聚焦“COMDEX/Fall 2000”

“COMDEX/Fall 2000”展览会于2000年11月13日～17日在美国拉斯维加斯举行。本次展览会的主题是“蓝芽”技术(Bluetooth)和“无所不在的计算技术”(Ubiquitous Computing)。 “蓝芽”技术产品琳琅满目 在“蓝芽”技术领域一直按兵不动的韩国三星电子公司在COMDEX上同时展示了7种与“蓝芽”技术有关的设备样机。这7种设备是机顶盒、个人数字助理(PDA)(图1)。

COMDEX/FALL2000昭示业界潮流

COMDEX 2000秋季展会于当地时间11月12日在美国著名的繁华赌城拉斯维加斯的会展中心(Las VegasConvention Center)和沙滩展馆(SandsExpo and ConventionCenter)两会场同时拉开帷幕。在为期四天的展示会上,来自全球2300多家著名IT企业及信息家电等厂商纷纷拿出自己的杀手锏,极力宣扬自己的产品与技术,而20万热情的观众则把两个展馆挤得水泄不通。

Numerical and experimental study on the falling film flow characteristics with the effect of co-current gas flow in hydrogen liquefaction process

Liquid hydrogen storage and transportation is an effective method for large-scale transportation and utilization of hydrogen energy. Revealing the flow mechanism of cryogenic working fluid is the key to optimize heat exchanger structure and hydrogen liquefaction process(LH2). The methods of cryogenic visualization experiment, theoretical analysis and numerical simulation are conducted to study the falling film flow characteristics with the effect of co-current gas flow in LH2spiral wound heat exchanger.The results show that the flow rate of mixed refrigerant has a great influence on liquid film spreading process, falling film flow pattern and heat transfer performance. The liquid film of LH2mixed refrigerant with column flow pattern can not uniformly and completely cover the tube wall surface. As liquid flow rate increases, the falling film flow pattern evolves into sheet-column flow and sheet flow, and liquid film completely covers the surface of tube wall. With the increase of shear effect of gas-phase mixed refrigerant in the same direction, the liquid film gradually becomes unstable, and the flow pattern eventually evolves into a mist flow.

荣兮? 辱兮?——COMDEX Fall 2002展会记

这是第23个年头,2002年11月16日回到拉斯维加斯,赌城之夜有了不同的意义,交织的辉煌灯火向世界发射出耀眼光芒,整个IT业界在向这里瞩目。作为力图成为一家有分量的硬件媒体的我们,自然不能放过报导它的机会,故此专门采编了这篇文章,以飨有着地理隔阂、语言隔阂的读者们。

Ambulance Records as an Information Source to Document and Prevent Fall Injuries in Sweden

In Sweden, there has been only limited documentation for injuries requiring ambulance responses. The main objective of this study is, through the use of historic data, to assess the suitability of ambulance records to describe circumstances with fall injuries. Methods: The injury events data around patients were sourced from the ambulance data register. Descriptive statistics were used to describe injured patients based on age group, type of injury, place of injury, injury mechanism and consequence of an injury event. Two-group comparison was performed with Pearson’s chi-squared. Predictors of transport to hospital were identified using logistic regression analyses. Result: Ambulance provides unique data on all injury events, with direct implications for translational research, public policy and clinical practice (safety promotion). In 2002 ambulance attended 3964 injured people which represents 14% of ambulance attended workload in Värmland county, Sweden. The most common trauma location was the traffic area followed by residential area and nursing home. These three injury sites account for 2320 cases (61.6%). The most common cause of injury was falls (63.9%) followed by contact with another person (26.5%). Contact with another person is the most common site of injury in the traffic area (79.5%), and men aged 25-66 years are overrepresented. Conclusion: Logistic regression found that, age-group and place code were significant predictor for being attended by ambulance. Traffic, home and nursing homes were over-represented injury environments (61.6%) that require special attention. Most injury cases occur in the home and nursing homes among people over 67 years of age. Surprisingly, most of the injury events in the traffic environment are about hitting another person. Paramedics can provide rich and valuable data on injury events. Registration of such data is entirely possible and desirable, and can be used in preventive work.

Fuzzy inference system using genetic algorithm and pattern search for predicting roof fall rate in underground coal mines

One of the most dangerous safety hazard in underground coal mines is roof falls during retreat mining.Roof falls may cause life-threatening and non-fatal injuries to miners and impede mining and transportation operations.As a result,a reliable roof fall prediction model is essential to tackle such challenges.Different parameters that substantially impact roof falls are ill-defined and intangible,making this an uncertain and challenging research issue.The National Institute for Occupational Safety and Health assembled a national database of roof performance from 37 coal mines to explore the factors contributing to roof falls.Data acquired for 37 mines is limited due to several restrictions,which increased the likelihood of incompleteness.Fuzzy logic is a technique for coping with ambiguity,incompleteness,and uncertainty.Therefore,In this paper,the fuzzy inference method is presented,which employs a genetic algorithm to create fuzzy rules based on 109 records of roof fall data and pattern search to refine the membership functions of parameters.The performance of the deployed model is evaluated using statistical measures such as the Root-Mean-Square Error,Mean-Absolute-Error,and coefficient of determination(R_(2)).Based on these criteria,the suggested model outperforms the existing models to precisely predict roof fall rates using fewer fuzzy rules.

A Novel Fall Detection Framework Using Skip-DSCGAN Based on Inertial Sensor Data

With the widespread use of Internet of Things(IoT)technology in daily life and the considerable safety risks of falls for elderly individuals,research on IoT-based fall detection systems has gainedmuch attention.This paper proposes an IoT-based spatiotemporal data processing framework based on a depthwise separable convolution generative adversarial network using skip-connection(Skip-DSCGAN)for fall detection.The method uses spatiotemporal data from accelerometers and gyroscopes in inertial sensors as input data.A semisupervised learning approach is adopted to train the model using only activities of daily living(ADL)data,which can avoid data imbalance problems.Furthermore,a quantile-based approach is employed to determine the fall threshold,which makes the fall detection frameworkmore robust.This proposed fall detection framework is evaluated against four other generative adversarial network(GAN)models with superior anomaly detection performance using two fall public datasets(SisFall&MobiAct).The test results show that the proposed method achieves better results,reaching 96.93% and 92.75% accuracy on the above two test datasets,respectively.At the same time,the proposed method also achieves satisfactory results in terms ofmodel size and inference delay time,making it suitable for deployment on wearable devices with limited resources.In addition,this paper also compares GAN-based semisupervised learning methods with supervised learning methods commonly used in fall detection.It clarifies the advantages of GAN-based semisupervised learning methods in fall detection.

Factors associated with the incidence of patient falls in hospitals:A scoping review

When a patient falls within a hospital setting,there is a significant increase in the risk of severe injury or health complications.Recognizing factors associated with such falls is crucial to mitigate their impact on patient safety.This review seeks to analyze the factors contributing to patient falls in hospitals.The main goal is to enhance our understanding of the reasons behind these falls,enabling hospitals to devise more effective prevention strategies.This study reviewed literature published from 2013 to 2022,using the Arksey and O’Malley methodology for a scoping review.The research literature was searched from seven databases,namely,PubMed,ScienceDirect,Wiley Library,Garuda,Global Index Medicus,Emerald Insight,and Google Scholar.The inclusion criteria comprised both qualitative and quantitative primary and secondary data studies centered on hospitalized patients.Out of the 893 studies analyzed,23 met the criteria and were included in this review.Although there is not an abundance of relevant literature,this review identified several factors associated with falls in hospitals.These encompass environmental,patient,staff,and medical factors.This study offers valuable insights for hospitals and medical personnel aiming to enhance fall prevention practices.Effective prevention efforts should prioritize early identification of patient risk factors,enhancement of the care environment,thorough training for care staff,and vigilant supervision of high-risk patients.By comprehending the factors that contribute to patient falls,hospitals can bolster patient safety and mitigate the adverse effects of falls within the health-care setting.

A Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller Model Combined with an Improved Particle Swarm Optimization Method for Fall Detection

In many Eastern and Western countries,falling birth rates have led to the gradual aging of society.Older adults are often left alone at home or live in a long-term care center,which results in them being susceptible to unsafe events(such as falls)that can have disastrous consequences.However,automatically detecting falls fromvideo data is challenging,and automatic fall detection methods usually require large volumes of training data,which can be difficult to acquire.To address this problem,video kinematic data can be used as training data,thereby avoiding the requirement of creating a large fall data set.This study integrated an improved particle swarm optimization method into a double interactively recurrent fuzzy cerebellar model articulation controller model to develop a costeffective and accurate fall detection system.First,it obtained an optical flow(OF)trajectory diagram from image sequences by using the OF method,and it solved problems related to focal length and object offset by employing the discrete Fourier transform(DFT)algorithm.Second,this study developed the D-IRFCMAC model,which combines spatial and temporal(recurrent)information.Third,it designed an IPSO(Improved Particle Swarm Optimization)algorithm that effectively strengthens the exploratory capabilities of the proposed D-IRFCMAC(Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller)model in the global search space.The proposed approach outperforms existing state-of-the-art methods in terms of action recognition accuracy on the UR-Fall,UP-Fall,and PRECIS HAR data sets.The UCF11 dataset had an average accuracy of 93.13%,whereas the UCF101 dataset had an average accuracy of 92.19%.The UR-Fall dataset had an accuracy of 100%,the UP-Fall dataset had an accuracy of 99.25%,and the PRECIS HAR dataset had an accuracy of 99.07%.

Analysis of the Clinical Interventions for Falls in Elderly Patients in the Community From 2002 To 2022:A Bibliometric Analysis

Objective:To analyze and provide a comprehensive overview of the knowledge structure and research hotspots of clinical interventions for falls in elderly patients in the community.Methods:The search for publications related to clinical interventions for falls in elderly patients in the community from 2002 to 2022 was conducted on the Web of Science Core Collection(WoSCC)database.VOSviewers,CiteSpace,and the R package“bibliometrix”were used to conduct this bibliometric analysis.Results:2091 articles from 70 countries,primarily the United States and Australia,were included.The number of publications related to clinical interventions for falls in elderly patients is increasing yearly.The main research institutions in this field were the University of Sydney,Harvard University,and the University of California.BioMed Central(BMC)Geriatrics was the most popular journal in this field and Journals of the American Geriatrics Society was the most co-cited journal.These publications came from 8984 authors among which author Lord SR had published the most papers and author Tinetti Me had the most co-citations.The main keywords in this research field were“balance,”“exercise,”and“risk factor.”Conclusion:This was the first bibliometric study that comprehensively summarized the research hot spots and development of clinical interventions for falls in elderly patients in the community.This paper aims to provide a reference for scholars and researchers in this particular field.

Effectiveness of Extended Care in Preventing Falls in Disabled Elderly and Its Impact on Quality of Life

Objective:To analyze the value of extended care interventions for disabled elderly in preventing falls and optimizing quality of life.Methods:A sample of 60 cases of disabled elderly in a tertiary hospital from May 2022 to May 2023 was selected and grouped by the random number table method.The observation group received extended care,while the control group adopted routine care.The differences in complication rate,fall rate,36-Item Short Form Health Survey(SF-36)score,health knowledge awareness score,and nursing satisfaction were compared.Results:The complication rate and fall rate of the disabled elderly in the observation group were lower than those in the control group,P<0.05;the SF-36 score,health knowledge score,and nursing satisfaction of the observation group were higher than those of the control group,P<0.05.Conclusion:Extended care for the disabled elderly can reduce the risk of falls and complications related to disability,as well as optimize their cognition and improve their quality of life,which is efficient and feasible.

Biomass, litterfall and the nutrient fluxes in Chinese fir stands of different age in subtropical China

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.), a fast-growing, ever-green conifer tree with high yield and excellent quality, is the most important tree species of timber plantations in subtropical China. We investigated the characteristics of biomass, litterfall and nutrient fluxes in the 8, 14 and 24 year-old stands, representing the young, middle-aged and mature stands. The results showed that Chinese fir plantations in central Fujian province had high productivity, and the proportion of stem mass in total biomass was between 50%-70%. Chinese fir was low nutrient-return tree species with litterfall. Nutrient withdrawal from senescing needles was a strong age-dependence for nitrogen, phosphorous and potassium in Chinese fir. With a management system of such short-rotation and continuously pure-crop planting, harvesting timber can lead to great nutrient loss, which may be one of the causes for site degradation.

Numerical study on dehumidifying process in falling film dehumidifier

A counter flow model of simultaneous heat and mass transfer of a vapor absorption process in a falling film dehumidifier is developed. The governing equations with appropriate boundaries and interfacial conditions describing the dehumidifying process are set up. Calcium chloride is applied as the desiccant. The dehumidifying process between falling liquid desiccant film and process air is analyzed and calculated by the control volume approach. Velocity field, temperature distribution and outlet parameters for both the process air and desiccant solution are obtained. The effects of inlet conditions and vertical wall height on the dehumidification process are also predicted. The results show that the humidity ratio, temperature and mass fraction of salt decrease rapidly at the inlet region but slowly at the outlet region along the vertical wall height. The dehumidification processes can be enhanced by increasing the vertical wall height, desiccant solution flow rates or inlet salt concentration in the desiccant solution, respectively. Similarly, the dehumidification process can be improved by decreasing the inlet humidity ratio or flow rates of the process air. The obtained results can improve the performance of the dehumidifier and provide the theoretical basis for the optimization design, and the ooeration and modulation of the solar liquid desiccant air-conditioning systems.

养老机构老年人跌倒风险综合评估工具的研制与检验

背景我国自1999年宣布进入老龄化社会以来,人口老龄化程度日益严重,养老机构成为老年人养老热门选择,但跌倒问题频发且现有评估工具效果不佳。目的研制养老机构老年人跌倒风险综合评估工具并检验其信效度。方法2021年3—12月,通过文献回顾、半结构式访谈、2轮专家函询及预调查,形成量表初始条目,并在养老机构随机选择老年人和养老护理员进行调查。采用SPSS 26.0和AMOS 26.0软件进行信效度分析和评价,采用相关系数法、临界比值法、内部一致性分析及探索性因素分析进行条目分析和筛选,选用内在信度、分半信度、评定者间信度和同质性信度检验评估工具的信度,选用表面效度、内容效度、效标关联效度、结构效度和区分效度检验评估工具的效度,采用受试者工作特征曲线检验评估工具的预测能力。结果构建的评估工具包括3个子工具:(1)老年人跌倒风险评估量表;(2)老年人跌倒史风险追踪调查表;(3)老年人跌倒风险每日检查清单。老年人跌倒风险评估量表总Cronbach'sα系数为0.73,评定者间系数为0.85;探索性因子分析提取3个公因子,累识方差贡献率为57.95%;验证性因子模型拟合度参数中的卡方自由度比值(χ^(2)/df)、拟合优度指数(GFI)、调整后拟合优度指数(AGFI)、基于标准化适度指标(NFI)、比较拟合指数(CFI)、Tucker-Lewis系数(TLI)、近似误差均方根(RMSEA)分别为2.43、0.95、0.91、0.89、0.93、0.91、0.07,区分效度经验证存在统计学意义(P<0.001)。预测能力分析结果显示,以Morse跌倒评估表(MFS)≥55分为标准时,受试者工作特征曲线下面积(AUC)为0.87;以MFS≤25分为标准时,AUC为0.84。老年人跌倒史风险追踪调查表和老年人跌倒风险每日检查清单经专家和养老护理员的评价后,形成最终版本。结论本研究开发养老机构老年人跌倒风险综合评估工具,包含3个子量表,三者间相辅相成,完善养老机构从评估到预防的全路径,具有良好的信效度和预测能力,可为日后我国养老机构跌倒预防及管理提供参考。

人抗菌肽FALL-39突变分子的特性和抗菌功能的比较

目的对人抗菌肽FALL-39不同突变分子蛋白的特性及抗菌功能进行初步的比较。方法应用AU-PAGE电泳、RP-HPLC、Om iga蛋白分析软件,比较FALL-39及其突变蛋白FALL-39-Lys24、FALL-39-Lys32、FALL-39-Lys24′32的特性;测定M IC、MEC和MBC值,并比较抗菌作用。结果突变蛋白AU-PAGE电泳迁移速率较快,RP-HPLC出峰时间未见改变,蛋白的亲疏水性、α螺旋结构、抗原性等蛋白特性无明显改变。M IC、MEC和MBC值表明FALL-39突变肽对大肠杆菌和绿脓杆菌的抗菌活性有所增强。结论突变蛋白在增加正电荷的同时,虽未改变蛋白的特性,但抗菌活性增强。

人抗菌肽FALL-39基因定点突变体的构建及其大肠杆菌表达产物的抗菌活性研究

目的 构建人抗菌肽 FAL L - 3 9定点突变子及研究其抗菌活性。方法 采用 PCR体外定点突变技术( PCR- SDM) ,设计两对引物 ,引入一个突变点 ,通过重叠延伸法两次 PCR扩增 ,使 FAL L - 3 9第 3 2位密码子由AAT突变为 AAG,将扩增片段克隆入 PGEXλ1T质粒中 ,转化大肠杆菌 JM10 9,并用 IPTG诱导 ,表达的 FAL L -3 9- lys3 2经纯化后与 FAL L - 3 9进行抗菌活性比较。结果 DNA测序结果表明在预期位点发生突变 ,突变后的FAL L - 3 9- lys3 2蛋白对大肠杆菌 ML - 3 5 p的抗菌活性明显增强 ,其最低抑菌浓度 ( MIC)和最低杀菌浓度 ( MBC)分别由 FAL L - 3 9蛋白的 18.75和 3 7.5 0μg/ m l降低为 FAL L - 3 9- L ys- 3 2的 10 .94和 2 1.88μg/ m l,对绿脓杆菌ATCC2 785 3的 MIC和 MBC值分别为 FAL L - 3 9蛋白的 3 1.2 5和 3 7.5 0μg/ m l降低为 FAL L - 3 9- L ys- 3 2的 18.75和 3 1.2 5μg/ ml。两种蛋白均在含 Medium E的 L B培养基中表现出较高活性 ,在 L B培养基中抗菌活性最低 ,但在同一种培养基中 FAL L - 3 9- L ys- 3 2蛋白抗菌活性要高于 FAL L - 3 9蛋白。结论 用两步 PCR定点突变技术获得一个 FAL L - 3 9- L ys3 2突变子 ,其表达分子的抗菌活性明显增强 ,提示在 FAL L - 3 9分子中增加碱性?