Measurable Parameters Research Articles

Inline Measurement of Light Beam Induced Current (LBIC) Under High-Injection and Reverse Bias Conditions

Quality control in solar cell production relies on characterization methods that are fast enough to yield information on the properties of each solar cell in less than about one second. Imaging techniques such as electroluminescence (EL) are well established methods revealing spatially resolved quality mappings. Scanning techniques such as light beam induced current (LBIC) are common laboratory methods yielding complementary information but do not meet the speed requirements. In our work, we analyse an inline implementation of the LBIC method which is extended with respect to its measurement parameters, i.e., both the laser power and a solar cell bias-voltage are varied. As these extended conditions differ from conventional LBIC-applications at zero bias and low injection, we compare our inline-LBIC images with EL images and conventional LBIC images by means of an image contrast analysis. We find that our method resembles more the EL imaging as variations in the local series resistance are prominently detected. Thus, the proposed LBIC approach with extended measurement parameter range can yield both local short circuit information and local series resistance information. With our setup, measurement speeds around 700 ms are achieved.

Mechanical Tests of EN AW 5754 Aluminium Alloy Clinch Joints

The aim of the study is to learn about the possibilities of joining two sheets of the same thickness. The geometrical parameters significantly determine the strength of the resulting joint. Experimental tests were carried out to check the joint strength. During the test, the material used EN AW-5754 aluminium alloy, and the total clinched sheet thickness was 2 mm. The joints were prepared at the University of Miskolc with a TOX@ clinching tool. The most important parameters of the joints from the point of view of mechanical strength are the neck thickness and the undercut, besides which the only measurable parameter we analyzed is the bottom thickness. The cross-section of the joints was analyzed by microscopic examination and compared with the numerical simulation for FEA validation. The clinched joints were tested with a fatigue test and the effect of bottom thickness was investigated.

Online monitoring and fault early warning prediction method for the operational status of steam turbine sliding pin systems

Abstract In modern power systems, ensuring the safe and reliable operation of the sliding pin system in large steam turbine generator sets is crucial. However, the measurable parameters in the current distributed control system are insufficient for fault early detection of the sliding pin system’s operational state. Additionally, there is a lack of relevant research in this area at present. This paper utilizes a typical 300 MW-class unit as a case study. By analyzing the operational mechanism and fault modes of the sliding pin system, a method for online monitoring of its operational status based on cylinder expansion measurement parameters is proposed. Based on this foundation, taking the advantage of long short-term memory (LSTM) network to effectively extract features from univariate time series, and integrating improved particle swarm optimization (IPSO) for automatic hyperparameter optimization, a multi-step prediction model and fault prediction method for the operational status of sliding pin systems based on IPSO-LSTM is designed. Test results based on various performance evaluation metrics indicate that the IPSO-LSTM algorithm significantly enhances the prediction model’s accuracy. Specifically, the TVIWAC-PSO model, which varies the inertia weight (TVIW) and acceleration coefficients simultaneously in the PSO algorithm, optimizes by enhancing global search in the early stages and emphasizing local search in the later stages of iteration. Furthermore, TVIWAC-PSO demonstrates superior performance in optimizing the hyperparameters of the LSTM algorithm. Finally, based on the gap standard between sliding pins and keyway in the actual operating procedures of the unit, combined with the low-pressure cylinder and rotor expansion difference operation standard, thresholds for anomaly detection and early fault prediction of the sliding pin system’s operational status are provided. This study holds significant engineering application value.

Label Propagation Algorithm for Face Clustering using Shared Nearest Neighbor Similarity

Facial image datasets are particularly vulnerable to challenges such as lighting variations and occlusion, which can complicate data classification. Semi-supervised learning, using a limited amount of labeled facial data, offers a solution by enhancing face classification accuracy while reducing manual labeling efforts. The Label Propagation Algorithm (LPA) is a commonly used semi-supervised algorithm that employs Radial Basis Function (RBF) to measure similarities between data nodes. However, RBF struggles to capture complex nonlinear relationships in facial data. To address this, an improved LPA is proposed that integrates Shared Nearest Neighbor (SNN) to enhance the correlation measurement between facial data and RBF. Three known datasets were considered: FERET, Yale, and ORL. The experiments showed that in the case of insufficient label samples, the accuracy reached 89.76%, 92.46%, and 81.48%, respectively. The proposed LPA enhances clustering robustness by introducing 128 dimensional facial features and more complex similarity measurement. The parameter of similarity measurement can be adjusted based on the characteristics of different datasets to achieve better clustering results. The improved LPA achieved better performance and face clustering effectiveness by enhancing robustness and adaptability.

Transient gas path fault diagnosis of aero-engine based on domain adaptive offline reinforcement learning

Real-time measurement parameters are crucial for diagnosing faults in aero-engine gas path performance, ensuring engine reliability, and mitigating potential economic losses. Traditional aero-engines performance diagnosis was mainly based on the measurements of steady-state condition and lacked the utilization of data under transient conditions. Gas path diagnosis of aero-engines under transient conditions is crucial for early fault detection and safety of flight within the envelope. The challenge lies in the inconsistent distribution of performance deviations caused by variable operating conditions, especially with complex fault types, which can undermine diagnostic credibility. To improve reliability of gas path diagnosis under transient conditions, an offline reinforcement learning fault diagnosis framework based on a transient aero-engine performance model is proposed. To address the issue of variable operating conditions during transient states, a domain adaptive approach is utilized to reconstruct the measurement baseline and facilitate the transfer of different performance deviation distributions. Additionally, by adding spool acceleration as a measurement parameter, the multi-component fault coupling is solved. Finally, validation with actual operating data simulates fault cases, demonstrating the proposed method's efficacy in quantitatively detecting gradual, sudden, and multiple component faults under transient conditions with high accuracy and efficiency. The method proposed in this study achieves a computational speed improvement by 64% compared to the conventional method, achieving a time of 0.13 seconds, with an average error of less than 0.00389%. Additionally, it demonstrates strong robustness in the presence of noise, with an average error of less than 0.03125%. This proposed method improves real-time fault detection under transient conditions for its higher accuracy and efficiency, and therefore significantly enhance gas path health monitoring and diagnosis capability.

Capacitance-based mass flow rate measurement of two-phase hydrogen in a 0.5 in. tube

Mass flow rate is a critical measurement parameter when designing cryogenic hydrogen fluid systems. It is important in custody transfer applications for calculating financial obligations, fundamental fluid property research/modeling, and fluid system design applications to optimize chill down performance, maintain thermal equilibriums, and provide feedback control for pumps and valves. However, due to the large temperature differential between cryogenic fluids and the environment, there is often multiphase flow during system chilldown and steady state operation. Current available cryogenic flow measurement techniques are not equipped to deal with the complex multiphase flow inherent in cryogenic fluid systems, resulting in significant measurement errors. This mass flow measurement inaccuracy can cause financial loss, system instability, and even component failure, resulting in a strong market demand for a multiphase cryogenic mass flow meter to optimize and control sophisticated and costly cryogenic systems. This paper presents a solution in the form of a novel capacitance-based technique for measuring the multiphase mass flow rate of cryogenic hydrogen in a terrestrial environment. The device was calibrated and tested on a ½” tube multiphase hydrogen flow loop at a cryogenic hydrogen test facility. An error of ± 2 % full scale was achieved across a range of flow conditions, including transient and steady states.

The Views and Experiences of Integrated Care System Commissioners About the Adoption and Implementation of Virtual Wards in England: Qualitative Exploration Study.

Virtual wards (VWs) are being introduced within the National Health Service (NHS) in England as a new way of delivering care to patients who would otherwise be hospitalized. Using digital technologies, patients can receive acute care, remote monitoring, and treatment in their homes. Integrated care system commissioners are employees involved in the planning of, agreeing to, and monitoring of services within NHS England and have an important role in the adoption and implementation of VWs in clinical practice. This study aims to develop an understanding of the acceptability and feasibility of adopting and implementing VWs in England from integrated care system commissioners' perspectives, including the identification of barriers and facilitators to implementation. Qualitative semistructured interviews were conducted with 20 commissioners employed by NHS England (NHSE) in various geographic regions of England. Thematic analysis was conducted, structured using the framework approach, and informed by the Consolidated Framework for Implementation Research. The COREQ (Consolidated Criteria for Reporting Qualitative Research) guidelines were followed. Four overarching themes were identified reflecting the acceptability and feasibility of key adoption and implementation processes: (1) assessing the need for VWs, (2) coordinating a system approach, (3) agreeing to Program Outcomes: NHSE Versus Organizational Goals, and (4) planning and adapting services. Commissioners expressed the need for system-level change in care provision within the NHS, with VWs perceived as a promising model that could reform patient-centered care. However, there was uncertainty over the financial sustainability of VWs, with questions raised as to whether they would be funded by the closure of hospital beds. There was also uncertainty over the extent to which VWs should be technology-enabled, and the specific ways technology may enhance condition-specific pathways. Differing interpretations of the NHSE instructions between different health care sectors and a lack of clarity in definitions, as well as use of hospital-centric language within national guidance, were considered hindrances to convening a system approach. Furthermore, narrow parameters of success measures in terms of goals and outcomes of VWs, unrealistic timescales for planning and delivery, lack of interoperability of technology and time-consuming procurement procedures, liability concerns, and patient suitability for technology-enabled home-based care were identified as barriers to implementation. Motivated and passionate clinical leads were considered key to successful implementation. VWs have the potential to reform patient-centered care in England and were considered a promising approach by commissioners in this study. However, there should be greater clarity over definitions and specifications for technology enablement and evidence provided about how technology can enhance patient care. The use of less hospital-centric language, a greater focus on patient-centered measures of success, and more time allowance to ensure the development of technology-enabled VW services that meet the needs of patients and staff could enhance adoption and implementation.

Structural dynamics of contractile injection systems

The dynamics of many macromolecular machines is characterized by chemically mediated structural changes that achieve large-scale functional deployment through local rearrangements of constitutive protein subunits. Motivated by recent high-resolution structural microscopy of a particular class of such machines, contractile injection systems (CISs), we construct a coarse-grained semianalytical model that recapitulates the geometry and bistable mechanics of CISs in terms of a minimal set of measurable physical parameters. We use this model to predict the size, shape, and speed of a dynamical actuation front that underlies contraction. Scaling laws for the velocity and physical extension of the contraction front are consistent with our numerical simulations and may be generally applicable to related systems.

A Study of Measurable Parameters of Sustainability Practices inRural Built Environment: An Indian Perspective

A Study of Measurable Parameters of Sustainability Practices inRural Built Environment: An Indian Perspective

Microstomia is associated with functional impairment and is a poor prognostic factor in systemic sclerosis – a single center observational study with survival analysis

BackgroundObjectives were to assess the mouth opening ability (MOA) among patients with systemic sclerosis (SSc) in comparison to a healthy control population. The impact of microstomia (decrease in any of the MOA parameters) on physical performance and long-term survival was also investigated.MethodsInterincisal (ID), interlabial (LD), the intercommissural distances at both opened mouth and closed mouth (OW, CW) and the oral area (OA) and circumference (OC) all were assessed in 131 SSc patients. Microstomia was defined based on the oral aperture values of a healthy control group (n = 63) with similar median age and sex distribution. Tests evaluating functional performance were performed. Survival analysis by univariate and multivariate Cox regression analysis was performed.ResultsMicrostomia was present in 56.5% of the entire SSc cohort. Patients with microstomia had higher number of contractures compared to those with preserved oral aperture parameters (median 10 vs. 7, p < 0.01). LD, OA and OC correlated negatively with the number of joint contractures, both in the entire SSc cohort and separately in the diffuse (dcSSc) and limited cutaneous subsets (lcSSc), (rho: between − 0.267 and − 0.516, p < 0.05). Reduced ID was associated with worse Health Assessment Questionnaire Disability Index (HAQ-DI) only in dcSSc while reduced LD was linked to increased HAQ-DI scores in both SSc subsets. Decreased OA upon enrollment was associated with an increased risk in mortality by multivariate Cox regression analysis (HR: 2.74; 95% CI, 1.15–6.53).ConclusionsMicrostomia was associated with joint damage, and higher overall disability based on HAQ-DI. Interlabial distance was a beneficial, convenient measurable parameter to characterize oral aperture. Oral area was an independent poor prognostic factor regarding long-term survival.

COMPARISON OF CONFOCAL SENSOR FOR DIAMETER MEASUREMENT WITH MEASURING PROBE

The measurement and inspection of products and their dimensions in industry plays an important role in determining the quality of a product. Correct measurement is a key factor in production. Many companies are subject to stringent safety standards and specific product requirements. Accurate measurement ensures compliance with these guidelines, avoiding fines, penalties and legal complications. Effective measurement processes can identify inefficiencies, defects and areas for improvement, leading to cost savings. By detecting defects early in the production cycle, manufacturers can reduce waste and optimize resource utilization thereby reducing overall production costs. A fundamental principle of good measurement is to ensure that the measuring instruments are suitable for the specific application and that they meet the measurement requirements for the measurement parameter. The objective of the experiment is to verify and compare the measurement capability of a confocal chromatic sensor against a measurement probe used in production. The parameter to be measured is the diameter, since the correct diameter plays an essential role in the production of shafts or other cylindrical products. The results contained in the thesis highlight the importance and differences between the different measuring devices and the qualification to use the measurement of a given parameter.

Stability in fecal metabolites amid a diverse gut microbiome composition: a one-month longitudinal study of variability in healthy individuals

ABSTRACT An extensive network of microbial-host interactions exists in the gut, making the gut microbiome a complex ecosystem to untangle. The microbial composition and the fecal metabolites are important readouts to investigate intricate microbiota-diet-host interplay. However, this ecosystem is dynamic, and it is of interest to understand the degree and timescale of changes occurring in the gut microbiota, during disease as well as in healthy individuals. Cross-sectional study design is often used to investigate the microbiome, but this design provides a static snapshot and cannot provide evidence on the dynamic nature of the gut microbiome. Longitudinal studies are better suited to extrapolate causation in a study or assess changes over time. This study investigates longitudinal change in the gut microbiome and fecal metabolites in 14 healthy individuals with weekly sampling over a period of one-month (four time points), to elucidate the temporal changes occurring in the gut microbiome composition and fecal metabolites. Utilizing 16S rRNA amplicon sequencing for microbiome analysis and NMR spectroscopy for fecal metabolite characterization, we assessed the stability of these two types of measurable parameters in fecal samples during the period of one month. Our results show that the gut microbiome display large variations between healthy individuals, but relatively lower within-individual variations, which makes it possible to uniquely identify individuals. The fecal metabolites showed higher stability over time compared to the microbiome and exhibited consistently smaller variations both within and between individuals. This relative higher stability of the fecal metabolites suggests a balanced, consistent output even amid individual’s differences in microbial composition and they can provide a viable complementary readout to better understand the microbiome activity.

A temporal convolution network-based just-in-time learning method for industrial quality variable prediction

Real-time acquisition of quality variables is paramount for enhancing control and optimization of industrial processes. Process modeling methods, such as soft sensors, offer a means to predict difficult-to-obtain quality variables using easily measurable process parameters. However, the dynamic nature of industrial processes poses significant challenges to modeling. For instance, conventional models are typically trained offline using historical data, rendering them incapable of adapting to real-time changes in data distribution or environmental conditions. To tackle this challenge, we introduce a novel approach termed the Residual Temporal Attention Temporal Convolution Network (RTA-TCN) and propose a just-in-time learning method based on RTA-TCN for industrial process modeling. The RTA-TCN model incorporates temporal attention into TCN, enabling the integration of previous time-step process variables into the current ones, as well as the fusion of internally relevant features among inputs. Moreover, to prevent the partial loss of original information during feature integration, residual connections are introduced into the temporal attention mechanism. These connections facilitate the retention of original feature information to a maximal extent while integrating relevant features. Consequently, the proposed RTA-TCN demonstrates significant advantages in handling the non-linearity and long-term dynamic dependencies inherent in industrial variables. Additionally, the proposed just-in-time learning method leverages RTA-TCN as a local model and updates it in real-time using online industrial data. This just-in-time learning method enables effective adaptation to varying data distributions and environmental conditions. We validate the performance of our method using two industrial datasets (Debutanizer Column and Sulfur Recovery Unit).

A codifiable methodology for estimating pallet sliding displacements on steel racking systems

AbstractTo facilitate the logistic processes within a modern warehouse, the contents of steel racking systems are not mechanically connected to the supporting beams, allowing a content‐sliding mechanism to develop when static friction is exceeded. Given that the mass of contents is dominant, this is beneficial for limiting the apparent inertia. On the other hand, pallet fall‐off may occur during strong seismic excitations, which is a failure mode that is not addressed by current seismic design processes and guidelines for racks. Along these lines, a codifiable methodology is proposed for estimating sliding displacements on steel racking systems, based on the statistical interpretation of a large set of response history analyses, using different rack configurations and ground motions. Firstly, a multi‐parametric analysis is conducted using simplified rack models to (i) select the intensity measure and engineering demand parameter that can best describe the problem of pallet sliding and (ii) identify the salient rack characteristics that dominate sliding behavior. Thereafter, a series of multi‐stripe analyses are performed using 180 rack realizations with different feature combinations to derive a so‐called, Empirical Sliding Prediction Equation (ESPE) by following a three‐step procedure: (a) perform regression on maximum sliding, (b) perform regression on the normalized sliding profile, and (c) combine steps a‐b to derive the denormalized profile at a given confidence level. The proposed empirical relationships are then validated through a comparison between the observed and fitted sliding displacements in three rack case studies.

On adaptive resilient secondary control for DC microgrids under false data injection attacks

AbstractDistributed cooperative control strategies for DC microgrids have been rapidly evolving in recent years. However, introducing a cyber layer to enhance robustness, scalability, and reliability also exposes the system to potential cyber‐attacks. The damage inflicted by such attacks on the system performance can be catastrophic, reaching a point where it may devastate the system normal operation. By using model reference adaptive control (MRAC), this article proposes a resilient approach that does not require an accurate model of the system and despite the uncertainties for detecting false data injections into the reference DC voltage and simultaneously mitigating their adverse effects on the system stability and performance. The proposed technique employs an observer to detect possible false data injections in an online manner. By emulating the behavior of an ideal reference model, the MRAC ensures adaptive adjustments of the control parameters over time to mitigate the negative effects of potential attacks effectively and despite non‐idealities such as measurement noise, parameter variations, and environmental changes in DC microgrids, the MRAC effectively manages false data injection attacks. Simulation studies are conducted using diverse scenarios involving a three‐node DC microgrid to show the effectiveness of the proposed method.

Radiation dermatitis in the hairless mouse model mimics human radiation dermatitis

Over half of all people diagnosed with cancer receive radiation therapy. Moderate to severe radiation dermatitis occurs in most human radiation patients, causing pain, aesthetic distress, and a negative impact on tumor control. No effective prevention or treatment for radiation dermatitis exists. The lack of well-characterized, clinically relevant animal models of human radiation dermatitis contributes to the absence of strategies to mitigate radiation dermatitis. Here, we establish and characterize a hairless SKH-1 mouse model of human radiation dermatitis by correlating temporal stages of clinical and pathological skin injury. We demonstrate that a single ionizing radiation treatment of 30 Gy using 6 MeV electrons induces severe clinical grade 3 peak toxicity at 12 days, defined by marked erythema, desquamation and partial ulceration, with resolution occurring by 25 days. Histopathology reveals that radiation-induced skin injury features temporally unique inflammatory changes. Upregulation of epidermal and dermal TGF-ß1 and COX-2 protein expression occurs at peak dermatitis, with sustained epidermal TGF-ß1 expression beyond resolution. Specific histopathological variables that remain substantially high at peak toxicity and early clinical resolution, including epidermal thickening, hyperkeratosis and dermal fibroplasia/fibrosis, serve as specific measurable parameters for in vivo interventional preclinical studies that seek to mitigate radiation-induced skin injury.

THE RESILIENCE OF CRITICAL INFRASTRUCTURE AND VITAL FUNCTIONS AND SERVICES: THE FORMALIZATION OF THE TASKS AND CONTENT OF STAKEHOLDER’S ACTIONS

In the article, the author analyzes the content and tasks of activity to implement the concept of resilience. The article begins with a short overview of the theoretical background of the resilience concept and examines legislation on national resilience recently approved in several countries. The author then demonstrates the relevance of the research regarding the resilience of life-supporting vital functions and services and of critical infrastructure under Ukrainian law. The main tasks and challenges of stakeholders in a certain domain of regulation are outlined, along with an approach to rationalize the content of activities. Next, examples of typical response measures by stages of the crisis response cycle to ensure resilience of certain areas of regulation are given. Ukraine’s response to power supply disruptions due to the destruction of the energy infrastructure by Russia in autumn-winter of 2022–2023 are summarized. The author provides a conceptual model for the formalization of objectives, goal setting and development of regulatory tools to ensure the resilience of vital functions and services and functioning of critical infrastructure. This model is extended with a description of the approach for designing the target parameters of response measures and for determining the necessary and possible levels of performance of critical infrastructure or/and vital services within the goals of the area of regulation in focus. This includes an example of the usage of the model developed to justify measures for ensuring continuity of power supply to communities. The author then proposes principles to determine the actors responsible for resilience planning at different levels of governance. He demonstrates the differences in the remit and authorities of various participants and the need to develop a separate formal tool, which prescribes the activities of all participants involved in ensuring community resilience. Finally, the author outlines a proposed structure and content of community resilience plans.

Preoperative Delta Neutrophil Index, Platelet Lymphocyte Ratio and Immature Granulocyte Count for Differentiating Metastatic Colon Cancer from Non-Metastatic Colon Cancer: A Retrospective Study.

Immature granulocytes show bone marrow activation before neutrophil response and there are studies in the literature showing that the number of immature granulocytes is an auxiliary marker in the diagnosis and treatment of different diseases. The Delta Neutrophil Index (DNI), Immature Granulocyte Count (IGC) have previously been studied as markers in thyroid and breast cancers. The aim of this study was to determine whether immature granulocyte IGC and DNI values measured in preoperative blood parameters have a diagnostic benefit for the detection of advanced colon cancer. A study was conducted on patients who had undergone selective operation for colon cancer in our clinic from February 2015 to February 2020. The patients were divided into two groups: early stage (stage I-III) and advanced stage (stage IV) colon cancer. The IGC and DNI values as well as other hematological parameters, demographic parameters (sex, age) in these two groups were compared. A total of 43 patients with mean age 67.47 (35-96) years were included in the study. Eighteen of the patients were male and 25 were female. When the early stage and advanced stage colon cancer groups were compared, no statistically significant difference was found between age, sex, white blood cell count, lymphocyte-to-monocyte ratio, eosinophil count, basophil count, mean platelet volume and: systemic immune-inflammation index score. It was observed that platelet-to-lymphocyte ratio, IGC and DNI or Immature Granulocyte Percentage (IGP) values were statistically significantly higher in the metastatic colon cancer group compared to the non-metastatic group. When the specificity and sensitivity of laboratory markers in metastatic colon cancer were examined, it was observed that the specificity and sensitivity of DNI or IGP and IGC were statistically higher than other values. DNI, IGC and PLR values, which are the parameters measured in the preoperative period are easily measurable laboratory parameters and do not involve additional costs in differentiating metastatic from non-metastatic colon cancer in the preoperative period.

Higher CALLY index levels indicate lower sarcopenia risk among middle-aged and elderly community residents as well as hospitalized patients.

The C-reactive protein-albumin-lymphocyte (CALLY) index, which integrates albumin, lymphocytes, and C-reactive protein levels, has emerged as a novel method to assess nutritional and inflammatory statuses in patients. This study examined the correlation between the CALLY index and sarcopenia risk using two cohorts: 1804 community dwellers from the NHANES database in the United States and 139 patients from the Department of Gerontology at Kunshan Hospital, China. In the US community cohort, RCS curve analysis was used to examine the non-linear relationship between inflammatory/nutritional markers and sarcopenia, subgroup analysis was also conducted. Logistic regression was employed to evaluate the association between the CALLY index and the risk of sarcopenia in both cohorts. Results demonstrated a significant non-linear relationship between the CALLY index and the risk of sarcopenia (P < 0.001). Elevated levels of the CALLY index are independently linked to a decreased risk of sarcopenia in both community residents (OR = 0.35, 95% CI 0.20-0.57, Q3 CALLY index and OR = 0.26, 95% CI 0.11-0.56, Q4 CALLY index) and hospitalized patients (OR = 0.35, 95% CI 0.12-0.96). This finding identified low CALLY index as a conveniently measurable parameter, serving as a nutritional and inflammatory risk factor for sarcopenia.

Waist circumference as a parameter in school-based interventions to prevent overweight and obesity - a systematic review and meta-analysis

BackgroundPreventing childhood obesity remains an important public health issue worldwide. Since visceral fat in particular is understood as an important risk factor for many chronic diseases, waist circumference is recommended as a measurement parameter for global obesity surveillance. This systematic review and meta-analysis focused on waist circumference as an outcome parameter for studies of school-based interventions to prevent overweight and obesity.MethodsA systematic literature search was conducted at the end of 2019 in nine data bases, including Medline and Embase, in order to identify relevant studies evaluating interventions in schools aimed at preventing obesity. Eligibility criteria admitted randomised and non-randomised controlled trials. After screening titles, abstracts and full texts, the data of the identified studies were systematically extracted. Risk of bias was assessed according to study type with the appropriate Cochrane Risk of Bias Tool. The review gives a qualitative overview over all included studies structured by extracted data. Separate meta-analyses were done for the outcome mean difference in change in waist circumference, measured in cm or reported as z-score value, using an inverse variance random-effects model due to study design.ResultsA total of 2421 publications were screened based on titles, abstracts and full texts. Complemented by results of a former systematic literature search 44 studies were identified for inclusion, comprising a total of 39.837 participants (age range: 6 to 18 years). Nearly half of the studies were conducted in Europe, two-thirds combined diet and exercise-based interventions. Likewise two thirds of the studies were conducted as cluster-randomised trials. Most of the reported effects favoured the experimental groups, indicating the basic effectiveness of school-based measures. Based on reported data, only one third of the studies could be included in the meta-analyses. For the difference in mean change of the outcome parameter waist circumference measured in cm (95% CI), we found a pooled effect estimate of -0.95 (-1.87; -0.46). For the difference in mean change of the outcome parameter waist circumference reported as z-score value (95% CI), the pooled effect estimate was -0.10 (-0.15; -0.05). Both effect estimates were in favour of the experimental group. The overall effect sizes were small with a p-value < 0.05.ConclusionsPooled effect estimates were small but in favour of the experimental groups. The same applies to the majority of the effects reported in the included studies. The included cluster of randomised controlled trials demonstrated an especially sound methodological standard. The possibility of achieving larger effects in studies of preventive interventions and health promotion is limited. Schools can only realise their full potential in preventing overweight and obesity in children and adolescents if they are accompanied by measures in other areas of the obesogenic environment.