ALERT方案与我国青少年毒品预防教育的完善

我国青少年毒品预防教育起步较晚。尽管相关部门出台了一系列旨在加强学校毒品预防教育的政策文件,但由于缺乏系统、科学的理论指导,毒品预防教育各行其是,效果不彰。ALERT方案①是国际流行的循证干预措施之一,该方案以先进的理论为基础,1984年以来,经过不断的实验、测试、评估和调整,在预防青少年毒品滥用方面发挥了积极作用。我国可以借鉴ALERT方案,联合相关领域专家,编制权威教材和教师指导用书,加强毒品预防教育师资正规化培训,创建青少年毒品预防教育专门网站,推动家长、社区参与毒品预防教育,提高我国青少年毒品预防教育的质量。

Quantifying the Impact of In-Cab Alerts on Truck Speed Reductions in Ohio

In-cab alerts warn commercial vehicle drivers of upcoming roadway incidents, slowdowns and work zone construction activities. This paper reports on a study evaluating the driver response to in-cab alerts in Ohio. Driver response was evaluated by measuring the statistical trends of vehicle speeds after the in-cab alerts were received. Vehicle speeds pre and post in-cab alert were collected over a 47 day period in the fall of 2023 for trucks traveling on interstate roadways in Ohio. Results show that approximately 22% of drivers receiving Dangerous Slowdown alerts had reduced their speeds by at least 5 mph 30 seconds after receiving such an alert. Segmenting this analysis by speed found that of vehicles traveling at or above 70 mph at the time of alerting, 26% reduced speeds by at least 5 mph. These speed reductions suggest drivers taking actional measures after receiving alerts. Future studies will involve further analysis on the impact of the types of alerts shown, roadway characteristics and overall traffic conditions on truck speeds passing through work zones.

A Framework for Cybersecurity Alert Distribution and Response Network (ADRIAN)

Security Information and Event Management (SIEM) platforms are critical for organizations to monitor and manage their security operations centers. However, organizations using SIEM platforms have several challenges such as inefficiency of alert management and integration with real-time communication tools. These challenges cause delays and cost penalties for organizations in their efforts to resolve the alerts and potential security breaches. This paper introduces a cybersecurity Alert Distribution and Response Network (Adrian) system. Adrian introduces a novel enhancement to SIEM platforms by integrating SIEM functionalities with real-time collaboration platforms. Adrian leverages the uniquity of mobile applications of collaboration platforms to provide real-time alerts, enabling a two-way communication channel that facilitates immediate response to security incidents and efficient SIEM platform management. To demonstrate Adrian’s capabilities, we have introduced a case-study that integrates Wazuh, a SIEM platform, to Slack, a collaboration platform. The case study demonstrates all the functionalities of Adrian including the real-time alert distribution, alert customization, alert categorization, and enablement of management activities, thereby increasing the responsiveness and efficiency of Adrian’s capabilities. The study concludes with a discussion on the potential expansion of Adrian’s capabilities including the incorporation of artificial intelligence (AI) for enhanced alert prioritization and response automation.

Influences of protein to energy ratios in breakfast on mood, alertness and attention in the healthy undergraduate students

Background: The high protein (HP) breakfast reduced gastric emptying and the most satiat-ing macronutrient appears to be dietary protein. Few studies have investigated the effects of protein to energy ratio in breakfast on mood, alertness and attention. Objective: This study was designed to investigate whether the HP breakfast is more beneficial to mood, alertness and attention of the healthy undergraduate student than adequate-protein (AP) breakfast through the rising body temperature and re-maining stable blood glucose or through other physiologic processes. Methods: Thirteen healthy male undergraduate students (18 - 23 y) were studied in a double-blind, randomized crossover design. Blood samples, body tem-perature, satiety, mood and Continuous Per-formance Test (CPT) were assessed after the consumption of two isocaloric breakfasts that differed in their protein and carbohydrate con-tent: an HP breakfast (50%, 30%, and 20% of energy from protein, carbohydrate, and fat, re-spectively) or an AP breakfast (10%, 70%, and 20% of energy from protein, carbohydrate, and fat, respectively). Results: Consumption of an HP breakfast resulted in more steady glucose and insulin than AP breakfast consumption (p < 0.05). Satiety scores and body temperature were higher after HP breakfast consumption (p < 0.05). And most important, the positive mood and CPT scores were higher after HP breakfast than after AP breakfast intake (p < 0.05). Conclusion: HP breakfast can effectively stabilize postprandial serum glucose concentration and elevate post-prandial temperature of healthy male under-graduate students. Our present findings dem-onstrate the relationship between HP breakfast and mood, alertness and attention. This study indicated that HP breakfast may enhance human performance probably by increasing the thermic effect of a food and elevating body temperature.

Alertness Staging Based on Improved Self-Organizing Map

In order to classify the alertness status, 19 channels of electroencephalogram(EEG) signals from 5 subjects were acquired during daytime nap. Ten different types of features(including time domain features, frequency domain features and nonlinear features) were extracted from EEG signals, and an improved self-organizing map(ISOM) neuron network was proposed, which successfully identify three different brain status of the subjects: awareness, drowsiness and sleep. Compared with traditional SOM, the experiment results show that the ISOM generates much better classification accuracy, reaching as high as 89.59%.

AlertInsight:Mining Multiple Correlation For Alert Reduction

Modern cloud services are monitored by numerous multidomain and multivendor monitoring tools,which generate massive numbers of alerts and events that are not actionable.These alerts usually carry isolated messages that are missing service contexts.Administrators become inundated with tickets caused by such alert events when they are routed directly to incident management systems.Noisy alerts increase the risk of crucial warnings going undetected and leading to service outages.One of the feasible ways to cope with the above problems involves revealing the correlations behind a large number of alerts and then aggregating the related alerts according to their correlations.Based on these guidelines,AlertInsight,a framework for alert event reduction,is proposed in this paper.In AlertInsight,the correlations among event sources are found by mining a sequence of historical events.Then,event correlation knowledge is employed to build an online detector targeting the correlated events that are hidden in the event stream.Finally,the correlated events are aggregated into a single high-level event for alert reduction.Because of theweaknesses of the commonly used pairwise correlation analysis methods in complex environments,an innovative approach for multiple correlation mining,which overcomes computational complexity challenges by scanning panoramic views of historical episodes from the perspective of holism,is proposed in this paper.In addition,a neural network-based correlated event detector that can learn the event correlation knowledge generated from correlation mining and then detect the correlated events in a sequence online is proposed.Experiments are conducted to test the effectiveness of AlertInsight.The experimental results(precision=0.92,recall=0.93,and F1-score=0.93)demonstrate the performance of AlertInsight for the recognition of multiple correlated alerts and its competence for alert reduction.

数字化转型下知识耦合如何重构组织边界——基于创业警觉的认知逻辑

数字化转型下制造企业的边界重构是知识的动态交互联接,从此视角打开组织边界重构的过程机制,对提升企业敏捷性、共生性具有重要作用。本文采用归纳式单案例研究,通过对制造企业多个层次的深入研究,探讨了数字化转型下企业通过知识耦合进行组织边界重构的机制。本文发现数字化转型下,制造企业运用知识重组(关键点识别、资源编排、匹配)、知识整合(数据挖掘、知识验证、跨界融合)、知识解耦(主动遗忘、流程调优、技术替代)三种知识耦合过程机制来重构组织边界。同时,研究发现创业警觉是潜在的边界重构认知逻辑,制造企业依靠创业警觉认知能力,从不同的行动领域设计边界重构决策。本文研究结论展现了数字化转型下制造企业如何通过知识的交互联接重塑组织边界,以彰显、获取知识权力;为数字化转型下制造企业的组织边界重构提供了新的、系统化的见解;对企业维持与发展知识权力优势、实现数字化转型具有借鉴意义。

Design and Simulation of an Audio Signal Alerting and Automatic Control System

A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in the need for applications and methodologies that are capable of automatically analyzing these contents. These technologies can be applied in automatic contentanalysis and emergency response systems. Breaks in manual communication usually occur in emergencies leading to accidents and equipment damage. The audio signal does a good job by sending a signal underground, which warrants action from an emergency management team at the surface. This paper, therefore, seeks to design and simulate an audio signal alerting and automatic control system using Unity Pro XL to substitute manual communication of emergencies and manual control of equipment. Sound data were trained using the neural network technique of machine learning. The metrics used are Fast Fourier transform magnitude, zero crossing rate, root mean square, and percentage error. Sounds were detected with an error of approximately 17%;thus, the system can detect sounds with an accuracy of 83%. With more data training, the system can detect sounds with minimal or no error. The paper, therefore, has critical policy implications about communication, safety, and health for underground mine.

护士高警示药品用药安全影响因素的质性研究

目的 :了解护士对高警示药品用药安全影响因素的认知体验,为护士更加安全有效地管理高警示药品提供参考。方法 :采用目的抽样法,选取不同科室的13名临床护士和护理管理者,以临床事件分析模型为理论框架,采用描述性质性研究方法对研究对象进行半结构式访谈和关键事件访谈,采用内容分析法对资料进行分析。结果 :构建了防止高警示药品错误实践的描述性模型——高警示药品用药安全:组织、护理与合作影响,提炼出组织因素、护士能力与责任、沟通合作3个主题和8个亚主题。结论 :护士高警示药品用药安全受到组织文化、自身知识与能力、医护患间沟通合作等因素影响。本研究为高警示药品用药安全管理实践提供了概念框架,同时也为医疗机构安全有效地管理高警示药品提供理论依据。

2012-2022年北京市石景山区传染病自动预警系统运行情况分析

目的 评价2012-2022年北京市石景山区传染病自动预警系统运行情况,为传染病智慧化预警多点触发机制的建立提供参考。方法 利用中国疾病预防控制信息系统中的传染病自动预警系统,收集石景山区2012-2022年传染病自动预警系统监测数据,并进行描述性分析。结果 2012-2022年北京市石景山区传染病自动预警系统发出涉及29种传染病的预警信号4 555条,响应4 555条,响应率100.00%;平均响应时间为3.23 h, 11年间预警信号数先呈波动性下降趋势,2022年急剧上升;固定阈值法、时间模型和时空模型及时响应率分别为99.75%、97.37%和95.90%;3种预警模式暴发事件阳性率不同,暴发事件涉及病种为麻疹、肺结核、流行性感冒和手足口病,表明传染病自动预警系统对麻疹、肺结核、流行性感冒和手足口病预测准确率较高。结论 北京市石景山区传染病自动预警系统运行较稳定,预警信号及时响应率高,但仍需进一步完善优化,切实提高传染病监测预警系统的敏感性和及时性。

心血管内科老年跌倒高危病人警觉度现状及影响因素

目的:调查心血管内科老年跌倒高危病人警觉度的现状,并分析其影响因素。方法:采用回顾性研究方法,选取2023年7月—9月我院心血管内科收治的236例老年跌倒高危病人,设计一般资料调查表调查病人的临床资料,采用跌倒警觉度量表评估病人跌倒警觉度现状,以多元线性回归分析心血管内科老年跌倒高危病人警觉度的影响因素。结果:236例心血管内科老年跌倒高危病人警觉度得分为(57.28±8.65)分。多元线性回归分析结果显示,预防跌倒教育、跌倒预后、跌倒恐惧是心血管内科老年跌倒高危病人警觉度的影响因素(P<0.05)。结论:心血管内科老年跌倒高危病人警觉度水平较高,护士应根据病人跌倒警觉度及相关影响因素,制订符合心血管内科老年病人的预防跌倒措施,进行个体化的健康指导,有效预防跌倒的发生。

多波段多信使天文警报信息汇集与发布平台的设计与实现

【目的】近年来天文学研究进入多信使、多波段天文学时代,天文学家可以根据天文警报信息及时地调整观测计划,追踪观测热点事件,及时全面地获取天文警报信息非常重要。【方法】基于天文警报信息获取的需求,设计了天文警报汇平台,一站式汇集国际主流信息渠道数据,利用ChatGPT完成关键信息抽取,优化提示工程,提高ChatGPT信息抽取成功率,对警报数据融合整理后进行可视化展示。【结果】实验验证了提示工程的优化使ChatGPT抽取关键信息的成功率得到显著提升。【结论】天文警报汇平台可以给天文学家提供便利,及时地发布、共享天文警报信息。ChatGPT在很大程度上能够帮助科研人员从原始警报文本中抽取需要的关键信息,提示工程的优化使ChatGPT的输出更加可靠。

工作繁荣视角下创业文化如何影响员工内部创业——创业警觉性的调节作用

基于社会认知理论,从工作繁荣视角切入,探索工作繁荣在创业文化与员工内部创业行为间的作用以及边界条件。通过对山东省176位企业员工进行问卷调查,运用Bootstrap进行数据分析。研究结果表明:工作繁荣在创业文化与员工内部创业之间发挥中介作用,资源警觉性和机会警觉性在员工内部创业过程中负向调节工作繁荣的中介效应。结论丰富了工作繁荣在内部创业领域的相关研究,补充了创业警觉性的消极作用研究,以及不同维度的创业动因研究,有助于指导企业开展复杂的员工创业实践。

技术经纪人谏言对创业者创业警觉的影响机理——基于扎根理论的多案例研究

技术经纪人日益成为科研成果转化服务领域的主力军,但目前对于技术经纪人促进早期科创项目孵化的研究较少。基于议题营销理论和创业警觉理论,运用扎根理论多案例研究法,深入探究技术经纪人谏言对创业者创业警觉的影响机理。研究发现:(1)技术经纪人谏言通过议题感知策略、议题选择策略和议题提出策略促进创业者创业警觉;(2)技术经纪人情绪体验(积极和消极)在技术经纪人谏言与创业者创业警觉之间发挥中介作用;(3)技术经纪人知识基础在技术经纪人谏言与技术经纪人情绪体验之间发挥调节作用。研究结论有助于丰富技术经纪人现有研究,对于进一步选择技术经纪人培训策略、加速科研成果商业化具有积极指导意义。

基于事件相关电位的监控员任务切换刺激模态差异性对警觉度的影响研究

为探究不同模态转换下任务切换对监控人员警觉度衰减现象的影响,采用脑电实验法,设计了危险动作识别、危险场景识别等任务,并结合行为数据及事件相关电位(Event Related Potential,ERP)技术进行综合分析;实验重点考察在任务切换过程中,不同模态的任务之间进行切换对监控人员警觉度的具体影响;通过对煤矿监控调度人员的实证研究,揭示了切换任务的模态差异性对监控员警觉度的影响及其内在机制。结果表明:当在相同刺激任务间进行切换时带来的工作绩效下降,主要原因在于任务切换产生的切换成本导致注意力分散,具体体现在任务切换后P300和P200平均波幅的升高;但是在不同刺激任务间进行切换时,尤其是切换到听觉刺激任务时,被试者的警觉度水平反而得到了一定程度的提升。

基于试验模拟的滑坡泥石流灾害链风险监测预警

[目的]开展以元阳梯田滑坡泥石流地质灾害链为基础的风险监测预警研究,为改善降雨诱发型滑坡泥石流灾害链的预警精度,提高防灾减灾工作针对性提供科学依据。[方法]采用降雨模型模拟试验来探讨元阳梯田滑坡—泥石流灾害链破坏过程,通过对降雨量、体积含水率和坡体变形破坏过程进行实时监测,分析不同降雨条件下灾害链风险预警阈值。试验设置长时间中雨(50 mm/h)、长时间暴雨(120 mm/h)、循环间歇暴雨和干旱突发型暴雨4种降雨工况。[结果]在降雨持续作用下,灾害链发展过程为:地表冲刷、蠕滑、快速滑动、泥石流运移及运移结束。坡体破坏最先从左侧坡脚开始,右侧坡脚稍后。不同降雨工况下坡体破坏形式不同:暴雨工况下坡体中部会产生一条横向裂缝,而形成上下两个滑块;中雨工况下坡体则陆续形成多个滑块;干旱突发暴雨工况下泥石流形成时间最短,运移距离最远,流通和堆积范围相比其他降雨工况更广。[结论]滑坡泥石流灾害链预警监测指标主要为累积降雨量、降雨持续时间、含水率变化和坡体变形发展现场监测。这些监测参数受降雨条件、土体性质、坡角和外部动力条件等诸多因素影响,因此在实际应用中需要综合考虑这些因素。

扬州城市规划区地下水应急供水方案可行性研究

突发事件会引起大范围的地表水污染,对城市供水水源的安全形成挑战,严重威胁人民生命安全,危害生态环境和经济社会稳定。地下水与地表环境联系较弱,利用地下水作为应急水源是最安全的水资源保障措施。本研究以扬州城市规划区为例,确定了规划区应急需水量为17.2万m^(3)/d,应急时长为15d,主要开采的第Ⅱ、Ⅲ承压含水层限采红线水位埋深分别为20m、30m,根据研究区应急供水需求制定了4种应急供水方案。方案1和2为水源地集中供水,方案3为分散式供水,方案4为分散与集中式联合供水。依据工作区水文地质条件和地下水位监测数据,基于HydroGeoSphere构建并校正了研究区三维地下水-地表水耦合数值模型,利用数值模型分析了不同供水方案应急抽水引起的地下水位降落趋势及其与地下水开采红线的关系。研究表明,分散与集中式联合供水方案可以明显减小工作区内的水位波动,减缓水源地的供水压力,降低地面沉降风险,对现有管网的利用也较为充分,可作为应急供水的首选方案。

BacT/ALERT 3D血液样本细菌检测中假阳性反应的分析

本研究通过分析BacT/ALERT 3D系统血液样本细菌检测中的假阳性反应结果,评估该系统的特异性,以减少假阳性反应的产生。对5年间BacT/ALERT 3D所有阳性反应瓶进行细菌分离和鉴定,并对留样和可获得的相关血袋进行重复试验,共检测11 395份血液样本。结果表明:初次培养阳性反应122份(1.07%),其中107份(88.7%)从阳性反应的培养瓶中分离出细菌,另15份(12.3%)中未分离出任何细菌。细菌生长引起的阳性反应的监测曲线显示明显的急剧上升。结论:在检测过程中维持孵箱温度的稳定、避免孵育箱的温度急剧降低可减少假阳性信号的产生;对报告阳性的培养瓶进行进一步的孵育,观察生长曲线是否有急剧上升的对数生长期有助于鉴别假阳性反应,从而提高BacT/ALERT 3D系统的特异性。

Bactec FX和Bact/Alert 3D两种血培养系统对菌血症的检出性能分析

目的对比分析Bactec FX血培养系统Bactec Plus树脂需氧瓶(简称BO-P瓶)和Bact/Alert 3D全自动血培养系统SA标准瓶(简称Bio-SA瓶)/SN厌氧瓶(简称Bio-SN瓶)对菌血症的检出能力及特点,探讨提高血培养阳性率、快速准确地作出病原学诊断的方法。方法从双侧部位抽取患者的静脉血,一侧注入BO-P瓶,另一侧注入Bio-SA瓶和Bio-SN瓶,置于相应培养系统培养,比较这3种血培养瓶的阳性率及检出时间。结果 6 188份标本中确认阳性765份(12.36%);确认污染134份(2.17%);假阳性11份(0.18%)。332株临床分离菌中BO-P瓶检出293例,占88.25%;Bio-SA瓶检出271例,占81.63%,前者阳性率高于后者(χ2=5.687,P<0.05);Bio-SN瓶检出201例,占60.54%,其中厌氧菌3例,占0.90%。与Bio-SA瓶相比,BO-P瓶检出阳性的时间优于Bio-SA瓶(P<0.05),尤其是对非发酵菌。污染菌以革兰阳性菌为主(89.55%),主要是凝固酶阴性的葡萄球菌(67.91%),少部分革兰阴性杆菌(9.7%)。结论双侧抽血并联合使用Bactec FX和Bact/Alert 3D血培养系统可利用各自优势,更有效地提高血培养阳性率。

BacT/ALERT 3D系统在魔芋罐头商业无菌检测中的应用

对BacT/ALERT3D系统在魔芋罐头商业无菌检测中的适用性进行评估。采用BacT/ALERT3D系统和GB/T4789.26两种方法对59份魔芋罐头进行孵育培养,并对19个BacT/ALERT3D系统测试阳性样品作验证实验和分析。结果表明BacT/ALERT3D系统检测结合日本方法的验证实验,能够快速准确地检测魔芋罐头中是否存在能增殖的微生物,而GB/T4789.26对高pH值的魔芋罐头商业无菌检测存在较大漏检率。