基于山区地质灾害危险性分区的建设用地适宜性评价

地质灾害是建设用地选址时考虑的关键因素之一,也是危险性区划的主要参考要素,其直接或间接危害到人类安全并给社会和经济建设造成重大损失。为了降低建设用地规划中地质灾害的影响,应将地质灾害危险性分区考虑到建设用地适宜性评价当中。以干旱河谷山区丹巴县为研究区,运用确定系数和逻辑回归相结合的方法,构建地质灾害危险性评价体系对该区进行地质灾害危险性分区。选择安全因子、自然因子、社会因子和生态因子共同构成建设用地适宜性评价指标体系,利用层次分析法对研究区进行建设用地适宜性评价。结果表明:(1)对丹巴县进行危险性分区,极高危险区217.20km2,高危险区744.95km2,中度危险区1352.44km2,低度危险区1295.08km2以及极低危险区875.32km2。(2)丹巴县建设用地最适宜区面积为115.72km2,占县域总面积的2.57%,适宜建设的土地少且多集中在小金川、革什扎河、东谷河和大渡河沿岸河谷地区。较适宜区、基本适宜区、较不适宜区和禁止建设区面积分别为683.47km2、623.21km2、590.66km2、2494.21km2。(3)已建成的城镇空间中38.50%和37.62%分布在最适宜区和较适宜区,整体分布状况良好。有5.85%的城镇空间建设在较不适宜区,2.67%在禁止建设区,存在生态安全风险,该区域应加强灾害预警与防灾减灾工作,有条件地适度搬迁。     

盾构隧道施工对邻近建筑物破坏风险初步评估

隧道开挖会引起地表和深层土体沉降,研究地层移动规律对于确定建筑物风险等级和保护邻近建筑物具有重要意义。首先,基于Peck公式并考虑深层土体横向沉降槽引起建筑物的沉降和倾斜,得到了建筑物风险区计算模型;然后,通过改变参数,分析了隧道直径D、基础埋深d以及地层损失率V_L等对建筑物风险区大小的影响规律,推导得到了风险区的边界值(C/D)₀和(x/D)₀。最后,根据不同风险控制等级,提出了隧道开挖对邻近建筑物风险的初步评估方法,并将风险区划分为4个部分。研究结果表明:所提风险区划分方法仅需隧道直径D、地层损失率值V_L、隧道埋深Z以及沉降槽宽度系数i即可实现,具有简单、高效等特点,且能够反映不同参数对风险区变化的影响。研究结果可为隧道开挖对邻近建筑物安全影响初步判断和风险预估提供参考。     

台州市安溶泾河道底泥重金属污染特征及生态风险评价

为顺利开展城市河道污染整治工程,有效控制河道底泥引发的二次污染,研究河道底泥污染特征并分析其生态风险具有重要意义。基于台州安溶泾河道底泥检测结果,采用单项污染指数法、潜在生态风险指数法、聚类分析法等多种方法对底泥重金属含量、污染状况、空间分布、生态风险等进行评价。结果表明:底泥中Cu、Zn、Pb、Cd这4种重金属污染严重;从流域上看,主要污染区域为安溶泾上游段、2条支流段和支流与干流交汇处;从河道纵剖面上看,随着底泥深度的增加,超标重金属浓度普遍降低;Cu和Cd的潜在生态危害较严重,且在安溶泾上游段源头、2条支流及支流与干流交汇处底泥Cd和Cu的受污染程度最为严重。研究成果可为城市河道底泥重金属污染的预防和综合整治提供依据。     

基于极限学习机的堤防工程多元风险指标评价方法

为提高堤防工程风险评价的准确性,提出了基于极限学习机的堤防工程多元风险指标评价方法。首先,综合考虑影响堤防风险的28个评价指标,利用层次分析法从预警系统、堤防工程系统、环境系统和社会经济系统这4个方面建立了堤防工程多元风险评价指标体系。接着,基于极限学习机算法对28个指标进行标准化处理及分级标准构建,以风险指标作为输入量,分级隶属度作为输出量,划分风险等级,量化评价指标,估计多元风险评价指标值和判断风险的严重程度。最后,依托鄱阳湖重点堤防——康山大堤,构建多元风险评价指标体系,运用极限学习机算法计算多元风险评价指标值。评价结果表明:康山大堤目前处于基本安全水平,符合康山大堤经过两次加固后的工程实际情况,并与其他方法进行对比,验证了提出方法的可靠性和有效性。该方法可拓展应用到其他重要水工结构工程风险评估中。     

220kV线路工程滑坡地质灾害危险性分析

文章介绍了喜德县红莫升压站-鲁基升压站220kV线路工程滑坡地质灾害危险性现状评估和预测评估,确定了评估区内滑坡地质灾害对工程的影响,以及工程建设加剧已有滑坡地质灾害的危险性和自身可能遭受已存在滑坡地质灾害的危险性。据此评估结果,为工程在建设过程中提出了具体的防治处理措施建议。     

电力工程中的地质灾害危险性评估

我国幅员辽阔,地质环境条件多样且复杂,导致了地质灾害发育强烈,种类繁多、危害较大。地质灾害与工程建设活动密切相关,既相互作用,相互依存,又相互影响[1]。电力工程项目遍布全国,特别是输电线路大多为人烟稀少的山区分布,线路长,跨越的地质地貌区域复杂,存在的地质灾害多种多样,或多或少面临着各种地质灾害的严重威胁[2]。通过电力工程地质灾害危险性评估工作的现状及评估工作流程的介绍,进一步分析电力工程地质灾害的危险性评估工作中存在的问题并提出了相应的看法。     

湿陷性黄土地区海绵城市建设湿陷性风险模拟评估研究

在湿陷性黄土地区开展雨水集中下渗的海绵城市建设面临着湿陷变形的风险,以黄土湿陷性较为严重的西咸新区空港新城临空产业区为例,采用数值模拟的方法模拟了研究区湿陷性黄土在不同设计降雨情况下的雨水集中入渗后的湿陷情况。应用GAST模型计算雨洪过程,并将降雨量下渗过程作为边界条件输入Midas GTS/NX软件来模拟黄土基础变形情况。通过分析5个典型黄土区因降雨下渗导致的湿陷量,发现其等级为Ⅱ级及以上,其中最严重情况下的雨水下渗深度为5.02~6.51 m,总湿陷量和自重湿陷量分别为468.18~1015.56 mm和88.99~239.03 mm,湿陷等级为Ⅲ级。可见局部集中下渗会导致较高的湿陷风险,故建议在湿陷性黄土地区海绵城市建设中应进行量化评估并合理规避湿陷风险。     

Forest harvesting in rural properties: Risks and worsening to the worker’s health under the ergonomics approach

Through an ergonomic approach, this study aimed to evaluate whether workers involved in forest harvesting activities in rural properties are subject to the development of work-related diseases, as well as their consequences. A cross-sectional study with 267 forest workers in rural properties in the Brazilian Central region was used. The following evaluations were performed for each of the activities (felling, delimbing, tracing, manual extraction and manual loading): physical workload evaluation; biomechanical evaluation; risk of repetitive strain injuries/work-related musculoskeletal disorders; environmental noise and vibration factors, where relevant, and thermal overload through the Wetbulb Globe Temperature index. The results showed that in general the physical workload was very high, exceeding the cardiovascular load limits and adding to the need for work reorganization. All activities exposed workers to serious and imminent risks of developing injuries to the spine and lower limbs. Likewise, in general the risk of the appearance of RSI/WMSDs was very high for all activities evaluated. Such results are due to the combination of organizational work factors and factors of the work environment such as exposure to bad weather, uneven terrain, lifting and handling loads above tolerable limits, excessive noise and thermal overload. All of this allows to conclude that ergonomic risks and workers’ health hazards in forest harvesting in rural properties are latent and very worrying, and that these workers are exposed to a form of labor exploitation that invariably leads to physical and emotional exhaustion and therefore to their decreased labor capacity and useful working life.     

The impact of risk and protective factors on online teaching experience in high school Italian teachers during the COVID-19 pandemic

The lockdown due to COVID-19 in Italy resulted in the sudden closure of schools, with a shift from traditional teaching to the online one. Through an online questionnaire, this survey explores teachers' experience of online teaching, the level of risk factors (e.g., stress) and protective factors (e.g., locus of control) and their impact on satisfaction levels during the social distancing. One hundred seven high school teachers from Lombardy, an Italian region very affected by the COVID-19 outbreak, participated. Results show that depression and stress are the main predictors of satisfaction levels for online teaching. In addition, coping, locus of control and self-efficacy emerge as important protective factors. Finally, although there is great satisfaction with the online teaching experience, critical elements emerged. This study is relevant because it describes the critical elements of the online teaching experience, and identifies some protective factors and the main risk factors in teachers operating in an area strongly marked by social restrictions imposed by the pandemic. High school teachers emerge as a sub-group of the general population with specific psychological reactions. Considering the results, it is possible to suggest providing high-quality educational support and crisis-psychological oriented services to teachers, and help to maintain the psychological well-being.     

A Data Security Framework for Cloud Computing Services

Cyberattacks are difficult to prevent because the targeted companies and organizations are often relying on new and fundamentally insecure cloud-based technologies, such as the Internet of Things. With increasing industry adoption and migration of traditional computing services to the cloud, one of the main challenges in cybersecurity is to provide mechanisms to secure these technologies. This work proposes a Data Security Framework for cloud computing services (CCS) that evaluates and improves CCS data security from a software engineering perspective by evaluating the levels of security within the cloud computing paradigm using engineering methods and techniques applied to CCS. This framework is developed by means of a methodology based on a heuristic theory that incorporates knowledge generated by existing works as well as the experience of their implementation. The paper presents the design details of the framework, which consists of three stages: identification of data security requirements, management of data security risks and evaluation of data security performance in CCS.