术前IDEAS模式访视在肺癌胸腔镜辅助小切口手术患者中的应用效果

目的 探讨术前IDEAS模式访视在肺癌胸腔镜辅助小切口手术(VAMT)患者中的应用效果。方法根据干预方式的不同将80例肺癌VAMT患者分为对照组(n=34)和IDEAS组(n=46),对照组患者给予常规术前访视,IDEAS组患者给予术前IDEAS模式访视。比较两组患者的生理指标[脉率(PR)、舒张压(DBP)、收缩压(SBP)]、疼痛程度[视觉模拟评分法(VAS)]、心理状态[汉密尔顿焦虑量表(HAMA)、汉密尔顿抑郁量表(HAMD)]、希望水平[Herth希望量表(HHI)]、满意度、住院时间及并发症发生情况。结果 干预后,两组患者PR、DBP、SBP均高于本组干预前,IDEAS组患者PR、DBP、SBP均低于对照组,差异均有统计学意义(P﹤0.05)。干预后,两组患者VAS、HAMD、HAMA评分均低于本组干预前,HHI量表各维度评分均高于本组干预前,IDEAS组患者VAS、HAMD、HAMA评分均低于对照组,HHI量表各维度评分均高于对照组,差异均有统计学意义(P﹤0.05)。IDEAS组患者的总满意率为100%,明显高于对照组患者的82.35%,住院时间明显短于对照组,差异均有统计学意义(P﹤0.01)。IDEAS组患者的并发症总发生率为4.35%,与对照组患者的11.76%比较,差异无统计学意义(P﹥0.05)。结论 术前IDEAS模式访视能有效改善肺癌VAMT患者的生理指标、心理状态和疼痛程度,提高希望水平,患者的满意度高。

基于IDEAS的多元化护理对溃疡性结肠炎患者生活质量及满意度的影响

目的探究基于IDEAS的多元化护理模式对溃疡性结肠炎患者生活质量及满意度的影响。方法方便选取2018年9月—2023年9月盐城市第三人民医院消化内科收治的84例溃疡性结肠炎患者作为研究对象,以随机数表法分为两组,对照组(42例)实行常规护理,观察组(42例)实行基于IDEAS的多元化护理模式。比较两组生活质量评分及护理满意度。结果观察组生活质量评分高于对照组,差异有统计学意义(P<0.05)。观察组护理总满意率远高于对照组,差异有统计学意义(P<0.05)。结论基于IDEAS的多元化护理模式对溃疡性结肠炎护理效果具有积极影响,利于提高患者生存质量与护理满意度。

基于IDEAS访视模式对腹腔镜下全子宫切除术患者生理、心理应激反应及应对方式的影响

目的:探讨基于IDEAS访视模式对腹腔镜下全子宫切除术患者生理、心理应激反应及应对方式的影响。方法:选取2021年1月—2022年12月于肇庆市第一人民医院拟行腹腔镜下全子宫切除术的患者60例作为研究对象,以随机数字表法分为对照组(实施常规术前访视)和观察组(实施基于IDEAS的访视模式),各30例。比较两组患者生理应激指标、心理应激水平、应对方式及护理满意度。结果:访视后,两组脉率、舒张压、收缩压水平高于访视前,观察组脉率、舒张压、收缩压水平低于对照组,差异有统计学意义(P<0.05);访视后,两组面对评分高于访视前,焦虑自评量表、抑郁自评量表评分及回避、屈服评分低于访视前,观察组优于对照组,差异有统计学意义(P<0.05);观察组护理满意度高于对照组,差异有统计学意义(P=0.0022)。结论:应用基于IDEAS访视模式于腹腔镜下全子宫切除术患者中的临床效果显著,有利于缓解患者的生理、心理应激反应,改善患者的应对方式,提高护理满意度。

Ideal Case Study of Adaptive Localization in Storm-scale Ensemble Kalman Filter Assimilation

This study explores the use of the hierarchical ensemble filter to determine the localized influence of observations in the Weather Research and Forecasting ensemble square root filtering(WRF-EnSRF)assimilation system.With error correlations between observations and background field state variables considered,the adaptive localization approach is applied to conduct a series of ideal storm-scale data assimilation experiments using simulated Doppler radar data.Comparisons between adaptive and empirical localization methods are made,and the feasibility of adaptive localization for storm-scale ensemble Kalman filter assimilation is demonstrated.Unlike empirical localization,which relies on prior knowledge of distance between observations and background field,the hierarchical ensemble filter provides continuously updating localization influence weights adaptively.The adaptive scheme improves assimilation quality during rapid storm development and enhances assimilation of reflectivity observations.The characteristics of both the observation type and the storm development stage should be considered when identifying the most appropriate localization method.Ultimately,combining empirical and adaptive methods can optimize assimilation quality.

SNR and RSSI Based an Optimized Machine Learning Based Indoor Localization Approach:Multistory Round Building Scenario over LoRa Network

In situations when the precise position of a machine is unknown,localization becomes crucial.This research focuses on improving the position prediction accuracy over long-range(LoRa)network using an optimized machine learning-based technique.In order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting method over LoRa technology,this study proposed an optimized machine learning(ML)based algorithm.Received signal strength indicator(RSSI)data from the sensors at different positions was first gathered via an experiment through the LoRa network in a multistory round layout building.The noise factor is also taken into account,and the signal-to-noise ratio(SNR)value is recorded for every RSSI measurement.This study concludes the examination of reference point accuracy with the modified KNN method(MKNN).MKNN was created to more precisely anticipate the position of the reference point.The findings showed that MKNN outperformed other algorithms in terms of accuracy and complexity.

基于IDEAS模式的术前访视联合共情支持对严重烧伤患者生理应激、应对方式和瘢痕恢复的影响

目的:基于IDEAS模式(即识别问题、确认选项、评估并选择最佳选项、行动和检验有效性)的术前访视联合共情支持对严重烧伤患者生理应激、应对方式和瘢痕恢复的影响。方法:选取2021年2月-2023年2月笔者科室收治的90例严重烧伤患者为研究对象,按照随机数字表法分为观察组和对照组,各45例。对照组给予共情支持,观察组给予基于IDEAS模式的术前访视护理联合共情支持,比较两组生理应激[去甲肾上腺素(Norepinephrine,NE)、血管紧张素Ⅱ(Angiotensin Ⅱ,AngⅡ)水平]、心理状况[采用汉密尔顿焦虑量表(Hamilton anxiety scale,HAMA)和汉密尔顿抑郁量表(Hamilton depression scale,HAMD)评估]、应对方式[采用医学应对问卷(Medical coping modes questionnaire,MCMQ)评估]、自理能力[采用自我护理能力量表(Exercise of self-care agency scale,ESCA)]和瘢痕恢复情况[采用温哥华瘢痕量表(Vancouver scar scale,VSS)评估]。结果:干预后,观察组血清NE、AngⅡ水平低于对照组,HAMA、HAMD评分低于对照组,MCMQ评分优于对照组,ESCA各维度评分高于对照组,VSS评分及总分低于对照组,差异均有统计学意义(P<0.05)。结论:基于IDEAS模式的术前访视联合共情支持可有效减轻严重烧伤患者生理应激,改善不良心理和应对方式,提高自我护理能力,进而促进瘢痕快速恢复。

Survey of Indoor Localization Based on Deep Learning

This study comprehensively examines the current state of deep learning (DL) usage in indoor positioning.It emphasizes the significance and efficiency of convolutional neural networks (CNNs) and recurrent neuralnetworks (RNNs). Unlike prior studies focused on single sensor modalities like Wi-Fi or Bluetooth, this researchexplores the integration of multiple sensor modalities (e.g.,Wi-Fi, Bluetooth, Ultra-Wideband, ZigBee) to expandindoor localization methods, particularly in obstructed environments. It addresses the challenge of precise objectlocalization, introducing a novel hybrid DL approach using received signal information (RSI), Received SignalStrength (RSS), and Channel State Information (CSI) data to enhance accuracy and stability. Moreover, thestudy introduces a device-free indoor localization algorithm, offering a significant advancement with potentialobject or individual tracking applications. It recognizes the increasing importance of indoor positioning forlocation-based services. It anticipates future developments while acknowledging challenges such as multipathinterference, noise, data standardization, and scarcity of labeled data. This research contributes significantly toindoor localization technology, offering adaptability, device independence, and multifaceted DL-based solutionsfor real-world challenges and future advancements. Thus, the proposed work addresses challenges in objectlocalization precision and introduces a novel hybrid deep learning approach, contributing to advancing locationcentricservices.While deep learning-based indoor localization techniques have improved accuracy, challenges likedata noise, standardization, and availability of training data persist. However, ongoing developments are expectedto enhance indoor positioning systems to meet real-world demands.

Seropositivity and Other Determinants Associated with Toxoplasmosis in Local Buffalo in Iraq

A cross-sectional study was conducted to determine the Seropositivity of Toxoplasma gondii in water buffalo in three Iraqi governorates (Baghdad, Dhi Qar, and Maysan) and to estimate the risk aspects related to infestation throughout the period from January to December 2019. A total of 430 serum samples were inspected with a commercial ELISA (Enzyme linked immunosorbent assay) kit. Indirect multi-species kit. The overall Seropositivity of T. gondii in the examined local buffalo was 7.4%, and the highest rate (9.3%) was in Baghdad Governorate. A multivariate regression analysis revealed that adult buffalo (OR = 7.10;95% CI: 0.87-57.68;P = 0.067) and young herds (OR = 8.42;95% CI: 1.07-66.02;P = 0.043) were more subject to infestation from young buffalo and large herds. Furthermore, the hazard of toxoplasmosis was increased in winter especially among animals in contact with cats. It is therefore requisite to determine risk aspects to evaluate which mitigation, control, prevention and procedures should be carried out to diminish, control and prevent infestation with T. gondii and its propagation.

Improved PSO-Extreme Learning Machine Algorithm for Indoor Localization

Wi Fi and fingerprinting localization method have been a hot topic in indoor positioning because of their universality and location-related features.The basic assumption of fingerprinting localization is that the received signal strength indication(RSSI)distance is accord with the location distance.Therefore,how to efficiently match the current RSSI of the user with the RSSI in the fingerprint database is the key to achieve high-accuracy localization.In this paper,a particle swarm optimization-extreme learning machine(PSO-ELM)algorithm is proposed on the basis of the original fingerprinting localization.Firstly,we collect the RSSI of the experimental area to construct the fingerprint database,and the ELM algorithm is applied to the online stages to determine the corresponding relation between the location of the terminal and the RSSI it receives.Secondly,PSO algorithm is used to improve the bias and weight of ELM neural network,and the global optimal results are obtained.Finally,extensive simulation results are presented.It is shown that the proposed algorithm can effectively reduce mean error of localization and improve positioning accuracy when compared with K-Nearest Neighbor(KNN),Kmeans and Back-propagation(BP)algorithms.

Interplay between topology and localization on superconducting circuits

Topological insulators occupy a prominent position in the realm of condensed matter physics. Nevertheless, the presence of strong disorder has the potential to disrupt the integrity of topological states, leading to the localization of all states.This study delves into the intricate interplay between topology and localization within the one-dimensional Su–Schrieffer–Heeger(SSH) model, which incorporates controllable off-diagonal quasi-periodic modulations on superconducting circuits.Through the application of external alternating current(ac) magnetic fluxes, each transmon undergoes controlled driving,enabling independent tuning of all coupling strengths. Within a framework of this model, we construct comprehensive phase diagrams delineating regions characterized by extended topologically nontrivial states, critical localization, and coexisting topological and critical localization phases. The paper also addresses the dynamics of qubit excitations, elucidating distinct quantum state transfers resulting from the intricate interplay between topology and localization. Additionally, we propose a method for detecting diverse quantum phases utilizing existing experimental setups.

Dynamical localization in a non-Hermitian Floquet synthetic system

We investigate the non-Hermitian effects on quantum diffusion in a kicked rotor model where the complex kicking potential is quasi-periodically modulated in the time domain.The synthetic space with arbitrary dimension can be created by incorporating incommensurate frequencies in the quasi-periodical modulation.In the Hermitian case,strong kicking induces the chaotic diffusion in the four-dimension momentum space characterized by linear growth of mean energy.We find that the quantum coherence in deep non-Hermitian regime can effectively suppress the chaotic diffusion and hence result in the emergence of dynamical localization.Moreover,the extent of dynamical localization is dramatically enhanced by increasing the non-Hermitian parameter.Interestingly,the quasi-energies become complex when the non-Hermitian parameter exceeds a certain threshold value.The quantum state will finally evolve to a quasi-eigenstate for which the imaginary part of its quasi-energy is large most.The exponential localization length decreases with the increase of the non-Hermitian parameter,unveiling the underlying mechanism of the enhancement of the dynamical localization by nonHermiticity.

网络关系视角下的用户创新生存影响因素分析——以LEGO Ideas为例

以LEGO Ideas作为数据来源,在社交网络平台的相关研究基础上,构建出作者网络和内容网络,并计算出用户创新节点在网络中的中心性。采用生存分析法,将用户创新的“存活”视为生存事件,建立生存回归模型,分阶段计算出网络中心性对用户创新生存的影响系数。研究认为,两类网络属性在用户创新发布早期为其生存提供正向影响,作者网络的影响在后期愈发明显,而内容网络则逐渐出现负向影响的迹象。企业应鼓励OI平台中高质量作者间的互动,更多地根据作者行为识别出高质量的用户创新。

Layered metastructure containing freely-designed local resonators for wave attenuation

Combining periodic layered structure with three-dimensional cylindrical local resonators,a hybrid metastructure with improved wave isolation ability was designed and investigated through theoretical and numerical approaches.The metastructure is composed of periodic rubber layers and concrete layers embedded with three-dimensional resonators,which can be freely designed with multi local resonant frequencies to attenuate vibrations at required frequencies and widen the attenuation bandgap.The metastructure can also effectively attenuate seismic responses.Compared with layered rubber-based structures,the metastructure has more excellent wave attenuation effects with greater attenuation and wider bandgap.

Scenario Modeling-Aided AP Placement Optimization Method for Indoor Localization and Network Access

Owing to the ubiquity of wireless networks and the popularity of WiFi infrastructures,received signal strength(RSS)-based indoor localization systems have received much attention.The placement of access points(APs)significantly influences localization accuracy and network access.However,the indoor scenario and network access are not fully considered in previous AP placement optimization methods.This study proposes a practical scenario modelingaided AP placement optimization method for improving localization accuracy and network access.In order to reduce the gap between simulation-based and field measurement-based AP placement optimization methods,we introduce an indoor scenario modeling and Gaussian process-based RSS prediction method.After that,the localization and network access metrics are implemented in the multiple objective particle swarm optimization(MOPSO)solution,Pareto front criterion and virtual repulsion force are applied to determine the optimal AP placement.Finally,field experiments demonstrate the effectiveness of the proposed indoor scenario modeling method and RSS prediction model.A thorough comparison confirms the localization and network access improvement attributed to the proposed anchor placement method.

Population genomic data reveal low genetic diversity,divergence and local adaptation among threatened Reeves's Pheasant(Syrmaticus reevesii)

Population genomic data could provide valuable information for conservation efforts;however,limited studies have been conducted to investigate the genetic status of threatened pheasants.Reeves’s Pheasant(Syrmaticus reevesii)is facing population decline,attributed to increases in habitat loss.There is a knowledge gap in understanding the genomic status and genetic basis underlying the local adaptation of this threatened bird.Here,we used population genomic data to assess population structure,genetic diversity,inbreeding patterns,and genetic divergence.Furthermore,we identified candidate genes linked with adaptation across the current distribution of Reeves’s Pheasant.The present study assembled the first de novo genome sequence of Reeves’s Pheasant and annotated 19,458 genes.We also sequenced 30 individuals from three populations(Dabie Mountain,Shennongjia,Qinling Mountain)and found that there was clear population structure among those populations.By comparing with other threatened species,we found that Reeves’s Pheasants have low genetic diversity.Runs of homozygosity suggest that the Shennongjia population has experienced serious inbreeding.The demographic history results indicated that three populations experienced several declines during the glacial period.Local adaptative analysis among the populations identified 241 candidate genes under directional selection.They are involved in a large variety of processes,including the immune response and pigmentation.Our results suggest that the three populations should be considered as three different conservation units.The current study provides genetic evidence for conserving the threatened Reeves’s Pheasant and provides genomic resources for global biodiversity management.

In-situ AFM and quasi-in-situ studies for localized corrosion in Mg-9Al-1Fe-(Gd) alloys under 3.5 wt.% NaCl environment

Revealing the localized corrosion process of Mg alloy is considered as one of the most significant ways for improving its corrosion resistance.The reliable monitor should be high distinguishability and real-time in liquid environment.Herein,Mg-9Al-1Fe and Mg-9Al-1Fe-1Gd alloys were designed to highlight the impact of intermetallic on the corrosion behaviour.In-situ AFM with a special electrolyte circulation system and quasi-in-situ SEM observation were used to monitor the corrosion process of the designed alloys.SEM-EDS and TEM-SAED were applied to identify the intermetallic in the designed alloys,and their volta potentials were measured by SKPFM.According to the real-time and real-space in-situ AFM monitor,the corrosion process consisted of dissolution of anodicα-Mg phase,accumulation of corrosion products around cathodic phase and shedding of some fine cathodic phase.Then,the localized corrosion process of Mg alloy was revealed combined with the results of the monitor of corrosion process and Volta potential difference.

基于Local Cascade Ensemble方法的胎儿健康自动分类

为更好地自动评估胎儿宫内状态,提出一种基于local cascade ensemble(LCE)方法的胎儿健康状态分类模型。选用UCI数据集,使用ADASYN方法对不平衡数据集进行填充平衡,接着结合随机森林算法对数据特征进行选择,最后使用LCE方法对胎儿状态进行自动分类。实验结果表明,所提出模型使用的方法平均准确率、精确率、召回率和F1分数分别达到了0.9554、0.9054、0.9557和0.9290,对比传统的机器学习算法能得到更好的分类效果,有效降低了误判率。

Genome-wide investigation to assess copy number variants in the Italian local chicken population

Background Copy number variants(CNV)hold significant functional and evolutionary importance.Numerous ongoing CNV studies aim to elucidate the etiology of human diseases and gain insights into the population structure of livestock.High-density chips have enabled the detection of CNV with increased resolution,leading to the identification of even small CNV.This study aimed to identify CNV in local Italian chicken breeds and investigate their distribution across the genome.Results Copy number variants were mainly distributed across the first six chromosomes and primarily associated with loss type CNV.The majority of CNV in the investigated breeds were of types 0 and 1,and the minimum length of CNV was significantly larger than that reported in previous studies.Interestingly,a high proportion of the length of chromosome 16 was covered by copy number variation regions(CNVR),with the major histocompatibility complex being the likely cause.Among the genes identified within CNVR,only those present in at least five animals across breeds(n=95)were discussed to reduce the focus on redundant CNV.Some of these genes have been associated to functional traits in chickens.Notably,several CNVR on different chromosomes harbor genes related to muscle development,tissue-specific biological processes,heat stress resistance,and immune response.Quantitative trait loci(QTL)were also analyzed to investigate potential overlapping with the identified CNVR:54 out of the 95 gene-containing regions overlapped with 428 QTL associated to body weight and size,carcass characteristics,egg production,egg components,fat deposition,and feed intake.Conclusions The genomic phenomena reported in this study that can cause changes in the distribution of CNV within the genome over time and the comparison of these differences in CNVR of the local chicken breeds could help in preserving these genetic resources.

Real-World Evidence in Localized Pancreatic: Coping with Uncertainty in Unselected Populations

Background: Localized pancreatic cancer, including resectable (R), borderline resectable (BR) and locally advanced unresectable disease (LAU), is considered in clinical guidelines for diverse treatment options based on clinical trials in selected populations. Hence, exploring with real world evidence (RWE) clinicians’ preferences for treatment options and their results seems pertinent. Methods: In a set of consecutive patients with localized pancreatic cancer assisted in a third level hospital from January 2013 to December 2022, medical records, symptoms, diagnostic process, distribution between subtypes, and treatment plans, with safety and efficacy results, were assessed. Results: A total of 152 patients with localized disease were included (43.4% R, 21.0% BR, 33.6% LAU). The population characteristics exemplified differences between daily practice and clinical trials. Tumor location and symptoms were as expected. Treatment plan was conditioned by PS or comorbidities in 23.0% of patients. In patients with R disease, surgery followed by different adjuvant chemotherapy (CT) regimes was the antineoplastic treatment of choice (64.8%) with efficacy results (OS 37.5 months;95% CI 18.4 - 56.7), in the range of contemporary standards. The common use of neoadjuvant CT for BR disease (94.4%), with surgery in 50% of them, and its results (OS 30.8 months;95% CI 10.5 - 51.2) reflected current controversies of treatment recommendations and evolution in this scenario. Paliative CT with or without radiotherapy was the standard specific treatment in LAU disease (95.1%) with survival results (PFS: 10.8 months;95% CI 8.8 - 12.7. OS: 20.3 months;95% CI 13.5 - 27.2) that justify the distinct character and the specific study of this entity. Conclusion: RWE for localized pancreatic cancer aroused from the analysis of this population confirms the distinct nature of patients assisted in daily practice, as well as mirrors the complexity of decision making in clinical assumptions in which achieving stronger evidence should be paramount.

A UWB/IMU-Assisted Fingerprinting Localization Framework with Low Human Efforts

With the rapid development of smart phone,the location-based services(LBS)have received great attention in the past decades.Owing to the widespread use of WiFi and Bluetooth devices,Received Signal Strength Indication(RSSI)fingerprintbased localization method has obtained much development in both academia and industries.In this work,we introduce an efficient way to reduce the labor-intensive site survey process,which uses an UWB/IMU-assisted fingerprint construction(UAFC)and localization framework based on the principle of Automatic radio map generation scheme(ARMGS)is proposed to replace the traditional manual measurement.To be specific,UWB devices are employed to estimate the coordinates when the collector is moved in a reference point(RP).An anchor self-localization method is investigated to further reduce manual measurement work in a wide and complex environment,which is also a grueling,time-consuming process that is lead to artificial errors.Moreover,the measurements of IMU are incorporated into the UWB localization algorithm and improve the label accuracy in fingerprint.In addition,the weighted k-nearest neighbor(WKNN)algorithm is applied to online localization phase.Finally,filed experiments are carried out and the results confirm the effectiveness of the proposed approach.