Evaluation of Infection Prevention and Control Programmes (IPC), and Assessment Tools for IPC-Programmes at MOH-Health Facilities in Saudi Arabia

Infection Prevention and Control is a Quality Standard and is crucial in all health care facilities. Many hospitals remain deficient in trained infection control professionals (ICPs), and now there is an acute awareness of the need to correct this shortfall. The objectives of the study were to describe the current status of ICP programs at ministry of health (MOH) and to evaluate the current status of infection prevention and control programs at health care facilities in kingdom of Saudi Arabia. A cross sectional interview and a self assessment study were conducted on infection prevention and control (IPC) program in Saudi Arabia. All the MOH hospital in all regions was randomly chosen to the study setting. The selection of facilities was done at random with a clear intention to include twenty regions. A random sample was taken from these hospitals with sample size 56 (55.4%), by Multi stage random sampling technique. Results showed that the total facility in all over the kingdom was 51.4% where central area covered the facility score 58.2%, followed by western area (54.8%), south (53.7%), east (46.3%), and lastly with (45.8%) north area. Survey revealed that the infrastructure for infection control program in Saudi Arabian hospitals remained underdeveloped. There were defects in the identified components of effective infection control programs.

Environmental Impact Assessment of Selected Oil Production Facilities in Parts of Niger Delta, Nigeria

The impact of oil production activities on the chemistry of soil and groundwater was investigated around seven production facilities, ranging from flow stations to wellhead in the western Niger Delta area. The method involved systematic sampling of soil and groundwater within a one kilometre radius of such facilities. The samples obtained were analysed for pH, TOC, TPH, V, Ni and Fe by standard procedures. The results indicate a general conformity of groundwater physico-chemistry to international standards for chemical potability. However, the investigated soil samples reveal in some cases elevated values of TPH (mean: 26.07 mg/kg) and Ni (mean: 8.89 mg/kg) which suggest a negative impact on the soil in the vicinity of such oil production facilities. Although ground-water may show no apparent contamination, pollutants trapped in the soil are in potential transit to groundwater, and may eventually be dissolved and transported through the soil profile to the water table by recharging rainwater. The environmental and health conditions of host communities are thereby endangered.

Comparative study of different machine learning models in landslide susceptibility assessment: A case study of Conghua District, Guangzhou, China

Machine learning is currently one of the research hotspots in the field of landslide prediction.To clarify and evaluate the differences in characteristics and prediction effects of different machine learning models,Conghua District,which is the most prone to landslide disasters in Guangzhou,was selected for landslide susceptibility evaluation.The evaluation factors were selected by using correlation analysis and variance expansion factor method.Applying four machine learning methods namely Logistic Regression(LR),Random Forest(RF),Support Vector Machines(SVM),and Extreme Gradient Boosting(XGB),landslide models were constructed.Comparative analysis and evaluation of the model were conducted through statistical indices and receiver operating characteristic(ROC)curves.The results showed that LR,RF,SVM,and XGB models have good predictive performance for landslide susceptibility,with the area under curve(AUC)values of 0.752,0.965,0.996,and 0.998,respectively.XGB model had the highest predictive ability,followed by RF model,SVM model,and LR model.The frequency ratio(FR)accuracy of LR,RF,SVM,and XGB models was 0.775,0.842,0.759,and 0.822,respectively.RF and XGB models were superior to LR and SVM models,indicating that the integrated algorithm has better predictive ability than a single classification algorithm in regional landslide classification problems.

Debris Flow Hazard Assessment Based on Support Vector Machine

Seven factors, including the maximum volume of once flow , occurrence frequency of debris flow , watershed area , main channel length , watershed relative height difference , valley incision density and the length ratio of sediment supplement are chosen as evaluation factors of debris flow hazard degree. Using support vector machine （SVM） theory, we selected 259 basic data of 37 debris flow channels in Yunnan Province as learning samples in this study. We create a debris flow hazard assessment model based on SVM. The model was validated though instance applications and showed encouraging results.

Damage assessment of the target area of the island/reef under the attack of missile warhead

Under the background of vigorously developing facilities of island/reef in the world,the economic value and strategic significance of the island/reef have become increasingly important.Unfortunately,they may easily become the attacking target of missiles in the war time.Therefore,aiming at the damage quantification of the targets in the island/reef under the missile attacking,a macroscopic damage assessment model for the target area is proposed in this paper.The model focuses on the construction of the assessment model framework.Firstly,the analytic hierarchy process and the grey relational analysis are applied to measure the importance of each target in the region through four indicators of the target hazard,striking urgency,damage advantage and mission relevance,respectively.Secondly,based on the damage mechanism of shock wave and fragments to target,the corresponding damage model is established,and the damage grade of each target in the evaluated area is obtained according to the damage criteria and grading standard.Finally,the model obtains the overall damage grade of the target area by employing the fuzzy comprehensive evaluation method,with synthesizing the importance and the damage grade of each target.Through the verification of an example,it demonstrates the certain feasibility of the model and provides a certain basis and reference for the subsequent research.

Condition assessment of structures under unknown support excitation

A new method is proposed to assess the condition of structures under unknown support excitation by simultaneously detecting local damage and identifying the support excitation from several structural dynamic responses. The support excitation acting on a structure is modeled by orthogonal polynomial approximations, and the sensitivities of structural dynamic response with respect to its physical parameters and orthogonal coefficients are derived. The identification equation is based on Taylor＇s first order approximation, and is solved with the damped least-squares method in an iterative procedure. A fifteen-story shear building model and a five-story three-dimensional steel frame structure are studied to validate the proposed method. Numerical simulations with noisy measured accelerations show that the proposed method can accurately detect local damage and identify unknown support excitation from only several responses of the structure. This method provides a new approach for detecting structural damage and updating models with unknown input and incomplete measured output information.

Stability assessment of rock surrounding an I-beam supported retreating roadway

The installation of a back-wall guard-board is the key to successfully supporting underground retreating roadways in coal mines. Based on the coordinate support principle, and using an I-shaped steel support for the surrounding rock, a mechanical model was developed for the stability of the roadway support and surrounding rock. Analysis of the bearing capacity of the roof back-wall guard-board and modelling of the equations for the maximum deflection and the maximum compressive stress of the top and side beams of the I-shaped steel support were undertaken. Simultaneously, the model was used to calculate and analyse the stability of the top and side beams of the I-shaped steel support structure and analyse the criteria for their stability. The results provide a reliable theoretical basis for the judgment of the stability of the surrounding rock and support structure. The theoretical evaluation results are consistent with field data. Finally, the key support parameters of the top and side beams of the I-shaped steel support structure and the variation of the maximum deflection and the maximum compressive stress as affected by the influence of the guard-board length were investigated. It is concluded that, as the back-board length increases, the maximum compressive stress in the top beam of the I-shaped steel support increases while the compressive stress in the side beam decreases. The results show that the accuracy of judgment of the stability of a supported retreating roadway is improved, providing guidance for the design of such typical I-shaped steel support and back-board structures.

Failure Assessment of Aero-engine Support Structure due to Blade-off

Aero-engine blade-off event could cause serious malfunction and endanger flight safety,which is an important issue widely concerned for a long period.This paper presents a comprehensive review on the regulation requirements,the major research methods and status at home and abroad.Firstly,the relevant certification regulations and standards about aero-engine structure safety due to blade-off event were overviewed and the research gaps between the abroad and the domestic were compared.Then,the simulation and experimental methodologies on aero-engine supporting structures undertake abnormal load due to blade-off event were discussed as major issue.Finally,the safety certification verification technology system for aero-engine support structures during blade-off event was proposed.

A new technique for rapid assessment of eutrophication status of coastal waters using a support vector machine

There is an urgent need to develop efficient evaluation tools that use easily measured variables to make rapid and timely eutrophication assessments, which are important for marine health management, and to implement eutrophication monitoring programs. In this study, an approach for rapidly assessing the eutrophication status of coastal waters with three easily measured parameters （turbidity, chlorophyll a and dissolved oxygen） was developed by the grid search （GS） optimized support vector machine （SVM）, with trophic index TRIX classification results as the reference. With the optimized penalty parameter C=64 and the kernel parameter y=l, the classification accuracy rates reached 89.3% for the training data, 88.3% for the cross-validation, and 88.5% for the validation dataset. Because the developed approach only used three easy-to-measure variables, its application could facilitate the rapid assessment of the eutrophication status of coastal waters, resulting in potential cost savings in marine monitoring programs and assisting in the provision of timely advice for marine management.

Comparison of LR,5-CV SVM,GA SVM,and PSO SVM for landslide susceptibility assessment in Tibetan Plateau area,China

The applicability of statistics-based landslide susceptibility assessment methods is affected by the number of historical landslides.Previous studies have proposed support vector machine(SVM)as a small-sample learning method.However,those studies demonstrated that different parameters can affect model performance.We optimized the SVM and obtained models as 5-fold cross validation(5-CV)SVM,genetic algorithm(GA)SVM,and particle swarm optimization(PSO)SVM.This study compared the prediction performances of logistic regression(LR),5-CV SVM,GA SVM,and PSO SVM on landslide susceptibility mapping,to explore the spatial distribution of landslide susceptibility in the study area in Tibetan Plateau,China.A geospatial database was established based on 392 historical landslides and 392 non-landslides in the study area.We used 11 influencing factors of altitude,slope,aspect,curvature,lithology,normalized difference vegetation index(NDVI),distance to road,distance to river,distance to fault,peak ground acceleration(PGA),and rainfall to construct an influencing factor evaluation system.To evaluate the models,four susceptibility maps were compared via receiver operating characteristics(ROC)curve and the results showed that prediction rates for the models are 84%(LR),87%(5-CV SVM),85%(GA SVM),and 90%(PSO SVM).We also used precision,recall,F1-score and accuracy to assess the quality performance of these models.The results showed that the PSO SVM had greater potential for future implementation in the Tibetan Plateau area because of its superior performance in the landslide susceptibility assessment.

Landslide susceptibility assessment in Western Henan Province based on a comparison of conventional and ensemble machine learning

Landslide is a serious natural disaster next only to earthquake and flood,which will cause a great threat to people’s lives and property safety.The traditional research of landslide disaster based on experience-driven or statistical model and its assessment results are subjective,difficult to quantify,and no pertinence.As a new research method for landslide susceptibility assessment,machine learning can greatly improve the landslide susceptibility model’s accuracy by constructing statistical models.Taking Western Henan for example,the study selected 16 landslide influencing factors such as topography,geological environment,hydrological conditions,and human activities,and 11 landslide factors with the most significant influence on the landslide were selected by the recursive feature elimination(RFE)method.Five machine learning methods[Support Vector Machines(SVM),Logistic Regression(LR),Random Forest(RF),Extreme Gradient Boosting(XGBoost),and Linear Discriminant Analysis(LDA)]were used to construct the spatial distribution model of landslide susceptibility.The models were evaluated by the receiver operating characteristic curve and statistical index.After analysis and comparison,the XGBoost model(AUC 0.8759)performed the best and was suitable for dealing with regression problems.The model had a high adaptability to landslide data.According to the landslide susceptibility map of the five models,the overall distribution can be observed.The extremely high and high susceptibility areas are distributed in the Funiu Mountain range in the southwest,the Xiaoshan Mountain range in the west,and the Yellow River Basin in the north.These areas have large terrain fluctuations,complicated geological structural environments and frequent human engineering activities.The extremely high and highly prone areas were 12043.3 km^(2)and 3087.45 km^(2),accounting for 47.61%and 12.20%of the total area of the study area,respectively.Our study reflects the distribution of landslide susceptibility in western Henan Province,which provides a scientific basis for regional disaster warning,prediction,and resource protection.The study has important practical significance for subsequent landslide disaster management.

Pedestrian choice behavior analysis and simulation of vertical walking facilities in transfer station

Considering the interlayer height, luggage, the difference between queuing pedestrians, and walking speed, the pedestrian choice model of vertical walking facilities is established based on a support vector machine. This model is verified with the pedestrian flow data of Changchun light-rail transfer station and Beijing Xizhimen transfer station. Adding the pedestrian choice model of vertical walking facilities into the pedestrian simulation model which is based on cellular automata, the pedestrian choice behavior is simulated. In the simulation, the effects of the dynamic influence factors are analyzed. To reduce the conflicts between pedestrians in opposite directions, the layout of vertical walking facilities is improved. The simulations indicate that the improved layout of vertical walking facilities can improve the efficiency of pedestrians passing.

An Assessment Tool for Land Reuse with Artificial Intelligence Method

This paper focuses on land resource consumption due to urban sprawl. Special attention is given to shrinking regions, characterized by economic decline, demographic change, and high unemployment rates. In these regions, vast terrain is abandoned and falls derelict. A geographic information system （GIS） based multi-criteria decision tool is introduced to determine the reuse potential of derelict terrain, to investigate the possible reuse options （housing, business and trade, industry, services, tourism and leisure, and re-greening）, and to visualize the best reuse options for groups of sites on a regional scale. Achievement functions for attribute data are presented to assess the best reuse options based on a multi-attribute technique. The assessment tool developed is applied to a model region in Germany. The application of the assessment tool enables communities to become aware of their resources of derelict land and their reuse potential.

Indoor Dust-Based Pollution Status and Risk Assessment for a Rural Town, Ebedei in Nigeria Hosting Gas Flare Facility

Recently, there has been series of petitions and protestations from petroleum production gas flare facility host communities in Nigeria about the degradation of their environment. This study was designed to conduct indoor dust related human health risk assessment for Cd, Pb, Mn and Ni. Deposited indoor dust samples were collected from sixteen (16) residential buildings distributed across the four quarters of Ebedei waterside town in Nigeria, within the vicinity of a petroleum production gas flare facility. The samples were digested and analysed for Cd, Pb, Mn and Ni concentrations using inductively coupled plasma mass spectrometry (ICP-MS). Contamination/pollution index (C/PI) and human health risk assessments were conducted. The concentration ranges of 1.2 - 14.9 mg/kg, 44.0 - 161.6 mg/kg and 221.3 - 752.0 mg/kg, and below detection to 29.8 mg/kg were recorded for Cd, Pb, Mn and Ni, respectively. C/PI analyses for metals in the indoor dusts investigated suggested Cd levels to be polluted and Pb levels to be slightly polluted, while Mn and Ni levels indicated contamination. Risk assessment studies indicated that children may be more at risk for all the three exposure pathways. Exposure through the ingestion pathway indicated the highest risk for both the adult and children population.

Clinical Preceptor’s Role in the Development of Nursing Training Based on Professional and Competency Frameworks in Two Health Care Facilities of Bujumbura

Background: The aim of clinical preceptors is to support the development of expertise related to the preceptorship of groups of trainees among nurses in clinical settings by the acquisition and use of theoretical knowledge, know-how and know-that. The support of students remains a major problem in hospitals, because the requirements of the preceptors according to the standards are not considered. The lack of guidelines on nursing preceptorships, theoretical application based on the professional curriculum, and professional expertise were the main problems assessed in the two Health Care (HUCK, VNC) in this study. The purpose of this study is to assess the knowledge of nurses and learners during their preceptorship practices and to contribute to the direction of evidence-based preceptorship. Method: A descriptive cross-sectional study design was used in this study during the 3-month period. A sample of 121 nurses as well as 56 learners were selected from 381 nurses and 80 learners using Alain Bouchard’s formula. A questionnaire developed according to the guidelines of Ernestine Wiedenbach’s theory of care, was distributed. The data were analyzed using the Microsoft Excel and the software program version 16 (SPSS-16). Results: The current study found that the majority of nurses do not know the importance of the clinical tutor. The results state that students experience clinical practice problems, thus clinical preceptorship is required. Nurses showed that there are different barriers often encountered during their practices. The overall nurse preceptorship process is not optimal and the average of 97.6% of nurses does not have expertise in coaching interns in clinical settings. Conclusion: Although that nurses have some experience at work, they express their weakness based on a low level of education, a lack of knowledge and trained professionals on the job, and clinical preceptorship guidelines.

Current Situation and Development Proposals of Agricultural Facilities(Planting)Application in Beijing

Facility agriculture is an essential carrier for promoting stable production and supply.In2020,the planting area of facility agriculture in Beijing(290098000 m2)accounted for 29.06%of the total planting area of crops(998078000 m2),and the output value accounted for 46.56%.In2022,Beijing Agricultural Technology Extension Station organized relevant departments to summarize and evaluate the agricultural facilities in Beijing through consultation materials,interviews,questionnaires,and field trips,combining survey data and statistical data to draw the following conclusions.Facilities play a major supporting role in stabilizing production and ensuring supply.The number of traditional greenhouses is extensive and covers a large area,so special planning and classification upgrades are urgently needed.Facilities are rich in scientific and technological resources,but the mode of production is out of date.It is of great significance to improve the comprehensive production capacity of facility agriculture and promote the healthy and stable development of facility industry in Beijing to increase the utilization rate of facility agriculture land,strengthen the support of facility science and technology,and cultivate the socialized service organization of facility.

Assessment methods and services for older people with cancer in the United Kingdom

BACKGROUND National cancer strategy calls for comprehensive assessments for older people but current practice across the United Kingdom is not well described.AIM To identify current assessment methods and access to relevant supporting services for older people with cancer.METHODS A web-based survey(SurveyMonkey)targeting health professionals(oncologists,cancer surgeons,geriatricians,nurses and allied health professionals)was distributed January-April 2016 via United Kingdom nationally recognised professional societies.Responses were analysed in frequencies and percentages.Chi Square was used to compare differences in responses between different groups.RESULTS 640 health care professionals responded.Only 14.1%often/always involved geriatricians and 52.0%often/always involved general practitioners in assessments.When wider assessments were used,they always/often influenced decision-making(40.5%)or at least sometimes(34.1%).But 30.5%-44.3%did not use structured assessment methods.Most clinicians favoured clinical history taking.Few used scoring tools and few wished to use them in the future.Most had urgent access to palliative care but only a minority had urgent access to other key supporting professionals(e.g.geriatricians,social workers,psychiatry).69.6%were interested in developing Geriatric Oncology services with geriatricians.CONCLUSION There is variability in assessment methods for older people with cancer across the United Kingdom and variation in perceived access to supporting services.Clinical history taking was preferred to scoring systems.Fostering closer links with geriatricians appears supported.

Characteristics and Risk Assessment of Soil Heavy Metal Contents in Facility Agriculture of Guangxi

[Objectives]To study the characteristics of soil heavy metal contents in facility agriculture of Guangxi and analyze its risks.[Methods]The heavy metal content of 30 surface soil samples taken from facility agriculture in Guangxi was analyzed.The status of soil heavy metal pollution in facility agriculture of Guangxi was evaluated by the single factor index method,geo-accumulation index method and Hakanson potential ecological risk index method with reference to the soil background value in Guangxi.[Results]Compared with the soil background value in Guangxi,the over-limit rates of heavy metals cadmium,lead,arsenic,chromium,mercury,copper and zinc in soil samples were 56.67%,56.67%,16.67%,30.00%,50.00%,60.00%and 80.00%,respectively.Compared with the screening values of the Soil Environmental Quality-Risk Control Standard for Soil Contamination of Agricultural Land(for trial implementation)(GB15618-2018),the overlimit rates of the heavy metals cadmium,arsenic,copper and zinc in the surface soil of agricultural facilities in Guangxi were 56.67%,10.00%,16.67%and 23.33%,respectively.Except for the average content of soil cadmium exceeding the screening value,the evaluation content of the other six soil heavy metals did not exceed the screening value.According to the evaluation results of the single factor pollution index method,the surface soil arsenic and chromium of the agricultural facilities in Guangxi belonged to the clean level,lead,mercury,and copper belonged to mild pollution,and cadmium and zinc belonged to moderate pollution.According to the evaluation results of the geo-accumulation index,the lead,arsenic,chromium and mercury in the surface soil of the agricultural facilities in Guangxi belonged to the pollution-free level,while the cadmium,copper and zinc belonged to the mild-moderate pollution.According to the evaluation results of the potential ecological risk index method,the potential ecological risks of the heavy metals of lead,arsenic,chromium,copper and zinc in the soil of agricultural facilities in Guangxi belonged to low potential ecological risk level,and the potential ecological risks of cadmium and mercury belonged to moderate risk level.The potential ecological risk index(RI)of the seven heavy metals in the soil was 132.46,which belonged to moderate potential ecological risk.The largest contribution of soil heavy metals to the potential ecological risk index was cadmium and mercury.[Conclusions]Taking the soil of facility agriculture in Guangxi as the object,this paper studied the characteristics of heavy metal content in facility agricultural soil and its risk assessment,in order to provide a scientific basis for facility soil heavy metal risk prevention and control and provide safe technology for facility agriculture.

新能源场站快速频率支撑能力评估研究现状与技术展望

随着以风电、光伏为代表的新能源发电逐步取代同步机组,系统调频资源不足、抗扰动能力下降,频率安全问题凸显,新能源场站提供快速频率支撑成为构建新型电力系统的必然要求。新能源场站快速频率支撑是其内部多设备、多环节综合作用的结果,受风光资源、控制策略、电网条件等多因素的影响和制约。量化评估新能源场站的快速频率支撑能力是指导场站调频优化控制、分析新型电力系统频率响应特性、实现场站调频资源与电网交互的基础和前提。文中对新能源场站快速频率支撑能力评估问题进行了全面综述。首先,分析场站快速频率支撑的特征,并给出了场站快速频率支撑能力的定义;然后,从状态属性、控制特性、调频效果3个维度梳理了场站快速频率支撑能力的评估指标体系,并对各类评估指标的常用计算方法进行分析评述;最后,提出了值得关注和进一步研究的关键技术问题。