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The build-up of large-scale COVID-19 testing required an unprecedented effort of coordination within decentralized healthcare systems around the world. The aim of the study was to elucidate the challenges of vertical policy coordination between non-political actors at the national and regional levels regarding this policy issue, using Sweden as our case.

Interviews with key actors at the national and regional levels were analyzed using an adapted version of a conceptualization by Adam et al. (2019), depicting barriers to vertical policy coordination.

Our results show that the main issues in the Swedish context were related to parallel sovereignty and a vagueness regarding responsibilities and mandates as well as complex governmental structures and that this was exacerbated by the unfamiliarity and uncertainty of the policy issue. We conclude that understanding the interaction between the comprehensiveness and complexity of the policy issue and the institutional context is crucial to achieving effective vertical policy coordination.

Many studies have focused on countries’ overall pandemic responses, but in order to improve the outcome of future pandemics, it is also important to learn from more specific response measures.

Mobile learning has seen tremendous growth over the years. Like any other software application, usability is one of the key concerns in its successful implementation. There is a lack of study that provides a comprehensive overview of usability testing of mobile learning applications. Motivated by this a mapping study is conducted.

A systematic mapping study was conducted using 51 papers retrieved from the Scopus database published between 2005 and 2022 that reported on usability testing of mobile learning applications.

The key findings suggest that research is expected to expand in the near future. User-based testing is the commonly used method, while data are collected mainly through questionnaires, observation and interviews. Testing is mainly conducted in a controlled environment.

The study provides (1) an evidence-based discussion on usability testing of mobile learning applications, (2) an up-to-date map on state of the art on usability testing of mobile learning applications and (3) providing direction for further research to scientifically strengthen the field.

Testing business processes is crucial to assess the compliance of business process models with requirements. Automating this task optimizes testing efforts and reduces human error while also providing improvement insights for the business process modeling activity. The primary purposes of this paper are to conduct a literature review of Business Process Model and Notation (BPMN) testing and formal verification and to propose the Business Process Evaluation and Research Framework for Enhancement and Continuous Testing (bPERFECT) framework, which aims to guide business process testing (BPT) research and implementation. Secondary objectives include (1) eliciting the existing types of testing, (2) evaluating their impact on efficiency and (3) assessing the formal verification techniques that complement testing.

The methodology used is based on Kitchenham's (2004) original procedures for conducting systematic literature reviews.

Results of this study indicate that three distinct business process model testing types can be found in the literature: black/gray-box, regression and integration. Testing and verification approaches differ in aspects such as awareness of test data, coverage criteria and auxiliary representations used. However, most solutions pose notable hindrances, such as BPMN element limitations, that lead to limited practicality.

The databases selected in the review protocol may have excluded relevant studies on this topic. More databases and gray literature could also be considered for inclusion in this review.

Three main originality aspects are identified in this study as follows: (1) the classification of process model testing types, (2) the future trends foreseen for BPMN model testing and verification and (3) the bPERFECT framework for testing business processes.

Fuselage structures are subjected to combinations of axial, bending, shear and differential pressure loads. The validation of advanced metallic and composite fuselage designs against such loads is based on the full-scale testing of the fuselage barrel, which, however, is highly demanding from a time and cost viewpoint. This paper aims to assist in scaling-down the experimentation to the stiffened panel level which presents the opportunity to validate state-of-the-art designs at higher rates than previously attainable.

Development of a methodology to successfully design tests at the stiffened panel level and realize them using advanced, complex and adaptable test-rigs that are capable of introducing independently a set of distinct load types (e.g. internal overpressure, tension, shear) while applying appropriate boundary conditions at the edges of the stiffened panel.

A baseline test-rig configuration was developed after extensive parametric modelling studies at the stiffened panel level. The realization of the loading and boundary conditions on the test-rig was facilitated through innovative supporting and loading system set-ups.

The proposed test bench is novel and compared to the conventional counterparts more viable from an economic and manufacturing point of view. It leads to panel responses, which are as close as possible to those of the fuselage barrel in-flight and can be used for the execution of static or fatigue tests on metallic and thermoplastic curved integrally stiffened full-scale panels, representative of a business jet fuselage.

This study aims to evaluate the dynamics between healthcare resource capacity expansion and disease spread. Further, the study estimates the resources required to respond to a pandemic appropriately.

This study adopts a system dynamics simulation and scenario analysis to experiment with the modification of the susceptible exposed infected and recovered (SEIR) model. The experiments evaluate diagnostic capacity expansion to identify suitable expansion plans and timelines. Afterwards, two popularly used forecasting tools, artificial neural network (ANN) and auto-regressive integrated moving average (ARIMA), are used to estimate the requirement of beds for a period when infection data became available.

The results from the study reflect that aggressive testing with isolation and integration of quarantine can be effective strategies to prevent disease outbreaks. The findings demonstrate that decision-makers must rapidly expand the diagnostic capacity during the first two weeks of the outbreak to support aggressive testing and isolation. Further, results confirm a healthcare resource deficit of at least two months for Delhi in the absence of these strategies. Also, the study findings highlight the importance of capacity expansion timelines by simulating a range of contact rates and disease infectivity in the early phase of the outbreak when various parameters are unknown. Further, it has been reflected that forecasting tools can effectively estimate healthcare resource requirements when pandemic data is available.

The models developed in the present study can be utilised by policymakers to suitably design the response plan. The decisions regarding how much diagnostics capacity is needed and when to expand capacity to minimise infection spread have been demonstrated for Delhi city. Also, the study proposed a decision support system (DSS) to assist the decision-maker in short- and long-term planning during the disease outbreak.

The study estimated the resources required for adopting an aggressive testing strategy. Several experiments were performed to successfully validate the robustness of the simulation model. The modification of SEIR model with diagnostic capacity increment, quarantine and testing block has been attempted to provide a distinct perspective on the testing strategy. The prevention of outbreaks has been addressed systematically.

The purpose of this work is to optimize the monitoring of vibrations on dynamometric test rigs for railway brakes. This is a quite demanding application considering the continuous increase of performances of high-speed trains that involve higher testing specifications for brake pads and disks.

In this work, authors propose a mixed approach in which relatively simple finite element models are used to support the optimization of a diagnostic system that is used to monitor vibration levels and rotor-dynamical behavior of the machine. The model is calibrated with experimental data recorded on the same rig that must be identified and monitored. The whole process is optimized to not interfere with normal operations of the rig, using common inertial sensor and tools and are available as standard instrumentation for this kind of applications. So at the end all the calibration activities can be performed normally without interrupting the activities of the rig introducing additional costs due to system unavailability.

Proposed approach was able to identify in a very simple and fast way the vibrational behavior of the investigated rig, also giving precious information concerning the anisotropic behavior of supports and their damping. All these data are quite difficult to be found in technical literature because they are quite sensitive to assembly tolerances and to many other factors. Dynamometric test rigs are an important application widely diffused for both road and rail vehicles. Also proposed procedure can be easily extended and generalized to a wide value of machine with horizontal rotors.

Most of the studies in literature are referred to electrical motors or turbomachines operating with relatively slow transients and constant inertial properties. For investigated machines both these conditions are not verified, making the proposed application quite unusual and original with respect to current application. At the same time, there is a wide variety of special machines that are usually marginally covered by standard testing methodologies to which the proposed approach can be successfully extended.

This paper aims to simulate the potential impact of increasing non-performing loans (NPLs) on capital adequacy, interest income and firm value of banks and credit unions in the Eastern Caribbean Currency Union (ECCU) using stress tests.

A financial stress testing model was deployed at the levels of individual financial intermediary (FI), sectoral loan portfolio composition, individual member country, and the ECCU collectively, to investigate the impact of NPL shocks on FI stability.

The authors find that shocks impact the capital adequacy of banks less than that of credit unions, but that firm value of banks is more susceptible to increases in NPLs. Interest income responses to NPL shocks were linked to credit exposure from the tourism sector, which also reduced capital adequacy more than other economic sectors. Findings show that while the COVID-19 pandemic occasioned some increase in NPLs, the magnitude of impact was significantly mitigated by pro-stability policies including loan repayment moratoria and restructuring, guidance on the distribution of profits and deleveraging by financial institutions leading up to 2020.

The paper is among the first to use stress testing on the Caribbean in response to the COVID-19 pandemic. Past studies which have used stress test models in the region have not explicitly investigated the impact of credit shocks on risk-weighted assets or interest income as done herein, nor do they include credit unions in the modeling. The results offer novel evaluations as well as implications for FIs in other developing economies, especially those that share a comparable financial and economic architecture.

The purpose of this study was to provide an outline of the process of developing an on-road driving test route and rating form. Comprehensive evaluation of medical fitness to drive should comprise of an off-road and an on-road assessment. Much research attention has focussed on the off-road phase of assessment, while there is less standardisation evident in the completion and measurement of the on-road phase of fitness-to-drive assessment.

A scholarship of practice approach was used to inform the development of an on-road test route and an associated generic on-road assessment tool that was guided by research evidence and best practice recommendations.

A step-by-step guide, outlining seven recommended phases in the development of an on-road route for the assessment of fitness to drive that aligns with best practice recommendations, was developed. A preliminary generic on-road assessment tool (the Maynooth–Trinity Driving Test) that includes higher-order cognition alongside element of strategic, tactical and operational driving ability was developed and piloted alongside the newly developed on-road test route.

This paper offers an overview of an approach to developing evidence-based on-road test routes and an associated generic assessment tool that may assist occupational therapists and on-road driving assessors establish a standard practice for testing on-road behaviour as part of a comprehensive approach to evaluate fitness to drive.

Despite the many advantages this type of equipment offers, there are still some major drawbacks. Linear cutting machine (LCM) cannot accurately simulate the true rock-cutting process as 1. it does not account for the circular path along which tunnel boring machine (TBM) disk cutters cut the tunnel face, 2. it does not accurately model the position of a disk cutter on the cutterhead, 3. it cannot perfectly replicate the rotational speed of a TBM. To enhance the knowledge of these issues and in order to mimic the real rock-cutting process, a new lab testing equipment was developed by Hyundai Engineering and Construction.

A new testing machine called rotary cutting machine (RCM) is designed to simulate the excavation process of hard-rock TBMs and includes features such as TBM cutterhead, RPM simulation, constant normal force mode and constant penetration rate mode. Two sets of tests were conducted on Hwandeung granite using different disk cutter sizes to analyze the cutting forces in various excavation modes. The results are analyzed using statistical analysis and dimensional analysis. A new model is generated using dimensional analysis, and its results are compared against the results of actual cases.

The effectiveness of the new RCM test was demonstrated in its ability to apply various modes of excavation. Initial analysis of chip size revealed that the thickness of the chips is largely dependent on the cutter spacing. Tests with varying RPM showed that an increase in RPM results in an increase in the normal force and rolling force. The cutting coefficient (CC) demonstrated a linear correlation with penetration. The optimal specific energy is achieved at an S/p ratio of around 15. However, a slightly lower S/p ratio can also be used in the design if the cutter specifications permit. A dimensional analysis was utilized to develop a new RCM model based on the results from approximately 1200 tests. The model's applicability was demonstrated through a comparison of TBM penetration data from 26 tunnel projects globally. Results indicated that the predicted penetration rates by the RCM test model were in good agreement with actual rates for the majority of cases. However, further investigation is necessary for softer rock types, which will be conducted in the future using concrete blocks.

The originality of the research lies in the development of Hyundai Engineering and Construction’s advanced full-scale laboratory rotary cutting machine (RCM), which accurately replicates the excavation process of hard-rock tunnel boring machines (TBMs). The study provides valuable insights into cutting forces, chip size, specific energy, RPM and excavation modes, enhancing understanding and decision-making in hard-rock excavation processes. The research also presents a new RCM model validated against TBM penetration data, demonstrating its practical applicability and predictive accuracy.

This paper aims to present two Anand’s model parameter sets for the multilayer silver–tin (AgSn) transient liquid phase (TLP) foils.

The AgSn TLP test samples are manufactured using pre-defined optimized TLP bonding process parameters. Consequently, tensile and creep tests are conducted at various loading temperatures to generate stress–strain and creep data to accurately determine the elastic properties and two sets of Anand model creep coefficients. The resultant tensile- and creep-based constitutive models are subsequently used in extensive finite element simulations to precisely survey the mechanical response of the AgSn TLP bonds in power electronics due to different thermal loads.

The response of both models is thoroughly addressed in terms of stress–strain relationships, inelastic strain energy densities and equivalent plastic strains. The simulation results revealed that the testing conditions and parameters can significantly influence the values of the fitted Anand coefficients and consequently affect the resultant FEA-computed mechanical response of the TLP bonds. Therefore, this paper suggests that extreme care has to be taken when planning experiments for the estimation of creep parameters of the AgSn TLP joints.

In literature, there is no constitutive modeling data on the AgSn TLP bonds.