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Abstract Eyelid tumors pose diagnostic challenges due to their diverse pathological types and limited biopsy materials. This study aimed to develop an artificial intelligence (AI) diagnostic system for accurate classification of eyelid tumors. Utilizing mass spectrometry-based proteomics, we analyzed proteomic data from eight tissue types and identified eighteen novel biomarkers based on 233 formalin-fixed, paraffin-embedded (FFPE) samples from 150 patients. The 18-protein model, validated by an independent cohort (99 samples from 60 patients), exhibited high accuracy (84.8%), precision (86.2%), and recall (84.8%) in multi-class classification. The model demonstrated distinct clustering of different lesion types, as visualized through UMAP plots. Receiver operator characteristic (ROC) curve analysis revealed strong predictive ability with area under the curve (AUC) values ranging from 0.80 to 1.00. This AI-based diagnostic system holds promise for improving the efficiency and precision of eyelid tumor diagnosis, addressing the limitations of traditional pathological methods.

Abstract Active magnetic bearing (AMB) is a key technology in high‐speed rotating machines for rotor suspension, where the displacement sensors play a crucial role in detecting and controlling the rotor position. However, the traditional displacement sensors have the problems of high cost, large volume and poor reliability. To solve these problems, this paper proposes an innovative solution that utilises a recurrent neural network (RNN) to estimate the rotor displacement from the current in the AMB controller. The proposed method offers high‐quality prediction performance for the rotor displacement which is close to the high precision eddy current displacement sensors. The mathematical model of AMB is analysed to provide guidance in historical current data acquisition and design of RNN. The input dimensions and the architecture of the neural network are optimised to improve both prediction accuracy and computational complexity. Experimental results validate the effectiveness of the algorithm and demonstrate that the proposed method has high accuracy, robustness and generalisation ability.

Abstract Background Direct-acting antivirals (DAAs) show high cure rates in treating chronic hepatitis C virus (HCV). However, the effect of DAAs on patients infected with genotype 2 (GT2) is difficult to determine despite the availability of several DAA regimens. Methods A systematic search of six databases (PubMed, Embase, Cochrane Library, Web of Science, CNKI, and Clinicaltrial.gov) was conducted through April 20, 2022. We considered the sustained virological response 12 weeks after treatment (SVR12) as the efficacy outcome, and adverse events (AEs) as the safety outcome. By calculating the mean SVR12 and the proportion of AEs among patients, we considered the intervention effect for each DAA regimen. The random effect model was then used in all meta-analyses. This systematic review and meta-analysis aimed to summarize the evidence on efficacy and safety of DAAs in patients infected with HCV GT2. The Bayesian Markov Chain Monte Carlo (MCMC) network metanalysis was used to indirectly compare regimen in GT2 patients. Results Among 31 articles included (2,968 participants), consisting of 1,387 treatment-naive patients and 354 patients with cirrhosis. The overall pooled SVR12 rate was 94.62% (95% CI: 92.43-96.52%) among the participants who received all doses of treatment. Meta-analysis results of AEs revealed that fatigue was the most common AE (14.0%, 95% CI: 6.4-21.6%), followed by headache (13.1%, 95% CI: 9.2-17.1%), whereas death and serious adverse events were uncommon. Conclusions We compared DAA-based treatments indirectly using meta-analysis and found the combination of Sofosbuvir plus Velpatasvir and Glecaprevir plus Pibrentasvir, each administered over a 12-week period, were identified as the most effective and relatively safe in managing chronic hepatitis C virus genotype 2 (HCV GT2) infection. Both treatments achieved a SVR12 of 100% (95% CI 99–100%).

ABSTRACTBackground Proprietary Chinese medicine (PCM) is widely used in the Guangdong-Hong Kong-Macau Greater Bay Area (GBA) of China. However, the regulatory frameworks and procedures for PCM registration in the region are not well-established, and there are differences among the three jurisdictions. The study is aimed to compare the legal basis, regulatory guidelines, application requirements, and evaluation criteria in each jurisdiction.Methods We conducted a comprehensive review of the registration application processes for PCMs in the Chinese mainland, Hong Kong, and Macau based on publicly available information from respective regulators.Results The study found that the registration application process in the GBA was complex and time-consuming, with differences in requirements and procedures among the three jurisdictions. The study also identified several challenges faced by PCM manufacturers, such as the lack of harmonisation of regulatory requirements and procedures and the requirement of package inserts and labelling for PCM products. The study proposed recommendations for improving the registration process and promoting the development of the PCM industry in the GBA.Conclusion This study provides a comprehensive understanding of the PCM product license application procedures and requirements in the GBA, coupled with discernment of their similarities and disparities, equips applicants with the knowledge to formulate an appropriate strategy for obtaining product approval. Exploring potential methods for harmonising the regulatory process stands to benefit manufacturers, regulators, and patients by improving efficiency and curtailing costs.

Abstract This paper investigates the impact of big data on deep learning models to help solve the full waveform inversion (FWI) problem. While it is well known that big data can boost the performance of deep learning models in many tasks, its effectiveness has not been validated for FWI. To address this gap, we present an empirical study that investigates how deep learning models in FWI behave when trained on openfwi, a collection of large-scale, multi-structural, synthetic datasets published recently. In particular, we train and evaluate the FWI models on a combination of 10 2D subsets in openfwi that contain 470 K pairs of seismic data and velocity maps in total. Our experiments demonstrate that training on the combined dataset yields an average improvement of 13.03% in MAE, 7.19% in MSE and 1.87% in SSIM compared to each split dataset, and an average improvement of 28.60%, 21.55% and 8.22% in the leave-one-out generalization test. We further demonstrate that model capacity needs to scale in accordance with data size for optimal improvement, where our largest model yields an average improvement of 20.06%, 13.39% and 0.72% compared to the smallest one.

Social desirability has been recognized as a predictor of life satisfaction but it has yet to know the mechanism of this effect. This research aimed to explore the relationship between social desirability and life satisfaction, as well as the mediation effects of mental toughness and emotional intelligence. In Sample 1, we asked 1200 youths (12-24 years old) to complete an online questionnaire measuring social desirability, life satisfaction, mental toughness, and emotional intelligence. Results indicated that social desirability had a direct positive effect on youth’s life satisfaction. In addition, mental toughness and emotional intelligence mediated the relationship between social desirability and life satisfaction, showing a chain role of mental toughness and emotional intelligence. A second sample (n = 750) was then used to verify the above findings, and similar results were found. These findings are consistent with our hypotheses, revealing the mechanisms of social desirability in relation to life satisfaction and the important role of mental toughness and emotional intelligence.

ObjectiveTo develop and validate a method for detecting ureteral stent encrustations in medical CT images based on Mask-RCNN and 3D morphological analysis.MethodAll 222 cases of ureteral stent data were obtained from the Fifth Affiliated Hospital of Sun Yat-sen University. Firstly, a neural network was used to detect the region of the ureteral stent, and the results of the coarse detection were completed and connected domain filtered based on the continuity of the ureteral stent in 3D space to obtain a 3D segmentation result. Secondly, the segmentation results were analyzed and detected based on the 3D morphology, and the centerline was obtained through thinning the 3D image, fitting and deriving the ureteral stent, and obtaining radial sections. Finally, the abnormal areas of the radial section were detected through polar coordinate transformation to detect the encrustation area of the ureteral stent.ResultsFor the detection of ureteral stent encrustations in the ureter, the algorithm’s confusion matrix achieved an accuracy of 79.6% in the validation of residual stones/ureteral stent encrustations at 186 locations. Ultimately, the algorithm was validated in 222 cases, achieving a ureteral stent segmentation accuracy of 94.4% and a positive and negative judgment accuracy of 87.3%. The average detection time per case was 12 s.ConclusionThe proposed medical CT image ureteral stent wall stone detection method based on Mask-RCNN and 3D morphological analysis can effectively assist clinical doctors in diagnosing ureteral stent encrustations.

The accurate measurement of pulverized coal concentration (PCC) is crucial for optimizing the production efficiency and safety of coal-fired power plants. Traditional microwave attenuation methods typically rely on a single frequency for analysis while neglecting valuable information in the frequency domain, making them susceptible to the varying sensitivity of the signal at different frequencies. To address this issue, we proposed an innovative frequency selection method based on principal component analysis (PCA) and orthogonal matching pursuit (OMP) algorithms and implemented a multi-frequency microwave sensing system for PCC measurement. This method transcended the constraints of single-frequency analysis by employing a developed hardware system to control multiple working frequencies and signal paths. It measured insertion loss data across the sensor cross-section at various frequencies and utilized PCA to reduce the dimensionality of high-dimensional full-path insertion loss data. Subsequently, the OMP algorithm was applied to select the optimal frequency signal combination based on the contribution rates of the eigenvectors, enhancing the measurement accuracy through multi-dimensional fusion. The experimental results demonstrated that the multi-frequency microwave sensing system effectively extracted features from the high-dimensional PCC samples and selected the optimal frequency combination. Filed experiments conducted on five coal mills showed that, within a common PCC range of 0–0.5 kg/kg, the system achieved a minimum mean absolute error (MAE) of 1.41% and a correlation coefficient of 0.85. These results indicate that the system could quantitatively predict PCC and promptly detect PCC fluctuations, highlighting its immediacy and reliability.

With the proposal of “double carbon strategy” and new power system construction, the increasing proportion of renewable energy sources and the wide access of power line sub-devices, the inertia support capacity of the power grid is gradually weakened and shows low inertia characteristics, which seriously threatens the system operation safety and frequency stability. In order to comprehensively grasp the operation status of the new power system and ensure its frequency stability, this paper proposes a renewable energy virtual control theory based on the established frequency response model of new power systems considering multiple inertial resources. Secondly, the inertial safety region (ISR) of the new power system considering the virtual inertia and frequency regulation capability of renewable energy is proposed to determine the frequency stability boundary, and its estimation method and procedure are introduced in detail. Finally, a case study and analysis are conducted in the New England system with actual operational data to verify the feasibility and effectiveness of the proposed method. The simulation results show that the method can effectively identify the ISR of the new power system and analyze the mechanism of the influence of renewable energy on ISR, and relevant conclusions are drawn from the simulation results.

In traction application, speed range of motor is an important index for motor drives. In AC motor control, the maximum speed of the motor is limited by the output voltage capability of the traditional three-phase inverter with star connenction of windings. Switching the star connection to delta connection in high-speed range can extend the speed range. In order to extend the speed operation region, star-delta switch proposed by many literatures relies on mechanical relay, which needs a dead zone of tens of milliseconds and seriously affects torque output. Besides, the traditional method will cause current overshoot during the switch transient process, decreasing the device security and reliability. Aiming at the defects existing in the star-delta hard switching, this paper proposes a star-delta soft switching method. Without adding extra power electronics devices, DC-bus capacitor is used to provide the path of zero axis current in the transient process, which helps to achieve the smooth torque output and zero current switch in the transient. Experiments have been done to validate the performance of the proposed method. The switching transient from star to delta connection in the motor drive can be much more stable than hard switching method.

Osteosarcoma is a common malignant tumor occurring in children and young adults. Chondroitin sulfate (CS) participates in cell adhesion, cell division, and the formation of neural networks in the body, the biosynthesis of which requires the participation of glycosyltransferases. CHPF, a glycosyltransferase, plays a role in the extension of CS. Recently, CHPF's biological roles and functional importance in human diseases including malignant tumors have been widely discussed. However, whether CHPF is involved in osteosarcoma development and growth has not been revealed. The present work aimed to investigate the expression levels, functional significance and molecular mechanism of CHPF in osteosarcoma progression. Our results revealed that CHPF is strongly expressed in osteosarcoma tissues and cells. Furthermore, CHPF serves as a tumor promoter in the development and progression of osteosarcoma through enhancing cell proliferation and migration while suppressing apoptosis. Exploration of the mechanism by which CHPF promotes osteosarcoma indicated that CHPF promotes osteosarcoma through counteracting SKP2's ubiquitination and activating the Akt signaling pathway. For the first time, we clarified the roles of CHPF in osteosarcoma, and our results suggested that CHPF might be a novel therapeutic target in the treatment strategies for osteosarcoma.

Abstract The development of high‐performance organic blue light‐emitting emitters is in urgent to act as an excitation source to contribute the white light generation. On the other hand, the investigation on optical waveguides have been received increasing attentions because they can manipulate the light propagation accurately in the microscale to boost the optoelectronic and energy conversion applications. In this work, we facilely prepared a deep‐blue aggregation‐induced emission (AIE) dye, namely TPP‐4OMe, which shows high luminescent efficiency, narrow emission band and good stability in the aggregate state. TPP‐4OMe can be fabricated as deep‐blue AIE microfibers readily with definite morphology and composition. Based on the AIE microfibers, the active waveguide to transmit deep‐blue emission signals can be achieved with a very low optical loss coefficient (α) of 6.7 × 10−3 dB μm−1. Meanwhile, the full‐visible broadband low‐loss passive waveguide can be well performed with these AIE microfibers, which has never been observed in the pure organic crystals. More interestingly, the excellent properties of AIE microfibers enable them to act as a wave‐guiding excitation source, resulting in a distinct and pure white light emission. The present work not only provides excellent blue light‐emitting materials but also bridges the waveguide to realize the efficient white light emission to accelerate the practical applications.

Objectives: Tetanus is a serious infectious disease. In recent decades, the epidemiology and disease characteristics of tetanus have been reported by many medical workers, but these studies usually have limited sample sizes. Methods: We retrieved all the epidemiological data related to tetanus from the Global Burden of Disease Study 2019, and a secondary analysis was performed to report the global epidemiology and disease burden of tetanus. Results: From 1990 to 2019, the incidence and death rate of tetanus decreased worldwide. In general, high sociodemographic index (SDI) countries have lower age-standard incidence rates and age-standard death rates than low SDI countries. Moreover, in low SDI regions, newborns were the highest-risk group for tetanus. In high SDI areas, half of the tetanus cases occurred in the 70+ years age group. The disease burden of tetanus was significantly higher in males than in females. Conclusion: The disease burden of tetanus decreased significantly worldwide from 1990 to 2019. Neonatal tetanus is serious in low SDI areas, whereas the proportion of elderly tetanus is the highest in high SDI areas. The containment of tetanus in all age groups and sex still requires effort from all sectors.

Abstract The high temperature (HT) characteristics of silicon carbide (SiC) devices enable power electronic converters to operate at higher ambient temperature, and the importance of HT isolated gate drivers is becoming increasingly significant. Compared with the complex silicon on insulator (SOI) HT chips and normal silicon (Si) ICs, the Si‐based discrete devices can well balance the temperature capability and design cost. A feasible isolated gate driver design method is proposed in this paper by using discrete MOSFETs, discrete BJTs and other passive components with consideration of cost and can be with less leakage current than normal integrated circuits. The function of gate driver includes signal isolation and signal amplification. In the signal isolation part, a CMOS‐based isolation circuit is proposed with its merits. In the signal amplification part, normal topologies are improved to get better efficiency and high‐speed capability. SiC power module‐based double pulse test is used to verify the switching performance, and experiments are done to verify the continuous operating capability. The main factors which affect the performance of the proposed isolated gate driver are summarized. This technology provides a novel solution for SiC MOSFET gate driver in HT environment.

This paper describes an N-path sub-GHz ultra-low power receiver exploiting an N-path notch filter topology in 90nm CMOS process. The receiver achieves the flexibility in the operating frequency due to an adjustable internal impedance matching network with an N-path notch filter. The receiver consists of two current-reused topologies, which greatly simplifies the structure and achieves ultra-low power consumption. Specifically, the receiver incorporates: 1) an amplifier with an N-path notch filter, which acts as the first stage of the receiver to provide an input impedance of $50~\Omega $ without an inductor. This input matching network is frequency flexible and adjustable to suit different frequencies of the input signal. Meanwhile, the N-path notch filter can suppress out-of-band interference to cope with limited frequency bands. 2) N-path passive mixers are reused for simultaneous filtering and down-conversion. 3) Amplifiers are frequency-division multiplexed to amplify both RF and baseband signals simultaneously. Finally, the receiver is fabricated in 90 nm CMOS and operates at 0.6 V supply voltage with a power consumption of $780~\mu \text{W}$ . The receiver achieves a conversion gain of 41.2 ± 3.2 dB, a noise figure of 5.7 ± 0.3 dB and an OB-IIP3 of 14.6 ± 0.5 dBm. The chip area of the implemented receiver is 0.08 mm2.

Albumins from animals are highly cross-reactive allergens for patients suffering from immunoglobulin E (IgE)-mediated allergy. Approximately 20-30% of cat and dog allergic patients show IgE reactivity and mount IgE-mediated allergic reactions to cat and dog albumin. It is astonishing that allergic patients can develop specific IgE responses against animal albumins because these proteins exhibit a more than 70% sequence identity to human serum albumin (HSA) which is the most abundant protein in the blood of the human body. The sequence identity of cat albumin (Fel d 2) and dog albumin (Can f 3) and HSA are 82% and 80%, respectively. Given the high degree of sequence identity between the latter two allergens and HSA one would expect that immunological tolerance would prohibit IgE sensitization to Fel d 2 and Can f 3. Here we discuss two possibilities for how IgE sensitization to Fel d 2 and Can f 3 may develop. One possibility is the failed development of immune tolerance in albumin-allergic patients whereas the other possibility is highly selective immune tolerance to HSA but not to Fel d 2 and Can f 3. If the first assumption is correct it should be possible to detect HSA-specific T cell responses and HSA-containing immune complexes in sensitized patients. In the latter scenario few differences in the sequences of Fel d 2 and Can f 3 as compared to HSA would be responsible for the development of selective T cell and B cell responses towards Fel d 2 as well as Can f 3. However, the immunological mechanisms of albumin sensitization have not yet been investigated in detail although this will be important for the development of allergen-specific prevention and allergen-specific immunotherapy (AIT) strategies for allergy to albumin.

Background and objective At present, more and more studies predict invasive adenocarcinoma (IAC) through three-dimensional features of pulmonary nodules, but few studies have confirmed that three-dimensional features have more advantages in diagnosing IAC than traditional two-dimensional features of pulmonary nodules. This study analyzed the differences of chest computed tomography (CT) features between IAC and minimally invasive adenocarcinoma (MIA) from three-dimensional and two-dimensional levels, and compared the ability of diagnosing IAC. The non-invasive adenocarcinoma group includes precursor glandular lesions (PGL) and minimally invasive adenocarcinoma (MIA). Methods The clinical data of 1,045 patients with ground glass opacity (GGO) from January to December 2019 were collected. Then the correlation between preoperative CT image characteristics and pathological results were analyzed retrospectively. The independent influencing factors for the identification of IAC were screened out according to two-dimensional and three-dimensional classification by multivariate Logistic regression and the cut-off point for the identification of IAC was found out through the receiver operating characteristic (ROC) curve. At last, the ability of diagnosing IAC was evaluated by Yoden index. Results The diameter of nodule, the diameter of solid component, the diameter of mediastinal window nodule in two-dimensional factors, and the volume of nodule, the volume of solid part and the average CT value in three-dimensional factors were independent risk factors for the diagnosis of IAC. These factors were arranged by Yoden index: solid partial volume (0.601)>nodule volume (0.536)>solid component diameter (0.525)>nodule diameter (0.518)>mediastinal window nodule diameter (0.488)>proportion of solid component volume (0.471)>1-tumor disappearance ratio (TDR) (0.468)>consolidation tumor ratio (CTR) (0.394)>average CT value (0.380). Conclusion The CT features of three-dimensional are better than two-dimensional in the diagnosis of IAC, and the size of solid components is better than the overall size of nodules.

ObstructiveTo develop and validate radiomics and machine learning models for identifying encrusted stents and compare their recognition performance with multiple metrics.MethodsA total of 354 patients with ureteral stent placement were enrolled from two medical institutions and divided into the training cohort (n = 189), internal validation cohort (n = 81) and external validation cohort (n = 84). Based on features selected by Wilcoxon test, Spearman Correlation Analysis and least absolute shrinkage and selection operator (LASSO) regression algorithm, six machine learning models based on radiomics features were established with six classifiers (LR, DT, SVM, RF, XGBoost, KNN). After comparison with those models, the most robust model was selected. Considering its feature importance as radscore, the combined model and a nomogram were constructed by incorporating indwelling time. Accuracy, sensitivity, specificity, area under the curve (AUC), decision curve analysis (DCA) and calibration curve were used to evaluate the recognition performance of models.Results1,409 radiomics features were extracted from 641 volumes of interest (VOIs) and 20 significant radiomics features were selected. Considering the superior performance (AUC 0.810, 95%CI, 0.722–0.888) in the external validation cohort, feature importance of XGBoost was used as a radscore, constructing a combined model and a nomogram with indwelling time. The accuracy, sensitivity, specificity and AUC of the combined model were 98, 100, 97.3% and 0.999 for the training cohort, 83.3, 80, 84.5% and 0.867 for the internal cohort and 78.2, 76.3, 78.8% and 0.820 for the external cohort, respectively. DCA indicates the favorable clinical utility of models.ConclusionMachine learning model based on radiomics features enables to identify ureteral stent encrustation with high accuracy.

ABSTRACT Anopheles mosquitoes are the primary vectors for the transmission of malaria parasites, which poses a devastating burden on global public health and welfare. The recent invasion of Anopheles stephensi in Africa has made malaria eradication more challenging due to its outdoor biting behavior and widespread resistance to insecticides. To address this issue, we developed a new approach for mosquito larvae control using gut microbiota-mediated RNA interference (RNAi). We engineered a mosquito symbiotic gut bacterium, Serratia fonticola, by deleting its RNase III gene to produce double-stranded RNAs (dsRNAs) in the mosquito larval gut. We found that the engineered S. fonticola strains can stably colonize mosquito larval guts and produce dsRNAs dsMet or dsEcR to activate RNAi and effectively suppress the expression of methoprene-tolerant gene Met and ecdysone receptor gene EcR, which encode receptors for juvenile hormone and ecdysone pathways in mosquitoes, respectively. Importantly, the engineered S. fonticola strains markedly inhibit the development of A. stephensi larvae and leads to a high mortality, providing an effective dsRNA delivery system for silencing genes in insects and a novel RNAi-mediated pest control strategy. Collectively, our symbiont-mediated RNAi (smRNAi) approach offers an innovative and sustainable method for controlling mosquito larvae and provides a promising strategy for combating malaria. IMPORTANCE Mosquitoes are vectors for various diseases, imposing a significant threat to public health globally. The recent invasion of A. stephensi in Africa has made malaria eradication more challenging due to its outdoor biting behavior and widespread resistance to insecticides. RNA interference (RNAi) is a promising approach that uses dsRNA to silence specific genes in pests. This study presents the use of a gut symbiotic bacterium, Serratia fonticola, as an efficient delivery system of dsRNA for RNAi-mediated pest control. The knockout of RNase III, a dsRNA-specific endonuclease gene, in S. fonticola using CRISPR-Cas9 led to efficient dsRNA production. Engineered strains of S. fonticola can colonize the mosquito larval gut and effectively suppress the expression of two critical genes, Met and EcR, which inhibit mosquito development and cause high mortality in mosquito larvae. This study highlights the potential of exploring the mosquito microbiota as a source of dsRNA for RNAi-based pest control.

With the rapid development of magnetic technology, the biological effects of moderate static magnetic fields (SMFs) have attracted increasing research interest due to their potential medical diagnosis and treatment application. The present study explored the effects of moderate SMFs on the lipid metabolism of Caenorhabditis elegans (C. elegans) in different genders including male, female, and hermaphrodite. We found that the fat content was significantly decreased by moderate SMFs in wild-type N2 worms, which was associated with their development stages. The diameters of lipid droplets in N2 worms, him-5 worms, and fog-2 worms were greatly decreased by 19.23%, 15.38%, and 23.07% at young adult stage under 0.5 T SMF, respectively. The mRNA levels of lipolysis related genes atgl-1 and nhr-76 were significantly up-regulated by SMF exposure, while the mRNA levels of the lipogenesis related genes fat-6, fat-7, and sbp-1 were down-regulated by SMF, whereas the concentration of β-oxidase was increased. There was a slight effect of SMF on the mRNA levels of β-oxidation related genes. Moreover, the insulin and serotonin pathway were regulated by SMF, instead of the TOR pathway. In wild-type worms, we found that their lifespan was prolonged by exposure to 0.5 T SMF. Our data suggested that moderate SMFs could significantly modify the lipogenesis and lipolysis process in C. elegans in a gender and development stage-dependent manner, which could provide a novel insight into understanding the function of moderate SMFs in living organisms.

With the rapid development of renewable energy and High Voltage Direct Current (HVDC), the power system is turning to be a low-inertia system. Due to insufficient inertia on the power side, the proportion of inertia on the load side increases. The frequency support ability of the induction machine in the inertial time scale needs to be investigated. The purpose of this paper is to analyze the time-varying characteristics of the effective inertia of induction machine and to estimate the frequency support ability of induction machine. In this paper, the induction machine model in electromechanical transient process is established, and its transfer function is deduced by using small-signal model, and the time-varying characteristics and affecting factors of the induction machine’s inertia on the grid are analyzed. Besides, an evaluation model of the equivalent inertia of induction machine is proposed to quantify the inertial support ability of dynamic loads, and the frequency support ability of the model and the dynamic characteristics of induction machine are analyzed. Finally, the simulation model is conducted on MATLAB/Simulink platform to verify the correctness and effectiveness of the model proposed in this paper.

Inappropriate soil management accelerates soil erosion and thus poses a serious threat to food security and biodiversity. Due to poor data availability and fragmented terrain, the landscape pattern of garden erosion in tropical Xishuangbanna is not clear. In this study, by integrating multi-source satellite imagery, field investigation and visual interpretation, we realized high-resolution mapping of gardens and soil conservation measures at the landscape scale. The Chinese Soil Loss Equation (CSLE) model was then performed to estimate the garden erosion rates and to identify critical erosion-prone areas; the landscape pattern of soil erosion was further discussed. Results showed the following: (1) For the three major plantations, teas have the largest degree of fragmentation and orchards suffer the highest soil erosion rate, while rubbers show the largest patch area, aggregation degree and soil erosion ratio. (2) The average garden erosion rate is 1595.08 t·km−2a−1, resulting in an annual soil loss of 9.73 × 106 t. Soil erosion is more susceptible to elevation and vegetation cover rather than the slope gradient. Meanwhile, irreversible erosion rates only occur in gardens with fraction vegetation coverage (FVC) lower than 30%, and they contribute 68.19% of total soil loss with the smallest land portion, indicating that new plantations are suffering serious erosion problems. (3) Garden patches with high erosion intensity grades and aggregation indexes should be recognized as priorities for centralized treatment. For elevations near 1900 m and lowlands (

Abstract Background Periacetabular malignant tumor seriously endangers the life and health of patients. Hemipelvic replacement provides a good method for patients who want complete resection of the tumor while retaining or restoring the function of the affected limb. Objective To investigate the performance and clinical application of the new adjustable modular hemipelvic prosthesis and to compare the effects of three kinds of hemipelvic prosthesis. Methods In this study, 23 patients, with an average age of 44.6 years (21–75 years), were collected, who received hemipelvic replacement with new adjustable, modular, and screw-rod system hemipelvic prosthesis. Preoperative preparation was conducted on them, and operative complications were recorded. Postoperative functional follow-up was performed regularly. Results The average operation time was 319 min (170–480 min), and the average blood loss was 2813 ml (1000 mL-8000 ml). The incidence of complications was 47.8%, and type A (wound-related complications) had the highest incidence (34.8%). Postoperative dislocation occurred in 3 cases (13.0%), and no dislocation occurred in the new adjustable modular hemipelvic prosthesis group. The average MSTS score of the patients was 18.6 (10–23), and the average Harris score was 73.7 (53–87). Conclusions The new adjustable modular hemipelvic prosthesis has the feasibility of reconstruction and good functional outcome, making it ideal for periacetabular tumors. Furthermore, preoperative tumor-feeding artery embolization and abdominal aortic balloon implantation may be an effective choice to reduce intraoperative blood loss and facilitate the operation of tumor resection.

Background and objective At present, the research progress of targeted therapy for epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) gene mutations in lung adenocarcinoma is very rapid, which brings new hope for the treatment of advanced lung adenocarcinoma patients. However, the specific imaging and pathological features of EGFR and ALK gene mutations in adenocarcinoma are still controversial. This study will further explore the correlation between EGFR, ALK gene mutations and imaging and pathological features in invasive lung adenocarcinoma. Methods A total of 525 patients with lung adenocarcinoma who underwent surgery in our center from January 2018 to December 2019 were included. According to the results of postoperative gene detection, the patients were divided into EGFR gene mutation group, ALK gene mutation group and wild group, and the EGFR gene mutation group was divided into exon 19 and exon 21 subtypes. The pathological features of the mutation group and wild group, such as histological subtype, lymph node metastasis, visceral pleural invasion (VPI) and imaging features such as tumor diameter, consolidation tumor ratio (CTR), lobulation sign, spiculation sign, pleural retraction sign, air bronchus sign and vacuole sign were analyzed by univariate analysis and multivariate Logistic regression analysis to explore whether the gene mutation group had specific manifestations. Results EGFR gene mutation group was common in women (OR=2.041, P=0.001), with more pleural traction sign (OR=1.506, P=0.042), and had little correlation with lymph node metastasis and VPI (P>0.05). Among them, exon 21 subtype was more common in older (OR=1.022, P=0.036), women (OR=2.010, P=0.007), and was associated with larger tumor diameter (OR=1.360, P=0.039) and pleural traction sign (OR=1.754, P=0.029). Exon 19 subtype was common in women (OR=2.230, P=0.009), with a high proportion of solid components (OR=1.589, P=0.047) and more lobulation sign (OR=2.762, P=0.026). ALK gene mutations were likely to occur in younger patients (OR=2.950, P=0.045), with somking history (OR=1.070, P=0.002), and there were more micropapillary components (OR=4.184, P=0.019) and VPI (OR=2.986, P=0.034) in pathology. Conclusion The EGFR and ALK genes mutated adenocarcinomas have specific imaging and clinicopathological features, and the mutations in exon 19 or exon 21 subtype have different imaging features, which is of great significance in guiding the clinical diagnosis and treatment of pulmonary nodules.

The incidence and mortality of lung cancer rank first among all malignant tumors in China. With the popularization of high resolution computed tomography (CT) in clinic, chest CT has become an important means of clinical screening for early lung cancer and reducing the mortality of lung cancer. Imaging findings of early lung adenocarcinoma often show partial solid nodules with ground glass components. With the development of imaging, the relationship between the imaging features of some solid nodules and their prognosis has attracted more and more attention. At the same time, with the development of 3D-reconstruction technology, clinicians can improve the accuracy of diagnosis and treatment of such nodules.This article focuses on the traditional imaging analysis of partial solid nodules and the imaging analysis based on 3D reconstruction, and systematically expounds the advantages and disadvantages of both.

Artificial nest boxes are placed to attract birds to nest and breed in a specific location, and they are widely used in avian ecology research and in the attraction of insectivorous birds. There is evidence that artificial nest boxes can adversely affect breeding fitness but no great focus has been placed on this issue by researchers. Therefore, we retrieved 321 research papers regarding artificial nest boxes published from 2003 to 2022 and used the ‘Biblioshiny’ program to extract and integrate keywords; we then summarized the adverse effects of artificial nest boxes on avian breeding success. The studies highlighted many drawbacks and misuses in the designing and placement of nest boxes; furthermore, bird attraction was decreased by their inappropriate selection, thus reducing breeding success. Regarding nest box production, there were shortcomings in the construction material, color, smell, and structural design of the boxes used. Nest boxes were also placed at inappropriate densities, locations, orientations, heights, and managed incorrectly. Finally, we propose suggestions for more efficient and safer artificial nest boxes for future use in avian ecology research and bird conservation.

Objectives: Pulmonary air leakage is a common complication following lung resection. We have designed a new method combining oxidized regenerated cellulose and fibrin glue to cover the intersegmental plane in clinical lung segmentectomy to prevent postoperative air leakage. In this study, an excised porcine lung segmentectomy model was created to validate its adhesive strength and effect on reducing air leakage.Methods: In the pre-experiment, six different larger lung segments were separated using electrocautery on the fresh isolated porcine lungs (n = 5 in each group). The air leakage degree and operation time of the lung segments were comprehensively evaluated to select the most suitable target segment for establishing the ex vivo porcine lung segmentectomy models. In the experiment, according to the different materials covered on the intersegmental plane, these models were randomly divided into four groups: group A used fibrin glue and oxidized regenerated cellulose (ORC) mesh (n = 20); group B used fibrin glue and polyglycolic acid (PGA) sheet (n = 20); group C used fibrin glue (n = 20); group D was the blank control group (n = 20). The minimum air leakage pressure (MALP) of the selected target segment in each group was measured using a stepwise increase of airway pressure, and histological assessment was performed on the sealed area samples from the four groups.Results: The operation time of the a segment of the right cranial lobe (R1a) was shorter than that of other segments (p < 0.05), and there was no significant difference in the air leakage pressures between the six isolated segments (p = 0.76); thus, R1a was chosen for segmentectomy. In addition, the MALP was significantly higher in group A (41.8 ± 4.5 cmH2O) than in groups C (28.1 ± 2.3 cmH2O) and D (17.3 ± 1.2 cmH2O) (both p < 0.001). The MALP of group B (69.5 ± 5.2 cmH2O) was significantly higher than that of group A (p < 0.001), whereas that of group C was significantly higher than that of group D (p < 0.001). Histological examination confirmed that the combined use of fibrin glue and ORC or PGA patch adhered more firmly to the intersegmental plane than that of fibrin glue alone, although some gaps could be seen between the fibrin glue and the surface of the lung segments in group C.Conclusion: The application of ORC combined with fibrin glue on the intersegmental plane has a good sealing performance in the ex vivo porcine lung segmentectomy model, suggesting that ORC may be an effective alternative material to replace PGA sheet to combine with fibrin glue for preventing air leakage after segmentectomy.

With the global attention given to energy issues, the electrification of aviation and the development of more electric aircraft (MEA) have become important trends in the modern aviation industry. The electric actuator plays multiple roles in aircraft such as flight control, making it a crucial technology for MEA. Given the limited space available inside an aircraft, the power density of electric actuators has become a critical design factor. However, the pursuit of high power density results in the need for larger rated power and higher switching frequency, which can lead to severe electromagnetic interference (EMI) issues. This, in turn, poses significant challenges to the overall reliability of the electric actuator. This paper provides a comprehensive review of EMI in high power density motor drive systems for electric actuator systems. Firstly, the state of the art of electric actuator systems are surveyed, pointing out the contradictory relationship between high power density and EMI. Subsequently, various EMI modeling approaches of motor control systems are reviewed. Additionally, the main EMI suppression methods are summarized. Active EMI mitigation methods are emphasized in this paper due to their advantages of higher power density compared with passive EMI filters. Finally, the paper concludes by summarizing the EMI research in motor drive systems and offering the prospects of electric actuators.

The real-time monitoring of food freshness in refrigerators is of significant importance in detecting potential food spoiling and preventing serious health issues. One method that is commonly reported and has received substantial attention is the discrimination of food freshness via the tracking of volatile molecules. Nevertheless, the ambient environment of low temperature (normally below 4 °C) and high humidity (90% R.H.), as well as poor selectivity in sensing gas species remain the challenge. In this research, an integrated smart gas-tracking device is designed and fabricated. By applying pump voltage on the yttria-stabilized zirconia (YSZ) membrane, the oxygen concentration in the testing chamber can be manually tailored. Due to the working principle of the sensor following the mixed potential behavior, distinct differences in sensitivity and selectivity are observed for the sensor that operated at different oxygen concentrations. Typically, the sensor gives satisfactory selectivity to H2S, NH3, and C2H5OH at the oxygen concentrations of 10%, 30%, and 40%, respectively. In addition, an acceptable response/recovery rate (within 24 s) is also confirmed. Finally, a refrigerator prototype that includes the smart gas sensor is built, and satisfactory performance in discriminating food freshness status of fresh or semi-fresh is verified for the proposed refrigerator prototype. In conclusion, these aforementioned promising results suggest that the proposed integrated smart gas sensor could be a potential candidate for alarming food spoilage.

Abstract Background During thoracoscopic segmentectomy, accurately and rapidly identifying the intersegmental plane (ISP) is of great importance. This study aimed to investigate the effect and safety of a nitrous oxide (N2O)/oxygen (O2) inspired mixture on the appearance time of the ISP (TISP) via the modified inflation‐deflation method. Methods A total of 65 participants who underwent segmentectomy were randomized into three groups: 75% N2O (n = 24), 50% N2O (n = 23) or 0% N2O (n = 18). The 75% N2O group received a gas mixture of N2O/O2 (Fio2 = 0.25), the 50% N2O group received N2O/O2 (Fio2 = 0.5), and the 0% N2O group received 100% oxygen during lung expansion. The appearance time of satisfactory and ideal planes was recorded. Furthermore, arterial blood gas at breathing room air, one‐lung ventilation (OLV) before lung expansion, 5 and 15 min after lung expansion were also recorded. Results TISP was significantly shorter in the 75% N2O group (320.2 ± 65.9 s) compared with that of the 50% N2O group (552.4 ± 88.9 s, p

This paper presents a wideband dB-linear variable-gain amplifier (VGA) with a DC-offset cancellation network in a 90-nm CMOS technology for high-speed applications. The VGA consists of a four-stage Cherry-Hooper amplifier, which is based on a feedback resistor and negative Miller capacitance to obtain wide bandwidth without inductors in the main circuit. A unique method for this structure to generate pseudo-exponential function is analyzed in detail. Therefore, an accurate dB-linear characteristic is realized in this VGA without any exponential generator circuits. The linear control voltage is applied directly to the gate of the transistor and this simple control method exhibits good robustness to process and temperature variation. Measurement results show that the voltage gain varies from −28 dB to 27 dB continuously with more than 4.3 GHz bandwidth and a dB-linear range of 32 dB with less than ±0.6 dB gain error. Without the output buffer, it consumes 8.5 mW from a 1.2V supply and occupies a small die area of only 0.04 mm2.

Due to the rapid growth of transportation demand for economic development, the importance of effective urban traffic signal control can never be underestimated, and the severe space saturation greatly limit the operations of a transportation system. In this paper, public buses and other vehicles are treated as different traffic flows. We address the urban traffic signal control problem in a scheduling framework by considering that the capacity of a public bus is much greater than that of other vehicles. The dynamics of an urban traffic network controlled by traffic lights are described by a novel model, which is formed by inserting mixed logical constraints into a cell transmission flow dynamic model. It includes the nonlinear relationship among the current link volume from the upstream, the current remaining link capacity from the downstream, and the state of the traffic lights. With the objective of minimizing the total delay time in a traffic network for people in the private vehicles and buses, we obtain a mixed integer linear programming formulation, which is built from the traffic signal control problem. We further analyze the influence of the number of passengers on buses and the time interval. The efficiency of the proposed method is verified by making comparisons between the models with and without considering the public transport regular. When the average number of passengers on a bus increases from 10 to 60, the degree of optimization ranges from 17% to 51% for the two-stage model and from 4% to 26% for the four-stage model. Finally, we consider the case without bus lanes and show the importance of dedicated bus lanes.

The continuous transformation from biodiverse natural forests and mixed-use farms into monoculture rubber plantations may lead to a series of hazards, such as natural forest habitats fragmentation, biodiversity loss, as well as drought and water shortage. Therefore, understanding the spatial distribution of rubber plantations is crucial to regional ecological security and a sustainable economy. However, the spectral characteristics of rubber tree is easily mixed with other vegetation such as natural forests, tea plantations, orchards and shrubs, which brings difficulty and uncertainty to regional scale identification. In this paper, we proposed a classification method combines multi-source phenology characteristics and random forest algorithm. On the basis of optimization of input samples and features, phenological spectrum, brightness, greenness, wetness, fractional vegetation cover, topography and other features of rubber were extracted. Five classification schemes were constructed for comparison, and the one with the highest classification accuracy was used to identify the spatial pattern of rubber plantations in 2014, 2016, 2018 and 2020 in Xishuangbanna. The results show that: (1) the identification results are in consistent with field survey and rubber plantations area generally shows a first increasing and then decreasing trend; (2) the Overall Accuracy (OA) and Kappa coefficient of the proposed method are 90.0% and 0.86, respectively, with a Producer’s Accuracy (PA) and User’s Accuracy (UA) of 95.2% and 88.8%, respectively; (3) cross-validation was employed to analyze the accuracy evaluation indexes of the identification results: both PA and UA of the rubber plantations stay stable over 85%, with the minimum fluctuation and best stability of UA value. The OA value and Kappa coefficient were stable in the range of 0.88–0.90 and 0.84–0.86, respectively. The method proposed provides reliable results on spatial distribution of rubber, and is potentially transferable to other mountainous areas as a robust approach for rapid monitoring of rubber plantations.

As industrial development increases, electric machine systems are more widely used in industrial production. Rolling bearings play a key role in machine systems and so the prevention of faults in rolling bearings is more important than ever before. Recently, with the development of artificial intelligence, neural networks have been used to monitor the remaining useful life of rolling bearings. However, there are two problems with this technique. First, a network trained by data for a single operating condition (source domain) cannot predict the remaining useful life of bearings under a different operating condition (target domain), such as a different load or speed. Second, a large number of labeled data are needed for network training, but the acquisition of labeled data for different operating conditions is a challenging task. To address these problems, this paper proposes a domain-adaptive adversarial network, in which a transfer learning strategy and maximum mean discrepancy algorithm are used for network optimization, so that remaining useful life can be predicted without labeled data in target domain training. Our results confirm that a model trained by source domain data alone cannot predict the remaining useful life of bearings under different conditions, but the domain-adaptive adversarial network can accurately predict remaining useful life for varying operating conditions. The method proposed also exhibits good performance even if there are noises in the signals.

With the phase angle and shape modifications for carriers, two improved carrier-based pulse width modulation (CPWM) methods with common-mode voltage (CMV) suppression effects for the five-phase open-winding drive topologies are introduced. Theoretical analysis reveals that, by employing reversed triangular carriers for two inverters under the carrier-reversed PWM (CRPWM), CMV contributions of two bridge legs belonging to the same phase can be cancelled, realizing the zero CMV effect. By dynamically employing positive and negative sawtooth carriers for all bridge legs under the carrier-switching PWM (CSPWM), the CMV contribution of each inverter can be reduced, decreasing both the amplitude and step frequency of the CMV. Current qualities and dead-time effects on CMV under the above PWM methods are analyzed. Moreover, performances of two PWM methods are verified by experiments implemented on a five-phase open-winding topology with the induction motor load.

BackgroundAseptic prosthetic loosening is one of the main factors causing poor prognosis of limb function after joint replacement and requires troublesome revisional surgery. It is featured by wear particle-induced periprosthetic osteolysis mediated by excessive osteoclasts activated in inflammatory cell context. Some natural compounds show antiosteoclast traits with high cost-efficiency and few side effects. Tussilagone (TUS), which is the main functional extract from Tussilago farfara generally used for relieving cough, asthma, and eliminating phlegm in traditional medicine has been proven to appease several RAW264.7-mediated inflammatory diseases via suppressing osteoclast-related signaling cascades. However, whether and how TUS can improve aseptic prosthetic loosening via modulating osteoclast-mediated bone resorption still needs to be answered.MethodsWe established a murine calvarial osteolysis model to detect the preventative effect of TUS on osteolysis in vivo. Micro-CT scanning and histomorphometric analysis were used to determine the variation of bone resorption and osteoclastogenesis. The anti–osteoclast-differentiation and anti–bone-resorption bioactivities of TUS in vitro were investigated using bone slice resorption pit evaluation, and interference caused by cytotoxicity of TUS was excluded according to the CCK-8 assay results. Quantitative polymerase chain reaction (qPCR) analysis was applied to prove the decreased expression of osteoclast-specific genes after TUS treatment. The inhibitory effect of TUS on NF-κB and p38 MAPK signaling pathways was testified by Western blot and NF-κB-linked luciferase reporter gene assay.ResultsTUS better protected bones against osteolysis in murine calvarial osteolysis model with reduced osteoclasts than those in the control group. In vitro studies also showed that TUS exerted antiosteoclastogenesis and anti–bone-resorption effects in both bone marrow macrophages (BMMs) and RAW264.7 cells, as evidenced by the decline of osteoclast-specific genes according to qPCR. Western blotting revealed that TUS treatment inhibited IκBα degradation and p38 phosphorylation.ConclusionsCollectively, our studies proved for the first time that TUS inhibits osteoclastogenesis by suppressing the NF-κB and p38 MAPK signaling pathways, therefore serving as a potential natural compound to treat periprosthetic osteolysis-induced aseptic prosthetic loosening.

Multiphase machines are gaining increasing popularity because of their distinct advantages over three-phase counterparts, such as reduced per phase power rating, improved reliability and increased degrees of freedom. This paper overviews the development history of multiphase machines and drive techniques in Section II. Three kinds of drive algorithms, including Field-Oriented Control (FOC), Direct Torque Control (DTC) and Model Predictive Control (MPC), are introduced in Section III. Then two types of fault-tolerant methods are compared in Section IV, which are the Vector Space Decomposition (VSD) strategy and Optimal Current Control (OCC) method. Furthermore, different types of existing multiphase converter topologies are listed in Section V, and various kinds of multiphase PWM methods are discussed in Section VI. Finally, based on the review, developing trends of multiphase drive techniques are forecasted.

Abstract BaTi1−xSnxO3 (BTSn, 0 ≤ x ≤ 0.30) ceramics were prepared by both the conventional sintering (CS) and sparking plasma sintering (SPS). Composition, temperature and grain size dependences of the nonlinear dielectric behaviors were systematically studied. BTSn was found to have especially large tunability (≥90%), which is larger than most other Pb-free systems, and is comparable to Pb-based relaxors. The high dielectric tunability in BTSn is attributed to its specific domain structures. Besides, temperature dependent tunability of BTSn presents a dispersed behavior and the dispersion is enhanced with the increase of Sn4+ concentrations, which is explained by the compositional fluctuation model.

It is very difficult to schedule a single-arm cluster tool with wafer revisiting such that wafer residency time constraints are satisfied. This article conducts a study on this challenging problem for a single-arm cluster tool with atomic layer deposition process. With a so-called p -backward strategy being applied, a Petri net model is developed to describe the dynamic behavior of the system. Based on the model, the existence of a feasible schedule is analyzed, schedulability conditions are derived, and scheduling algorithms are presented if there is a schedule. A schedule is obtained by simply setting the robot waiting time if schedulable, and it is very computationally efficient. The obtained schedule is shown to be optimal. Illustrative examples are given to demonstrate the proposed approach.

Bearing temperature rise amplitude is related to the running state of bearing and spindle thermal error, so the measurement of bearing temperature field is helpful to ascertain the bearing running characteristic and analysis of the spindle thermal error. On the basis of thoroughly understood several reasons of bearing heat generation, this article analyzes bearing temperature field simulation based on ANSYS and bearing temperature field measurement based on fiber Bragg grating sensors. The results showed that using fiber Bragg grating is able to complete the bearing temperature field distribution measurement perfectly.

This paper proposes optimized control methods for global minimum backflow power based on a triple-phase-shift (TPS) control strategy. Three global optimized methods are derived to minimize the backflow power on the primary side, on the secondary side and on both sides, respectively. Backflow power transmission is just a portion of non-active power transmission in a dual active bridge (DAB) converter. Non-active power transmission time is proposed in this paper, which unifies zero power transmission and backflow power transmission. Based on the proposed index, an optimized control method is derived to achieve both the maximum effective power transmission time and minimum current stress of DAB at the same time. A comparative analysis is performed to show the limitations of the minimum backflow power optimization method. Finally, a prototype is built to verify the effectiveness of our theoretical analysis and the proposed control methods by experimental results.