Mapping Climate Services for Disaster Risk Management: A Systematic Review and Research Gaps from a Policy Process Perspective

Climate services (CS) are crucial for mitigating and managing the impacts and risks associated with climate-induced disasters. While evidence over the past decade underscores their effectiveness across various domains, particularly agriculture, to maximize their potential, it is crucial to identify emerging priority areas and existing research gaps for future research agendas. As a contribution to this effort, this paper employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to review the state-of-the-art in the field of climate services for disaster risk management. A comprehensive search across five literature databases combined with a snowball search method using ResearchRabbit was conducted and yielded 242 peer-reviewed articles, book sections, and reports over 2013-2023 after the screening process. The analysis revealed flood, drought, and food insecurity as major climate-related disasters addressed in the reviewed literature. Major climate services addressed included early warning systems, (sub)seasonal forecasts and impact-based warnings. Grounded in the policy processes’ theoretical perspective, the main focus identified and discussed three prevailing policy-oriented priority areas: 1) development of climate services, 2) use-adoption-uptake, and 3) evaluation of climate services. In response to the limitations of the prevalent supply-driven and top-down approach to climate services promotion, co-production emerges as a cross-cutting critical aspect of the identified priority areas. Despite the extensive research in the field, more attention is needed, particularly pronounced in the science-policy interface perspective, which in practice bridges scientific knowledge and policy decisions for effective policy processes. This perspective offers a valuable analytical lens as an entry point for further investigation. Hence, future research agendas would generate insightful evidence by scrutinizing this critical aspect given its importance to institutions and climate services capacity, to better understand intricate facets of the development and the integration of climate services into disaster risk management.

Analytic Hierarchy Process for Technological Risks in the Process of Innovative Drug Development in China

Objective To identify the critical risks in the process of innovative drug research and development,and to provide reference for improving the efficiency of innovative drug development and risk control in China.Methods Expert investigation and analytic hierarchy process were used to determine the weights of different risks.Results and Conclusion The research and analysis results showed that the risks at different stages of development had different effects on the success rate of drug development,among which the risk at the drug discovery stage influenced the most.In the drug discovery stage,inappropriate target selection had the greatest impact on the success rate of drug development.The lack of appropriate cell tissue or animal models had the greatest impact on the success rate of drug development from the discovery of a compound to the application for clinical trials.The difference in changes between nonclinical and clinical studies had the greatest impact on the success rate of drug development from early clinical studies to pivotal clinical studies.Incorrect dose selection had the greatest impact on the success rate of drug development from pivotal clinical studies to marketing authorization applications.The biggest impact from the marketing authorization application to the approval stage was inadequate communication with regulators.After investigating the weight of risk factors in the process of innovative drug development based on scientific methods,a new perspective for the risk control of new drug development and improving the research and development efficiency is provided.

An Edge-Fog-Cloud Computing-Based Digital Twin Model for Prognostics Health Management of Process Manufacturing Systems

The prognostics health management(PHM)fromthe systematic viewis critical to the healthy continuous operation of processmanufacturing systems(PMS),with different kinds of dynamic interference events.This paper proposes a three leveled digital twinmodel for the systematic PHMof PMSs.The unit-leveled digital twinmodel of each basic device unit of PMSs is constructed based on edge computing,which can provide real-time monitoring and analysis of the device status.The station-leveled digital twin models in the PMSs are designed to optimize and control the process parameters,which are deployed for the manufacturing execution on the fog server.The shop-leveled digital twin maintenancemodel is designed for production planning,which gives production instructions fromthe private industrial cloud server.To cope with the dynamic disturbances of a PMS,a big data-driven framework is proposed to control the three-level digital twin models,which contains indicator prediction,influence evaluation,and decisionmaking.Finally,a case study with a real chemical fiber system is introduced to illustrate the effectiveness of the digital twin model with edge-fog-cloud computing for the systematic PHM of PMSs.The result demonstrates that the three-leveled digital twin model for the systematic PHM in PMSs works well in the system’s respects.

Physicochemical Properties and Health Risks of Informal E-Waste Processing at Alaba International Market in Lagos, Nigeria

This study investigated the groundwater quality and health risks associated with informal e-waste processing in the Alaba International Market in Lagos, Nigeria. Twenty-two groundwater samples were collected from hand-dug wells in the market area and analyzed for physicochemical properties and heavy metal concentrations. The results showed that the groundwater quality was poor, with high levels of heavy metals, including cadmium, lead, and chromium. The health index (HI) for children and adults was above the tolerable threshold levels, indicating a potential health risk to the population. Principal component analysis and hierarchical cluster analysis were used to identify the sources of metals in groundwater, and the results showed that informal e-waste processing was a significant source of contamination. The study highlights the need for effective management strategies to mitigate the potential health risks associated with informal e-waste processing and ensure public health and environmental safety.

Risk Management of Clinical Reference Dosimetry of a Large Hospital Network Using Statistical Process Control

Managing TG-51 reference dosimetry in a large hospital network can be a challenging task. The objectives of this study are to investigate the effectiveness of using Statistical Process Control (SPC) to manage TG-51 workflow in such a network. All the sites in the network performed the annual reference dosimetry in water according to TG-51. These data were used to cross-calibrate the same ion chambers in plastic phantoms for monthly QA output measurements. An energy-specific dimensionless beam quality cross-calibration factor, , was derived to monitor the process across multiple sites. The SPC analysis was then performed to obtain the mean, , standard deviation, σk, the Upper Control Limit (UCL) and Lower Control Limit (LCL) in each beam. This process was first applied to 15 years of historical data at the main campus to assess the effectiveness of the process. A two-year prospective study including all 30 linear accelerators spread over the main campus and seven satellites in the network followed. The ranges of the control limits (±3σ) were found to be in the range of 1.7% - 2.6% and 3.3% - 4.2% for the main campus and the satellite sites respectively. The wider range in the satellite sites was attributed to variations in the workflow. Standardization of workflow was also found to be effective in narrowing the control limits. The SPC is effective in identifying variations in the workflow and was shown to be an effective tool in managing large network reference dosimetry.

Managing Health Risks during the Balkans Floods

Floods have always had and will continue to have significant consequences for society. In May 2014, there was widespread flooding in the Balkans affecting Bosnia and Herzegovina, Croatia and Serbia. The aim of this article is to show that resilient and proactive health systems that anticipate needs and challenges are more likely to reduce risks and respond effectively during emergencies, saving lives and alleviating human suffering. The method draws on multiple sources of information, including a Balkan case study questionnaire survey with public health professionals involved in response to floods (n = 18) from three affected countries, and focus group discussion results (n = 43) presented at the meeting on “Prevention, preparedness and response to reduce or avoid health effects of flood events”, held in Bonn, Germany, in October 2015. The proposed range of measures to protect population health, organized around flood prevention, preparedness, response and recovery listed issues and considerations largely corresponds to the identified needs by Member State requests, following the Balkan country experiences. The consideration of lessons for early warning, preparedness and response and the integration of research results would lead to improved preparedness measures to better prevent flooding risks. Experiences in the WHO European Region point to a need to shift the emphasis from disaster response to long-term risk management.

Business Process Analysis and Simulation: The Contact Center of a Public Health and Social Information Office

This article proposes a framework, called BP-M* which includes: 1) a methodology to analyze, engineer, restructure and implement business processes, and 2) a process model that extends the process diagram with the specification of resources that execute the process activities, allocation policies, schedules, times of activities, management of queues in input to the activities and workloads so that the same model can be simulated by a discrete event simulator. The BP-M* framework has been applied to a real case study, a public Contact Center which provides different typologies of answers to users’ requests. The simulation allows to study different system operating scenarios (“What-If” analysis) providing useful information for analysts to evaluate restructuring actions.

Overview of the Importance of Intelligent Approaches on Machinery Faults Diagnosis and Prediction Based on Prognostic and Health Management/Condition-Based Maintenance

Condition monitoring is increasingly used to anticipate and detect failures of industrial machines.Failures of machines can cause high maintenance or replacement costs.If neglected,it may result in catastrophic accidents leading to production shrinkage.The potential failure would negatively affect the profitability of the company,including production shut down,cost of spare parts,cost of labor,damage of reputation,risk of injury to people and the environment.In recent years,condition-based maintenance( CBM) and prognostic and health management( PHM) are developed and formed a strong connection among science,engineering,computer,reliability,communication,management,etc.Computerized maintenance management systems( CMMS) store a lot of data regarding the fault diagnosis and life prediction of the machinery equipment.It's too necessary to uncover useful knowledge from the huge amount of data.It's vital to find the ways to obtain useful and concise information from these data.This information can be of great influence in the decision making of managers.This article is a review of intelligent approaches in machinery faults diagnosis and prediction based on PHM and CBM.

Implications of the Reanalysis and Weight of Evidence Determination of Human Health Studies for Exposure to Perchlorates under Cumulative and Aggregate Risk Assessment

This paper applies cumulative and aggregate risk methods and weight of evidence determination to re-analysis of epidemiological and clinical studies of exposure to perchlorates. The implications of cumulative and aggregate risk are considered for 28 epidemiological studies on IUI, serum thyroid hormone levels and clinical indicators. Consideration is given to simultaneous exposures to perchlorates, nitrates, thiocyanates and organohalogens in the study populations. The elevation of effects by perchlorates alone is found only in the studies that use urinary perchlorate as the metric of exposure. These studies are beset by a problem with use of urinary perchlorate concentration in that there is large inter-subject variability in the relationship between intake and urinary concentration due to differences in metabolism and disposition of the compounds following ingestion. As a result, an individual placed into the “high urinary concentration” group may be there due to high values of exposure, to long biological clearance halflives, or due to high transfer fractions from the serum into the urine. The influence could be removed by correcting urinary levels by measured clearance half-times for individuals in a study, but that has not been done in the case of the studies examined here. It is of interest therefore that the studies that use direct measures of intake of perchlorates rather than urine concentration fail to display the hormone effects. The current study uses a “weight of evidence” approach for perchlorates, employing all 28 studies. The result is a slope of the exposure response curve (percentage change in hormone effect per unit exposure) of 0.3% per μg/kg-day, with 95% confidence interval of (?0.05%, 1%). This confidence interval for the slope encompasses 0, indicating no statistically significant slope when all data are combined in a weight of evidence determination. This is consistent with the conclusions of the USEPA and EFSA that the epidemiological studies do not provide compelling evidence for a causal association between exposures to perchlorates and either hormone effects or clinically adverse effects. The conclusions are 1) that current epidemiological results do not provide evidence of effects induced by perchlorates apart from the IUI effects, 2) that the same results provide evidence that the IUI effects induced at environmental levels of exposure are associated with down-stream adverse effects and 3) that effective risk management requires the cumulative and aggregate risk framework adopted here, suggesting a need for risk assessors to return to the original studies and provide separate estimates of exposure response relationships for all four compounds or at the least to control for exposures to nitrates, thiocyanates and organohalogens.

Research on Risk Management of Cross-Sea Bridges Based on Analytic Hierarchy Process—Taking Hangzhou Bay Bridge as an Example

Today, as the process of urbanization is accelerating, the country builds an extensive transportation network through bridges and roads, which facilitates the daily travel of the people and greatly promotes the development of the national economy. However, due to the cross-sea bridge spanning the bay, the overall scale, the complex construction environment, and the high technology content, the objective existence of risk factors in the construction process cannot be completely avoided. In the construction of cross-sea bridges, once a construction safety accident occurs, it will cause irreparable losses to the construction of the project. Taking Hangzhou Bay Bridge as an actual case, using the Analytic Hierarchy Process to identify possible risk factors during the life cycle of Hangzhou Bay Bridge, establish a corresponding risk evaluation system to evaluate the importance and probability of risk, and to rank the importance of risks, and control the corresponding construction risks by adopting measures such as risk transfer and risk retention. The research example shows that the project risk of the cross-sea bridge project can be combined with the analytic hierarchy process to identify, analyze and evaluate the importance of the various risks faced by the project, so as to adopt corresponding avoidance methods to reduce the project risk loss and achieve the project construction expectations Target.

Health evaluation method for degrading systems subject to dependent competing risks

This paper proposes a health evaluation method for degrading systems subject to competing risks of dependent soft and hard failures. To characterize the time-varying degradation rate, the degradation process is determined by a non-stationary Gamma process and the soft failure is encountered when it exceeds a predefined critical level. For the hard failure, a Cox’s proportional hazard model is applied to describe the hazard rate of the time to system failure. The dependent relationship is modeled by incorporating the degradation process as a time-varying covariate into the Cox’s proportional hazard model. To facilitate the health characteristics evaluation, a discretization technique is applied both to the degradation process and the monitoring time.All health characteristics can be obtained in the explicit form using the transition probability matrix, which is computationally attractive for practical applications. Finally, a numerical analysis is carried out to show the effectiveness and the performance of the proposed health evaluation method.

On Computing the Suitability of Non-Human Resources for Business Process Analysis

Business process improvement is a systematic approach used by several organizations to continuously improve their quality of service.Integral to that is analyzing the current performance of each task of the process and assigning the most appropriate resources to each task.In continuation of our previous work,we categorize resources into human and non-human resources.For instance,in the healthcare domain,human resources include doctors,nurses,and other associated staff responsible for the execution of healthcare activities;whereas the non-human resources include surgical and other equipment needed for execution.In this study,we contend that the two types of resources(human and non-human)have a different impact on the process performance,so their suitability should be measured differently.However,no work has been done to evaluate the suitability of non-human resources for the tasks of a process.Consequently,it becomes difficult to identify and subsequently overcome the inefficiencies caused by the non-human resources to the task.To address this problem,we present a three-step method to compute a suitability score of non-human resources for the task.As an evaluation of the proposed method,a healthcare case study is used to illustrate the applicability of the proposed method.Furthermore,we performed a controlled experiment to evaluate the usability of the proposed method.The encouraging response shows the usefulness of the proposed method.

A Novel Method for Assessing and Optimizing Software Project Process Based Risk Control

A new approach for assessing and optimizing software project process based on software risk control presented, which evaluates and optimizes software project process from the view of controlling the software project risks. A model for optimizing software risk control is given, a discrete optimization algorithm based on dynamic programruing is proposed and an example of using above method to solve a problem is also included in this paper. By improving the old passive post-project control into an active effective preaction, this new method can greatly promote the possibility of success of software projects.

HV Process Model of Software Development

Software Development Life Cycle (SDLC) is one of the major ingredients for the development of efficient software systems within a time frame and low-cost involvement. From the literature, it is evident that there are various kinds of process models that are used by the software industries for the development of small, medium and long-term software projects, but many of them do not cover risk management. It is quite obvious that the improper selection of the software development process model leads to failure of the software products as it is time bound activity. In the present work, a new software development process model is proposed which covers the risks at any stage of the development of the software product. The model is named a Hemant-Vipin (HV) process model and may be helpful for the software industries for development of the efficient software products and timely delivery at the end of the client. The efficiency of the HV process model is observed by considering various kinds of factors like requirement clarity, user feedback, change agility, predictability, risk identification, practical implementation, customer satisfaction, incremental development, use of ready-made components, quick design, resource organization and many more and found through a case study that the presented approach covers many of parameters in comparison of the existing process models. .

Managing Public Health Risks Using Air Monitoring at a Former Manufactured Gas Plant Site

Monitoring emissions from a former Manufactured Gas Plant (MGP) site during remediation was used to manage risks associated with inhalation of Volatile Organic Compounds (VOCs) and contaminated particulates acting as an exposure conduit for Polycyclic Aromatic Hydrocarbons (PAHs) and heavy metals. This risk management case study presents a USEPA-approved air monitoring program implemented to manage public health risks during remediation at a former MGP site located in the southeast United States. Risk-based Acceptable Air Concentrations (AACs) were developed and a sampling regimen established to monitor potential emissions to maintain contaminant concentrations below the AACs. The exposure duration used was based on a twelve-month project duration and an exposure time of 24 hours per day;equations, toxicity values and sources were based on USEPA’s Regional Screening Levels. A total 535 twenty-four hour time weighted samples (269 VOC samples and 266 PAH samples) were collected over the project duration. Only minor levels of VOCs and PAHs were detected and no results were above the AACs. These timeweighted averages demonstrate that the real-time air monitoring and control measures implemented at the site effectively maintained concentrations below the AACs and were protective of public health.

Study of Volatility Stochastic Processes in the Context of Solvency Forecasting for Sri Lankan Life Insurers

The main business of Life Insurers is Long Term contractual obligations with a typical lifetime of 20 - 40 years. Therefore, the Solvency metric is defined by the adequacy of capital to service the cash flow requirements arising from the said obligations. The main component inducing volatility in Capital is market sensitive Assets, such as Bonds and Equity. Bond and Equity prices in Sri Lanka are highly sensitive to macro-economic elements such as investor sentiment, political stability, policy environment, economic growth, fiscal stimulus, utility environment and in the case of Equity, societal sentiment on certain companies and industries. Therefore, if an entity is to accurately forecast the impact on solvency through asset valuation, the impact of macro-economic variables on asset pricing must be modelled mathematically. This paper explores mathematical, actuarial and statistical concepts such as Brownian motion, Markov Processes, Derivation and Integration as well as Probability theorems such as the Probability Density Function in determining the optimum mathematical model which depicts the accurate relationship between macro-economic variables and asset pricing.

Common Management Process Model of New TQM Based on the Situation Analysis

In the previous study, we suggested the concept of new TQM based on the consideration of basic concept of Quality Control. Also, in the previous study, we suggested the target domains and entities of product and process based on the TQM Matrix and view point of Three Dimensional Unification Value Models for managing quality of organization systems. Furthermore, in the previous study, we suggest the Common Management Process of organizations. Based on the above suggestion, in this paper, we would like to propose the Common Management Process Model of Total Quality Management based on the consideration of situation analysis and more precise definition of TQM Matrix and Three Dimensional Unification Value Model of “Product and Process”. Improvement of quality and efficiency of organization management can be expected by the integration of conventional different management such as quality assurance, quality improvement, risk management, investment individually from the view point of common management process.

IAM Excellence: Exploring Saviynt’s Role in Modern Information Technology

Organizations may increase data security and operational efficiency by connecting Salesforce with Identity and Access Management (IAM) systems like Saviynt. This study delves deeply into the details of this revolution that is being encouraged to shift towards IAM software and potential drawbacks such as excessive provisioning and implementation issues. The study illuminated excellent practices and emphasized the importance of constant monitoring by using secondary theme analysis and qualitative research as proof. The findings indicate Saviynt as a viable solution and provide detailed information for firms seeking a smooth and secure integration path.