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Attention, working memory, and executive control are commonly considered distinct cognitive functions with important reciprocal interactions. Yet, longstanding evidence from lesion studies demonstrated both overlap and dissociation in their behavioural expression and anatomical underpinnings, suggesting that a lower dimensional framework could be employed to further identify processes supporting goal-directed behaviour. Here, we describe the anatomical and functional correspondence between attention, working memory, and executive control by providing an overview of cognitive models as well as recent data from lesion studies and both invasive and noninvasive multimodal neuroimaging and brain stimulation. We emphasize the benefits of considering converging evidence from multiple methodologies centred on the identification of brain mechanisms supporting goal-driven behaviour. We propose that expanding on this approach should enable the construction of a comprehensive anatomo-functional framework with testable new hypotheses, and aid clinical neuroscience to understand and treat neuropathologies of executive functions.

Software project management (SPM) is a discipline that comprises of different topics, practice and theories. There are two dimensions in the knowledge of SPM, theoretical or concepts of SPM and; practical or experience of SPM. These two dimensions although grow separately but come across at one point that is experiential knowledge of SPM. To present these dimensions through a proper training, a practitioner needs to have a proper view on SPM process. In this paper we present a new framework for practicing SPM through a distinct simulation technique to bring on an in-process decision support system, supporting the proper training approach. The framework developed based on three different methods of simulation technique, discrete event simulation (DES), system dynamics (SD) and partially observable Markov decision process (POMDP).1

As mechanical simulations play an increasingly role in engineering projects, an appropriate integration of simulations into design-oriented product development processes is essential for efficient collaboration. To identify and overcome barriers between design and simulation departments, the BRIDGES approach was elaborated for barrier reduction in design engineering and simulation. This paper shows the industrial evaluation of the approach using a multi-method study of an online survey and focus group workshops. The experts' assessments were statistically analysed to build a connection matrix of barriers and recommendations. 59 participants from multiple industries with practical experience in the field contributed to the online survey, while 24 experts could be acquired for the focus group workshops. As a result of the workshops, both the data-based and the workshop-based part of the BRIDGES approach were assessed as beneficial to raise the efficiency of collaboration and practically applicable. This provides an empirically secured connection of barriers and suitable recommendations, allowing companies to identify and overcome collaboration barriers between design and simulation.

Background: Helicobacter pylori infection and its treatment still remain a challenge for human health worldwide. A variety of antibiotics and combination therapies are currently used to treat H. pylori induced ulcers and carcinoma; however, no effective treatment is available to eliminate the pathogen from the body. Additionally, antibiotic resistance is also one of the main reasons for prolonged and persistent infection. Aims: Until new drugs are available for this infection, vaccinology seems the only alternative opportunity to exploit against H. pylori induced diseases. Methods: Multiple epitopes prioritized in our previous study have been tested for their possible antigenic combinations, resulting in 169-mer and 183-mer peptide vaccines containing the amino acid sequences of 3 and 4 epitopes respectively, along with adjuvant (Cholera Toxin Subunit B adjuvant at 5’ end) and linkers (GPGPG and EAAAK). Results: Poly-epitope proteins proposed as potential vaccine candidates against H. pylori include SabA-HP0289-Omp16-VacA (SHOV), VacA-Omp16-HP0289-FecA (VOHF), VacA-Omp16-HP0289- SabA (VOHS), VacA-Omp16-HP0289-BabA (VOHB), VacA-Omp16-HP0289-SabA-FecA (VOHSF), VacA-Omp16-HP0289-SabA-BabA (VOHSB) and VacA-Omp16-HP0289-BabA-SabA (VOHBS). Structures of these poly-epitope peptide vaccines have been modeled and checked for their affinity with HLA alleles and receptors. These proposed poly-epitope vaccine candidates bind efficiently with A2, A3, B7 and DR1 superfamilies of HLA alleles. They can also form stable and significant interactions with Toll-like receptor 2 and Toll-like receptor 4. Conclusion: Results suggest that these multi-epitopic vaccines can elicit a significant immune response against H. pylori and can be tested further for efficient vaccine development.

Low information exchange in global production networks results in long response time to disruption and negative performance impact. Digitalization enables a more intensive information exchange. This paper analyses the performance of order management, quality problem resolution and engineering change management in production networks with respect to different disruptions and information flows. Cause-effect relationships are revealed based on a multi-method simulation model and statistical experiments. Using surrogate modelling and robust optimization, a target picture for information exchange is determined. The benefits of the approach are demonstrated using a case study for the production of metal-plastic parts for the automotive supplier industry.

This article contributes to ongoing debate about the effectiveness of information-based policy tools by evaluating environmental information posters using a novel eye-tracking method to examine vie...

An optimal control problem withphase constraints is considered, which contains control parameters both in the right-hand sides of the controlled system and in the initial conditions. To solve this complex problem, it is proposed first to reduce to a mathematical programming problem, and then to find the optimal parameter values and control functions, we use a multi-method algorithm consisting of linearization methods, the reduced gradient method, and the designed Lagrangian method

The literature on policy design provides insightful resources to improve policy evaluation. We compare how this literature addresses causation, evaluation, instrumentation, and intervention, based on different methodologies. Then, we explain how the realist approach can contribute to theory-based evaluation with multi-methods. We go through the process leading from the adoption of policy aims to the production of a policy outcome by a causal mechanism linking agenda setting to policy formulation, cross-sectorial coordination, political interplays, and this policy’s outcome. This hypothesis is then tested against a typology of policy instruments classified by the State resources. These instruments are hereby treated as expected empirical observations that provide an empirical basis to assess the theoretical process following a Bayesian logic. We eventually present a five-step protocol aimed at making realist policy evaluation easier, which includes process theorization and operationalization, empirical tests design, case selection and justification, congruence analysis, and deep within-case study.

Background Recruiting participants to a clinical study is a resource-intensive process with a high failure rate. The Scottish Health Research Register (SHARE) provides recruitment support service which helps researchers recruit participants by searching patients’ Electronic Health Records (EHRs). The current study aims to evaluate the performance of SHARE in participant recruitment. Methods Recruitment projects eligible for evaluation were those that were conducted for clinical trials or observational studies and finished before 2020. For analysis of recruitment data, projects with incomplete data were excluded. For each project we calculated, from SHARE records, 1) the fraction of the participants recruited through SHARE as a percentage of the number requested by researchers (percentage fulfilled), 2) the percentage of the potential candidates provided by SHARE to researchers that were actually recruited (percentage provided and recruited), 3) the percentage of the participants recruited through SHARE of all the potentially eligible candidates identified by searching registrants’ EHRs (percentage identified and recruited). Research teams of the eligible projects were invited to participate in an anonymised online survey. Two metrics were derived from research teams’ responses, including a) the fraction of the recruited over the study target number of participants (percentage fulfilled), and b) the percentage of the participants recruited through SHARE among the candidates received from SHARE (percentage provided and recruited). Results Forty-four projects were eligible for inclusion. Recruitment data for 24 projects were available (20 excluded because of missingness or incompleteness). Survey invites were sent to all the eligible research teams and received 12 responses. Analysis of recruitment data shows the overall percentage fulfilled was 34.2% (interquartile 13.3–45.1%), the percentage provided and recruited 29.3% (interquartile 20.6–52.4%) and percentage identified and recruited 4.9% (interquartile 2.6–10.2%). Based on the data reported by researchers, percentage fulfilled was 31.7% (interquartile 5.8–59.6%) and percentage provided and recruited was 20.2% (interquartile 8.2–31.0%). Conclusions SHARE may be a valuable resource for recruiting participants for some clinical studies. Potential improvements are to expand the registrant base and to incorporate more data generated during patients’ different health care encounters into the candidate-searching step.

Smart monitoring plays a principal role in the intelligent automation of manufacturing systems. Advanced data collection technologies, like sensors, have been widely used to facilitate real-time data collection. Computationally efficient analysis of the operating systems, however, remains relatively underdeveloped and requires more attention. Inspired by the capabilities of signal analysis and information visualization, this study proposes a multi-method framework for the smart monitoring of manufacturing systems and intelligent decision-making. The proposed framework uses the machine signals collected by noninvasive sensors for processing. For this purpose, the signals are filtered and classified to facilitate the realization of the operational status and performance measures to advise the appropriate course of managerial actions considering the detected anomalies. Numerical experiments based on real data are used to show the practicability of the developed monitoring framework. Results are supportive of the accuracy of the method. Applications of the developed approach are worthwhile research topics to research in other manufacturing environments.

Test smells are poor design and implementation choices that can affect the test code’s understanding and maintainability. Recent studies show the industry is not aware of the test smells concept, while software engineers commonly encounter obstacles to maintain test code. This study investigated test creation and maintenance strategies through developers’ perception of eight test smells types. We surveyed 87 software testers and interviewed eight to understand their view on test smells in practice. Our results show that most participants use manual strategies for creating and maintaining test cases. Based on data captured from software testers’ perspectives, this study contributes with possible directions and treatments to analyze test smells, seeking to understand how the test affects and potential solutions for test smells.

Heat waves are increasingly common in many countries across the globe, and also in Germany, where this study is set. Heat poses severe health risks, especially for vulnerable groups such as the elderly and children. This case study explores visitors’ behavior and perceptions during six weekends in the summer of 2018 at a six-month open-air horticultural show. Data from a face-to-face survey (n = 306) and behavioral observations (n = 2750) were analyzed via correlation analyses, ANOVA, and multiple regression analyses. Differences in weather perception, risk awareness, adaptive behavior, and activity level were observed between rainy days (maximum daily temperature < 25°C), warm summer days (25 - 30°C), and hot days (> 30°C). Respondents reported a high level of heat risk awareness, but most (90 %) were unaware of actual heat warnings. During hot days, more adaptive measures were reported and observed. Older respondents reported taking the highest number of adaptive measures. We observed the highest level of adaptation in children, but they also showed the highest activity level. Based on our results we discuss how to facilitate individual adaptation to heat stress at open-air events by taking the heterogeneity of visitors into account. In order to mitigate negative health outcomes for citizens in the future, we argue for tailored risk communication aimed at vulnerable groups.

This paper examines grid interfaces which are currently used in many musical devices and instruments. This type of interface concept has been rooted in the NIME community since the early 2000s. We provide an overview of research projects and commercial products and conducted an expert interview as well as an online survey. In summary this work shares: (1) an overview on grid controller research, (2) a set of three usability issues deduced by a multi method approach, and (3) an evaluation of user perceptions regarding persistent usability issues and common reasons for the use of grid interfaces.

This study of Media Lengua examines production differences between mid and high vowels in order to identify the major correlates that distinguish these vowel types. The Media Lengua vowel system is unusual in that it incorporates lexical items originating in Spanish’s five-vowel system into a three-vowel system inherited from Quichua, resulting in high degrees of overlap between the front versus back, mid and high vowel pairs /e, i/ and /o, u/ in F1xF2 space. As Media Lengua speakers utilize and differentiate between all five vowels despite the large degree of acoustic overlap between mid and high vowels, this raises the question of what other correlates beyond F1 and F2 might be involved. To address this, our study looks at a range of variables, both acoustic and qualitative, in a multi-method approach using both 'factor analysis for mixed data and linear mixed effects regression modelling'. Each method provides a unique view on the correlates of vowel differentiation in Media Lengua. Taken together, our results indicate that Media Lengua speakers rely on both social and linguistic contextual cues to distinguish mid from high vowels, which overlap in acoustic space (F1 and F2).

Dissolved Gas Analysis (DGA) is the most effective method for detecting the gas abnormality in transformer insulating oil due to the thermal and electrical stresses received when the transformer operates. Various DGA interpretation techniques have developed rapidly. Each has its advantages and disadvantages. However, it is possible to misinterpret one oil sample. Besides that, the engineer's experiences and knowledge still have the most significant role in predicting the DGA sample subjectively. The multi-method interpretation technique is a method that is quite relevant to cover various techniques in increasing consistency and accuracy rate. This paper proposes Duval Pentagon Method (DPM) integration as the recent interpretation of the multi-method techniques. The method was developed based on IEC 10 TC database, then validated with 52 samples from previous researches. The results showed that there was a significant increase in accuracy and consistency rate with the multi-method using DPM integration. This method produces the highest level of accuracy, 96.15%, and consistency of 90.48% compared to others DGA interpretation techniques.

Integrating sustainability in humanitarian operations has been seen as a promising approach toward effective and long-term solutions. During disaster emergency management, the evacuation determines the risk of loss in a disaster. To better understand the effectiveness of the evacuation plan while considering the sustainability standpoint, this paper develops a multi-method simulation (MMS) approach to evaluate evacuation time, load balance of the shelters, and CO2 emission. The MMS integrating Agent-Based Modeling (ABM) and Discrete-Event Simulation (DES) incorporates evacuation decision-making and evacuation processes. Comparative analysis shows that the MMS outperforms the use of ABM solely. The simulation results indicate over-utilization and imbalanced load among the shelters, implying a need to expand shelters’ capacity and to revisit the evacuation plan concerning the location of the assembly points and the shelters and the resource allocation. Evacuation behavior heading to the nearest assembly point instead of the designated assembly point based on the evacuation plan worsens the imbalanced load among the shelters and results in higher CO2 emissions by 8%. The results demonstrate the necessity to include evacuation decision-making (social dimension) on top of the technical dimension and to adopt sustainable performance indicators in planning the evacuation sustainably. Avenues for future research are also discussed.

Tablets on the shop floor need handles because user requirements for handling differ from tablet usage in leisure time. The ergonomics of such handles is under-researched, resulting in a lack of methods for their design and evaluation. In this paper, we present a multi-method evaluation of handles for a shop floor tablet. We combine and compare results of focus groups and the Comfort Questionnaire for Hand tools (CQH) with electromyography (EMG). With a field and a laboratory study, we evaluate four handles in order to identify (i) the most ergonomically rated handle and (ii) the most efficient evaluation method. Results consist of an evaluated prototype, and data that shows the comparability of results from focus groups and questionnaires to results from EMG measurements. Classifying handles as tangible human machine interfaces, we suggest that subjective evaluation with focus groups and CQH is efficient to evaluate their ergonomic quality.

Considering that there is no single full reference image quality assessment method that could give the best performance in all situations, some multi-method fusion metrics were proposed. Machine learning techniques are often involved in such multi-method fusion metrics so that its output would be more consistent with human visual perceptions. On the other hand, the robustness and generalization ability of these multi-method fusion metrics are questioned because of the scarce of images with mean opinion scores. In order to comprehensively validate whether or not the generalization ability of such multi-method fusion IQA metrics are satisfying, we construct a new image database which contains up to 60 reference images. The newly built image database is then used to test the generalization ability of different multi-method fusion IQA metrics. Cross database validation experiment indicates that in our new image database, the performances of all the multi-method fusion IQA metrics have no statistical significant different with some single-method IQA metrics such as FSIM and MAD. In the end, a thorough analysis is given to explain why the performance of multi-method fusion IQA framework drop significantly in cross database validation.

This paper investigates measurement invariance as it relates to migration background using the Program for International Student Assessment measure of social belonging. We explore how the use of tw...

Many real-world decision problems consider more than one objective. These objectives usually conflict with each other. In the problem environments, many data and parameters are usually uncertain at the time of planning. So multi-objective optimization combined with uncertainty is a challenging research topic. To deal with the basic search process in such problems, in this paper, a new approach has been proposed that combines multiple population based algorithms under a single algorithm structure. To deal with the uncertainty, a dynamic scenario-based approach is developed and integrated with the search process, in which the number of scenarios is dynamically set during the solution process. This is a new way of solving multi-objective optimization problems under uncertainty. To judge the performance of the proposed approach, we have solved a set of standard test problems without uncertainty and a number of practical problems with uncertainty. The practical problems are the well-known dynamic economic and emission dispatch problems, with different combinations of energy sources. The experimental studies demonstrated that the proposed approach performs better than other well-known algorithms compared in this paper.

When evaluating personalized or adaptive systems, we frequently rely on one single evaluation objective and one single method. This remains us with “blind spots”. A comprehensive evaluation may require a thoughtful integration of multiple methods. This tutorial (i) demonstrates the wide variety of dimensions to be eval- uated, (ii) outlines the methodological approaches to evaluate these dimensions, (iii) pinpoints the blind spots when using only one ap- proach, (iv) demonstrates the benefits of multi-method evaluation, and (v) outlines the basic options how multiple methods can be integrated into one evaluation design. Participants familiarize with the wide spectrum of opportunities how adaptive or personalized systems may be evaluated, and have the opportunity to come up with evaluation designs that comply with the four basic options of multi-method evaluation. The ultimate learning objective is to stimulate the critical reflection of one’s own evaluation practices and those of the community at large.

Microfading testers have become widely accepted by the conservation science community for establishing and recommending appropriate lighting conditions that minimize damage to collections. These devices offer the opportunity of measuring the photostability of cultural heritage objects due to their optical setup, which allows to conduct and quantify accelerated photoaging over a spot of approximately 0.5 mm. Also, by using a high sensitivity photodetector it is possible to measure spectrocolorimetric change before it is perceived by the human eye. Although a considerable amount of testing is currently performed with these instruments, there are still safety concerns in terms of possible damage to the objects due to the use of a high intensity spot during testing. Nevertheless microfadeometry is widely considered a nondestructive technique. The advantages and disadvantages of several methods used to determine the beam shape and intensity profiles are described with the aim of providing various options to microfading researchers interested in characterizing their irradiation spots. Conventional and imaging methods were employed and are compared in terms of their accuracy, cost, reliability, and technical features. It has been found that both methods provide beam width measurements in satisfactory agreement within experimental error.

In a bid to help address the environmental footprints associated with products and services, life cycle assessment (LCA) applications have become increasingly popular throughout the years. This review summarizes some important methodological developments in recent years, such as the advent of dynamic LCA, as well as highlighting recent LCA applications in the context of plastics/recycling with a focus on their methodological choices. Furthermore, this review aims to offer a set of possible research lines to improve the gap between LCA and decision-making (policy). It was found that the majority of reviewed papers are mostly conservative in their methodological practice, employing mostly static analyses and making little use of other methods. In order to bridge the gap between LCA and policy, it is suggested to broaden system boundaries through the integration of dynamic modelling methods, incorporating interactions between fore- and background systems, and including behavioral components where relevant. In addition, advanced sampling routines to further explore and assess the policy space are recommended. This is of paramount importance when dealing with recycling processes as the molecules/polymers constituting the output of those processes have to be benchmarked in terms of costs and, crucially, their sustainability character against virgin ones.

The use of high resolution 3D point clouds and digital terrain models (DTM) from laserscanning or photogrammetry becomes more and more state of the art in landslide studies. Based on a multi-temporal terrestrial laserscanning (TLS) dataset of the deep-seated compound rockslide Laatsch, South Tyrol, we present a multi-method approach to characterize processes such as sliding, falling, toppling, and flows. Sliding is the predominant process of the Laatsch rockslide, accompanied by secondary processes such as rockfall, debris flows and erosion. The presented methods are applicable to all kind of 3D point clouds and not limited to TLS data. For remote sensing-based landslide analyses a distinction between two classes of surface processes is necessary: i) processes where the original surface is destroyed and no correlations between the shape and texture of the pre- and post-failure surfaces can be found (falls, rapid flows, rapid slides) and ii) processes where the surface is displaced without major surface changes (slow slides, slow flows and toppling). For processes where the original surface is destroyed, the distance between the pre- and post-failure terrain surface is measured with the aim to delineate the scarp and depositional area, and to quantify the failure volume as well as the scarp thickness. With DTMs of differences (DoD), the distance is measured along the plumb line. DoDs can be used to quickly and reliably assess the volume and extent of fall processes on flat to moderate slopes. For steep or even overhanging terrain, a 3D distance measurement approach must be used, where the distance is measured along the local surface normal. After 3D distance measurement, the volume of steep scarp areas can be calculated by first rotating, the point cloud into the horizontal plane (by making use of the average surface normal) and by interpolating the rotated 3D distance measurement values into a grid. Summing up the distances and multiplying with the cell area of the grid yields the scrap rupture volume. Remote sensing-based analyses of sliding and toppling processes are more complex compared to fall processes because the displaced surface patch must be detected in both surveys. Displacement analyses based on image correlation of ambient occlusion shaded relief images, together with DTMs of both epochs, are used to analyse the displacement of the entire rockslide area. The result is a map with displacement vectors. Disadvantages of image correlation are the coarse spatial resolution and the inability, as it is a 2.5D approach, to deal with steep slope parts. To analyse the displacement and toppling of steep rock walls a combination of the 3D distance measurement approach and an iterative closest point (ICP) based approach is applied. The 3D distance measurement values are clustered and used for a segmentation of the point cloud. In a next step, the ICP is applied on each of the resulting segments. This approach can deal with 3D displacements. The results are still sensitive towards the geometric contrast within the segments and not fully automated yet.

Code obfuscation is a kind of powerful protection technique for software code. At present, research on obfuscation techniques is mainly focused on analyzing the effect of single obfuscation method, leaving few discussions on cooperative obfuscation of multiple methods. This paper firstly presented a brief introduction of the concept and methods of code obfuscation, then designed and implemented an obfuscator with multiple obfuscation methods. Then, a collaborative obfuscation strategy suitable for multiple obfuscation methods is proposed in detail. Finally, we verified that the obfuscation strategy indeed improves the performance of obfuscation through experiments.

Traditional offline product ergonomics evaluation method is easy to be affected by the external environmental conditions and a single evaluation method cannot satisfy users’ demands for multi-channel experience of products, which promotes the diversified transformation of product ergonomics evaluation. In this paper, the evaluation methods of the online and offline product ergonomics and the selection principles of the product ergonomics evaluation methods are introduced, and the index system and the evaluation model based on online and offline multi-method collaboration are established. Part of indexes are selected to conduct the evaluation by users and experts with online and offline methods, by comparing the results, it is verified that there is no significant difference between online and offline method.

The proportion of older adults (OAs) is increasing throughout the globe. One of the most important needs of this age group is to maintain active social engagement, which can be achieved through smartphone applications offering active social engagement facilities. But OAs are often reluctant to use these apps, which leads to lower uptake over time. The underlying problem is pitfalls in guidance to develop smartphone applications for older adults. This leads to a lack of usage of the guidance by practitioners and hence the reflection of these guidelines on apps for older adults is limited. We have researched this problem space by undertaking a mixed-methods empirical study with 235 OAs. We elicited requirements that can be used in the design and development of smartphone applications for older adults. The contribution of this study is an evaluated classification of the derived recommendations, called ReDEAP (Recommendations for DEveloping smartphone applications for an aging Population). ReDEAP serves as a starting point for researchers and practitioners designing smartphone applications for older adults.

This paper investigates the feasibility and viability of providing power to Ada County, Idaho, using a distributed network of rooftop solar photovoltaic panels. Using a multi-disciplinary and multi-method modeling approach, a detailed simulation is performed where existing structures are retro-fitted with grid-tied solar photovoltaic systems using currently available technology. Feasibility is determined using simulated supply and demand per building, while viability is determined through standard financial metrics used in the energy sector. A major critique of solar energy comes from the vast amounts of space required to efficiently capture solar power, along with the inefficiencies created by transmission loss and intermittency. Under a system where structures become both producers and consumers of energy, with PV panels deployed in unused rooftop space, this paper mitigates those critiques and analyzes the results. Four case scenarios are discussed based on the perspectives of differing energy stakeholders; consumers, private firms, public utilities, and national governments.

BackgroundValue-based healthcare (VBHC) argues healthcare needs to be refocused to maximize value creation, defining value as the value quota (VQ) of outcomes important for the patient divided by the cost of the care. Value is central to the VBHC concept but could be an ambiguous term for professionals wanting to adopt the concept in an implementation process. We set out to explore the perception of value amongst different stakeholders who implement VBHC.Methods The perception of value, cost and VBHC was analysed using content analysis of semi-structured interviews from 19 clinicians and non-clinicians involved in implementation of VBHC. In addition, we exemplified the value quota (VQ) with data from a clinical trial to exemplify the possible association between patient reported outcome measurements (Kansas City Cardiomyopathy Questionnaire and the EQ5D ), their perception of care (n=248) and cost. ResultsClinicians described value as a dynamic concept dependent on the patient and the clinical setting, stating that improving outcomes was more important than containing costs. Value for non-clinicians appeared more driven by the interplay between the outcome and cost or resources. The quantitative data suggested a poor association between patients’ perception of value and VQ. ConclusionsOur findings indicate that there is great variation in how different stakeholders (clinicians, non-clinicians) perceive the key concept of value when implementing VBHC. The most dominant influence was the voice of clinicians, focusing on increasing treatment efficacy and improving medical outcomes but having a limited focus on cost and what matters to patients. Moreover, patients’ own perception of value provided during a care period was poorly connected to the calculated value quota. If the concept of value is defined primarly by clinicians’ own assumptions, there is a clear risk that history will simply be repeated and the need for innovation will not be met. A single-minded focus on value” could therefore result in missing the target. The patients’ and non-clinicians’ perception of value must also be integrated with the clinical perception, if VBHC is going to deliver on the promise to increase healthcare efficiency and effectiveness.

Multi-sectoral, interdisciplinary health research is increasingly recognizing integrated knowledge translation (iKT) as essential. It is characterized by diverse research partnerships, and iterative knowledge engagement, translation processes and democratized knowledge production. This paper reviews the methodological complexity and decision-making of a large iKT project called Seniors - Adding Life to Years (SALTY), designed to generate evidence to improve late life in long-term care (LTC) settings across Canada. We discuss our approach to iKT by reviewing iterative processes of team development and knowledge engagement within the LTC sector. We conclude with a brief discussion of the important opportunities, challenges, and implications these processes have for LTC research, and the sector more broadly.

Political decisions, adaptation planning, and impact assessments need reliable estimates of future climate change and related uncertainties. Different approaches to constrain, filter, or weight climate model simulations into probabilistic projections have been proposed to provide such estimates. Here six methods are applied to European climate projections using a consistent framework in order to allow a quantitative comparison. Focus is given to summer temperature and precipitation change in three different spatial regimes in Europe in the period 2041-2060 relative to 1995-2014. The analysis draws on projections from several large initial condition ensembles, the CMIP5 multi-model ensemble, and perturbed physics ensembles, all using the high-emission scenario RCP8.5. The methods included are diverse in their approach to quantifying uncertainty, and include those which apply weighting schemes based on baseline performance and inter-model relationships, so-called ASK (Allen, Stott and Kettleborough) techniques which use optimal fingerprinting to scale the scale the response to external forcings, to those found in observations and Bayesian approaches to estimating probability distributions. Some of the key differences between methods are the uncertainties covered, the treatment of internal variability, and variables and regions used to inform the methods. In spite of these considerable methodological differences, the median projection from the multi-model methods agree on a statistically significant increase in temperature by mid-century by about 2.5°C in the European average. The estimates of spread, in contrast, differ substantially between methods. Part of this large difference in the spread reflects the fact that different methods attempt to capture different sources of uncertainty, and some are more comprehensive in this respect than others. This study, therefore, highlights the importance of providing clear context about how different methods affect the distribution of projections, particularly the in the upper and lower percentiles that are of interest to 'risk averse' stakeholders. Methods find less agreement in precipitation change with most methods indicating a slight increase in northern Europe and a drying in the central and Mediterranean regions, but with considerably different amplitudes. Further work is needed to understand how the underlying differences between methods lead to such diverse results for precipitation.

Wildfires constitute a major natural hazard and pose huge risk to many regions of the world. The series of large fires across both hemispheres in recent years have led to inevitable questions about how human-induced climate change may be altering the character of such events. Providing answers to these questions is a crucial step to increasing resilience to major wildfires.Long-term projections produced by state-of-the-art climate models, even when reliable, are not always a suitable means of communicating risk. Methodologies to attribute trends in meteorological phenomena associated with high-impact events to anthropogenic influence have the potential to better communicate risk and guide adaptation strategies. While the link between a warming world and heat-related extremes (e.g. heatwaves and droughts) is reasonably well-understood, there is a lack of consensus on the most appropriate and effective methodological approach for many variables, potentially impacted by warming climate, such as wildfire attribution. The link with climate change remains poorly understood and wildfires have been largely ignored by attribution studies to date.As a first step towards the development of a seamless, globally-applicable framework for assessing past, present and future risk in wildfire danger, we present a global attribution analysis of wildfire danger. With initial focus on observational records, we use both established and novel empirical-statistical methods to attribute historical trends in episodes of extreme weather and climate conducive to wildfire ignition and spread. Particular consideration is given to the sensitivity of attribution findings to the spatial scale upon which the analysis is conducted. We also draw attention to a series of important, often overlooked, conceptual and technical challenges in event attribution, including validation and bias-correction of climate models and discuss the value of linking attribution of recent wildfire events with future risk assessment.

Multifaceted study of law, owing to complex social problems attached to it, calls for the combination of several methods of research. Integration rather than isolated application of methods of research leads to multi-method legal research (MMLR). It combines doctrinal and non-doctrinal research, qualitative and quantitative research, and a combination of various methods within each. This method is highly valuable as it looks at law from different angles, uses interdisciplinary research, collaborates with community or stakeholders, and avoids undetected errors arising from the use of mono-method. The synergy of using deductive and inductive reasoning enhances quality of research. The procedure of MMLR is not rigid. Therefore, research design should consider the suitability of combination; combination of methods should be linked with theory; sequential or simultaneous application of multiple methods should be carefully executed; and management of MMLR should be smooth. MMLR’s use in research on vulnerable groups, development issues, and biographical and behavioural studies is of great importance.

In order to develop valid and reliable instruments, psychometric validation should be conducted as an iterative process that “requires a multi-method assessment” (Schimmack, 2019, p. 4). In this study, a multi-method psychometric approach was applied to a recently developed and validated scale, the Affinity for Technology Interaction (ATI) scale (Franke, Attig, & Wessel, 2018). The dataset (N ​= ​240) shared by the authors of the scale (Franke et al., 2018) was used. Construct validity of the ATI was explored by means of hierarchical clustering on variables, and its psychometric properties were analysed in accordance with an extended psychometric protocol (Dima, 2018) by methods of Classical Test Theory (CTT) and Item Response Theory (IRT). The results showed that the ATI is a unidimensional scale (homogeneity H ​= ​0.55) with excellent reliability (ω ​= ​0.90 [0.88-0.92]) and construct validity. Suggestions for further improvement of the ATI scale and the psychometric protocol were made.

Design-loop adaptivity, which involves data-driven redesign of an instructional system based on student learning data, has shown promise in improving student learning. We present a general, systematic approach that combines new and existing data mining and instructional design methods to redesign intelligent tutors. Our approach is driven by the main goal of identifying knowledge components that are demonstrably difficult for students to learn and to optimize effective and efficient practice of them. We applied this approach to redesigning an algebraic symbolization tutor. Our classroom study with 76 high school freshmen shows that, compared to the original tutor, the redesigned tutor led to higher learning efficiency on more difficult skills, higher learning gain on unscaffolded whole tasks, and more robust transfer to less practiced tasks. Our work provides general guidance for performing design-loop adaptations for continuous improvement of intelligent tutors.

Copyright: © 2019 INFORMS Behavioral operations is now an established and fundamental research field dedicated to understanding how the behavior of managers, workers, and customers influences operational decisions and outcomes. Just 20 years ago, behavioral research within operations management was relatively small and dispersed. Manufacturing & Service Operations Management has played an integral role in the field’s development since then through its openness to new research questions and methodologies. In this article, we reflect on the research goals pursued in behavioral operations as well as the operational contexts explored. We also share thoughts on promising areas for future research.

With online-learning becoming the new mode of learning, providers need to understand the barriers that learners face. The objective of this study is to utilise a multi-method approach to examine th...

Patient arrivals at the emergency department (ED) of hospitals has an unpredictable behavior. So that, adequate forecasting of this process can serve a management baseline to better allocate ED hum...

Context Continuous experimentation guides development activities based on data collected on a subset of online users on a new experimental version of the software. It includes practices such as canary releases, gradual rollouts, dark launches, or A/B testing. Objective Unfortunately, our knowledge of continuous experimentation is currently primarily based on well-known and outspoken industrial leaders. To assess the actual state of practice in continuous experimentation, we conducted a mixed-method empirical study. Method In our empirical study consisting of four steps, we interviewed 31 developers or release engineers, and performed a survey that attracted 187 complete responses. We analyzed the resulting data using statistical analysis and open coding. Results Our results lead to several conclusions: (1) from a software architecture perspective, continuous experimentation is especially enabled by architectures that foster independently deployable services, such as microservices-based architectures; (2) from a developer perspective, experiments require extensive monitoring and analytics to discover runtime problems, consequently leading to developer on call policies and influencing the role and skill sets required by developers; and (3) from a process perspective, many organizations conduct experiments based on intuition rather than clear guidelines and robust statistics. Conclusion Our findings show that more principled and structured approaches for release decision making are needed, striving for highly automated, systematic, and data- and hypothesis-driven deployment and experimentation.

Split-ballot multi-trait-multi-method experiments are used to evaluate the quality of measurement of different response scales of survey items gauging “evaluation of government services” and “polit...

Several attempts have been made to assess the efficacy of healthy menu labeling with mixed findings. Recent studies have focused mainly on traditional survey techniques; the present study focused o...

Purpose This study aims to develop a method of segmenting markets by using the functional approach to attitudes. The adopted approach identifies and groups individuals based on what functions their held attitudes serve for them. Specific marketing mixes can, thus, be designed for each functional profile. Design/methodology/approach The multi-method approach adopted consists of a qualitative assessment of consumers’ attitudinal functions in the physical fitness context and the development of an instrument to identify the distribution of attitudinal function segments in the same context. Findings A valid and reliable instrument that can be used to segment a market based on functional profiles is developed. Practical implications The outlined method provides a method for practitioners to identify existing functional segments, thus creating marketing mixes based on these functional segments and, ultimately, maximizing the value created for each segment. Originality/value The value in this research lies in the integration of old concepts (functional approach and scale development) to solving a new problem. The functional approach reaches deep to determine “why attitudes are held” vs simply “what attitudes are held”. Operationalization difficulties led to the abandonment of the approach. This research, thus, contributes theoretically by actually operationalizing the functional approach via a scale development, and using the operationalized form as a new means for segmenting markets.

Background There is a growing interest in using person-generated wearable device data for biomedical research, but there are also concerns regarding the quality of data such as missing or incorrect data. This emphasizes the importance of assessing data quality before conducting research. In order to perform data quality assessments, it is essential to define what data quality means for person-generated wearable device data by identifying the data quality dimensions. Objective This study aims to identify data quality dimensions for person-generated wearable device data for research purposes. Methods This study was conducted in 3 phases: literature review, survey, and focus group discussion. The literature review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guideline to identify factors affecting data quality and its associated data quality challenges. In addition, we conducted a survey to confirm and complement results from the literature review and to understand researchers’ perceptions on data quality dimensions that were previously identified as dimensions for the secondary use of electronic health record (EHR) data. We sent the survey to researchers with experience in analyzing wearable device data. Focus group discussion sessions were conducted with domain experts to derive data quality dimensions for person-generated wearable device data. On the basis of the results from the literature review and survey, a facilitator proposed potential data quality dimensions relevant to person-generated wearable device data, and the domain experts accepted or rejected the suggested dimensions. Results In total, 19 studies were included in the literature review, and 3 major themes emerged: device- and technical-related, user-related, and data governance–related factors. The associated data quality problems were incomplete data, incorrect data, and heterogeneous data. A total of 20 respondents answered the survey. The major data quality challenges faced by researchers were completeness, accuracy, and plausibility. The importance ratings on data quality dimensions in an existing framework showed that the dimensions for secondary use of EHR data are applicable to person-generated wearable device data. There were 3 focus group sessions with domain experts in data quality and wearable device research. The experts concluded that intrinsic data quality features, such as conformance, completeness, and plausibility, and contextual and fitness-for-use data quality features, such as completeness (breadth and density) and temporal data granularity, are important data quality dimensions for assessing person-generated wearable device data for research purposes. Conclusions In this study, intrinsic and contextual and fitness-for-use data quality dimensions for person-generated wearable device data were identified. The dimensions were adapted from data quality terminologies and frameworks for the secondary use of EHR data with a few modifications. Further research on how data quality can be assessed with respect to each dimension is needed.

Innovative product design is essentially an activity involving creative cognitive thinking. Therefore, research on the innovative design process and of methods, computer-aided innovation tools should be conducted based on systematic exploration based on the principles of innovative cognitive thinking. We aim to uncover some general principles that can serve as a systematic thinking framework for product designers, provide a feasible framework and method of innovative thinking for designers, and provide theoretical and methodological support for further development of computer-aided innovation platforms. This paper summarizes the sources and content of studies on the idea generation and design processes behind product innovation. Specifically, we break down the general innovative design process of products, outlining the cognitive mechanisms and propose an integrated application strategy that incorporates multiple methods. And taking “the solution program to the coking of oily sludge pyrolysis equipment” as an example, this paper demonstrated and verified the effectiveness and practicability of the method and strategy proposed. Based on the results on improvements in the equipment, the designers put forward some creative and implementable design schemes. The entire thinking process was relatively smooth and efficient. The example presented in this paper shows that the proposed method can effectively guide/assist/motivate designers to think creatively.