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.

Participatory Technique Supporting Environmental Management: A Systematic and Bibliometric Review

The increasing need to manage natural resources sustainably, driven by population growth, requires the simultaneous use of Participatory Techniques (PT) and landscape planning for structured decision-making. We conducted a bibliometric and systematic review to provide an overview of PT usage, identifying evolution in scientific production. We considered the number of publications and citations, prominent journals, and highly cited articles on scientific papers published in the Web of Science database between 1993 and 2023. A total of 415 articles related to PT were identified. After content evaluation, 19 critical articles were selected that underpin the growing combined use of models and indices with PT, enhancing the robustness and credibility of decision-making processes.

Development and Application of Procedures for the Management of Skin Toxicity Related to Immune Checkpoint Inhibitors in Patients with Lung Cancer

Objective: To establish the procedures for the management of skin toxicity related to immune checkpoint inhibitors in patients with lung cancer and explore the effect of application. Methods: A total of 24 evidence-based evidences were collected from 7 aspects, including risk factors, baseline screening, ICIs monitoring, daily skin care, multidisciplinary management, symptom management and health education. A total of 157 lung cancer patients and 94 nurses from 8 wards of the Oncology department of our hospital from November 2022 to May 2023 were selected by convenience sampling. A total of 77 patients and 46 nurses from ward 1 - 4 were divided into the baseline group. There were 80 patients and 48 nurses in Ward 5 - 8 as the evidence-based practice group. In the baseline group, patients were treated with routine methods such as assessing skin symptoms, taking medication according to symptoms, guiding to keep skin clean and moist, eating a light diet, and avoiding scratching. The evidence-based practice group adopts an evidence-based continuous improvement model for nursing. The differences in the severity of symptoms of skin toxicity in the second cycle of medication and the knowledge and practice of self-care of skin toxicity were compared between the two groups before and after the use of the syndrome, as well as the differences in the implementation rate of review indicators, evidence-based ability and knowledge and practice of skin toxicity care before and after the use of the syndrome. Results: The incidence and severity of cutaneous toxicity were significantly lower after treatment than before treatment (P P < 0.05). Conclusion: The implementation of immune checkpoint inhibitor-related skin toxicity management procedures can effectively reduce the incidence and severity of skin toxicity symptoms, optimize the clinical pathway, and improve the quality of care.

AI-Driven Learning Management Systems:Modern Developments, Challenges and Future Trends during theAge of ChatGPT

COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus.The foremost and most prime sector among those affected were schools,colleges,and universities.The education system of entire nations had shifted to online education during this time.Many shortcomings of Learning Management Systems(LMSs)were detected to support education in an online mode that spawned the research in Artificial Intelligence(AI)based tools that are being developed by the research community to improve the effectiveness of LMSs.This paper presents a detailed survey of the different enhancements to LMSs,which are led by key advances in the area of AI to enhance the real-time and non-real-time user experience.The AI-based enhancements proposed to the LMSs start from the Application layer and Presentation layer in the form of flipped classroom models for the efficient learning environment and appropriately designed UI/UX for efficient utilization of LMS utilities and resources,including AI-based chatbots.Session layer enhancements are also required,such as AI-based online proctoring and user authentication using Biometrics.These extend to the Transport layer to support real-time and rate adaptive encrypted video transmission for user security/privacy and satisfactory working of AI-algorithms.It also needs the support of the Networking layer for IP-based geolocation features,the Virtual Private Network(VPN)feature,and the support of Software-Defined Networks(SDN)for optimum Quality of Service(QoS).Finally,in addition to these,non-real-time user experience is enhanced by other AI-based enhancements such as Plagiarism detection algorithms and Data Analytics.

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.

Research on Quality Management Measures of Green Building Construction

Urbanization has led to the rapid development of the construction industry.However,this has also led to higher requirements for the construction engineering management.Other than the quality monitoring of engineering construction,the energy-saving properties of the building should also be considered.Therefore,a scientific management approach should be adopted to improve green building management.This paper primarily examines the importance of quality management in green building construction,along with the factors influencing it.It also identifies the quality issues present in current green building construction.Finally,it proposes measures for quality management in the green building construction process to facilitate the industry’s healthy development.

Process Discovery and Refinement of an Enterprise Management System

The need for the analysis of modern businesses is rapidly increasing as the supporting enterprise systems generate more and more data.This data can be extremely valuable for executing organizations because the data allows constant monitoring,analyzing,and improving the underlying processes,which leads to the reduction of cost and the improvement of the quality.Process mining is a useful technique for analyzing enterprise systems by using an event log that contains behaviours.This research focuses on the process discovery and refinement using real-life event log data collected from a large multinational organization that deals with coatings and paints.By investigating and analyzing their order handling pro-cesses,this study aims at learning a model that gives insight inspection of the processes and performance analysis.Furthermore,the animation is also performed for the better inspection,diagnostics,and compliance-related questions to specify the system.The configuration of the system and the conformance checking for further enhancement is also addressed in this research.To achieve the objectives,this research uses process mining techniques,i.e.process discovery in the form of formal Petri nets models with the help of process maps,and process refinement through conformance checking and enhancement.Initially,the identified executed process is reconstructed by using the process discovery techniques.Following the reconstruction,we perform a deep analysis for the underlying process to ensure the process improvement and redesigning.Finally,some recommendations are made to improve the enterprise management system processes.

How Does Robotics Process Automation (RPA) Affect Project Management Practices

The main purpose of this literature review is to understand the effectiveness and impacts of Robotics Process Automation (RPA) on the practices of Project Management (PM). For attaining the purposes of the research study, an extensive literature review was conducted, which helped in gaining a theoretical understanding. These findings were then justified with the help of current and relevant secondary sources in the analysis section. The findings suggested that RPA is quite advantageous for implementing in varied aspects of a business, especially in the field of project management. However, it can pose several challenges, which need to be taken into due consideration by the organizations during execution such as the capabilities of the employees and the abilities of the existing systems to incorporate automation, among others. It was ultimately concluded that RPA is highly advantageous for project management teams but its effective implementation is the key to success.

A New Fuzzy Clustering-Ranking Algorithm and Its Application in Process Alarm Management

Overmany alarms of modern chemical process give the operators many difficulties to decision and diag- nosis. In order to ensure safe production and process operating, management and optimization of alarm information are challenge work that must be confronted. A new process alarm management method based on fuzzy clustering- ranking algorithm is proposed. The fuzzy clustering algorithm is used to cluster rationally the process variables, and difference driving decision algorithm ranks different clusters and process parameters in every cluster. The alarm signal of higher rank is handled preferentially to manage effectively alarms and avoid blind operation. The validity of proposed algorithm and solution is verified by the practical application of ethylene cracking furnace system. It is an effective and dependable alarm management method to improve operating safety in industrial process.

Formal Modeling and Discovery of Multi-instance Business Processes: A Cloud Resource Management Case Study

Process discovery, as one of the most challenging process analysis techniques, aims to uncover business process models from event logs. Many process discovery approaches were invented in the past twenty years;however, most of them have difficulties in handling multi-instance sub-processes. To address this challenge, we first introduce a multi-instance business process model(MBPM) to support the modeling of processes with multiple sub-process instantiations. Formal semantics of MBPMs are precisely defined by using multi-instance Petri nets(MPNs)that are an extension of Petri nets with distinguishable tokens.Then, a novel process discovery technique is developed to support the discovery of MBPMs from event logs with sub-process multi-instantiation information. In addition, we propose to measure the quality of the discovered MBPMs against the input event logs by transforming an MBPM to a classical Petri net such that existing quality metrics, e.g., fitness and precision, can be used.The proposed discovery approach is properly implemented as plugins in the Pro M toolkit. Based on a cloud resource management case study, we compare our approach with the state-of-theart process discovery techniques. The results demonstrate that our approach outperforms existing approaches to discover process models with multi-instance sub-processes.

Digital Twin-based Quality Management Method for the Assembly Process of Aerospace Products with the Grey-Markov Model and Apriori Algorithm

The assembly process of aerospace products such as satellites and rockets has the characteristics of single-or small-batch production,a long development period,high reliability,and frequent disturbances.How to predict and avoid quality abnormalities,quickly locate their causes,and improve product assembly quality and efficiency are urgent engineering issues.As the core technology to realize the integration of virtual and physical space,digital twin(DT)technology can make full use of the low cost,high efficiency,and predictable advantages of digital space to provide a feasible solution to such problems.Hence,a quality management method for the assembly process of aerospace products based on DT is proposed.Given that traditional quality control methods for the assembly process of aerospace products are mostly post-inspection,the Grey-Markov model and T-K control chart are used with a small sample of assembly quality data to predict the value of quality data and the status of an assembly system.The Apriori algorithm is applied to mine the strong association rules related to quality data anomalies and uncontrolled assembly systems so as to solve the issue that the causes of abnormal quality are complicated and difficult to trace.The implementation of the proposed approach is described,taking the collected centroid data of an aerospace product’s cabin,one of the key quality data in the assembly process of aerospace products,as an example.A DT-based quality management system for the assembly process of aerospace products is developed,which can effectively improve the efficiency of quality management for the assembly process of aerospace products and reduce quality abnormalities.

Evaluation of process management of postpartum hemorrhage due to uterine atony

Objective: To evaluate the management process and the guidelines for management of postpartum hemorrhage due to uterine atony at the General Hospital Vienna, Medical University Vienna. Material and Methods: A retrospective analysis was carried out on all 24 cases of postpartum hemorrhage due to uterine atony with an estimated blood loss of more than 800 mL, in which standardized guidelines were obtained. We included all women who gave birth at the General Hospital of Vienna, the Medical University Vienna, during the period from January 1st 2003 and December 31st 2009 and who suffered blood loss 800 mL at minimum due to uterine atony. Results: The guidelines were in use for 14% - 71%. The average blood loss of the 24 cases with uterine atony was 1342 mL. Conclusion: The management process of postpartum hemorrhage due to uterine atony deviates from the hospital’s guidelines in many cases.

Reflections on Research and Development Management Innovation in Huawei Enterprises

As an advanced global provider of information and communication technology solutions,Huawei has always maintained a leading position in the ICT field and is committed to achieving a future information society and building a better fully connected world.Looking at the rapid development of Huawei,it is inseparable from its comprehensive and advanced enterprise management innovation concept,which is also one of the main reasons for helping Huawei become a world-class enterprise.“Huawei has not succeeded,it is just growing”is a famous quote from Ren Zhengfei,the main founder and president of Huawei.In the context of the rapid development of the Internet industry and information technology,enterprises must establish the concept of innovative development,implement innovation management,and create a good production and development environment.This paper analyzes the content of Huawei’s enterprise management innovation,including Huawei’s management philosophy,management mode,management status quo,and management innovation suggestions,understands and grasps the choice of enterprise management mode,learns advanced enterprise management experience,and provides reference for other enterprises to practice innovation management.

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.

Innovation Management Processes and Routines for Business Success and Value Creation

Innovation is managed through the development of processes and routines, considered as critical for business success and value creation. The identification of relevant routines as well as the understanding of which factors affect business innovation is the main objective of this research, based on a survey applied in Portuguese companies and their experience shared in best practices guides. Conclusions highlighted 10 key innovation routines, reinforcing the idea that innovation must be supported through a systematic and sustained management process. Results also indicate that SMEs face greater difficulties in benefiting from the potential of innovation practices and collaboration may present opportunities to overcome their limited resources. Therefore, regardless of size, business activity, science and technology intensity or other factors influencing firms dynamic capabilities, innovation should be considered as a management imperative as it can influence not only the present but also the future of business success.

PERFORMANCE-DRIVEN BUSINESS PROCESS MANAGEMENT METHODOLOGY FOR SMALL AND MEDIUM SIZED-ENTERPRISES

Based on the analysis of the common limitations of business processmanagement (BPM) methodologies and the requirements of small and medium sized-enterprises (SMEs),the importance of a 'performance construct' of BPM methodologies is identified, a six-phaseperformance-driven BPM methodology for the production and operation processes of Chinese SMEs isdeveloped. A case study on the process management of a medium-sized enterprise shows a successfulexample of running the methodology.

Enterprise Process Modeling Methodology and Environment Supporting Project Management

Development of the global economy makes modem enterprises confront challenges of efficient managements for large projects and complex processes. Projects are typically managed in rather special manners. On the contrary, there exist many methodologies for product process management to achieve consistency and continuance. However, processes often lack flexibility offered by projects. This paper dis~ the relationship of conceptual characteristics between process and project, gives low-level details to tackle the difference between them, and proposes an enterprise process modeling method for project management. An integrated environment is designed to support the method from which both project management and process management can receive benefits and conform to the limitations.

Integration of Management Systems: A Process Based Model

The paper discusses the barriers of integration of management systems （IMS）. A model based on process is explored, It is indicated that integrating management systems should not ignore the characteristics of the management systems, especially scope issues. IMS needs to take into the continuous improvement.

Controlling of crustacean zooplankton reproduction in biological activated carbon (BAC) filters by strengthen operation and management of conventional process

To counter the mass reproduction and penetration of crustacean zooplankton in Biological Activated Carbon(BAC)filters which may result in the presence of organisms in potable water and water pollution,this paper analyzed the factors affecting organisms' reproduction in BAC filters.A comparative study was performed on the density and composition of crustacean zooplankton of the concerned water treatment units of two advanced water plants(Plant A and B)which with the same raw water and the same treatment technique in southern China.The results obtained show that the crustaceans' density and composition was very different between the sand filtered water of Plant A and Plant B.which Harpacticoida bred sharply in the sediment tanks and penetrated sand filter into BAC filters was the primary reason of crustaceans reproduce in BAC filters of Plant A.For prevention of the organisms reproduction in BAC,some strengthen measures was taken including pre-chlorination,cleaning coagulation tanks and sediment tanks completely,increasing sludge disposal frequency to stop organisms enter BAC filters,and the finished water quality was improved and enhanced.

Analyzing and Designing Business Processes Management System Based on Transformation of Instantiated Ontology’s State

The paper discusses efforts of finding a simple and transparent method to analyze business processes and developing its management system architecture. By introducing ontology and its state, the approach tried to find a unified representation and a flexible choreography of business processes. The main idea of the paper is the transformation of ontology＇s states, which are the most important scenarios of enterprises. The business activity composition, that is, case composition based on an AI technique, Case Based Reason （CBR）, which is to solve new problems by retrieving solutions to previous problems, and then store the modified solution. The main interest in CBR relies on that it allows a system to avoid past failures and exploit past successes.