Closed-loop Management Research Articles

Early Warning for Stepwise Landslides Based on Traffic Light System: A Case Study in China

The phenomenon of stepwise landslides, characterized by displacement exhibiting a step-like pattern, is often influenced by reservoir operations and seasonal rainfall. Traditional early warning models face challenges in accurately predicting the sudden initiation and cessation of displacement, primarily because conventional indicators such as rate or acceleration are ineffective in these scenarios. This underscores the urgent need for innovative early warning models and indicators. Viewing step-like displacement through the lens of three phases—stop, start, and acceleration—aligns with the green-yellow-red warning paradigm of the Traffic Light System (TLS). This study introduces a novel early warning model based on the TLS, incorporating jerk, the derivative of displacement acceleration, as a critical indicator. Empirical data and theoretical analysis validate jerk’s significance, demonstrating its clear pattern before and after step-like deformations and its temporal alignment with the deformation’s conclusion. A comprehensive threshold network encompassing rate, acceleration, and jerk is established for the TLS. The model’s application to the Shuiwenzhan landslide case illustrates its capability to signal in a timely manner the onset and acceleration of step-like deformations with yellow and red lights, respectively. It also uniquely determines the deformation’s end through jerk differential analysis, which is a feat seldom achieved by previous models. Furthermore, leveraging the C5.0 machine learning algorithm, a comparison between the predictive capabilities of the TLS model and a pure rate threshold model reveals that the TLS model achieves a 93% accuracy rate, outperforming the latter by 7 percentage points. Additionally, in response to the shortcomings of existing warning and emergency response strategies for this landslide, a closed-loop management framework is proposed, grounded in the TLS. This framework encompasses four critical stages: hazard monitoring, warning issuance, emergency response, and post-event analysis. We also suggest support measures to ensure implementation of the framework.

ARTIFICIAL INTELLIGENCE FOR OPTIMIZED WELL CONTROL AND MANAGEMENT IN SUBSURFACE MODELS WITH UNPREDICTABLE GEOLOGY

A comprehensive control policy structure utilizing Artificial Intelligence (AI) is presented for closed-loop management in subsurface models. Conventional Closed-Loop Optimisation (CLO) approaches entail the iterative implementation of information assimilation, past synchronization details, and effective optimizing procedures. Information assimilation is more difficult when there is uncertainty in the geological approach and the specific model conclusions. Closed-Loop Reservoir Monitoring (CLRM) offers a control strategy that promptly correlates flow information obtained from wells, as typically accessible, to appropriate well stress configurations. The rule is characterized by time-based compression and gate-based converter sections. Learning is conducted during a preprocessing phase utilizing geological modeling derived from various geological settings. Illustrative instances of oil extraction using water insertion, utilizing both 2 and 3-dimensional geological designs, are shown. The AI-oriented technique demonstrates a 17.2% increase in Net Present Value (NPV) for 2D instances, an additional 31.5% for 3D cases compared to the effective optimization of previous models, and a 1-6.5% enhancement in NPV relative to standard CLRM. Based on the methods and variable configurations examined in this study, the controlling policy method yields a 71.34% reduction in processing expenses compared to conventional CLRM.

Targeted gene sequencing and hearing follow-up in 7501 newborns reveals an improved strategy for newborn hearing screening.

Hearing loss is a common congenital condition. Concurrent newborn hearing and limited genetic screening has been implemented in China for the last decade. However, the role of gene sequencing screening has not been evaluated. In this study, we enrolled 7501 newborns (52.7% male, 47.3% female) in our Newborn Screening with Targeted Sequencing (NESTS) program, and 90 common deafness genes were sequenced for them. Hearing status assessments were conducted via telephone from February 2021 to August 2022, for children aged 3 to 48 months. Of the universal newborn hearing screening, 126 (1.7%) newborns did not pass. Targeted sequencing identified 150 genetically positive newborns (2.0%), with 25 exhibiting dual-positive results in both screening. Following diagnostic audiometry revealed 18 hearing loss newborns and half of them had abnormal results in both screening. The positive predictive value for universal newborn hearing screening alone was merely 14.3% (18/126). However, when combined with targeted sequencing, this rate increased to 36.0% (9/25). Furthermore, limited genetic screening identified 316 carriers of hot-spot variants, but none exhibited biallelic variants. All 15 hot-spot carriers who failed physical screening demonstrated normal hearing during follow-up. In this cohort study of 7501 Newborns, Combining targeted sequencing with universal newborn hearing screening demonstrated technical feasibility and clinical utility of identifying individuals with hearing loss, especially when coupled with genetic counseling and closed-loop management. It is suggested to use this integrated method as an improved strategy instead of the current limited genetic screening program in some regions of China.

Establishment and application of infectious disease monitoring, early warning and disposal system

Using big data and artificial intelligence to establish a multi-point monitoring, early warning, and disposal system to achieve early warning and intervention of infectious disease outbreaks is an important means of controlling the spread of the epidemic. Taking Xiaoshan district as an example, this study analyzes the monitoring contents, warning methods, and application effectiveness of the infectious disease monitoring, early warning and disposal system. Based on Xiaoshan's health big data resources, the system starts with syndrome, disease diagnosis and etiology. Through advanced technologies such as artificial intelligence and block chain, it realizes early identification of infectious disease outbreaks, data fusion, multi-cross collaboration, and closed-loop management. It has improved the sensitivity of clustered outbreaks monitoring and the effectiveness of epidemic disposal and provided a reference for grassroots disease prevention and control departments to establish an infectious disease monitoring and early warning system.

Research and Development of A Comprehensive Management Platform for Intelligent Production and Construction of the Entire Process of Sulige Gas Field

Abstract The Sulige gas field is the first fully installed atmospheric field in China with an annual production capacity exceeding 30 billion cubic meters. It has the characteristics of low permeability and density, rapid development decline, and large annual compensation decline workload. As a pilot project for the regional production and construction project system in Changqing Oilfield, Sulige Gas Field Development Branch is facing problems such as a wide range of project management points, limited personnel, difficulty in engineering data collection, and tight time connection between various professional businesses. By using digital and information technology, it has developed and created a closed-loop management platform for the digital production capacity construction of the entire business chain of production and construction project drilling, testing, and investment, and constructed a multi-dimensional visual control mechanism for the entire process of a single well, Realized digital management of the operation of a single account for the entire business chain production and construction project of drilling and trial investment; Relying on operator resources to quickly and low-cost expand the basic network, achieving real-time video monitoring of multi platform drilling and testing sites, collection of construction data, and online tracking; Establish a big data model for condition analysis and early warning, and innovate the formation of a “digital+safety dual prevention mechanism” linkage management and dynamic and static risk early warning push; Develop 16 APP functions such as supporting coordinates and well site handover to achieve online flow management of production and construction business, more efficiently guide production organization and close connection of processes, and significantly improve the efficiency of production and construction organization; Creating a dedicated digital and intelligent environment for production and construction, achieving deep integration of digital and intelligent business with Oil and gas fields production and construction, further enhancing project management and collaborative combat capabilities among various specialties. The innovative digital production capacity closed-loop management of Sulige Gas Field platform realizes the full lifecycle and multidisciplinary integrated management of wellbore engineering. Its efficient digital production organization model can provide a certain reference for the organization and management of similar projects in the upstream of exploration and development.

Integrating frailty management into cardiac intensive care unit nursing practice: A qualitative study

BackgroundFrailty is prevalent among older patients in intensive care units (ICUs) and poses significant challenges to recovery. Despite its importance, there is limited research on effective nurse-led frailty management strategies in this context. ObjectiveThe purpose of this qualitative study was to explore nurses' perceptions of frailty management in cardiac ICUs through the lens of the Wuli-Shili-Renli (WSR) system approach. MethodsSixteen nurses from two tertiary hospitals in Shandong province, China, participated in semi-structured interviews. Participants were selected based on their involvement in frailty training, educational background, and cardiac ICU work experience. Thematic analysis was conducted to identify key themes and sub-themes. ResultsAnalysis in three categories revealed the need for foundational support, including the need for appropriate screening tools, updated evidence-based practices, and institutional support. Closed-loop management involved frailty screening, personalized program implementation, information management, and follow-up assessment. Personnel training and coordination emphasized enhancing nurses' professionalism, multidisciplinary teamwork, and cooperation from patients and their caregivers. ConclusionThe insights gained can inform evidence-based practices and improve the quality of care provided to frail patients in cardiac ICUs. There is a need for future research to empirically investigate these strategies.

A wearable, rapidly manufacturable, stability-enhancing microneedle patch for closed-loop diabetes management

The development of a wearable, easy-to-fabricate, and stable intelligent minisystem is highly desired for the closed-loop management of diabetes. Conventional systems always suffer from large size, high cost, low stability, or complex fabrication. Here, we show for the first time a wearable, rapidly manufacturable, stability-enhancing microneedle patch for diabetes management. The patch consists of a graphene composite ink-printed sensor on hollow microneedles, a polyethylene glycol (PEG)-functionalized electroosmotic micropump integrated with the microneedles, and a printed circuit board for precise and intelligent control of the sensor and pump to detect interstitial glucose and deliver insulin through the hollow channels. Via synthesizing and printing the graphene composite ink, the sensor fabrication process is fast and the sensing electrodes are stable. The PEG functionalization enables the micropump a significantly higher stability in delivering insulin, extending its lifetime from days to weeks. The patch successfully demonstrated excellent blood glucose control in diabetic rats. This work may introduce a new paradigm for building new closed-loop systems and shows great promise for widespread use in patients with diabetes.

The effect of environmental values, beliefs, and norms on social entrepreneurial intentions among Chinese university students

This study explores the factors influencing university students’ social entrepreneurial intentions based on the values-beliefs-norms theory. Data were collected from 769 Chinese university students through online surveys. The hypotheses were tested using partial least squares-structural equation modeling. The results confirmed the positive influence of altruistic and traditional values on normative beliefs. Awareness of the consequences and attribution of responsibility had no significant effect on personal norms among university students, which have been discussed in-depth in relation to the phenomenon of inadequate student socialization due to closed-loop management policies at Chinese universities during the COVID-19 pandemic. Furthermore, the findings verified the positive and significant effects of personal, injunctive, and descriptive social norms on social entrepreneurship intentions. With the aim of promoting social entrepreneurship among university students and broadening the understanding of the phenomenon of social entrepreneurs, this study provides a favorable direction and expands the discussion on the topic. The results will help the government and universities foster more effective prosocial behaviors among university students.

End-to-End Network SLA Quality Assurance for C-RAN: A Closed-Loop Management Method Based on Digital Twin Network

End-to-End Network SLA Quality Assurance for C-RAN: A Closed-Loop Management Method Based on Digital Twin Network

Facile eco-friendly process for upcycled sustainable perovskite solar cells

Developing a green technology to eliminate the impact of the toxic element Pb and harmful solvent is a challenge for sustainable perovskite solar cells (PSCs). Herein, we report a facile eco-friendly process for upcycled sustainable PSC by screening the polar Pb solubilizers (N,N-dimethylformamide, DMF, dimethyl sulfoxide, DMSO and butylamine, BA) coupling with multi-function potassium iodide (KI) precipitator. We find that DMF with strong Pb-dissolution capacity and weak coupled C = O − Pb adhesion exhibits superb separation and recovery of Pb from obsolete PSC devices. Subsequent closed-loop management of the DMF completely eliminates its potential harm to the ecological environment. Interestingly, the KI precipitator added to the Pb-containing DMF solution not only induces the formation of high-quality PbI2 and thus high-crystallized defect-less perovskite matrix, but also relieves the residual tensile strain stemming from lattice expansion leading to orderly lattice orientation for perovskite crystallization. As a result, the re-fabricated PSC based on recovered components (PbI2, ITO and Ag) shows a PCE of 22.78 % higher than that (20.76 %) of PSC based on fresh components, also exceeding the reported record efficiency of PSCs based on one or more recovered components. Such a stable, environment-friendly, upcycled process of retired PSCs offers a sustainable pathway for eliminating the adverse factors such as toxic Pb leakage and harmful solvent effluence, and thus boost their competitiveness in future energy market.

TeamSTEPPS improves patient safety

BackgroundExamine how Team Strategies and Tools to Enhance Performance and Patient Safety (TeamSTEPPS) can be used to manage patient safety and improve the standard of care for patients.MethodsIn order to...

24Model-based comparative analysis of two catastrophic hazardous chemical pipeline accidents

ABSTRACT Objectives. This study conducted a comparative analysis of two catastrophic pipeline accidents in China in order to identify some common mistakes and lessons learned to prevent similar accidents. Methods. The 24Model was used in this study, which provides a universal pathway for accident analysis from the individual level to the organizational level. Results. There were similarities between the two cases in the aspects of the occurrence, development, emergency and causation at different levels: both were caused by leaks of pipelines and evolved into multiple explosions during emergency response; both leaks were caused by the corrosion of pipelines in the confined space of a damp or salt-spray environment; both were classified as ‘responsibility accidents’, and unsafe acts, such as the failure to identify hidden hazards of pipelines that were the direct cause of accidents, reflected the shortcomings of individual safety habitual behaviour in terms of knowledge, awareness, habits and psychology; weaknesses in the organizational management mainly concerned hazard identification, pipeline maintenance, emergency disposal, etc.; and there is not a good safety climate within the organization. Conclusions. Organizations should develop a closed-loop management system and strengthen the construction of safety culture, and the government should supervise the implementation of procedures.

An intelligent continuous bladder irrigation monitoring and control system: Development and preliminary assessment

Abstract Objectives: To design an intelligent continuous bladder irrigation monitoring and control system and preliminarily assess its sensitivity of the early warning of flushing anomalies. Methods: According to the principle of bladder irrigation, an intelligent continuous bladder irrigation monitoring and control system was designed. The Amesim fluid simulation software was used to establish a parameterized simulation model for the bladder perfusion process and simulate the dynamic changes of bladder pressure and volume under different perfusion speeds to assess the sensitivity of the early warning of flushing anomalies. Results: The intelligent system consisted of 3 parts: the monitoring part (a flushing fluid inlet flow monitoring device, a flushing fluid outlet flow monitoring device, and a flushing fluid outlet color recognition sensor), the transition part (a control motherboard), and the regulation part (an alarm device, an electric control device for flushing fluid input speed, and a squeezing device for flushing waste fluid line). The data of the parameterized simulation model for the bladder perfusion process suggested that the sensitivity of the system was acceptable. Conclusion: The intelligent bladder irrigation system can automatically detect, report, and resolve signal abnormalities, thereby achieving the closed-loop management of bladder irrigation. The intelligent system might be used in clinical settings to reduce the burdens of nurses and promote patients’ recovery.

Application of information-based closed-loop management in optimizing surgical process

Application of information-based closed-loop management in optimizing surgical process

Quality assurance: a conceptual framework for teaching and learning standards in vocational and technical education programs

PurposeThe issue of quality assurance in vocational and technical education (VTE) programs identifies a perilous need to develop a conceptual framework for teaching and learning standards. This study aims to identify standard components for teaching and learning to ensure quality delivery for the achievement of VTE objectives. The quality assurance framework for teaching and learning is envisioned as a closed-loop management process that functions as an effective operational scheme to coordinate teaching processes that support the structure for quality assurance in VTE programs.Design/methodology/approachSurvey data were collected through a questionnaire developed to examine the quality standards for teaching and learning in VTE from 259 respondents from colleges of education. The identified quality components for teaching and learning and their quality indicators were analysed.FindingsThe conceptual framework for teaching and learning with the 12 quality components and 62 quality indicators is the key standard for improving quality teaching and learning to meet the desired goals of VTE programs.Originality/valueThe framework proposed is flexible and can be applied to many other programs to ensure that teachers are professional enough to teach effectively to provide adequate learning outcomes.

Application of a digital twin for highway tunnels based on multi-sensor and information fusion

Due to the harsh environment of highway tunnels and frequent breakdowns of various detection sensors and surveillance devices, the operational management of highway tunnels lacks effective data support. This paper analyzes the characteristics of operational surveillance data in highway tunnels. It proposes a multimodal information fusion method based on CNN–LSTM–attention and designs and develops a digital twin for highway tunnel operations. The system addresses issues such as insufficient development and coordination of the technical architecture of operation control systems, weak information service capabilities, and insufficient data application capabilities. The system also lacks intelligent decision-making and control capabilities. The developed system achieves closed-loop management of “accurate perception–risk assessment–decision warning–emergency management” for highway tunnel operations based on data-driven approaches. The engineering demonstration application underscores the system’s capacity to enhance tunnel traffic safety, diminish tunnel management costs, and elevate tunnel driving comfort.

Development and validation of the screening tool for age-related hearing loss in the community based on the information platform

IntroductionCurrently, age-related hearing loss has become prevalent, awareness and screening rates remain dismally low. Duing to several barriers, as time, personnel training and equipment costs, available hearing screening tools do not adequately meet the need for large-scale hearing detection in community-dwelling older adults. Therefore, an accurate, convenient, and inexpensive hearing screening tool is needed to detect hearing loss, intervene early and reduce the negative consequences and burden of untreated hearing loss on individuals, families and society.ObjectivesThe study harnessed "medical big data" and "intelligent medical management" to develop a multi-dimensional screening tool of age-related hearing loss based on WeChat platform.MethodsThe assessment of risk factors was carried out by cross-sectional survey, logistic regression model and receiver operating characteristic (ROC) curve analysis. Combining risk factor assessment, Hearing handicap inventory for the elderly screening version and analog audiometry, the screening software was been developed by JavaScript language and been evaluated and verified.ResultsA total of 401 older adults were included in the cross-sectional study. Logistic regression model (univariate, multivariate) and reference to literature mention rate of risk factors, 18 variables (male, overweight/obesity, living alone, widowed/divorced, history of noise, family history of deafness, non-light diet, no exercising habit, smoking, drinking, headset wearer habit, hypertension, diabetes, hyperlipidemia, cardiovascular and cerebrovascular diseases, hyperuricemia, hypothyroidism, history of ototoxic drug use) were defined as risk factors. The area under the ROC curve (AUC) of the cumulative score of risk factors for early prediction of age-related hearing loss was 0.777 [95% CI (0.721, 0.833)]. The cumulative score threshold of risk factors was defined as 4, to classify the older adults into low-risk (< 4) and high-risk (≥ 4) hearing loss groups. The sensitivity, specificity, positive predictive value, and negative predictive value of the screen tool were 100%, 65.5%, 71.8%, and 100.0%, respectively. The Kappa index was 0.6.ConclusionsThe screening software enabled the closed loop management of real-time data transmission, early warning, management, whole process supervision of the hearing loss and improve self-health belief in it. The software has huge prospects for application as a screening approach for age-related hearing loss.

Development and applications of an integrated space-air-ground observation network in natural resource monitoring and supervision

Timely and accurate monitoring is a prerequisite to survey the types, quantities, quality, and distribution of various natural resources. Currently, satellite remote sensing is the major observation method, which has advantages in observation scale, fast speed, and low cost. However, with the increasingly precise management of natural resource, satellite remote sensing faces some shortcomings in observation timeliness, dynamism, and accuracy. To solve these problems, combining space-based, air-based, and ground-based observation technologies can offer an effective approach by taking the advantages of each technology. This study focuses on development and applications of an integrated space-air-ground observation network to avoid the insufficiencies of individual monitoring method in natural resource monitoring and supervision. In this paper, we combined satellite remote sensing, drone photography, video surveillance, and field survey to establish an integrated space-air-ground observation network, proposed a cooperative observation mechanism in observation task, scale, and time. Then monitoring indicators and supervision process was established via indicator library and workflow engine, realizing closed-loop management of “discovery, analysis, verification, disposal, and cancellation” for natural resource monitoring and supervision. Afterward, by connecting the observation network and following the closed-loop management process, a cross terminal software was designed and developed to achieve process automation of natural resource monitoring and supervision. Finally, the observation network and software was put into practice, and the results indicate that the integrated space-air-ground observation network can effectively improve the efficiency and accuracy of natural resource of monitoring and supervision.

Design and Implementation of Closed Loop Management System for GMP Workshop Cleanroom Garment

Design and Implementation of Closed Loop Management System for GMP Workshop Cleanroom Garment

GSA-KELM-KF: A Hybrid Model for Short-Term Traffic Flow Forecasting

Short-term traffic flow forecasting, an essential enabler for intelligent transportation systems, is a fundamental and challenging task for dramatically changing traffic flow over time. In this paper, we present a gravitational search optimized kernel extreme learning machine, named GSA-KELM, to avoid manually traversing all possible parameters to improve the potential performance. Furthermore, with the interference of heavy-tailed impulse noise, the performance of KELM may be seriously deteriorated. Based on the Kalman filter that cleverly combines observed data and estimated data to perform the closed-loop management of errors and limit the errors within a certain range, we propose a combined model, termed GSA-KELM-KF. The experimental results of two real-world datasets demonstrate that GSA-KELM-KF outperforms the state-of-the-art parametric and non-parametric models.