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Differences in insomnia-related self-reported outcomes among elderly hospitalized patients

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World Journal of Psychiatry 2024年第5期14卷 686-694页

作者： xia Ding Ling-xia Qi Dong-yun sun Department of Gangzha General Medical Center The Affiliated Hospital of Nantong UniversityNantong 226000Jiangsu ProvinceChina Department of Anesthesiology and Surgery The Affiliated Hospital of Nantong UniversityNantong 226000Jiangsu ProvinceChina Department of Ophthalmic Surgery Room The Affiliated Hospital of Nantong UniversityNantong 226000Jiangsu ProvinceChina

Insomnia is among the most common sleep disorders *** in older adults is a social and public health *** affects the physical and mental health of elderly hospitalized patients and can aggravate or induce physical *** subjective feelings and providing reasonable and standardized care for elderly hospitalized patients with insomnia are urgent *** To explore the differences in self-reported outcomes associated with insomnia among elderly hospitalized *** One hundred patients admitted to the geriatric unit of our hospital between June 2021 and December 2021 were included in this ***-reported symptoms were assessed using the Athens Insomnia Scale(AIS),Generalized Anxiety Disorder Scale-7(GAD-7),Geriatric Depression Scale-15(GDS-15),Memorial University of Newfoundland Scale of Happiness(MUNSH),Barthel Index Evaluation(BI),Morse Fall Scale(MFS),Mini-Mental State Examination,and the Short Form 36 Health Survey Questionnaire(SF-36).Correlation coefficients were used to analyze the correlation between sleep quality and self-reported *** of insomnia was analyzed using Logistic regression *** Nineteen patients with AIS≥6 were included in the insomnia group,and the incidence of insomnia was 19%(19/100).The remaining 81 patients were assigned to the non-insomnia *** were significant differences between the two groups in the GDA-7,GDS-15,MUNSH,BI,MFS,and SF-36 items(P<0.05).Patients in the insomnia group were more likely to experience anxiety,depression,and other mental illnesses,as well as difficulties with everyday tasks and a greater risk of falling(P<0.05).Subjective well-being and quality of life were poorer in the insomnia group than in the control *** AIS scores positively correlated with the GAD-7,GDS-15,and MFS scores in elderly hospitalized patients with insomnia(P<0.05).Logistic regression analysis showed that GDS-15≥5 was an independent risk factor for ins

关键词： Elderly hospitalized patients Insomnia Self-reported outcomes Symptoms Subjective feelings Correlation

X-ray-activated Bi^(3+)/Pr^(3+)co-doped LiYGeO_4 phosphor with UV and NIR dual-emissive persistent luminescence

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Journal of Rare Earths 2024年第5期42卷 955-961,I0005页

作者： xianggui Yin Hongyun Zhong Lin Liu Junpeng Shi xia sun yun Zhang State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of MatterChinese Academy of SciencesFuzhou350002China xiamen Key Laboratory of Rare Earth Photoelectric Functional Materials Xiamen Institute of Rare Earth MaterialsHaixi InstituteChinese Academy of SciencesXiamen361021China Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou350108China

X-ray-activated luminescence materials have broad application prospects in photodynamic therapy of deep *** them,X-ray-activated persistent luminescence materials(PLMs)exhibiting multiple emission peaks have drawn extensive attention for the ir capacity to achieve a combination of bioimaging and therapeutic ***,we developed a novel PLM,LiYGeO_4:Bi^(3+),Pr^(3+),that simultaneously exhibits UV and NIR dual persistent luminescence(PersL)emissions after irradiation by *** material can be re peatedly excited by X-ray and emits similar lumine scence intensity every time,which shows good PersL *** addition,LiYGeO_4:Bi^(3+),Pr^(3+)exhibits photostimulated PersL properties by stimulation with a red light-emitting diode(LED)or NIR laser after long-term *** work provides a new choice of X-ray-excited PLMs with UV and NIR dual emission and the novel phosphor shows promise as a potential candidate for the integration of treatment and diagnosis of deep tumors.

关键词： Co-doping X-ray-activated Dual emissions Persistent luminescence Rare earths

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Pretreating and normalizing metabolomics data for statistical analysis

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Genes & Diseases 2024年第3期11卷 188-205页

作者： Jun sun Yinglin xia Division of Gastroenterology and Hepatology Department of MedicineDepartment of Microbiology/ImmunologyUIC Cancer CenterUniversity of Illinois ChicagoJesse Brown VA Medical Center Chicago(537)ChicagoIL 60612USA Division of Gastroenterology and Hepatology Department of MedicineUniversity of Illinois ChicagoChicagoIL 60612USA

Metabolomics as a research field and a set of techniques is to study the entire small molecules in biological *** is emerging as a powerful tool generally for pre-cision ***,integration of microbiome and metabolome has revealed the mechanism and functionality of microbiome in human health and ***,metabo-lomics data are very ***/pretreating and normalizing procedures on metabolomics data are usually required before statistical *** this review article,we comprehensively review various methods that are used to preprocess and pretreat metabolo-mics data,including MS-based data and NMR-based data preprocessing,dealing with zero and/or missing values and detecting outliers,data normalization,data centering and scaling,data *** discuss the advantages and limitations of each *** choice for a suitable preprocessing method is determined by the biological hypothesis,the characteristics of the data set,and the selected statistical data analysis *** then provide the perspective of their applications in the microbiome and metabolome research.

关键词： Data centering and scaling Data normalization Data transformation Missing values MS-Baseddata preprocessing NMRData preprocessing Outliers Preprocessing/pretreatment

X-ray excited Mn^(2+)-doped persistent luminescence materials with biological window emission for in vivo bioimaging

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Journal of Rare Earths 2024年第1期42卷 28-35,I0001页

作者： Hanrun Zheng Lin Liu Yi’ang Li Rui Rong Liang Song Junpeng Shi Jing Teng xia sun yun Zhang State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of MatterChinese Academy of SciencesFuzhou350002China University of the Chinese Academy of Sciences Beijing100049China xiamen Hospital of Traditional Chinese Medicine Xiamen361015China Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou350108China

In recent years,persistent luminescence materials(PLMs)excited by X-rays and emitting in biological windows have received extensive attention in the field of high-sensitivity *** metal Mn^(2+)is an ideal emission center,but few studies focus on Mn^(2+)-doped PLMs with X-ray excitation and biological window ***,we report a Mn^(2+)-doped PLM,LiYGeO_(4):Mn^(2+)(LYGM),with excellent biological window persistent luminescence *** excitation by UV,LYGM produces a durable biological window of persistent luminescence emission at 660 nm for up to 20 *** *** can be repeatedly excited by X-rays,resulting in long-term biological window persistent luminescence *** addition,we obtain LYGM around 200 nm in diameter by ball milling and centrifugation and improve its biocompatibility by surface modification to apply it to in vivo imaging in *** LYGM are injected into mice through the tail vein,in situ excitation of X-rays can be *** the persistent luminescence decays,LYGM can be re-excited for repeated ***,LYGM shows potential prospects for in vivo deep tissue and long-term bioimaging.

关键词： Persistent luminescence X-ray Biological window In vivo imaging Rare earths

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Data-driven Detection and Identification of Line Parameters with PMU and Unsynchronized SCADA Measurements in Distribution Grids

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 261-271页

作者： Jinping sun Qifang Chen Mingchao xia School of Electrical Engineering Beijing Jiaotong University(BJTU)Beijing 100044China

Line parameters play an important role in the control and management of distribution ***,phasor measurement unit(PMU)systems and supervisory control and data acquisition(SCADA)systems coexist in distribution ***,SCADA and PMU measurements usually do not match each other,resulting in inaccurate detection and identification of line parameters based on *** solve this problem,a data-driven method is *** measurements are taken as samples and PMU measurements as the population.A probability parameter identification index(PPII)is derived to detect the whole line parameter based on the probability density function(PDF)parameters of the *** parameter identification,a power-loss PDF with the PMU time stamps and a power-loss chronological PDF are derived via kernel density estimation(KDE)and a conditional ***,the power-loss samples with the PMU time stamps and chronological correlations are generated by the two PDFs of the power loss via the Metropolis-Hastings(MH)***,using the power-loss samples and PMU current measurements,the line parameters are identified using the total least squares(TLS)*** simulations demonstrate the effectiveness of the proposed method for distribution network line parameter detection and identification.

关键词： Distribution systems line parameter detection and identification probability density function sampling algorithm the time skew of PMU and SCADA measurements

Path signature-based XAI-enabled network time series classification

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Science China(Information Sciences) 2024年第7期67卷 91-106页

作者： Le sun Yueyuan WANG Yongjun REN Feng xia Department of Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science and Technology School of Computing Technologies Royal Melbourne Institute of Technology

Classifying network time series(NTS) is crucial for automating network administration and ensuring cyberspace security. It enables the detection of anomalies, the identification of network attacks,and the monitoring of performance issues, thereby providing valuable support for network protection and optimization. However, modern communication networks pose challenges for NTS classification *** include handling large-scale and complex NTS data, extracting features from intricate datasets, and addressing explainability requirements. These challenges are particularly pronounced for complex 5G networks. Notably, explainability has become crucial for the widespread deployment of network automation for 5G networks and beyond. To tackle these challenges, we propose a path-signature-based NTS classification model called recurrent signature(Recur Sig). This innovative model is designed to overcome the time-consuming feature selection problem by utilizing deep-learning(DL) techniques. Additionally, it provides a solution for addressing the black-box issue associated with DL models in network automation systems(NAS) by incorporating an explainable classification approach. Extensive experimentation on various public datasets demonstrates that Recur Sig outperforms existing models in accuracy and explainability. The results indicate its potential for application in cyberspace security and automated network management, offering an explainable solution for network protection and optimization.

关键词： network time series classification explainable artificial intelligence path signature automated network management recurrent neural network

Probabilistic seismic inversion based on physics-guided deep mixture density network

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Petroleum Science 2024年第3期21卷 1611-1631页

作者： Qian-Hao sun Zhao-yun Zong Xin Li National Key Laboratory of Deep Oil and Gas China University of Petroleum(East China)Qingdao266580ShandongChina Laoshan Laboratory Qingdao266580ShandongChina CNOOC Research Institute Ltd. Beijing100028China

Deterministic inversion based on deep learning has been widely utilized in model parameters *** by logging data,seismic data,wavelet and modeling operator,deterministic inversion based on deep learning can establish nonlinear relationships between seismic data and model ***,seismic data lacks low-frequency and contains noise,which increases the non-uniqueness of the *** conventional inversion method based on deep learning can only establish the deterministic relationship between seismic data and parameters,and cannot quantify the uncertainty of *** order to quickly quantify the uncertainty,a physics-guided deep mixture density network(PG-DMDN)is established by combining the mixture density network(MDN)with the deep neural network(DNN).Compared with Bayesian neural network(BNN)and network dropout,PG-DMDN has lower computing cost and shorter training time.A low-frequency model is introduced in the training process of the network to help the network learn the nonlinear relationship between narrowband seismic data and low-frequency *** addition,the block constraints are added to the PG-DMDN framework to improve the horizontal continuity of the inversion *** illustrate the benefits of proposed method,the PG-DMDN is compared with existing semi-supervised inversion *** synthetic data examples of Marmousi II model are utilized to quantify the influence of forward modeling part,low-frequency model,noise and the pseudo-wells number on inversion results,and prove the feasibility and stability of the proposed *** addition,the robustness and generality of the proposed method are verified by the field seismic data.

关键词： Deep learning Probabilistic inversion Physics-guided Deep mixture density network

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Risk Assessment for Hybrid AC/DC Systems Based on Transient Energy Function

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1654-1663页

作者： Peng sun yun Teng Mingli Zhang Zhe Chen Shenyang University of Technology Shenyang 110870China Liaoning Electric Power Co.Ltd.Economic Research Institute Shenyang 110000China Department of Energy Technology Aalborg UniversityAalborgDK DK 9220

In order to accurately assess the risk of the hybrid AC/DC network under fault,a risk assessment method for the hybrid AC/DC system based on the transient energy function is ***,based on the energy transfer relationship of the hybrid AC/DC power system,the transient energy function model of the hybrid AC/DC system is *** on the operating data of the power grid,the energy function is used as an efficiency variable,and the efficiency variable is integrated into the prior risk probability calculation of nodes in the network,and a Bayesian network-based risk assessment model of hybrid AC/DC system is *** the dynamic update model of network cascading failures,the clique tree propagation algorithm is used to dynamically calculate the posterior risk probability of the node to realize the dynamic assessment of the network ***,the improved IEEE-39 node hybrid AC/DC system is used as an example for *** results show that the proposed model can not only effectively evaluate the overall safety of the network,but also has feasibility in predicting faults,which can provide a theoretical basis for the stability control of the hybrid AC/DC system.

关键词： Cascading failure energy function hybrid AC-DC system risk assessment

Microbiome and intestinal pathophysiology in post-acute sequelae of COVID-19

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Genes & Diseases 2024年第3期11卷 220-231页

作者： Jilei Zhang Yongguo Zhang Yinglin xia Jun sun Division of Gastroenterology and Hepatology Department of MedicineUniversity of Ilinois ChicagoIL60612USA Uic Cancer Center Department of Microbiology and ImmunologyUniversity of Ilinois ChicagoChicagoIL60612USA Jesse Brown VA Medical Center ChicagoIL60612USA

Long CoVID,also known for post-acute sequelae of CovID-19,describes the people who have the signs and symptoms that continue or develop after the acute coviD-19 *** CovID patients suffer from an inflammation or host responses towards the virus approx-imately 4 weeks after initial infection with the SARS CoV-2 virus and continue for an unchar-acterized *** infected with CovID-19 before could experience long-CcovID conditions,including the patients who were infected with SARS CoV-2 virus confirmed by tests and those who never knew they had an infection *** with long CoviD may experience health problems from different types and combinations of symptoms over time,such as fa-tigue,dyspnea,cognitive impairments,and gastrointestinal(Gl)symptoms(e.g.,nausea,vom-iting,diarrhea,decreased or loss of appetite,abdominal pain,and dysgeusia).The critical role of the microbiome in these Gl symptoms and long CovID were reported in clinical patients and experimental ***,we provide an overall view of the critical role of the Gl tract and microbiome in the development of long COVID,including the clinical Gl symptoms in patients,dysbiosis,viral-microbiome interactions,barrier function,and inflammatory bowel disease patients with long *** highlight the potential mechanisms and possible treatment based on Gl health and ***,we discuss challenges and future direction in the long CoVID clinic and research.

关键词： Gastrointestinal symptoms Gl tract Gut microbiome Inflammatorybowel diseases Intestinal barrier Long CoVID Metabolites Tight junctions