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Abstract Objective The aim of this study was to establish an ensemble learning model based on clinicopathological parameter and ultrasound radomics for assessing the risk of lateral cervical lymph node with short diameter less than 8 mm (small lymph nodes were used instead) metastasis in patients with papillary thyroid cancer (PTC), thereby guiding the selection of surgical methods. Methods This retrospective analysis was conducted on 454 patients diagnosed with papillary thyroid carcinoma who underwent total thyroidectomy and lateral neck lymph node dissection or lymph node intraoperative frozen section biopsy at the First Hospital of China Medical University between January 2015 and April 2022. In a ratio of 8:2, 362(80%) patients were assigned to the training set and 92(20%) patients were assigned to the test set. Clinical pathological features and radomics features related to ultrasound imaging were extracted, followed by feature selection using recursive feature elimination (RFE). Based on distinct feature sets, we constructed ensemble learning models comprising random forest (RF), extreme gradient boosting (XGBoost), categorical boosting (CatBoost), gradient boosting decision tree (GBDT), and light gradient boosting machine (Lightgbm) to develop clinical models, radiomics models, and clinical-radiomic models. Through the comparison of performance metrics such as area under curve (AUC), accuracy (ACC), specificity (SPE), precision (PRE), recall rate, F1 score, mean squared error (MSE) etc., we identified the optimal model and visualized its results using shapley additive exPlanations (SHAP). Results In this study, a total of 454 patients were included, among whom 342 PTC patients had small lymph node metastasis in the lateral neck region, while 112 did not have any metastasis. A total of 1035 features were initially considered for inclusion in this study, which were then narrowed down to 10 clinical features, 8 radiomics features, and 17 combined clinical-omics features. Based on these three feature sets, a total of fifteen ensemble learning models were established. In the test set, RF model in the clinical model is outperforms other models (AUC = 0.72, F1 = 0.75, Jaccard = 0.60 and Recall = 0.84), while CatBoost model in the radiomics model is superior to other models (AUC = 0.91, BA = 0.83 and SPE = 0.76). Among the clinical-radiomic models, Catboost exhibits optimal performance (AUC = 0.93, ACC = 0.88, BA = 0.87, F1 = 0.91, SPE = 0.83, PRE = 0.88, Jaccard = 0.83 and Recall = 0.92). Using the SHAP algorithm to visualize the operation process of the clinical-omics CatBoost model, we found that clinical omics features such as central lymph node metastasis (CLNM), Origin_Shape_Sphericity (o_shap_sphericity), LoG-sigma3_first order_ Skewness (log-3_fo_skewness), wavelet-HH_first order_Skewness (w-HH_fo_skewness) and wavelet-HH_first order_Skewness (sqr_gldm_DNUN) had the greatest impact on predicting the presence of lateral cervical small lymph node metastasis in PTC patients. Conclusions (1) In this study, among the ensemble learning models established based on clinicopathological features and radiomics features for predicting PTC lateral small lymph node metastasis, the clinical-radiomic CatBoost model has the best performance. (2) SHAP can visualize how the clinical and radiomics features affect the results and realize the interpretation of the model. (3) The combined CatBoost model can improve the diagnostic accuracy of suspicious lymph nodes with short diameter

Sorting is one of the basic algorithms in computer science, and has been extensively used in a variety of applications.In the big data era, as the volumes of data increase rapidly, parallel sorting has attracted much attention.Existing parallel sorting algorithms suffered from excessive communication overhead and load imbalance, making it difficult to scale massively.To solve above problems, a scalable parallel algorithm sorting by regular sampling (ScaPSRS) was proposed, which sampled the p-1 pivot elements to divide the entire data set into p disjoint subsets by all parallel processes, rather than by only one given process as PSRS did.Furthermore, ScaPSRS adopted a novel iterative update strategy of selecting pivots to guarantee that the workloads and data were evenly scheduled among the parallel processes, thus ensuring superior overall performance.A variety of experiments conducted on the Tianhe-Ⅱ supercomputer demonstrated that ScaPSRS succeeded in scaling to 32 000 cores and outperformed state-of-the-art works significantly.

Natural gas depressurization at city gate stations can cause hydrate formation, necessitating preheating before pressure regulation. To reduce the high energy consumption of traditional city gate station preheating processes, this study introduces four novel multi-energy coupled systems: photovoltaic-air source heat pump (PV-ASHP), solar thermal-combined heat and power-ASHP (ST-CHP-ASHP), CHP-ASHP, and ASHP system, with a typical city gate station in Shanghai taken as the research case. Dynamic energy simulation systems were developed in Dymola software to evaluate the proposed systems from energy, environmental, and economic perspectives, conducting a comparison with conventional boiler preheating systems, including sensitivity analysis of energy prices on system economics. Results indicate PV-ASHP has the lowest annual total cost (ATC) and shortest discounted payback period, while ATC values for ST-CHP-ASHP, CHP-ASHP, and ASHP increase by 6.4 %, 9.6 %, and 12.6 %, respectively. ST-CHP-ASHP and PV-ASHP demonstrate advantages in primary energy rate and carbon emissions, with ST-CHP-ASHP performing slightly better than PV-ASHP. Currently, PV-ASHP demonstrates the highest development potential. If photovoltaic feed-in tariffs remain constant, and natural gas prices decrease by over 12.5 % or CHP feed-in tariffs increase by over 38.4 %, ST-CHP-ASHP becomes more economically viable. This research provides valuable insights for retrofitting China's existing city gate station preheating systems.

Abstract Introduction Breast cancer ranks second as the most common malignancy globally, after lung cancer. Among the various subtypes of breast cancer, HER2 positive breast cancer (HER2 BC)poses a particularly challenging prognosis due to its heightened invasiveness and metastatic potential. The objective of this study was to construct a composite piezoelectric nanoparticle based on poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)) for imaging and treatment of HER2 BC. Method By reshaping the crystal structure of P(VDF-TrFE) piezoelectric nanoparticles, improving hydrophilicity, and incorporating imaging capabilities, we developed piezoelectric composite nanoparticles (PGd@tNBs) that integrate imaging and therapeutic functions. The in vitro characterization encompassed the assessment of piezoelectric properties, hydrophilicity, imaging performance, and therapeutic efficacy of these particles. The targeting and therapeutic effectiveness of PGd@tNBs particles were further validated in the SK-BR3 cell line and subsequently confirmed in HER2-positive tumor-bearing mice. Results The nanoparticle demonstrated excellent biocompatibility and impressive multimodal imaging performance. Magnetic resonance imaging (MRI) observations revealed significant accumulation of PGd@tNBs particles in the HER2 positive tumor, exhibiting superior contrast-enhanced ultrasound performance compared to traditional ultrasound contrast agents, and small animal in vivo imaging showed that PGd@tNBs particles were primarily excreted through respiration and urinary metabolism. Piezoforce Microscopy characterization highlighted the outstanding piezoelectric properties of PGd@tNBs particles. Upon targeted binding to HER2-BC, ultrasound stimulation influenced the cell membrane potential, leading to reversible electroporation. This, in turn, affected the balance of calcium ions inside and outside the cells and the mitochondrial membrane potential. Following ingestion by cells, PGd@tNBs, when exposed to ultrasound, triggered the generation of reactive oxygen species (ROS), resulting in the consumption of glutathione and superoxide dismutase and achieving sonodynamic therapy. Notably, repeated ultrasound stimulation, post PGd@tNBs particles binding and entry into cells, increased ROS production and elevated the apoptosis rate by approximately 45%. Conclusion In conclusion, the PGd@tNBs particles developed exhibit outstanding imaging and therapeutic efficacy, holding potential for precise diagnosis and personalized treatment of HER2 BC.

Abstract Drug resistance represents a significant obstacle in cancer treatment, underscoring the need for the discovery of novel therapeutic targets. Ubiquitin-specific proteases (USPs), a subclass of deubiquitinating enzymes, play a pivotal role in protein deubiquitination. As scientific research advances, USPs have been recognized as key regulators of drug resistance across a spectrum of treatment modalities, including chemotherapy, targeted therapy, immunotherapy, and radiotherapy. This comprehensive review examines the complex relationship between USPs and drug resistance mechanisms, focusing on specific treatment strategies and highlighting the influence of USPs on DNA damage repair, apoptosis, characteristics of cancer stem cells, immune evasion, and other crucial biological functions. Additionally, the review highlights the potential clinical significance of USP inhibitors as a means to counter drug resistance in cancer treatment. By inhibiting particular USP, cancer cells can become more susceptible to a variety of anti-cancer drugs. The integration of USP inhibitors with current anti-cancer therapies offers a promising strategy to circumvent drug resistance. Therefore, this review emphasizes the importance of USPs as viable therapeutic targets and offers insight into fruitful directions for future research and drug development. Targeting USPs presents an effective method to combat drug resistance across various cancer types, leading to enhanced treatment strategies and better patient outcomes.

Energy conservation and emission reduction are critical global concerns, with infrared gas stoves recognized for their superior thermal efficiency and low emissions. However, research on infrared gas stoves with vertical ejectors, particularly those designed for use in horizontally constrained spaces, remains sparse. To bridge this gap, an experimental system is constructed to investigate the effects of perforated plate height, nozzle exit position (NXP), and heating height on stove performance. The experimental results reveal that gas uniformity is significantly influenced by the height of the perforated plate, while NXP has a lesser impact. The optimal height of the perforated plate is 12 mm, and the recommended value for NXP is −4 mm. With the heating height increasing from 15.0 mm to 36.5 mm, the thermal efficiency of the infrared gas stove decreases from 70.2 % to 59.3 %. The concentration of carbon monoxide in the flue gas initially declines sharply then gradually increases with the increase of heating height. Meanwhile, the concentration of nitrogen oxide exhibits slight fluctuations, with a mere 2 ppm difference between maximum and minimum values. Based on the results, a heating height of 19.3 mm is recommended. This study provides guidance for optimizing domestic gas stoves.

Abstract Waste heat recovery is common in high‐temperature water electrolysis production, but the latent heat from the hydrogen–water mixture is not fully utilized, and the electric heater to generate steam consumes much energy. In this research, a cascade heat pump is proposed to recover the latent heat from electrolysis products and generate steam. The heat pump can save as much as 65% electric energy compared with a single electric heater. Although in some cases, the latent heat is not enough to generate sufficient steam, it can still save 46.1% of energy. Also, this research emphasizes the significant influence of hydrogen and water proportion in electrolysis products. Compared with 80% water proportion, 50% water proportion can save 1.67 MW energy just in the water vaporization process for a 10 MW electrolyzer. The payback period is 3.43 years, which makes it worth investing.

Introduction: Poly(vinylidene fluoride-trifluoroethylene) [P(VDF-TrFE)] stands out as an organic polymer with remarkable piezoelectric properties, coupled with high chemically stability and biocompatibility, rendering it the most promising organic piezoelectric nanomaterial. Therefore, we aim to explore its developmental history, find current research hotspots, and identify emerging trends.Methods: To comprehensively review the pertinent literature on poly(vinylidene fluoride-trifluoroethylene) or P(VDF-TrFE) in English from 1992 to 2022, we utilized the Web of Science Core Collection. Additionally, bibliometric tools such as CiteSpace, VOSviewer, Bibliometrics online analysis platforms (https://bibliometric.com), along with SCImage graphics, were employed to delineate historical features, track the evolution of active topics, and identify emerging trends on the P(VDF-TrFE) field.Results: The annual publication and citation counts for articles on P(VDF-TrFE) have exhibited consistent growth since 1992, with Asia, notably China, contributing the highest number of publications on P(VDF-TrFE) materials. Interestingly, researchers in the United States demonstrated the most robust international collaborations across various countries. Keywords were categorized into nine clusters: 0# vinylidene fluoride, 1# thin-film transient, 2# energy harvesting, 3# dielectric property, 4# thin film, 5# film, 6# mobile modeling, 7# growth, and 8# pyroelectric sensor. The performance of constituent materials in electronic energy-storage applications and current and future research in nanofields, including nanofilms, nanofibers, and nanogenerator, are considered hotspots and developmental trends, respectively. Among the most cited articles, these articles are commonly related to PVDF and P(VDF-TrFE) ferroelectricity.Conclusion: Therefore, we believe that the electromechanical coupling performance of P(VDF-TrFE) and the research in nano fields is research hotspot that will trend into the future.

Utilization of gas engine-driven heat pumps (GEHP) can reduce the heavy loads on the power grid when electric heat pumps operate during the heating season. This study is to examine the performance of GEHP as a water heater with different engine speeds and water flow rates providing space-heating and sanitary hot water. When the engine speed rises from 1400 rpm to 1900 rpm, the temperature rise of water increases by 37% from 25.7 °C to 35.3 °C. Moreover, the system heat capacity rises from 71.8 kW to 97.7 kW with an increase of 36%, while the COP decreases from 3.6 to 3.0. As the inlet water flow rate an increase from 2.5 m3/h to 4.0 m3/h, the temperature rise decreases from 44.3 °C to 24.1 °C, with decreasing heat capacity from 128.8 kW to 112.1 kW. Additionally, the primary energy ratio (PER) initially increases from 1.46 to 1.50 at the engine speed of 1800 rpm, followed by a slight decrease to 1.48 when the engine speed reaches 1900 rpm. With an increasing water flow rate, the PER achieves its highest value of 1.64 at 3 m3/h and its lowest value of 1.49 at 3.5 m3/h.

Abstract Stroke is closely associated with carotid plaques. The assessment of carotid plaque is still the key issue of stroke prevention in clinical practice. This prospective cross‐sectional study included patients with carotid plaque evaluated by ultrasonography (US). The intima‐media thickness (IMT), lumen stenosis severity, thickness, and length of carotid plaque were measured by the routine US, and the amplitudes of subharmonics in the upstream shoulder, top, and downstream shoulder of all plaques and corresponding lumens were observed by Subharmonic Aided Pressure Estimation (SHAPE) US examination from the US contrast agent perflubutane microbubbles (Sonazoid), which analyzed the clinical parameters of patients, the subharmonic amplitude characteristics of all plaques and lumens, and the parameter differences between the ischemic stroke (IS) group and control group. From May 2021 to February 2022, 46 carotid plaques of 23 patients were included. For plaques, the subharmonic amplitude in the plaque (−60.52 ± 4.46) was lower than that in the opposing level lumen (−56.82 ± 5.68 dB), the subharmonic gradient across the plaque cap was negatively correlated with plaque thickness (r = −0.51, p

Key-value stores based on LSM-Tree have been widely used.LSM-Tree gains excellent write performance by collecting updated data in memory and then flushing data into storage in batches.However, in LSMTree-based key-value stores, old data generated by update operations will not be eliminated immediately from the storage system, resulting in a large amount of invalid data accumulated in the entire storage system, which will eventually significantly reduce the read performance of key-value stores.For the above problems, an active compaction method was proposed.By recording the history information of updated key-value pairs, recognizing hot-updated keys, finding SSTables that contain a large amount of invalid data in the storage system, and triggering compaction as soon as possible to clear much more invalid data, the proposed method could reduce write amplification and improve the read performance of LSM-Tree based key-value stores.Experiments showed that this method could reduce the average read latency of LevelDB by 65.2%, 99% read tail latency by 69.4%, and write amplification by 71.4%.

Abstract Background Carotid vulnerable plaque is an important risk factor for stroke occurrence and recurrence. However, the relationship between risk parameters related to carotid vulnerable plaque (plaque size, echogenicity, intraplaque neovascularization, and plaque stiffness) and neurological outcome after ischemic stroke or TIA is unclear. This study investigates the value of multimodal ultrasound-based carotid plaque risk biomarkers to predict poor short-term functional outcome after ischemic stroke or TIA. Methods This study was a single-center, prospective, continuous, cohort study to observe the occurrence of adverse functional outcomes (mRS 2–6/3–6) 90 days after ischemic stroke or TIA in patients, where the exposure factors in this study were carotid plaque ultrasound risk biomarkers and the risk factors were sex, age, disease history, and medication history. Patients with ischemic stroke or TIA (mRS ≤3) whose ipsilateral internal carotid artery stenosis was ≥50% within 30 days were included. All patients underwent multimodal ultrasound at baseline, including conventional ultrasound, superb microvascular imaging (SMI), and shear wave elastography (SWE). Continuous variables were divided into four groups at interquartile spacing for inclusion in univariate and multifactorial analyses. After completion of a baseline ultrasound, all patients were followed up at 90 days after ultrasound, and patient modified neurological function scores (mRSs) were recorded. Multivariate Cox regression and ROC curves were used to assess the risk factors and predictive power for predicting poor neurological function. Results SMI revealed that 20 (30.8%) patients showed extensive neovascularization in the carotid plaque, and 45 (69.2%) patients showed limited neovascularization in the carotid plaque. SWE imaging showed that the mean carotid plaque stiffness was 51.49 ± 18.34 kPa (23.19–111.39 kPa). After a mean follow-up of 90 ± 14 days, a total of 21 (32.3%) patients had a mRS of 2–6, and a total of 10 (15.4%) patients had a mRS of 3–6. Cox regression analysis showed that the level of intraplaque neovascularization and plaque stiffness were independent risk factors for a mRS of 2–6, and the level of intraplaque neovascularization was an independent risk factor for a mRS of 3–6. After correcting for confounders, the HR of intraplaque neovascularization level and plaque stiffness predicting a mRS 2–6 was 3.06 (95% CI 1.05–12.59, P = 0.041) and 0.51 (95% CI 0.31–0.83, P = 0.007), respectively; the HR of intraplaque neovascularization level predicting a mRS 3–6 was 6.11 (95% CI 1.19–31.45, P = 0.031). For ROC curve analysis, the mRSs for intraplaque neovascularization level, plaque stiffness, and combined application to predict 90-day neurological outcome ranged from 2 to 6, with AUCs of 0.73 (95% CI 0.59–0.87), 0.76 (95% CI 0.64–0.89) and 0.85 (95% CI 0.76–0.95), respectively. The mRSs for the intraplaque neovascularization level to predict 90-day neurological outcome ranged from 3 to 6, with AUCs of 0.79 (95% CI 0.63–0.95). Conclusion Intraplaque neovascularization level and plaque stiffness may be associated with an increased risk of poor short-term functional outcome after stroke in patients with recent anterior circulation ischemic stroke due to carotid atherosclerosis. The combined application of multiple parameters has efficacy in predicting poor short-term functional outcome after stroke.

Abstract Background Parkinson’s disease (PD) is a neurodegenerative disease and is clinically characterized by a series of motor symptoms (MS) and nonmotor symptoms (NMS). NMS often appear before MS, while cognitive impairment mostly occurs within a few years after the diagnosis of PD. Therefore, we aimed to predict the risk factors for cognitive impairment (CI) in PD patients based on transcranial sonography, clinical symptoms, and demographic characteristics. Methods Based on the occurrence time of CI, a total of 172 PD patients were divided into non-CI (N-CI, n = 48), CI at the first treatment (F-CI, n = 58), and CI at the last treatment (L-CI, n = 66) groups. Clinical data (including MS and NMS) and ultrasonic data of all patients at the first treatment and the last treatment were collected retrospectively. Independent samples t tests were used to compare continuous data, and chi-square tests were used to compare categorical data. The risk factors for CI and Parkinson’s disease dementia were identified by logistic regression analysis, and an ROC curve was established to explore the diagnostic efficacy. Results 1) The age of onset, first treatment and smoking history of CI patients were significantly different from those of N-CI patients. When age of first treatment ≥61 years was considered the boundary value to diagnose CI, the sensitivity and specificity were 77.40 and 66.70%, respectively. 2) The severity of depression was significantly different between F-CI and N-CI patients at the first treatment, while the cumulative and new or aggravated memory deficit was significantly different between the L-CI and N-CI patients at the last treatment. 3) There was a significant difference in TCS grading between the first and last treatment in L-CI patients. 4) Depression, sexual dysfunction, and olfactory dysfunction in NMS were independent risk factors for CI during the last treatment. 5) The sensitivity and specificity of predicting CI in PD patients were 81.80 and 64.60%, respectively. Conclusions PD patients with CI were older, and most of them had a history of smoking. Furthermore, there was good diagnostic efficiency for predicting CI in PD via TCS combined with clinical characteristics (especially NMS).

Background Hyperparathyroidism (HPT) is classified into primary HPT (PHPT), secondary HPT (SHPT), tertiary HPT (THPT), and pseudohyperparathyroidism. Parathyroid surgery is generally reserved for patients with symptomatic PHPT and asymptomatic patients who meet the surgical guideline criteria. However, the risk of complications and mortality after parathyroid gland surgery increases with increasing patient age.Aim This study aimed to review existing research on laser ablation, radiofrequency ablation, microwave ablation, and high-intensity focused ultrasound in the treatment of HPT and analyze its application prospects.Conclusions Thermal ablation is a good alternative treatment for patients with parathyroid hyperplasia who do not meet the criteria or decline surgery. Being a type of minimally invasive treatment, ultrasound-guided thermal ablation has the advantages of easy operation, rapid recovery, and reusability and is used widely.

Abstract Background The aim of this study is to propose a new TI-RADS and compare it with the American College of Radiology (2017 ACR)-TI-RADS and the 2020 Chinese (2020 C)-TI-RADS. Methods A retrospective analysis of 749 thyroid nodules was performed. Based on the calculated odds ratio of ultrasonic signs between benign and malignant nodules, a new thyroid nodule score and malignancy rate were calculated. A receiver operating characteristic curve was drawn to analyze the new system’s effectiveness in the differential diagnosis of benign and malignant thyroid nodules and was compared with the 2020 C-TI-RADS and 2017 ACR-TI-RADS. Five ultrasound physicians with different qualifications graded another 123 thyroid nodules according to the 2017ACR-TI-RADS, 2020 C-TI-RADS, and the newly proposed TI-RADS. Intergroup and intragroup consistency was evaluated using the Kappa test and intraclass correlation coefficient (ICC) test. Results 1) The new thyroid nodule score was divided into 0, 1, 2, 3, 4, and 5 points, with malignancy rates of 1.52%, 7.69%, 38.24%, 76.00%, 90.75%, and 93.75%, respectively. Using 3 points as the cutoff value to diagnose benign and malignant thyroid nodules, the sensitivity and specificity were 94.03% and 67.39%, respectively, which were higher than those of the 2017 ACR-TI-RADS and 2020 C-TI-RADS. The simplified TI-RADS, namely, sTI-RADS, was established as follows: sTI-RADS 3 (0 points), malignancy rate 90%. 2) Five ultrasound doctors graded thyroid nodules by the 2017 ACR-TI-RADS, 2020C-TI-RADS and sTI-RADS. Intragroup consistency was good among all tests; ICC were 0.86 (0.82–0.90), 0.84 (0.78–0.88), and 0.88 (0.84–0.91), respectively, while only sTI-RADS had good intergroup consistency. Conclusion In summary, we proposed a new TI-RADS, namely, sTI-RADS, which was obtained using a simple assignment method with higher specificity, accuracy, positive predictive value, and Youden index than the 2017 ACR-TI-RADS and 2020 C-TI-RADS.

Regenerative combustion technology has many advantages such as fuel saving, high combustion efficiency and low emission, and it has been widely used for large-scale furnaces. However, when regenerative combustion technology is adopted for small-scale furnaces, many technical problems occur. In this paper, a small-scale regenerative furnace with heat load of 70–80 kW and primary air coefficient of 1.00–1.60 was designed. It was found that the flame shifts from bright pale blue with faint rotating streamlines to yellowish transparent without apparent streamlines and to bright and transparent eventually. When main burners work stably, the temperature inside the furnace raises rapidly at first, and then the temperature increases steadily and fluctuates periodically. The highest temperature in the furnace can reach around 1300 °C. As the reversing time increases, the temperature fluctuation becomes more dramatically and the highest temperature is higher. NOx concentrations at all measurement points are below 50 ppm. Heat transfer efficiencies of each heat retainer show an increasing trend with the rise of the number of reversions. As reversing time increases, the heat transfer efficiency shows a decreasing trend.

With non-volatile memory becoming commercially available, the design and implementation of traditional storage systems need a fundamental change since they can not fully utilize the performance of non-volatile memory.To build a highthroughput, low-latency, large-scale storage system, there is an urgent need for efficient persistent index data structures that adapt to the characteristics of non-volatile memory.In terms of persistent index data structures, the optimizations applied for B+-Tree and Hash Table on non-volatile memory were summarized, and the pros and cons among these schemes were compared.And the future research directions with the challenges and opportunities that need to be resolved were showed.

With the increasingly stringent requirements for nitrogen oxide emissions, fully premixed water-cooled burners have been gradually discussed and studied due to their low cost and obvious effect on NOx reduction. However, their application in civil gas appliances is relatively rare, and there are few systematic studies combining experiments and simulations. In this paper, the experimental research and numerical simulation of the water-cooled burner are firstly carried out, and the accuracy of the numerical model is verified by the measured results. Then, the location and influencing factors of NOx generation are analyzed, and the direct factors affecting NOx generation in the water-cooled combustion technology are determined. The results show that the primary air coefficient is the main factor affecting the formation of NOx, the secondary air has little effect on the formation of NOx, and the premixed air temperature has little effect on it. The results have certain guiding significance for the design of water-cooled burners.

The application of gas engine driven heat pump (GHP) system can improve the peak valley difference of power and gas system and promote the low-carbon utilization of energy system. The energy consumption of GHP system in different types of buildings and especially the coefficient of performance (COP) under partial load rate needs more analysis. In this paper, according to the local meteorological parameters in Shanghai, the COP operation curve of GHP and electric driven heat pump (EHP) units under partial load rate was analyzed. Combined with the load calculation, the annual energy consumption of GHP and EHP units in different types of buildings, and the influence of energy price on economy of GHP system were analyzed. For office buildings and catering buildings, the energy consumption and operating costs of GHP system were slightly lower than those of EHP system, while for hotel buildings, the annual operating costs of GHP were lower than those of EHP only when the winter gas price was 2.39 yuan/m3 and the summer gas price was 2.19 yuan/m3. Therefore, in order to promote the market competitiveness of gas air conditioning, it is necessary to further refine the gas price or charge standard.

To study the effect of hydrogen-blended natural gas on the combustion stability and emission of domestic gas water heater, a test system is built in this paper, taking a unit of the partial premixed burner commonly used in water heaters as the object. Under the heat load of 0.7–2.3 kW, the changes of flame shape, burner temperature and pollutant emission of natural gas with hydrogen volume ratio of 0–40% are studied with independent control of primary air supply and mixing. The results show that: with the increase of hydrogen blending ratio, the inner flame height increases firstly and then reduces, while the change of burner temperature is opposite. The maximum inner flame height and the minimum temperature of the burner both appear at the hydrogen blending ratio of 10–20%. It can be seen that the limit of hydrogen blending ratio which can maintain the burner operate safely and stably under rated heat load is 40% through the maximum temperature distribution on the burner surface. The CO emission in the flue gas gradually decreases with the increase of hydrogen blending ratio, while the NOx emission fluctuates slightly when the hydrogen blending ratio is less than 20%, but then decreases gradually.

De-carbonization actions, represented by the electrification of end-use energy sources, have been strongly promoted, while space heating in residential buildings is an important aspect. In this paper, Jinan and Qingdao in northern China are selected to explore the challenges that electrification of heating will bring. The electricity demand for heating of different types of buildings is simulated, with the assumption that all heating loads are provided by electric heat pumps. Then the comparison of heating electricity demand with current electricity consumption in various social sectors has been analyzed to investigate the impact of the newly added electrical load on the power grid. The annual dynamic power supply under the currently installed wind turbines and photovoltaic modules is calculated to explore the interrelationship between the power supply potential of the available renewable energy and the heating electricity demand. The results show that the implementation of heating electrification will bring a strong impact on the existing grid, with photovoltaic generation almost negligible during the heating period and wind generation severely affected by intermittency. In the future, the deployment of installed renewable energy needs to continue to be promoted, while the layout of energy storage facilities needs to be strengthened.

ObjectiveTo evaluate the efficacy and safety of thermal ablation, including radiofrequency ablation (RFA), microwave ablation (MVA), and laser ablation (LA), for treating lymph node metastasis (LNM) from papillary thyroid carcinoma (PTC).Design and MethodsPubMed and EMBASE were searched for studies reporting the efficacy and safety of thermal ablation for treating LNM in PTC. After selecting the relevant literature (including 11 papers, 208 patients, 412 lymph nodes), the QUADAS-2 tool was used to evaluate its quality. Then, both the fixed-effects and random-effects models combined with subgroup analysis were used to calculate data on volume changes in metastatic lymph nodes and changes in serum thyroglobulin (Tg) levels. We pooled the proportion of major and overall complication rates and complete disappearance rates and used subgroup forest plots and funnel plots for visual representation. Because of publication bias, we also performed a trim-and-filled model for correction. The rate of recurrence and distant metastasis with ablated details were pooled.ResultsIn the 11 articles (208 patients and 412 diseased lymph nodes), all thermal ablation methods showed effectiveness in reducing lymph node volume (P = 0.02) and serum Tg levels (P < 0.01) which showed no between-group difference. The pooled proportion of major complications was 0%(95% CI: -0.14; 0.15, P = 1) and the overall complication rate was 5% (95% CI: -0.09; 0.20, P = 1), which revealed no significant difference among modalities. The pooled proportion of the complete disappearance rate was 82% (95% CI: 0.43; 0.96, P < 0.01) and the data with statistical significance which contains RFA and LA showed complete disappearance rate was 59% and 81% respectively.ConclusionAll thermal ablation methods, including RFA, MWA, and LA, were effective and safe for treating LNM in PTC and were especially suitable for nonsurgical patients. Besides, subgroup analysis showed no significant difference, except for LA is better than RFA in complete disappearance rate.

Abstract Background Centromere protein F (CENPF) is a key component of the kinetochore complex involved in mitosis, cell differentiation and cellular response to stresses. However, the alteration of CENPF in response to endoplasmic reticulum (ER) stress has not been well described. In the present study, we investigate CENPF regulation in response to ER stress. Methods Quantitative real-time polymerase chain reaction and western blotting were used to determine CENPF expression under ER stress. Luciferase activity analysis was performed to investigate the promoter regions contributing to CENPF transcription in response to TG. Chromatin immunoprecipitation (ChIP) and ChIP Re-IP assays were used to determine if X-box binding protein 1 (XBP1) and/or activating transcription factor 6α (ATF6α) bind in the CENPF promoter region. Cell apoptosis and proliferation were analyzed using TUNEL, cell growth and clonogenic assays. Results CENPF expression is dramatically reduced under ER stress induced by thapsigargin (TG), brefeldin A (BFA), or tunicamycin (TM) and this downregulation of CENPF expression was dependent on XBP1 and ATF6α. Luciferase activity analysis of the truncated CENPF promoter indicates that regions from bases − 679 to − 488 and from − 241 to − 78 in the CENPF promoter were sensitive to TG treatment. Additionally, ChIP and ChIP Re-IP assays reveal that XBP1 and ATF6α were assembled on the same regions of CENPF promoter. Notably, we identify two XBP1 binding sequences at positions − 567 and − 192, to which XBP1 binding was enhanced by TG. Finally, CENPF overexpression inhibits cell apoptosis and promotes cell proliferation in response to ER stress. Conclusion In summary, these results demonstrate that ER stress plays a crucial role in CENPF expression, and XBP1 may up-regulate DNA-binding affinities after TG treatment to the promoter of CENPF. These findings may contribute to the understanding of the molecular mechanism of CENPF regulation.

Abstract Objective To establish Greater Omentum Imaging-Reporting and Data System (GOI-RADS) to evaluate the possibility of omental diseases being malignant. Method A retrospective analysis was made of 883 patients who had undergone biopsy of the greater omentum in our center from October 2009 to October 2019. Twelve parameters of ultrasonographic images were evaluated, and the odds ratio of each group calculated. We assigned scores for the direct signs (omental echo, omental structure, and omental nodules) and indirect signs (separation of ascites, echo of ascites, mesenteric lymph nodes, and thickening of parietal peritoneum) of omental lesions. We created an omental score (OS) for each patient and receiver operating characteristic (ROC) curve to analyze its effectiveness in the differential diagnosis of benign and malignant omental diseases. Results The OS was divided into ≤5, 6, 7, 8, 9, 10, 11, 12, 13, and ≥ 14 points, and the malignant rate was 0, 1.85, 5.56, 30.36, 37.25, 87.72, 96.72, 98.28, 99.08, and 100%, respectively. The area under the ROC curve (AUC) was 0.976. When taking 10 points as the cutoff value to diagnose benign and malignant omental diseases, the sensitivity and specificity was 93.85 and 98.21%, respectively. A grading system was established: grade 1: omental score ≤ 5, malignant rate 0%; grade 2: omental score 6–7, malignant rate ≤ 5.56%; grade 3: omental score 8-–9, malignant rate ≤ 37.25%; grade 4: omental score ≥ 10, malignant rate ≥ 87.72. Conclusion GOI-RADS had high sensitivity and specificity in the differential diagnosis of benign and malignant omental lesions. We believe that GOI-RADS will aid the diagnosis of omental diseases based on objective and accurate interpretation of ultrasound features, and also to promote the ultrasonography of omental diseases in clinical application.

Person Re-Identification (ReID) is an important yet challenging task in computer vision. Background clutter is one of the greatest challenges to overcome. In this paper, we propose a Mask-pooling model with local-level triplet loss (MPM-LTL) to tackle this problem and improve person ReID performance. Specifically, we present a novel pooling method, called mask pooling (MP), to gradually remove background features in feature maps through deep convolutional network. With mask pooling, the network can learn the most crucial person features. Moreover, we raise a novel local-level triplet loss for discriminative feature training. Furthermore, we propose a new hard triplets selection algorithm named Mask-guided TriHard. The method is based on human outline information, which is, to our best knowledge, employed for the first time for hard triplets selection. We achieve the state-of-the-art results on three benchmark person datasets Market-1501 [1], CUHK03 [2] and DukeMTMC-reID [3], [4].

Study Region: Three-River Source Region, Qinghai-Tibetan Plateau, China. Study Focus: Evapotranspiration (ET) is often the largest loss of water from grassland ecosystems and consists of two constituents: evaporation (E) and transpiration (T), but it is very difficult to separate E and T. In this study, we used an energy balance model (Shuttleworth-Wallace) and a water balance model (SOILWAT2) to estimate the water budget variables over a 10-year period (2007–2016) in a degraded alpine meadow in the Three-River Source Region on the Qinghai-Tibetan Plateau. New Hydrological Insights for the Region: The models produced contrasting patterns of precipitation and ET partitioning at the study site. Precipitation partitioning by SW2 resulted in substantial fluxes of both ET and deep drainage, while ET estimated by SW consumed almost all precipitation. ET was partitioned by the models into different annual E and T fluxes as well as different monthly and annual T/ET. Our study site located in an important water source region suggests that its water balance would contribute to drainage which aligns better with SW2 results. The surprising discrepancies between the models in the partitioning of precipitation into T, E, and deep drainage, however, is limiting our understanding and management of the degraded site and will require future work to reconcile.

Cholesterol granuloma (CG) is a histological lesion caused by an inflammatory reaction of the cholesterol crystal rather than an independent disease. We report the case of an 87-year-old woman who came to our hospital for slight abdominal pain lasting a week and who had a history of a pelvic mass found forty years ago. Ultrasound examination revealed abnormal omentum, which was suspected to be a source of metastasis from the pelvic mass. However, ultrasound-guided biopsy confirmed the abnormal omentum was CG. By describing this case, we aim to share the value of ultrasound-guided omentum biopsy in clinical diagnosis and treatment.

The general volume of data has exploded to unimaginable levels in the past decade. Therefore, the big data analytics has become an area of focus. Many frameworks have been developed for data analytics, such as Hadoop, Spark, etc. Most of the frameworks are built on multi-core or many-core memory systems, requiring developers and users to have an in-depth understanding of the architectures to take full advantage of the hardware. In this paper, we present a comprehensive study of both multi-core and many-core memory systems and discuss the different characteristics, including core, cache, memory, and the on-chip network. Furthermore, we propose a simple but effective mechanism for cache false-sharing overhead that can reduce a large number of LLC-load/store instructions and LLC cache-misses. In addition, we conduct detailed experiments with Ligra, a graph analytics framework, on four different-sized datasets. The results show that it can achieve up to a 2.5× and 9.5× speed-up for multi-core and many-core memory systems, respectively. We finally share our key findings and discuss the platform development on multi-core and many-core memory systems.

The exhaust gas temperature of SOFC is as high as 600–1000 °C and contains combustible components that can be reused. In this paper, an experimental system was set up to study the combustion characteristics of SOFC simulated exhaust gas in a porous medium burner, the combustion of SOFC exhaust gas under different equivalence ratio, the effects of hydrogen concentration and water vapor fraction in the anode exhaust gas and the stable combustion limits of the burners had been analyzed. Results showed that: equivalence ratio and adiabatic flame temperature had a significant effect on the combustion, when the adiabatic flame temperature of mixed gas below 440 °C, or the water vapor content in the anode gas was greater than 85%, the flame couldn’t be stably burned; On the condition of the fuel utilization rate of 60% and the equivalence ratio of 0.40, the burner could burn stably with the inlet airflow velocity from 0.16 to 0.24m/s; The combustion stability limit of the exhaust gas burner varied with the utilization ratio of the stack, with increasing of fuel utilization ratio, the equivalence ratio of lifting and flashback limit was changing, and the adiabatic flame temperature of stable combustion limit had been studied.

This paper presents dynamic learning from adaptive neural control with prescribed tracking error performance for flexible joint robot (FJR) included unknown dynamics. Firstly, a system transformation method is introduced to convert the original FJR system into a normal system. As a result, only one neural network (NN) approximator is used to identify the uncertain system nonlinear dynamics and the verification on the convergence of neural weights is simplified extremely. To further solve the predefined performance issue, a performance function is introduced to describe a tracking error constraint and a error transformation technique is used to convert the constrained tracking control problem into the unconstrained stabilization of error system. By combining a high-gain observer and the backsteppig method, the adaptive neural controller is presented to stabilize the unconstrained error system. Under the satisfaction of the partial persistent excitation condition, the adaptive neural controller is shown to be capable of achieving unknown dynamics acquisition, expression and storage. Furthermore, a neural learning control with using the stored NN weights is proposed for the same or similar control task so that a time-consuming NN online adjustment process can be avoided and a better control performance can be obtained. Simulation results demonstrate the effectiveness of the proposed control method.

The relationship between lifted flames and burner head temperature of partially premixed gas burners supplied by various natural gas sources was investigated, and the application of AGA(American Gas Association) lifting limit for Chinese domestic gas burners was studied. Results showed that lifted flames became more seriously with the burner head temperature decreasing, also with the increase of lift height of flames, it would lead to reduce the burner head temperature, eventually the burner head would reach the thermal equilibrium state which maintained stable flames and temperature. The lifting limit curve of partially premixed gas burners was only one under the same gas source, and it only depended on the burner structures and gas source characteristics, but nothing to do with the burner head temperature. The gas source with lower Wobbe index and calorific value made the burner appearing lifted flame more easily. Comparing with the experiment results and AGA lifting index prediction, it suggested that the limits of AGA lifting index IL≤ 1.10 should be change into IL≤ 1.05 using in China. Keywords: Partially premixed gas burners, Lifted flames, Natural gas, AGA lifting index

Graphs are ubiquitous, and graph analytics has been widely adopted in many big data applications such as social computation and natural language processing, as well as web-search and recommendation systems. Prior research focuses on processing large-scale graphs on distributed environments or a single multi-core machine with several terabytes of RAM. Increasing complex memory systems and on-chip interconnects are developed to mitigate the data movement bottlenecks in manycore processors such as Xeon Phi KNL CPU with heterogeneous memory, with up to 72 dual-core tiles. This paper presents a detailed study on the characteristics of manycore memory systems and their impact on the efficiency of graph analytics. Based on this paper, we introduce Ants, the first graph analytics platform on manycore memory systems. First, Ants differentially allocates graph data according to their access patterns and the behavior of heterogeneous memory. Second, to reduce excessive memory access and ease congestion on interconnects and memory controllers, Ants develops a fine-grained and effective task partitioning strategy for many cores. A detailed experiment on a 64 dual-core tile machine shows that Ants outperforms the state-of-the-art graph analytics platform-Ligra by up to 8.97X for real-world graphs.

Recent advances in non-volatile memory (NVM) technology offer more capacity, scalability, and durability than regular volatile memory. However, adopting emerging memory introduces new challenges such as endurance issue and performance degradation. This paper proposes a software wear leveling technique that is designed specifically for a scenario, where the NVM is managed by generational garbage collectors that divide heap into separate young and old space. Prior work found that the majority of write traffic occurs to young generation heap, thus proposed a hybrid generational heap, where the NVM is utilized as old space and DRAM works as young space. We further investigate the access pattern in NVM-contained old generation. This paper first highlights a common observation across various workloads that the write distribution of old space is highly unbalanced. Specifically, among all writes to the NVM, 56%-96% occurs to 2% memory pages, and in worst cases, 83%-96% traffic occurs to only 0.5% pages. This leveling can be achieved by only swapping a very small fraction of NVM pages during the garbage collection cycle, which makes a low performance overhead runtime approach possible. We maintain a write intensity counter for each thread and insert a new garbage collection phase, where a few hottest pages are selected and remapped. Results show our approach significantly mitigates the skewness indicated by Gini coefficient dropping from 0.95 to 0.60, leading to extending lifetime 41 times on average. Meanwhile, it incurs a performance cost of 7.2% longer mutation time measured on emulated memory without performance penalty, and 3.31 % extra stop time for garbage collection cycles.

Deep learning (DL) is currently the most promising approach in complicated applications such as computer vision and natural language processing. It thrives with large neural networks and large datasets. However, larger models and larger datasets result in longer training times that impede research and development progress. The modern high-performance and data-parallel nature of hardware equipped with high computing power, such as GPUs, has triggered the widespread adoption of such hardware in DL frameworks, such as Caffe, Torch, and TensorFlow. However, most DL frameworks cannot make full use of this high-performance hardware, and computational efficiency is low. In this paper, we present SingleCaffe1, a DL framework that can make full use of such hardware and improve the computational efficiency of the training process. SingleCaffe opens up multiple threads to speed up the training process within a single node and adopts data parallelism on multiple threads. During the training process, SingleCaffe selects a thread as a parameter server thread and the other threads as worker threads. Both data and workloads are distributed across worker threads, while the server thread maintains the globally shared parameters. The framework also manages memory allocation carefully to reduce the memory overhead. The experimental results show that SingleCaffe can improve training efficiency well, and the performance on a single node can even achieve the distributed training of a dozen nodes.

The porous media combustion technology is an effective solution to stable combustion and clean utilization of low heating value gas. For observing the combustion characteristics of porous media burners under various back pressures, investigating flame stability and figuring out the distribution laws of combustion gas flow and resistance loss, so as to achieve an optimized design and efficient operation of the devices, a bench of foamed ceramics porous media combustion devices was thus set up to test the cold-state resistance and hot-state combustion characteristic of burners in working conditions without back pressures and with two different back pressures. The following results are achieved from this experimental study. (1) The strong thermal reflux of porous media can preheat the premixed air effectively, so the flame can be kept stable easily, the combustion equivalent ratio of porous media burners is lower than that of traditional burners, and its pollutant content of flue gas is much lower than the national standard value. (2) The friction coefficient of foamed ceramics decreases with the increase of air flow rate, and its decreasing rate slows down gradually. (3) When the flow rate of air is low, viscosity is the dominant flow resistance, and the friction coefficient is in an inverse relation with the flow rate. (4) As the flow rate of air increases, inertia is the dominant flow resistance, and the friction coefficient is mainly influenced by the roughness and cracks of foamed ceramics. (5) After the introduction of secondary air, the minimum equivalent ratio of porous media burners gets much lower and its range of equivalent ratio is much larger than that of traditional burners.

This document aims to assess the different performance of swirling strip-port and normal round-port domestic gas cookers with gas property fluctuation and propose suitable structure design parameter for both port types. Comparing with normal round-port gas cookers, swirling strip-port samples are not advantage on aspects of thermal efficiency and CO emission, but in term of NOx emission it performs very well which can effectively control NOx emission in a suitable range and improve gas cooker′s adaptive capacity, when natural gas is interchanged. It is easier to qualify CO emission with low NOx emission for swirling strip-port gas cookers, though it will sacrifice a part of thermal efficiency, while normal round-port gas cookers are easier to qualify CO emission with high thermal efficiency. The burner head design structure parameters of normal round-port gas cookers which can well adapt natural gas interchange are port thermal intensity in 7.2–8.4 W/mm2 and structure factor ε in 30–40, as well as swirling strip-port gas cookers are port thermal intensity in 8.0–11.5 W/mm2 with structure factor ε in 35–45. Keywords: Domestic gas cooker, Swirling strip-port, Normal round-port, Thermal efficiency, Emission, Natural gas interchange

High-performance computing (HPC) environment is the core information infrastructure supporting national scientific and technological innovation, economic development and national defense construction.High-performance computing powers around the world have been building wide-area HPC environments based on multi-supercomputing center resources.However, in the high-performance computing environment, there are many kinds of resources and wide geographical distribution, which cannot effectively exert the aggregation effect of resources, and it is difficult to meet the requirements of large-scale applications for unified management and efficient access to wide-area distributed data.To this end, a complete set of technologies were proposed, which could be used to build wide-area global virtual data space, including virtual data space model, cross-domain virtual data space constructing, efficiently migrating data in a wide-area environment, co-scheduling of storage resources and computing job and cross-domain high concurrency data aggregation processing, etc.Based on the above, a virtual data space system has been developed for the national high-performance computing environment (NHPCE), which can effectively support the unified and efficient access to the wide area distributed heterogeneous storage resources, and the distributed data in the wide-area environment can be shared and cooperative processed in a cross-domain manner.At present, the system was experimental deployed in NHPCE and three typical large-scale applications, such as molecular docking, genome-wide association study and weather forecasting model, have been verified.The verification results show that the developed technology and software system can effectively aggregate the wide area distributed storage resources and meet the data space requirements of large-scale applications.

In an HPC system where multiple computation nodes of an MPI application simultaneously access files in underlying storage systems, the I/O overhead is affected by the access mode and the properties of external storage devices.Based on the patterns of MPI applications to access files, an optimization for MPI-IO interface for persistent memories was introduced on high-bandwidth, low-latency, byte-addressable, data-persistent memories.By constructing distributed data cache, maintaining persistent metadata and leveraging optimizations on data movements among processes, applications were enabled to efficiently manage and utilize persistent memories with data consistency guaranteed, resulting in tens of times improvement on read/write bandwidth.Further optimizations on parallelism were set for future work.

This paper focuses on neural learning from adaptive neural control (ANC) for a class of flexible joint manipulator under the output tracking constraint. To facilitate the design, a new transformed function is introduced to convert the constrained tracking error into unconstrained error variable. Then, a novel adaptive neural dynamic surface control scheme is proposed by combining the neural universal approximation. The proposed control scheme not only decreases the dimension of neural inputs but also reduces the number of neural approximators. Moreover, it can be verified that all the closed-loop signals are uniformly ultimately bounded and the constrained tracking error converges to a small neighborhood around zero in a finite time. Particularly, the reduction of the number of neural input variables simplifies the verification of persistent excitation (PE) condition for neural networks (NNs). Subsequently, the proposed ANC scheme is verified recursively to be capable of acquiring and storing knowledge of unknown system dynamics in constant neural weights. By reusing the stored knowledge, a neural learning controller is developed for better control performance. Simulation results on a single-link flexible joint manipulator and experiment results on Baxter robot are given to illustrate the effectiveness of the proposed scheme.

In China, it has become a more common practice to introduce natural gases from different sources into the same distribution system to improve supply security and reliability. Variable gas constituents may cause a negative impact on the performance of domestic gas appliances. This paper aims to study the CO emission of a Chinese gas cooker under different constituents of natural gas. A typical Chinese gas cooker with two burners, each of which has a nominal heat input of 3.8 kW, was selected. One of the burners was modified to a forced-mixed mode to replace primary air injection. Within operational ranges corresponding to the permissible Wobbe index—namely, primary air coefficients and heat inputs—the equivalence between original gas and the CH4/C3H8/N2 three-component mixture in terms of CO emission was experimentally validated. Then, different three-component mixtures were input into the other unmodified burner, which operates under injected primary air, to investigate how the CO emission changed with different gas constituents. It was found that the CO emission of a natural gas and a CH4/C3H8/N2 three-component mixture, in terms of CO emission, were equivalent. The combination of the two indexes, W and PN, can describe the CO emission from a gas cooker accurately. By means of a three-component mixture, the empirical formula, which can correlate CO and the gas property parameters, was proposed. A set of equal-CO lines was revealed for a given initial primary air adjustment. Finally, a feasible approach to manage gas quality management in China was put forward, and the conclusion can help control the CO emission of gas cookers and improve indoor air quality.

BACKGROUND: Acupuncture in humans can produce clinical effects via the central nervous system. However, the neural substrates of acupuncture's effects remain largely unknown. RESULTS: We utilized functional MRI to investigate the topological efficiency of brain functional networks in eighteen healthy young adults who were scanned before and after acupuncture at the ST36 acupoints (ACUP) and its sham point (SHAM). Whole-brain functional networks were constructed by thresholding temporal correlations matrices of ninety brain regions, followed by a graph theory-based analysis. We showed that brain functional networks exhibited small-world attributes (high local and global efficiency) regardless of the order of acupuncture and stimulus points, a finding compatible with previous studies of brain functional networks. Furthermore, the brain networks had increased local efficiency after ACUP stimulation but there were no significant differences after SHAM, indicating a specificity of acupuncture point in coordinating local information flow over the whole brain. Moreover, significant (P