled efficiently by directionally varying the lattice constant of the metamaterial. Furthermore, this absorption process involving hybrid modes can lead to resonances with ultra-high quality factors, which will provide a strong platform for the applications in the field of sensing and detection.

Background With the increased use of assisted reproductive technology (ART), assessing the potential health risks of children conceived on ART important to public health. Most research in this area has focused on the effects of ART on perinatal, metabolic, and oncological risks in children. Although an increased risk of immune-related diseases has been reported in children born after ART, there are no studies on the immunological status of these children. This study aimed to evaluate the impact of different embryo transfer methods and fertilization strategies on the immune status of the offspring. Methods A total of 69 children born to women treated with ART and a matched control group of 17 naturally conceived (NC) children, all aged from 3 to 6 years, were recruited in the reproductive hospital affiliated to Shandong University. The frequency of immune cells in the peripheral blood was assayed using flow cytometry; plasma cytokine levels were determined by multiplex cytokine immunoassay with human cytokine magnetic beads. Results Compared to children born after natural conception, children born after ART had elevated interferon-γ (IFN-γ) levels, regardless of embryo transfer and fertilization strategies. Children in the fresh-embryo transfer group had significantly higher IL-4 levels and a lower ratio of IFN-γ to IL-4 than those in the NC group ((P = 0.004, 10.41 ± 5.76 pg/mL vs 18.40 ± 7.01 pg/mL, P = 0.023, 1.00 ± 0.48 vs 0.67 ± 0.32, respectively). Similar results were shown in either the in vitro fertilization (IVF) group or the intra-cytoplasmic sperm injection (ICSI) group (P P = 0.08 for IVF; P P 2 (estradiol) levels on the day of hCG administration (R = 0.502, P = 0.017; R = − 0.537, P = 0.010, respectively). Consistently, the frozen embryo transfer did not result in alterations of these immune indicators in the offspring. Overall, there were no significant differences between the ART group and NC group in the frequencies of T cells, B cells, natural killer (NK) cells, CD4+T cells, CD8+T cells, T helper (TH)1 cells, TH17 cells, and regulatory T (Treg) cells and cytokine levels of IL-10 and IL-17a (all P > 0.05). Conclusions Immunological alterations existed in children born after the use of ART. The elevated E2 levels before embryo implantation contributed to the increased IL-4 levels in children conceived by fresh embryo transfer. The assessment of immunological alteration is of importance to children conceived by ART for early monitoring and intervention.

In this article, power flow transfer entropy (PFTE) is proposed as a criterion to evaluate the power flow transfer characteristics of the multiterminal HVdc (MTdc) wind power integration grid. This proposed criterion can detect and locate the ac three-phase to ground (TPG) faults in the MTdc grid by its sensitivity to power flow change to avoid communication. The transient energy dissipation control strategy is then designed according to the variety of PFTE, which reflects the power flow reversal characteristic of the MTdc grid during ac faults. Experimental results show that the system based on the proposed communication-free method can ride through ac TPG faults without blocking any converter.

Metallized Film Capacitors (MFC) are vital devices in many important fields such as energy, transportation, and aviation, whilst Digital Twin (DT) technology opens a new channel to leverage existing data resources of metallized film capacitors. This paper review current knowledge about metallized film capacitors and digital twin, list the key issues, propose frameworks, and provide the outlook to clarify the potential of digital twin’s application in metallized film capacitors. First, based on the development history and research status of metallized film capacitors, this review sorts out the key research issues of data utilization. Then, the connotation and typical characteristics of the digital twin definition are combed and refined, and the typical architecture of digital twin implementation is presented. Furthermore, the overall application architecture of digital twin in metallized film capacitors is constructed, and the technology system of each application scenario and the role of digital twin are analyzed. Finally, the main challenges in the application of the digital twin in metallized film capacitors and the future development directions are discussed. This review promotes the performance improvement, cost reduction and application expansion of metallized film capacitors, which can be used as a guide for the application of digital twin in other power equipment of energy system.

The use of air vessels is an effective measure to control water hammers, and its volume selection has a certain blindness. This paper aims to reveal the surge wave characteristics and provide design guidelines for air vessels in long-distance water supply systems. First, the analytical formulas of water-level oscillations in the air vessel are derived based on the Krylov–Bogoliubov–Mitropolsky method. Then, an optimization model is constructed for selecting the optimal volume of the air vessels. Finally, the validation of the analytical formulas and the optimization of the model are conducted through two actual projects. The results show that the calculation error of the analytical formulas can be controlled within a very small range, and the process of selecting air vessel volume can be simplified with the provided model. In addition, increasing the air chamber height within its range can reduce the volume of air vessels with the same protection requirements. The optimization analysis results of the air vessel can provide guidance and reference for the design of actual projects. HIGHLIGHTS The analytical formulas for water-level oscillations considering pipe friction are derived.; The volume optimization model can preliminarily estimate the minimum volume of the air vessel.; Under the same protection requirements, the volume of air vessels decreases with the increase of air chamber height.

Background: Cerebral ischemia-reperfusion injury is caused by a blood reperfusion injury in the ischemic brain and usually occurs in the treatment stage of ischemic disease, which can aggravate brain tissue injury. Objective: Curcumin was reported to exert a good therapeutic effect on neural cells against ischemia- reperfusion injury, However, the mechanism is not clear. Methods: In this study, Oxygen-Glucose Deprivation (OGD) model of fetal rat cerebral cortical neurons and the Middle Cerebral Artery Occlusion (MCAO) model of rats were employed to mimic cerebral ischemia-reperfusion injury in vitro and in vivo, respectively. Results: We confirmed that curcumin has a promotive effect on neuronal proliferation and an inhibitory effect on neuronal pyroptosis. Furthermore, we found that curcumin could improve cerebral infarction. The results of western blotting showed that curcumin down-regulated the expression of nucleotide-binding oligomerization domain-containing protein-, leucine-rich repeats-, and pyrin domain-containing protein 1 (NLRP1), cysteinyl aspartate-specific protease 1 (caspase-1), gasdermin D (GSDMD), IL-1β, IL-6, TNF-α, and iNOS proteins in OGD and MCAO models. NLRP1- dependent neuronal pyroptosis played an important role in cerebral ischemia-reperfusion injury. Conclusion: Curcumin could effectively inhibit NLRP1-dependent neuronal pyroptosis by suppressing the p38 MAPK pathway and therefore exerted neuroprotective effects against cerebral ischemia- reperfusion injury.