BACKGROUND Chronic sinusitis is a kind of chronic suppurative inflammation of the sinus mucosa.Nasal endoscopy is a good method to treat nasal polyps.However postoperative rehabilitation and care should not be neglect...BACKGROUND Chronic sinusitis is a kind of chronic suppurative inflammation of the sinus mucosa.Nasal endoscopy is a good method to treat nasal polyps.However postoperative rehabilitation and care should not be neglected.AIM To investigate the Effect of nursing intervention on the rehabilitation of patients with chronic sinusitis and nasal polyps(CSNPS)after nasal endoscopy.METHODS A total of 129 patients with CSNPS hospitalized from February 2017 to February 2019 were studied.Using the digital parity method,we investigated nursing cooperation strategies for endoscopic surgery.The comparison group(64 cases):Surgical nursing was carried out with traditional nursing measures;experimental group(65 cases):Surgical nursing was carried out by traditional nursing countermeasures+comprehensive nursing measures.We compared postoperative recovery rates,nursing satisfaction rates,and nasal cavity ratings between the two groups.RESULTS Experimental group patients with CSNPS had a significantly higher recovery rate(98.46%)compared to the control group(79.69%).This difference was statistically significant(χ2=11.748,P<0.05).Additionally,the satisfaction rate with treatment was also significantly higher in the experimental group(98.46%)compared to the control group(79.69%),with a statistically significant difference(χ2=11.748,P<0.05).Before nursing,there was no significant difference in sinus nasal cavity scores between the experimental group(20.29±7.25 points)and the control group(20.30±7.27 points)(t=0.008,P>0.05).However,after nursing,the sinus nasal cavity score in the experimental group(8.85±3.22 points)was significantly lower than that in the control group(14.99±5.02 points)(t=8.282,P<0.05).CONCLUSION Comprehensive nursing intervention in patients with CSNPS can significantly improve the total recovery rate after endoscopic surgery.展开更多
β-Sitosterol-D-glucoside(β-SDG)is a phytosterol compound whose antitumor activity has been confirmed by previous studies.However,its suppression on breast cancer remains unclear.To that purpose,we isolatedβ-SDG fro...β-Sitosterol-D-glucoside(β-SDG)is a phytosterol compound whose antitumor activity has been confirmed by previous studies.However,its suppression on breast cancer remains unclear.To that purpose,we isolatedβ-SDG from sweet potato and investigated the breast-cancer-inhibiting mechanism using proteomic analysis.The sweet potato species S6 with highβ-SDG content were chosen form 36 species andβ-SDG was isolated by HPLC.Afterwards,an in situ animal model of breast cancer was established,andβ-SDG significantly reduced the tumor volume of MCF-7 xenograft mice.Proteomic analysis of tumor tissues revealed that 127 of these proteins were upregulated and 80 were downregulated.Gene ontology and network analysis showed that regulatory proteins were mainly associated with epithelial-mesenchymal transition(EMT),myogenesis,cholesterol homeostasis,oxidative phosphorylation and reactive oxygen pathways,while Vimentin,NDUF,VDAC1,PPP2CA and SNx9 were the most significant 5 node degree genes.Meanwhile,in vitro and in vivo results showed that the protein expression of PPP2CA and Vimentin,which are markers of EMT,were involved in breast cancer cell metastasis and could be reversed byβ-SDG.This work highlightsβ-SDG as a bioactive compound in sweet potato and the potential therapeutic effect ofβ-SDG for the treatment of breast cancer by inhibiting metastasis.展开更多
Digital twin is an essential enabling technology for 6G connected vehicles.Through highfidelity mobility simulation,digital twin is expected to make accurate prediction about the vehicle trajectory,and then support in...Digital twin is an essential enabling technology for 6G connected vehicles.Through highfidelity mobility simulation,digital twin is expected to make accurate prediction about the vehicle trajectory,and then support intelligent applications such as safety monitoring and self-driving for connected vehicles.However,it is observed that even if a digital twin model is perfectly derived,it might still fail to predict the trajectory due to tiny measurement noise or delay in the initial vehicle locations.This paper aims at investigating the sources of unpredictability of digital twin.Take the car-following behaviors in connected vehicles for case study.The theoretical analysis and experimental results indicate that the predictability of digital twin naturally depends on its system complexity.Once a system enters a complex pattern,its longterm states are unpredictable.Furthermore,our study discloses that the complexity is determined,on the one hand,by the intrinsic factors of the target physical system such as the driver’s response sensitivity and delay,and on the other hand,by the crucial parameters of the digital twin system such as the sampling interval and twining latency.展开更多
Traditional vibrating screen usually adopts the linear centralized excitation mode,which causes the difficulty in particles loosening and low screening efficiency.The variable elliptical vibrating screen(VEVS)trajecto...Traditional vibrating screen usually adopts the linear centralized excitation mode,which causes the difficulty in particles loosening and low screening efficiency.The variable elliptical vibrating screen(VEVS)trajectory is regulated to adapt the material mass along the direction of the screen length,improving the particles distribution as well as the screening efficiency.In this work,a theoretical model was developed for analyzing the screen surface motion law during VEVS-based screening process.An equation was obtained to show the relationship between the horizontal amplitude and the vertical amplitude.The materials kinetic characteristics were studied by using high-speed camera during screening process.Compared with equal-amplitude screen(EAS),the material moving velocity was increased by 13.03%on the first half but decreased by 3.52% on the second half,and the total screening time was reduced by 9.42% by using VEVS.In addition,-6 mm screening test was carried out.At the length of VEVS equaled to 1.2 m,the screening efficiency and the total misplaced material content were 92.50% and 2.90%,respectively.However,the screening efficiency was 89.91% and the total misplaced material content was 3.76% during EAS-based screening process.Furthermore,when external moisture is 5.96%,the screening efficiency of VEVS could reach 86.95%.The 2 TKB50113 type VEVS with double-layered screen surface used in Huoshizui Coal Mine was 5.0 m in width and 11.3 m in length.The areas of single layer and double layer were 56.5 and 113 m~2,respectively.In industrial production,the processing capacity was 2500-3000 t/h and the screening efficiency was larger than 90%.展开更多
As Information,Communications,and Data Technology(ICDT)are deeply integrated,the research of 6G gradually rises.Meanwhile,federated learning(FL)as a distributed artificial intelligence(AI)framework is generally believ...As Information,Communications,and Data Technology(ICDT)are deeply integrated,the research of 6G gradually rises.Meanwhile,federated learning(FL)as a distributed artificial intelligence(AI)framework is generally believed to be the most promising solution to achieve“Native AI”in 6G.While the adoption of energy as a metric in AI and wireless networks is emerging,most studies still focused on obtaining high levels of accuracy,with little consideration on new features of future networks and their possible impact on energy consumption.To address this issue,this article focuses on green concerns in FL over 6G.We first analyze and summarize major energy consumption challenges caused by technical characteristics of FL and the dynamical heterogeneity of 6G networks,and model the energy consumption in FL over 6G from aspects of computation and communication.We classify and summarize the basic ways to reduce energy,and present several feasible green designs for FL-based 6G network architecture from three perspectives.According to the simulation results,we provide a useful guideline to researchers that different schemes should be used to achieve the minimum energy consumption at a reasonable cost of learning accuracy for different network scenarios and service requirements in FL-based 6G network.展开更多
Device-free gesture recognition is an emerging wireless sensing technique which could recognize gestures by analyzing its influence on surrounding wireless signals,it may empower wireless networks with the augmented s...Device-free gesture recognition is an emerging wireless sensing technique which could recognize gestures by analyzing its influence on surrounding wireless signals,it may empower wireless networks with the augmented sensing ability.Researchers have made great achievements for singleperson device-free gesture recognition.However,when multiple persons conduct gestures simultaneously,the received signals will be mixed together,and thus traditional methods would not work well anymore.Moreover,the anonymity of persons and the change in the surrounding environment would cause feature shift and mismatch,and thus the recognition accuracy would degrade remarkably.To address these problems,we explore and exploit the diversity of spatial information and propose a multidimensional analysis method to separate the gesture feature of each person using a focusing sensing strategy.Meanwhile,we also present a deep-learning based robust device free gesture recognition framework,which leverages an adversarial approach to extract robust gesture feature that is insensitive to the change of persons and environment.Furthermore,we also develop a 77GHz mmWave prototype system and evaluate the proposed methods extensively.Experimental results reveal that the proposed system can achieve average accuracies of 93%and 84%when 10 gestures are conducted in Received:Jun.18,2020 Revised:Aug.06,2020 Editor:Ning Ge different environments by two and four persons simultaneously,respectively.展开更多
Poly(α-L-lysine)(PLL)is a class of water-soluble,cationic biopolymer composed ofα-L-lysine structural units.The previous decade witnessed tremendous progress in the synthesis and biomedical applications of PLL and i...Poly(α-L-lysine)(PLL)is a class of water-soluble,cationic biopolymer composed ofα-L-lysine structural units.The previous decade witnessed tremendous progress in the synthesis and biomedical applications of PLL and its composites.PLL-based polymers and copolymers,till date,have been extensively explored in the contexts such as antibacterial agents,gene/drug/protein delivery systems,bio-sensing,bio-imaging,and tissue engineering.This review aims to summarize the recent advances in PLL-based nanomaterials in these biomedical fields over the last decade.The review first describes the synthesis of PLL and its derivatives,followed by the main text of their recent biomedical applications and translational studies.Finally,the challenges and perspectives of PLL-based nanomaterials in biomedical fields are addressed.展开更多
文摘BACKGROUND Chronic sinusitis is a kind of chronic suppurative inflammation of the sinus mucosa.Nasal endoscopy is a good method to treat nasal polyps.However postoperative rehabilitation and care should not be neglected.AIM To investigate the Effect of nursing intervention on the rehabilitation of patients with chronic sinusitis and nasal polyps(CSNPS)after nasal endoscopy.METHODS A total of 129 patients with CSNPS hospitalized from February 2017 to February 2019 were studied.Using the digital parity method,we investigated nursing cooperation strategies for endoscopic surgery.The comparison group(64 cases):Surgical nursing was carried out with traditional nursing measures;experimental group(65 cases):Surgical nursing was carried out by traditional nursing countermeasures+comprehensive nursing measures.We compared postoperative recovery rates,nursing satisfaction rates,and nasal cavity ratings between the two groups.RESULTS Experimental group patients with CSNPS had a significantly higher recovery rate(98.46%)compared to the control group(79.69%).This difference was statistically significant(χ2=11.748,P<0.05).Additionally,the satisfaction rate with treatment was also significantly higher in the experimental group(98.46%)compared to the control group(79.69%),with a statistically significant difference(χ2=11.748,P<0.05).Before nursing,there was no significant difference in sinus nasal cavity scores between the experimental group(20.29±7.25 points)and the control group(20.30±7.27 points)(t=0.008,P>0.05).However,after nursing,the sinus nasal cavity score in the experimental group(8.85±3.22 points)was significantly lower than that in the control group(14.99±5.02 points)(t=8.282,P<0.05).CONCLUSION Comprehensive nursing intervention in patients with CSNPS can significantly improve the total recovery rate after endoscopic surgery.
基金supported by Special Key project of Technology Innovation and Application Development in Chongqing(CSTC2021jscx-gksb-N0033,CSTB2021TIAD-KPX0085)Science Foundation of School of Life Sciences SWU(20212005425201)County-University Cooperation Innovation Funds of Southwest University(SZ202102).
文摘β-Sitosterol-D-glucoside(β-SDG)is a phytosterol compound whose antitumor activity has been confirmed by previous studies.However,its suppression on breast cancer remains unclear.To that purpose,we isolatedβ-SDG from sweet potato and investigated the breast-cancer-inhibiting mechanism using proteomic analysis.The sweet potato species S6 with highβ-SDG content were chosen form 36 species andβ-SDG was isolated by HPLC.Afterwards,an in situ animal model of breast cancer was established,andβ-SDG significantly reduced the tumor volume of MCF-7 xenograft mice.Proteomic analysis of tumor tissues revealed that 127 of these proteins were upregulated and 80 were downregulated.Gene ontology and network analysis showed that regulatory proteins were mainly associated with epithelial-mesenchymal transition(EMT),myogenesis,cholesterol homeostasis,oxidative phosphorylation and reactive oxygen pathways,while Vimentin,NDUF,VDAC1,PPP2CA and SNx9 were the most significant 5 node degree genes.Meanwhile,in vitro and in vivo results showed that the protein expression of PPP2CA and Vimentin,which are markers of EMT,were involved in breast cancer cell metastasis and could be reversed byβ-SDG.This work highlightsβ-SDG as a bioactive compound in sweet potato and the potential therapeutic effect ofβ-SDG for the treatment of breast cancer by inhibiting metastasis.
基金supported in part by National Key R&D Program of China (No.2020YFB1807802)National Natural Science Foundation of China (Nos.61971148,U22A2054)。
文摘Digital twin is an essential enabling technology for 6G connected vehicles.Through highfidelity mobility simulation,digital twin is expected to make accurate prediction about the vehicle trajectory,and then support intelligent applications such as safety monitoring and self-driving for connected vehicles.However,it is observed that even if a digital twin model is perfectly derived,it might still fail to predict the trajectory due to tiny measurement noise or delay in the initial vehicle locations.This paper aims at investigating the sources of unpredictability of digital twin.Take the car-following behaviors in connected vehicles for case study.The theoretical analysis and experimental results indicate that the predictability of digital twin naturally depends on its system complexity.Once a system enters a complex pattern,its longterm states are unpredictable.Furthermore,our study discloses that the complexity is determined,on the one hand,by the intrinsic factors of the target physical system such as the driver’s response sensitivity and delay,and on the other hand,by the crucial parameters of the digital twin system such as the sampling interval and twining latency.
基金financially supported by the National Natural Science Foundation of China (Nos. U1903132 and 51904301)the Natural Science Foundation of Jiangsu Province (No. BK20180650)。
文摘Traditional vibrating screen usually adopts the linear centralized excitation mode,which causes the difficulty in particles loosening and low screening efficiency.The variable elliptical vibrating screen(VEVS)trajectory is regulated to adapt the material mass along the direction of the screen length,improving the particles distribution as well as the screening efficiency.In this work,a theoretical model was developed for analyzing the screen surface motion law during VEVS-based screening process.An equation was obtained to show the relationship between the horizontal amplitude and the vertical amplitude.The materials kinetic characteristics were studied by using high-speed camera during screening process.Compared with equal-amplitude screen(EAS),the material moving velocity was increased by 13.03%on the first half but decreased by 3.52% on the second half,and the total screening time was reduced by 9.42% by using VEVS.In addition,-6 mm screening test was carried out.At the length of VEVS equaled to 1.2 m,the screening efficiency and the total misplaced material content were 92.50% and 2.90%,respectively.However,the screening efficiency was 89.91% and the total misplaced material content was 3.76% during EAS-based screening process.Furthermore,when external moisture is 5.96%,the screening efficiency of VEVS could reach 86.95%.The 2 TKB50113 type VEVS with double-layered screen surface used in Huoshizui Coal Mine was 5.0 m in width and 11.3 m in length.The areas of single layer and double layer were 56.5 and 113 m~2,respectively.In industrial production,the processing capacity was 2500-3000 t/h and the screening efficiency was larger than 90%.
基金supported by the National Key Research and Development Program of China(Grant No.2020YFB1806804)the U.S.National Science Foundation(Grant US CNS-1801925,CNS-2029569,and CNS-2107057)。
文摘As Information,Communications,and Data Technology(ICDT)are deeply integrated,the research of 6G gradually rises.Meanwhile,federated learning(FL)as a distributed artificial intelligence(AI)framework is generally believed to be the most promising solution to achieve“Native AI”in 6G.While the adoption of energy as a metric in AI and wireless networks is emerging,most studies still focused on obtaining high levels of accuracy,with little consideration on new features of future networks and their possible impact on energy consumption.To address this issue,this article focuses on green concerns in FL over 6G.We first analyze and summarize major energy consumption challenges caused by technical characteristics of FL and the dynamical heterogeneity of 6G networks,and model the energy consumption in FL over 6G from aspects of computation and communication.We classify and summarize the basic ways to reduce energy,and present several feasible green designs for FL-based 6G network architecture from three perspectives.According to the simulation results,we provide a useful guideline to researchers that different schemes should be used to achieve the minimum energy consumption at a reasonable cost of learning accuracy for different network scenarios and service requirements in FL-based 6G network.
基金This work was supported by National Natural Science Foundation of China under grants U1933104 and 62071081LiaoNing Revitalization Talents Program under grant XLYC1807019,Liaoning Province Natural Science Foundation under grants 2019-MS-058+1 种基金Dalian Science and Technology Innovation Foundation under grant 2018J12GX044Fundamental Research Funds for the Central Universities under grants DUT20LAB113 and DUT20JC07,and Cooperative Scientific Research Project of Chunhui Plan of Ministry of Education.
文摘Device-free gesture recognition is an emerging wireless sensing technique which could recognize gestures by analyzing its influence on surrounding wireless signals,it may empower wireless networks with the augmented sensing ability.Researchers have made great achievements for singleperson device-free gesture recognition.However,when multiple persons conduct gestures simultaneously,the received signals will be mixed together,and thus traditional methods would not work well anymore.Moreover,the anonymity of persons and the change in the surrounding environment would cause feature shift and mismatch,and thus the recognition accuracy would degrade remarkably.To address these problems,we explore and exploit the diversity of spatial information and propose a multidimensional analysis method to separate the gesture feature of each person using a focusing sensing strategy.Meanwhile,we also present a deep-learning based robust device free gesture recognition framework,which leverages an adversarial approach to extract robust gesture feature that is insensitive to the change of persons and environment.Furthermore,we also develop a 77GHz mmWave prototype system and evaluate the proposed methods extensively.Experimental results reveal that the proposed system can achieve average accuracies of 93%and 84%when 10 gestures are conducted in Received:Jun.18,2020 Revised:Aug.06,2020 Editor:Ning Ge different environments by two and four persons simultaneously,respectively.
基金This work was financially supported by the National Natural Science Foundation of China,China(No.81803467)2020 Li Ka Shing Foundation Cross-Disciplinary Research Grant,Hong Kong(2020LKSFG18B,2020LKSFG02E)the grant for Key Disciplinary Project of Clinical Medicine under the Guangdong High-Level University Development Program,Guangdong,China(002-18120314,002-18120311).
文摘Poly(α-L-lysine)(PLL)is a class of water-soluble,cationic biopolymer composed ofα-L-lysine structural units.The previous decade witnessed tremendous progress in the synthesis and biomedical applications of PLL and its composites.PLL-based polymers and copolymers,till date,have been extensively explored in the contexts such as antibacterial agents,gene/drug/protein delivery systems,bio-sensing,bio-imaging,and tissue engineering.This review aims to summarize the recent advances in PLL-based nanomaterials in these biomedical fields over the last decade.The review first describes the synthesis of PLL and its derivatives,followed by the main text of their recent biomedical applications and translational studies.Finally,the challenges and perspectives of PLL-based nanomaterials in biomedical fields are addressed.