A Joint Extraction System Based on Conditional Layer Normalization for Health Monitoring.

Natural language processing (NLP) technology has played a pivotal role in health monitoring as an important artificial intelligence method. As a key technology in NLP, relation triplet extraction is closely related to the performance of health monitoring. In this paper, a novel model is proposed for joint extraction of entities and relations, combining conditional layer normalization with the talking-head attention mechanism to strengthen the interaction between entity recognition and relation extraction. In addition, the proposed model utilizes position information to enhance the extraction accuracy of overlapping triplets. Experiments on the Baidu2019 and CHIP2020 datasets demonstrate that the proposed model can effectively extract overlapping triplets, which leads to significant performance improvements compared with baselines.

Characterization of key aroma compounds in aged Qingxiangxing baijiu by comparative aroma extract dilution analysis, quantitative measurements, aroma recombination, and omission studies.

Aging aroma is an intriguing but an understudied phenomenon in baijiu. The aromatic characteristics of Qingxiangxing (QXX) baijiu stored for 45 years (aged) were investigated using the sensomics approach and were compared with those of young baijiu (0 year-old). Aroma extract dilution analysis revealed 59 odorants, with many long-retained components exhibiting greater flavor dilution values in the aged than the young sample. The analysis of variance of the quantitative data showed significant differences between the young and aged baijiu for 26 compounds. Based on the variations in the content of these compounds, QXX baijiu aged for 0, 5, 15, 20, and 45 years was analyzed and twelve compounds were significantly correlated with aging duration. Finally, eight positively correlated compounds were omitted from the recombinant model, and sotolon, methional, vanillin, dimethyl trisulfide, benzaldehyde, and 3-hydroxy-2-butanone were confirmed to primarily contribute toward the aging aroma of QXX baijiu.

Ultrasound-induced destruction of heparin-loaded microbubbles attenuates L-arginine-induced acute pancreatitis.

PURPOSE: Acute pancreatitis (AP) involves sudden inflammation caused by abnormal activation of pancreatic enzymes. The mechanisms underlying AP include oxidative stress, high levels of inflammatory mediators and inflammatory cell infiltration. Heparin, a key therapeutic drug, exerts anti-inflammatory, antioxidative, and anticoagulative effects. However, safe and effective drug delivery remains an obstacle. This study is the first to investigate the therapeutic effects of heparin-loaded microbubbles (HPMB) combined with ultrasound (UHPMB) and the role of heparin in acoustic cavitation. METHODS: The characteristics of the microbubbles, including particle size, concentration, release, stability, and development, were studied. Heparin concentration in the HPMB was measured, and heparin-induced anticoagulation was evaluated. Drug safety was explored using hemolysis and cell viability assessments. The ability of HPMB to alleviate oxidative stress and inflammation were investigated in vitro. L-arginine induces AP in vivo. UHPMB was used for AP treatment. Serum amylase levels were measured and pancreatic architecture and pathological features were evaluated to determine AP severity. In vivo efficacy was evaluated, and the underlying mechanism of heparin action during acoustic cavitation was explored. RESULTS: HPMB was spherical and presented as an emulsion-like solution without aggregation. HPMB was visible and stable and effectively released the drug under ultrasound (US). HPMB and UHPMB led to lower AP severity than in the untreated group. US-targeted microbubble destruction (UTMD) enhanced the therapeutic effect by decreasing oxidative stress and inflammation in AP models without injuring vital organs. UHPMB regulated VEGF/Flt-1 and SOD-1 expression. HPMB can also mitigate oxidative stress and inflammation in H2O2-pretreated cells. CONCLUSION: UHPMB exhibits a strong ability not only to selectively target pancreatic lesions and release heparin but also to provide efficient protection by inhibiting oxidative stress and inflammation.

Grading of clear cell renal cell carcinoma using diffusion MRI with a fractional order calculus model.

BACKGROUND: The fractional order calculus (FROC) model has been developed to describe restrained motion of water molecules as well as microstructural heterogeneity, providing a novel tool for non-invasive tumor grading. PURPOSE: To evaluate the role of the FROC model in characterizing clear cell renal cell carcinoma (ccRCC) grades. MATERIAL AND METHODS: A total of 59 patients diagnosed with ccRCC were included in this prospective study. The diffusion metrics derived from the mono-exponential model (apparent diffusion coefficient [ADC]), intra-voxel incoherent motion [IVIM] model [D, D*, f], and FROC model [Dfroc, ß, µ]) were calculated and compared between low- and high-grade ccRCCs. Binary logistic regression analysis was performed to establish the diagnostic models. Receiver operating characteristic (ROC) analysis and DeLong test were performed to evaluate and compare the diagnostic performance of metrics in grading ccRCC. RESULTS: All the metrics except D* and f exhibited statistical differences between low- and high-grade ccRCCs. ROC analysis showed individual FROC parameters, µ, Dfroc, and ß, outperformed ADC and IVIM parameters in grading ccRCC. For single parameter, µ demonstrated the highest AUC value, sensitivity, and diagnostic accuracy in discriminating the two ccRCC groups while ß exhibited the optimal specificity. Importantly, the combination of Dfroc, µ, and ß could further improve the diagnostic performance. CONCLUSION: The FROC parameters were superior to ADC and IVIM parameters in grading ccRCC, indicating the great potential of the FROC model in distinguishing low- and high-grade ccRCCs.

A Novel and Effective Model to Predict Skip Metastasis in Papillary Thyroid Carcinoma Based on a Support Vector Machine.

Introduction: Skip metastasis, referred to as lymph node metastases to the lateral neck compartment without involvement of the central compartment, is generally unpredictable in papillary thyroid carcinoma (PTC). This study aims to establish an effective predictive model for skip metastasis in PTC. Meterials and Methods: Retrospective analysis was performed of clinical samples from 18192 patients diagnosed with thyroid cancer between 2016 to 2020. The First Affiliated Hospital of Wenzhou Medical University. The lateral lymph node metastasis was occureed in the training set (630 PTC patients) and validation set (189 PTC patients). The univariate and multivariate analyses were performed to detect the predictors of skip metastasis and the support vector machine (SVM) was used to establish a model to predict skip metastasis. Results: The rate of skip metastasis was 13.3% (84/631). Tumor size (≤10 mm), upper location, Hashimoto's thyroiditis, extrathyroidal extension, absence of BRAFV600E mutation, and less number of central lymph node dissection were considered as independent predictors of skip metastasis in PTC. For the training set, these predictors performed with 91.7% accuracy, 86.4% sensitivity, 92.2% specificity, 45.2% positive predictive value (PPV), and 98.9% negative predictive value (NPV) in the model. Meanwhile, these predictors showed 91.5% accuracy,71.4% sensitivity, 93.1% specificity, 45.5% PPV, and 97.6% NPV in validation set. Conclusion: This study screened the predictors of the skip lateral lymph node metastasis and to establish an effective and economic predictive model for skip metastasis in PTC. The model can accurately distinguish the skip metastasis in PTC using a simple and affordable method, which may have potential for daily clinical application in the future.

Extracorporeal Shock Wave Combined with Teriparatide-Loaded Hydrogel Injection Promotes Segmental Bone Defects Healing in Osteoporosis.

BACKGROUND: Osteoporosis is a systemic bone disease characterized by decreased bone density and deterioration of bone microstructure, leading to an increased probability of fragility fractures. Once segmental bone defect occurs, it is easy to cause delayed union and nonunion. METHODS: The aim of this study is to investigate the efficacy of extracorporeal shock wave (ESW) and teriparatide-loaded hydrogel (T-Gel) combined strategy on the cell activity and differentiation of osteoporosis derived bone marrow mesenchymal stem cells (OP-BMSCs) in vitro and bone regeneration in osteoporotic segmental bone defects in vivo. RESULTS: In vitro, the strategy of combining ESW and T-Gel significantly enhanced OP-BMSCs proliferation, survival, migration, and osteogenic differentiation by up-regulating the alkaline phosphatase activity, mineralization, and expression of runt-related transcription factor-2, type I collagen, osteocalcin, and osteopontin. In the segmental bone defect models of osteoporotic rabbits, Micro-CT evaluation and histological observation demonstrated this ESW-combined with T-Gel injection significantly induced bone healing by enhancing the osteogenic activity of the local microenvironment in osteoporotic defects. CONCLUSION: In conclusion, ESW-combined with T-Gel injection could regulate the poor osteogenic microenvironment in osteoporotic defects and show potential for enhancing fragility fractures healing.

Construction of Enhanced Photostability Anthraquinone-Type Nanovesicles Based on a Novel Two-Step Supramolecular Assembly Strategy and Their Application on Multiband Laser-Responsive Composites.

The photostability and dispersity under aggregation states always become an obstacle for the development of small-molecular organic dye (SMOD) composites. Herein, a novel supramolecular assembly strategy with a two-step assembly method is implemented to encapsulate SMODs for improving their photostability and acquiring uniformly dispersed nanoaggregates in aqueous solution. By the novel assembly strategy, photodegradation rates of the anthraquinone-type dyes can decrease significantly, and the stability of dispersed nanoassembly bodies can be improved in solution. Based on the two-step supramolecular assembly strategy, a new kind of aqueous processing composite system can be developed for preparing multiband laser-responsive devices and in situ healing of optical composite films. This two-step supramolecular assembly strategy can provide a new template and reference for improving the defects of SMODs and fabricating high-performance optical devices.

Clinical Research and Technique Note of TLIF by Wiltse Approach for the Treatment of Degenerative Lumbar.

OBJECTIVE: To assess the clinical efficacy and share the technique notes of Wiltse Approach TLIF for the treating single segment degenerative lumbar spinal disease. METHOD: In this retrospective controlled study, 780 patients with single segment degenerative lumbar disease who were operated in our hospital from January 2016 to December 2020 were analyzed retrospectively. The patients were randomly assigned to Wiltse approach group (group A, 410 cases) and conventional open approach group (group B, 370 cases). Patient's assessment of pain and disability were evaluated by the visual analogue scale (VAS) and the Oswestry disability index (ODI) before and after surgery. The incision length, operative time, exposure time, intraoperative blood loss, hidden blood loss, time to ambulation, total length of hospitalization, serum creatine kinase, X-rays, CT and MRI were also evaluated. RESULTS: There were no differences in sex, age, pre-operative ODI score, VAS score between the two groups (P > 0.05). The Wiltse approach group had a shorter incision length with 7.69 ± 0.44 cm compared to the conventional group with 11.13 ± 0.36 cm (P < 0.01). The average operative time was 119.20 ± 14.64 min with exposure time of 16.20 ± 3.42 min in the Wiltse approach group and 145.65 ± 16.98 min with 29.20 ± 3.42 min in the conventional group (P < 0.05, P < 0.01). Comparing the intraoperative blood loss, hidden blood loss, serum creatine kinase, time to ambulation, total length of hospitalization, the Wiltse approach group was less than the conventional open approach group (P < 0.05). The VAS score of the two groups decreased significantly with time, and the VAS score of the Wiltse group was significantly lower than that of the conventional open approach group (P < 0.05). At last investigation after operation, ODI scores of the two groups were significantly decreased compared with that before operation. Wiltse approach group was significantly lower than that of the conventional open approach group (P < 0.05). The multifidus of the two groups of patients had a certain degree of atrophy. But the Wiltse approach group multifidus muscle atrophy rate is significantly lower than the conventional open approach group. CONCLUSION: The Wiltse approach TLIF significantly reduces the damage to the paravertebral muscles and the postoperative incidence of chronic low back pain.

Application of deep learning in the detection of breast lesions with four different breast densities.

OBJECTIVE: This retrospective study evaluated the model from populations with different breast densities and showed the model's performance on malignancy prediction. METHODS: A total of 608 mammograms were collected from Northern Jiangsu People's Hospital in Yangzhou City. The data from this province have not been used in the training or evaluation data set. The model consists of three submodules, lesion detection (Mask-rcnn), lesion registration between craniocaudal view and mediolateral oblique view, malignancy prediction network (ResNet). The data set used to train the model was obtained from nine institutions across six cities. For normal cases, there were no annotations. Here, we adopted the free-response receiver operating characteristic (FROC) curve as the indicator to evaluate the detection performance of all cancers and triple-negative breast cancer (TNBC). The FROC curves are also shown for mass/distortion/asymmetry and typical benign calcification in two kinds of populations with four types of breast density. RESULTS: The sensitivity to mass/distortion/asymmetry for the four types of breast (A, B, C, D) are 0.94, 0.92, 0.89, and 0.72, respectively, when false positive per image is 0.25, while these values are 1.00, 0.95, 0.92, and 0.90, respectively, for the amorphous calcification lesions. The sensitivity for the cancer is 0.85 at the same false-positive rate. The TNBC accounts for about 10%-20% of all breast cancers and is more aggressive with poor prognosis than other breast cancers. Herein, we also evaluated performance on the TNBC cases. Our results show that Yizhun AI could detect 75% TNBC lesions at the same false-positive level mentioned above. CONCLUSION: The Yizhun AI model used in our work has good diagnostic efficiency for different types of breast, even for the extremely dense breast. It has a guiding role in the clinical diagnosis of breast cancer. The performance of Yizhun AI on mass/distortion/asymmetry is affected by breast density significantly compared to that on amorphous calcification.

A comparison between deep learning convolutional neural networks and radiologists in the differentiation of benign and malignant thyroid nodules on CT images.

INTRODUCTION: We designed 5 convolutional neural network (CNN) models and ensemble models to differentiate malignant and benign thyroid nodules on CT, and compared the diagnostic performance of CNN models with that of radiologists. MATERIAL AND METHODS: We retrospectively included CT images of 880 patients with 986 thyroid nodules confirmed by surgical pathology between July 2017 and December 2019. Two radiologists retrospectively diagnosed benign and malignant thyroid nodules on CT images in a test set. Five CNNs (ResNet50, DenseNet121, DenseNet169, SE-ResNeXt50, and Xception) were trained-validated and tested using 788 and 198 thyroid nodule CT images, respectively. Then, we selected the 3 models with the best diagnostic performance on the test set for the model ensemble. We then compared the diagnostic performance of 2 radiologists with 5 CNN models and the integrated model. RESULTS: Of the 986 thyroid nodules, 541 were malignant, and 445 were benign. The area under the curves (AUCs) for diagnosing thyroid malignancy was 0.587-0.754 for 2 radiologists. The AUCs for diagnosing thyroid malignancy for the 5 CNN models and ensemble model was 0.901-0.947. There were significant differences in AUC between the radiologists' models and the CNN models (p < 0.05). The ensemble model had the highest AUC value. CONCLUSIONS: Five CNN models and an ensemble model performed better than radiologists in distinguishing malignant thyroid nodules from benign nodules on CT. The diagnostic performance of the ensemble model improved and showed good potential.

Ultrasound Shear Wave Elastography for Evaluation of Diaphragm Stiffness in Patients with Stable COPD: A Pilot Trial.

OBJECTIVES: Skeletal muscle dysfunction is one of the most common comorbidities in chronic obstructive pulmonary disease (COPD). The occurrence of respiratory failure in COPD is common and leads to the patient's death. The diaphragm is the most important muscle in the respiratory system and plays a key role in the onset of respiratory failure. This study explores the feasibility of ultrasound shear wave elastography (SWE) to measure diaphragmatic stiffness and evaluates its changes in COPD patients. METHODS: In total, 77 participants (43 patients with stable COPD and 34 healthy controls) were enrolled. All subjects underwent complete diaphragmatic ultrasound SWE measurements and pulmonary function tests. The diaphragmatic stiffness was indicated via diaphragmatic shear wave velocity (SWV) at functional residual capacity (FRC). A trained operator performed the ultrasound SWE examinations of the first 15 healthy controls thrice to assess the reliability of diaphragmatic SWE. RESULTS: A good to excellent reliability was found in diaphragmatic SWV at FRC (ICC = 0.93, 95%CI 0.82-0.98). As compared to the control group, the diaphragmatic SWV at FRC was considerably high in the COPD group (median 2.5 m/s versus 2.1 m/s, P = .008). Diaphragmatic SWV at FRC was linked to forced expiratory volume in one second (r = -0.30, P = .009), forced vital capacity (r = -0.33, P = .003), modified Medical Research Council score (r = 0.30, P = .001), and COPD assessment test score (r = 0.48, P < .001). CONCLUSIONS: Ultrasound SWE may be employed as an effective tool for quantitative evaluation of diaphragm stiffness and can help in personalized management of COPD, such as treatment guidance and follow-up monitoring.

Ultrasound-Induced Destruction of Nitric Oxide-Loaded Microbubbles in the Treatment of Thrombus and Ischemia-Reperfusion Injury.

Objectives: Early recanalization of large vessels in thromboembolism, such as myocardial infarction and ischemic stroke, is associated with improved clinical outcomes. Nitric oxide (NO), a biological gas signaling molecule, has been proven to protect against ischemia-reperfusion injury (IRI). However, the underlying mechanisms remain to be explored. This study investigated whether NO could mitigate IRI and the role of NO during acoustic cavitation. Methods: In vivo, thrombi in the iliac artery of rats were induced by 5% FeCl3. NO-loaded microbubbles (NO-MBs) and ultrasound (US) were used to treat thrombi. B-mode and Doppler US and histological analyses were utilized to evaluate the thrombolysis effect in rats with thrombi. Immunohistochemistry, immunofluorescence, and western blotting were conducted to investigate the underlying mechanisms of NO during acoustic cavitation. In vitro, hypoxia was used to stimulate cells, and NO-MBs were employed to alleviate oxidative stress and apoptosis. Results: We developed NO-MBs that significantly improve the circulation time of NO in vivo, are visible, and effectively release therapeutic gas under US. US-targeted microbubble destruction (UTMD) and NO-loaded UTMD (NO + UTMD) caused a significant decrease in the thrombus area and an increase in the recanalization rates and blood flow velocities compared to the control and US groups. We discovered that UTMD induced NO generation through activation of endothelial NO synthase (eNOS) in vivo. More importantly, we also observed significantly increased NO content and eNOS expression in the NO + UTMD group compared to the UTMD group. NO + UTMD can mitigate oxidative stress and apoptosis in the hind limb muscle without influencing blood pressure or liver and kidney functions. In vitro, NO-MBs alleviated oxidative stress and apoptosis in cells pretreated with hypoxia. Conclusion: Based on these data, UTMD affects the vascular endothelium by activating eNOS, and NO exerts a protective effect against IRI.

Utility of Point-of-Care Lung Ultrasound for Clinical Classification of COVID-19.

In this study, the utility of point-of-care lung ultrasound for clinical classification of coronavirus disease (COVID-19) was prospectively assessed. Twenty-seven adult patients with COVID-19 underwent bedside lung ultrasonography (LUS) examinations three times each within the first 2 wk of admission to the isolation ward. We divided the 81 exams into three groups (moderate, severe and critically ill). Lung scores were calculated as the sum of points. A rank sum test and bivariate correlation analysis were carried out to determine the correlation between LUS on admission and clinical classification of COVID-19. There were dramatic differences in LUS (p < 0.001) among the three groups, and LUS scores (r = 0.754) correlated positively with clinical severity (p < 0.01). In addition, moderate, severe and critically ill patients were more likely to have low (≤9), medium (9-15) and high scores (≥15), respectively. This study provides stratification criteria of LUS scores to assist in quantitatively evaluating COVID-19 patients.

A Theoretical Study on an Elastic Polymer Thin Film-Based Capacitive Wind-Pressure Sensor.

This study is devoted to the design of an elastic polymer thin film-based capacitive wind-pressure sensor to meet the anticipated use for real-time monitoring of structural wind pressure in civil engineering. This sensor is composed of four basic units: lateral elastic deflection unit of a wind-driven circular polymer thin film, parallel plate capacitor with a movable circular electrode plate, spring-driven return unit of the movable electrode plate, and dielectric materials between electrode plates. The capacitance of the capacitor varies with the parallel move of the movable electrode plate which is first driven by the lateral elastic deflection of the wind-driven film and then is, after the wind pressure is reduced or eliminated, returned quickly by the drive springs. The closed-form solution for the contact problem between the wind-driven thin film and the spring-driven movable electrode plate is presented, and its reliability is proved by the experiment conducted. The numerical examples conducted show that it is workable that by using the numerical calibration based on the presented closed-form solution the proposed sensor is designed into a nonlinear sensor with larger pressure-monitoring range and faster response speed than the linear sensor usually based on experimental calibration.

POSTAR2: deciphering the post-transcriptional regulatory logics.

Post-transcriptional regulation of RNAs is critical to the diverse range of cellular processes. The volume of functional genomic data focusing on post-transcriptional regulation logics continues to grow in recent years. In the current database version, POSTAR2 (http://lulab.life.tsinghua.edu.cn/postar), we included the following new features and data: updated ∼500 CLIP-seq datasets (∼1200 CLIP-seq datasets in total) from six species, including human, mouse, fly, worm, Arabidopsis and yeast; added a new module 'Translatome', which is derived from Ribo-seq datasets and contains ∼36 million open reading frames (ORFs) in the genomes from the six species; updated and unified post-transcriptional regulation and variation data. Finally, we improved web interfaces for searching and visualizing protein-RNA interactions with multi-layer information. Meanwhile, we also merged our CLIPdb database into POSTAR2. POSTAR2 will help researchers investigate the post-transcriptional regulatory logics coordinated by RNA-binding proteins and translational landscape of cellular RNAs.

Ribosome elongating footprints denoised by wavelet transform comprehensively characterize dynamic cellular translation events.

Translation is dynamically regulated during cell development and stress response. In order to detect actively translated open reading frames (ORFs) and dynamic cellular translation events, we have developed a computational method, RiboWave, to process ribosome profiling data. RiboWave utilizes wavelet transform to denoise the original signal by extracting 3-nt periodicity of ribosomes and precisely locate their footprint denoted as Periodic Footprint P-site (PF P-site). Such high-resolution footprint is found to capture the full track of actively elongating ribosomes, from which translational landscape can be explicitly characterized. We compare RiboWave with several published methods, like RiboTaper, ORFscore and RibORF, and found that RiboWave outperforms them in both accuracy and usage when defining actively translated ORFs. Moreover, we show that PF P-site derived by RiboWave shows superior performance in characterizing the dynamics and complexity of cellular translatome by accurately estimating the abundance of protein levels, assessing differential translation and identifying dynamic translation frameshift.

Identification of high-confidence RNA regulatory elements by combinatorial classification of RNA-protein binding sites.

Crosslinking immunoprecipitation sequencing (CLIP-seq) technologies have enabled researchers to characterize transcriptome-wide binding sites of RNA-binding protein (RBP) with high resolution. We apply a soft-clustering method, RBPgroup, to various CLIP-seq datasets to group together RBPs that specifically bind the same RNA sites. Such combinatorial clustering of RBPs helps interpret CLIP-seq data and suggests functional RNA regulatory elements. Furthermore, we validate two RBP-RBP interactions in cell lines. Our approach links proteins and RNA motifs known to possess similar biochemical and cellular properties and can, when used in conjunction with additional experimental data, identify high-confidence RBP groups and their associated RNA regulatory elements.

Effect of storage temperature and time on the nutritional quality of walnut male inflorescences.

The objective of this study was to investigate the effect of storage temperature and time on nutrients, bioactive compounds, and antioxidant activities of walnut male inflorescences. The results showed that the moisture, saccharides, fat, protein, amino acids, ascorbic acid, phenolic and flavonoid compound contents, and antioxidant activities of walnut male inflorescences were markedly influenced by storage temperature, and different degrees of decrease in these parameters were observed during the entire storage period. Moreover, higher storage temperature had a more significant effect on the nutrients, bioactive compounds, and antioxidant activities of walnut male flowers, and the loss rate of these components at 25°C was higher than that determined at 4°C. However, the results also presented that the ash and mineral contents did not appear to be influenced significantly by the storage temperature, and slightly significant changes were observed in crude fiber throughout storage, which indicated that the influence of storage on the individual mineral and crude fiber content was minimal. Based on the findings in this study, in order to maximize nutrients concentration, walnut male inflorescences should be kept at 4°C for <6 days and be consumed as fresh as possible.

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks.

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.