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Purpose: This paper aims to present how the project-based learning (PBL) methodology was implemented in the Faculty of Engineering of Mondragon Unibertsitatea in the second year of the Engineering in Industrial Organisation degree to help integrate statistical knowledge related to the design of experiments (DOE) and the use of advanced technologies, such as additive manufacturing (AD; also known as 3D printing). Design/methodology/approach: The methodology applied was PBL, which enables learners to apply theoretical concepts to a controlled real-world environment and to make decisions based on practical experience. PBL was applied in a team setting involving 51 students divided into 12 teams. Findings: The improvement in academic results demonstrate an improvement in the acquisition and assimilation of technical knowledge of the use of statistical tools through experimentation in a semi-industrial environment. In addition, the results of the satisfaction surveys show an increase in the motivation and commitment of the students during the project. Originality/value: The value of the work lies in the integration of advanced technologies (AM or 3D printing) and statistical knowledge in DOE through the PBL methodology in a higher education environment, Peer Reviewed

Corn is an example of an agricultural grain with a specific combustibility level and can promote smoldering fires during storage. This paper conducts an experimental design to numerically evaluate how three parameters, namely particle size, moisture, and air ventilation, influence the smoldering velocity. The work methodology is based on Minitab’s experimental design, which defined the number of experiments. First, a pile of corn is heated by a hot plate and a set of thermocouples registers all temperature variations. Then, a full-factorial experiment is implemented in Minitab to analyze the smoldering, which provides a mathematical equation to represent the smoldering velocity. The results indicate that particle size is the most influential factor in the reaction, with 35% and 45% variation between the dried and wet samples. Moreover, comparing the influence of moisture between corn flour and corn powder samples, a variation of 19% and 31% is observed; additionally, analyzing the ventilation as the only variant, we noticed variations of 15% and 17% for dried and wet corn flour, and 27% and 10% for dried and wet corn powder. Future studies may use the experimental design of this work to standardize the evaluation methodology and more effectively evaluate the relevant influencing factors., Peer Reviewed, Postprint (published version)

Projects focused on movement behaviour and home range are commonplace, but beyond a focus on choosing appropriate research questions, there are no clear guidelines for such studies. Without these guidelines, designing an animal tracking study to produce reliable estimates of space-use and movement properties (necessary to answer basic movement ecology questions), is often done in an ad hoc manner.We developed ‘movedesign’, a user-friendly Shiny application, which can be utilized to investigate the precision of three estimates regularly reported in movement and spatial ecology studies: home range area, speed and distance travelled. Conceptually similar to statistical power analysis, this application enables users to assess the degree of estimate precision that may be achieved with a given sampling design; that is, the choices regarding data resolution (sampling interval) and battery life (sampling duration).Leveraging the ‘ctmm’ R package, we utilize two methods proven to handle many common biases in animal movement datasets: autocorrelated kernel density estimators (AKDEs) and continuous-time speed and distance (CTSD) estimators. Longer sampling durations are required to reliably estimate home range areas via the detection of a sufficient number of home range crossings. In contrast, speed and distance estimation requires a sampling interval short enough to ensure that a statistically significant signature of the animal's velocity remains in the data.This application addresses key challenges faced by researchers when designing tracking studies, including the trade-off between long battery life and high resolution of GPS locations collected by the devices, which may result in a compromise between reliably estimating home range or speed and distance. ‘movedesign’ has broad applications for researchers and decision-makers, supporting them to focus efforts and resources in achieving the optimal sampling design strategy for their research questions, prioritizing the corre

Online active learning is a paradigm in machine learning that aims to select the most informative data points to label from a data stream. The problem of minimizing the cost associated with collecting labeled observations has gained a lot of attention in recent years, particularly in real-world applications where data is only available in an unlabeled form. Annotating each observation can be time-consuming and costly, making it difficult to obtain large amounts of labeled data. To overcome this issue, many active learning strategies have been proposed in the last decades, aiming to select the most informative observations for labeling in order to improve the performance of machine learning models. These approaches can be broadly divided into two categories: static pool-based and stream-based active learning. Pool-based active learning involves selecting a subset of observations from a closed pool of unlabeled data, and it has been the focus of many surveys and literature reviews. However, the growing availability of data streams has led to an increase in the number of approaches that focus on online active learning, which involves continuously selecting and labeling observations as they arrive in a stream. This work aims to provide an overview of the most recently proposed approaches for selecting the most informative observations from data streams in real time. We review the various techniques that have been proposed and discuss their strengths and limitations, as well as the challenges and opportunities that exist in this area of research., Funder: DTU Strategic Alliances Fund;Full text license: CC BY

Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal.

Projects focused on movement behavior and home range are commonplace, but beyond a focus on choosing appropriate research questions, there are no clear guidelines for such studies. The estimation of space-use and movement properties is often necessary to answer basic movement ecology questions, but designing an animal tracking study to produce reliable estimates is often done in an ad hoc manner. We developed 'movedesign', a user-friendly Shiny application, which can be utilized to investigate the precision of three estimates regularly reported in movement and spatial ecology studies: home range area, speed, and distance traveled. Conceptually similar to statistical power analysis, this application enables users to assess the degree of estimate precision that may be achieved with a given sampling design. Leveraging the 'ctmm' R package, we utilize two methods proven to handle many common biases in animal movement datasets: autocorrelated Kernel Density Estimators (AKDE) and continuous-time speed and distance (CTSD) estimators. Longer sampling durations are required to reliably estimate home range areas via the detection of a sufficient number of home range crossings. In contrast, speed and distance estimation requires a sampling interval short enough to ensure that a statistically significant signature of the animal's velocity remains in the data. This application addresses key challenges faced by researchers when designing tracking studies, including the trade-off between long battery life and high resolution of GPS devices, which may result in a compromise between reliably estimating home range or speed and distance. 'movedesign' has broad applications for researchers and decision-makers, supporting them to focus efforts and resources in achieving the optimal sampling design strategy for their research questions, prioritizing the correct deployment decisions for insightful and reliable outputs, while understanding the trade-off associated with these choices.

The study of movement behavior and home range in animals is fundamental to understanding ecological dynamics, yet designing efficient tracking studies remains a challenge due to the lack of clear guidelines. To address this knowledge gap we created 'movedesign,' a user-friendly application that enables researchers to evaluate the precision of three commonly reported movement and spatial ecology estimates: home range area, speed, and distance traveled. Leveraging the 'ctmm' R package, our application employs autocorrelated kernel density estimators (AKDEs) and continuous-time speed and distance (CTSD) estimators, effectively addressing biases inherent in animal movement datasets. By evaluating the interplay between data resolution and battery life, 'movedesign' guides researchers in making informed decisions to achieve reliable estimates of home range and velocity while considering trade-offs. With broad applications for researchers and decision-makers, this tool empowers efficient deployment strategies, optimizing sampling design for insightful and robust outcomes in movement ecology studies.

Projects focused on movement behavior and home range are commonplace, but beyond a focus on choosing appropriate research questions, there are no clear guidelines for such studies. The estimation of space-use and movement properties is often necessary to answer basic movement ecology questions, but designing an animal tracking study to produce reliable estimates is often done in an ad hoc manner. We developed 'movedesign', a user-friendly Shiny application, which can be utilized to investigate the precision of three estimates regularly reported in movement and spatial ecology studies: home range area, speed, and distance traveled. Conceptually similar to statistical power analysis, this application enables users to assess the degree of estimate precision that may be achieved with a given sampling design. Leveraging the 'ctmm' R package, we utilize two methods proven to handle many common biases in animal movement datasets: autocorrelated Kernel Density Estimators (AKDE) and continuous-time speed and distance (CTSD) estimators. Longer sampling durations are required to reliably estimate home range areas via the detection of a sufficient number of home range crossings. In contrast, speed and distance estimation requires a sampling interval short enough to ensure that a statistically significant signature of the animal's velocity remains in the data. This application addresses key challenges faced by researchers when designing tracking studies, including the trade-off between long battery life and high resolution of GPS devices, which may result in a compromise between reliably estimating home range or speed and distance. 'movedesign' has broad applications for researchers and decision-makers, supporting them to focus efforts and resources in achieving the optimal sampling design strategy for their research questions, prioritizing the correct deployment decisions for insightful and reliable outputs, while understanding the trade-off associated with these choices.

The study of movement behavior and home range in animals is fundamental to understanding ecological dynamics, yet designing efficient tracking studies remains a challenge due to the lack of clear guidelines. To address this knowledge gap we created 'movedesign,' a user-friendly application that enables researchers to evaluate the precision of three commonly reported movement and spatial ecology estimates: home range area, speed, and distance traveled. Leveraging the 'ctmm' R package, our application employs autocorrelated kernel density estimators (AKDEs) and continuous-time speed and distance (CTSD) estimators, effectively addressing biases inherent in animal movement datasets. By evaluating the interplay between data resolution and battery life, 'movedesign' guides researchers in making informed decisions to achieve reliable estimates of home range and velocity while considering trade-offs. With broad applications for researchers and decision-makers, this tool empowers efficient deployment strategies, optimizing sampling design for insightful and robust outcomes in movement ecology studies.

Does competition affect moral behavior? This fundamental question has been debated among leading scholars for centuries, and more recently, it has been tested in experimental studies yielding a body of rather inconclusive empirical evidence. A potential source of ambivalent empirical results on the same hypothesis is design heterogeneity—variation in true effect sizes across various reasonable experimental research protocols. To provide further evidence on whether competition affects moral behavior and to examine whether the generalizability of a single experimental study is jeopardized by design heterogeneity, we invited independent research teams to contribute experimental designs to a crowd-sourced project. In a large-scale online data collection, 18,123 experimental participants were randomly allocated to 45 randomly selected experimental designs out of 95 submitted designs. We find a small adverse effect of competition on moral behavior in a meta-analysis of the pooled data. The crowd-sourced design of our study allows for a clean identification and estimation of the variation in effect sizes above and beyond what could be expected due to sampling variance. We find substantial design heterogeneity—estimated to be about 1.6 times as large as the average standard error of effect size estimates of the 45 research designs—indicating that the informativeness and generalizability of results based on a single experimental design are limited. Drawing strong conclusions about the underlying hypotheses in the presence of substantive design heterogeneity requires moving toward much larger data collections on various experimental designs testing the same hypothesis.

This paper explored the effects of different feedback manipulations on letter-string problem solving by analogical transfer. Specifically, the present studies assessed the effects of the type of feedback (first experiment); long exposure to feedback (second experiment) and the number of feedback problems during the practice phase (experiment 3). Participants were college undergraduate students who voluntarily received and answered printed letter string problems. Results showed that correct answer feedback has a significant positive effect on deep structure problem solving; they also showed that problem solution occurs much faster and evolves in a more straightforward manner with this type of feedback. Results also showed a direct relationship between the number of problems with correct answer feedback during the training phase, and the number of correct answers during the testing trial. Results are discussed in terms of the importance of using within-subject experimental designs in both the feedback interventions and analogical transfer literatures., This paper explored the effects of different feedback manipulations on analogous letter-string problem solving. Specifically, the present studies assessed the effects of the type of feedback (first experiment); long exposure to feedback and training (second experiment) and the number of feedback problems during the practice phase (experiment 3). Participants were college undergraduate students who voluntarily received and answered printed letter string problems. Results showed that correct answer feedback had a significant positive effect on deep structure problem solving; they also showed that problem solution occurs much faster and evolves in a more straightforward manner with this type of feedback. Results also suggest a direct relationship between the number of problems with correct answer feedback during the training phase and the number of correct answers during the testing trial. The discussion centers on the importance of experimental design as a tool for better understanding causal relationships in educational and other sciences.

Does competition affect moral behavior? This fundamental question has been debated among leading scholars for centuries, and more recently, it has been tested in experimental studies yielding a body of rather inconclusive empirical evidence. A potential source of ambivalent empirical results on the same hypothesis is design heterogeneity-variation in true effect sizes across various reasonable experimental research protocols. To provide further evidence on whether competition affects moral behavior and to examine whether the generalizability of a single experimental study is jeopardized by design heterogeneity, we invited independent research teams to contribute experimental designs to a crowd-sourced project. In a large-scale online data collection, 18,123 experimental participants were randomly allocated to 45 randomly selected experimental designs out of 95 submitted designs. We find a small adverse effect of competition on moral behavior in a meta-analysis of the pooled data. The crowd-sourced design of our study allows for a clean identification and estimation of the variation in effect sizes above and beyond what could be expected due to sampling variance. We find substantial design heterogeneity-estimated to be about 1.6 times as large as the average standard error of effect size estimates of the 45 research designs-indicating that the informativeness and generalizability of results based on a single experimental design are limited. Drawing strong conclusions about the underlying hypotheses in the presence of substantive design heterogeneity requires moving toward much larger data collections on various experimental designs testing the same hypothesis.

Chemical recycling of polymers is taking off as a circular technology, typically targeting pure recyclates. However, this is often not achieved efficiently due to high energy demand of separation and purification steps. In addition, many polymer applications have complex formulations that may be sensitive to impure feedstocks. Substitution of virgin feedstocks by complex recyclates (often containing impurities) requires a good knowledge of the structure/composition-property re-lations of polymer formulations. As this is often not the case, current practice relies on costly and rather inefficient enumeration experiments, or, at best, classical design-of-experiments approaches. We review the state-of-the art in structure-property modeling, present an example for poly-urethane formulations, and propose a hybrid model-based framework. This involves a machine learning workflow for substitution problems in complex polymer formulations, combining existing data, novel reaction kinetics, structure-property models, molecular dynamics, and a mini-mum of experimental-analytical data where necessary, to build and validate the model.

Deep learning algorithms are increasingly popular for complex prediction and classification tasks, and hyperparameter configurations play an important role in algorithm performance. However, the best hyperparameter tuning strategy still remain unresolved. While grid search and random search can be used to detect better hyperparameters, they are costly for big deep learning algorithms and may not produce the optimal result. Bayesian Optimization balancing the exploration and exploitation trade-off shows significant improvement over grid search and random search in both efficiency and accuracy, but the algorithm makes computation on the entire domain, which can be still costly especially in higher dimension settings. In this paper, we propose a space adjustment algorithm selecting top percent points at each iteration that can be incorporated in additional to Bayesian Optimization framework to further reduce experimental cost and improve optimization efficiency. We show our algorithm’s adaptable nature to the response surface of hyperparameter configuration space. We demonstrate our algorithm’s outstanding performance compared with Efficient Global Optimization through a variety of test functions and an application to machine learning datasets.

INTRODUCCIÓ. Els xiquets amb Trastorn de l'Espectre Autista (TEA) presenten dificultats de socialització i comunicació que provoquen problemes d'atenció i de desenvolupament cognitiu. S'han utilitzat diversos tipus d'intervencions que ajuden a millorar les mancances d'aquest col·lectiu, entre les quals destaquen les intervencions mitjançant l'ús de l'art. En aquest treball presentem una intervenció educativa artística grupal en un conjunt de 14 xiquets amb TEA, amb l'objectiu d'analitzar els seus efectes en la millora de competències socials i emocionals. MÈTODE. Utilitzem un disseny experimental, amb un grup de control. A diferència d'altres treballs, en què la intervenció és individual, utilitzem un format grupal. Els canvis de comportament es van detectar mitjançant un qüestionari emplenat abans i després de la intervenció per pares, terapeutes i investigadors, en els quals les preguntes s'agrupen en quatre categories: Reciprocitat social i emocional, Comunicació no verbal, Inflexibilitat a canvis i Estereotipies i reactivitat sensorial. RESULTATS. S'obtenen dos tipus de resultats: d'una banda, una bona adaptació a la dinàmica de les sessions, i per un altre, progressos significatius després de la intervenció en el grup tractat, especialment en Estereotipies i Inflexibilitat a canvis. Les dades s'analitzen mitjançant dos procediments diferents per a garantir la seua robustesa. DISCUSSIÓ. Els resultats suggereixen que les intervencions grupals mitjançant l'art poden ser un instrument eficaç per a la socialització dels xiquets amb TEA, així com ajudar-los a compartir emocions. El disseny i la dinàmica de les sessions s'han adaptat bé a les preferències sensorials dels xiquets, afavorint la interacció. Aquest treball és un estudi preliminar de la potencialitat de les intervencions grupals mitjançant l'art per a xiquets amb TEA., INTRODUCTION. Children with Autism Spectrum Disorder (ASD) show difficulties of socialization and communication giving rise to attention and cognitive development problems. Different types of intervention have been used to help improving those disabilities, among them, art interventions. In this paper we present an art educative intervention in a group of 14 children with ASD, intending to analyze its effects in improving their emotional and social competencies. METHOD. We use an experimental design, with a control group. Instead of individual intervention, we here have a group format. To detect changes in behavior, a questionnaire, filled up by parents, therapists and researchers, before and after the intervention was used. The questions are grouped into four categories: Social and emotional reciprocity; Non-verbal communication; Inflexibility to changes; and Stereotypes and sensorial reactivity. RESULTS. Two different types of results emerge: on the one hand, a good adaptation to the dynamics of the sessions. On the other hand, significant progress after the intervention in the treated group, in particular in Stereotypes and sensorial reactivity and Inflexibility to changes. Two different procedures to analyze the data were used, to add robustness. DISCUSSION. Our results suggest that art interventions in a group format could be an efficient tool to help children with ASD to improve socialization and sharing emotions. The design and dynamics of the sessions adapted to the sensorial preferences of the children, favoring the interaction between the participants. This work is a preliminary study about the potential of group art interventions for children with ASD., INTRODUCCION. Los niños con Trastorno del Espectro Autista (TEA) presentan dificultades de socialización y comunicación que provocan problemas de atención y de desarrollo cognitivo. Se han utilizado diversos tipos de intervenciones que ayudan a mejorar las carencias de este colectivo, entre las que destacan las intervenciones mediante el uso del arte. En este trabajo presentamos una intervención educativa artística grupal en un conjunto de 14 niños con TEA, con el objetivo de analizar sus efectos en la mejora de competencias sociales y emocionales. METODO. Utilizamos un diseño experimental, con un grupo de control. A diferencia de otros trabajos, en que la intervención es individual, utilizamos un formato grupal. Los cambios de comportamiento se detectaron mediante un cuestionario rellenado antes y después de la intervención por padres, terapeutas e investigadores, en los que las preguntas se agrupan en cuatro categorías: Reciprocidad social y emocional, Comunicación no verbal, Inflexibilidad a cambios y Estereotipias y reactividad sensorial. RESULTADOS. Se obtienen dos tipos de resultados: por una parte, una buena adaptación a la dinámica de las sesiones, y por otro, progresos significativos tras la intervención en el grupo tratado, especialmente en Estereotipias e Inflexibilidad a cambios. Los datos se analizan mediante dos procedimientos diferentes para garantizar su robustez. DISCUSION. Los resultados sugieren que las intervenciones grupales mediante el arte pueden ser un instrumento eficaz para la socialización de los niños con TEA, así como ayudarles a compartir emociones. El diseño y la dinámica de las sesiones se han adaptado bien a las preferencias sensoriales de los niños, favoreciendo la interacción. Este trabajo es un estudio preliminar de la potencialidad de las intervenciones grupales mediante el arte para niños con TEA.

A novel, fast, and cost-effective indirect enzymatic method was successfully developed to assess the total 3-monochloropropane-1,2-diol (3-MCPD) in canned food's oil fraction by the action of Burkholderia cepacia lipase. The total 3-MCPD were derivatized with n-Heptafluorobutyrylimidazole (HFBI) for GC–MS analysis during dispersive liquid–liquid microextraction (DLLME). An asymmetrical 2213//8 screening design was used to study the influence of critical factors on the method's effectiveness. The analytical features of the proposed method were assessed following Food and Drug Administration (FDA) guidelines using extra virgin olive oil (EVOO) as a blank sample. Outstanding results were achieved in terms of linearity (r2 = 0.9995), sensitivity, precision (2.1 % to 10.4 % RSD), and accuracy (98.7 % ≤ recovery ≤ 101.9 %). Method efficacy was tested by comparing the results of 10 edible oils for total 3-MCPD with those reported in previous works. A total of 41 samples were analyzed. The lowest 3-MCPD content was found in samples of albacore canned in EVOO oil, while the highest amounts were found in albacore, mackerel, and Atlantic saury samples, all preserved in refined sunflower oil

Several recent works in human-robot-interaction (HRI) have begun to highlight the importance of the replication crisis and open science practices for our field. Yet, suggestions and recommendations tailored to child-robot-interaction (CRI) research, which poses its own additional set of challenges, remain limited. There is also an increased need within both HRI and CRI for inter and crossdisciplinary collaborations, where input from multiple different domains can contribute to better research outcomes. Consequently, this workshop aims to facilitate discussions between researchers from diverse disciplines within CRI. The workshop will open with a panel discussion between CRI researchers from different disciplines, followed by 3-minute flash talks of the accepted submissions. The second half of the workshop will consist of breakout group discussions, where both senior and junior academics from different disciplines can share their experiences of conducting CRI research. Through this workshop, we hope to create a common ground for addressing shared challenges in CRI, as well as identify a set of possible solutions going forward., Part of ISBN 9781450399708QC 20230801

A heterojunction is the key junction for charge extraction in many thin film solar cell technologies. However, the structure and band alignment of the heterojunction in the operating device are often difficult to predict from calculations and, due to the complexity and narrow thickness of the interface, are difficult to measure directly. In this study, we demonstrate a technique for direct measurement of the band alignment and interfacial electric field variations of a fully functional lead halide perovskite solar cell structure under operating conditions using hard X-ray photoelectron spectroscopy (HAXPES). We describe the design considerations required in both the solar cell devices and the measurement setup and show results for the perovskite, hole transport, and gold layers at the back contact of the solar cell. For the investigated design, the HAXPES measurements suggest that 70% of the photovoltage was generated at this back contact, distributed rather equally between the hole transport material/gold interface and the perovskite/hole transport material interface. In addition, we were also able to reconstruct the band alignment at the back contact at equilibrium in the dark and at open circuit under illumination., QC 20230412

The incorporation of drug-loaded mesoporous materials in dosage forms prepared with fused deposition modeling (FDM) has shown the potential to solve challenges relating to additive manufacturing techniques, such as the stability of poorly-soluble drugs in the amorphous state. However, the addition of these non-melting mesoporous materials significantly affects the mechanical properties of the filament used in FDM, which in turn affects the printability of the feedstock material. Therefore, in this study a full-factorial experimental design was utilized to investigate different processing parameters of the hot melt extrusion process, their effect on various mechanical properties and the potential correlation with the filaments' printability. The thermolabile, poorly-soluble drug ibuprofen was utilized as a model drug to assess the potential of two mesoporous materials, Mesoporous Magnesium Carbonate (MMC) and a silica-based material (MCM-41), to thermally protect the loaded drug. Factorial and principal components analysis displayed a correlation between non-printable MCM-41 filaments and their mechanical properties where printable filaments had a maximum stress >7.5 MPa and a Young's modulus >83 MPa. For MMC samples there was no clear correlation, which was in large part attributed to the filaments' inconsistencies and imperfections. Finally, both mesoporous materials displayed a thermal protective feature, as the decomposition due to the thermal degradation of a significant portion of the thermolabile drug was shifted to higher temperatures post-loading. This highlights the potential capability of such a system to be implemented for thermosensitive drugs in FDM applications.

Printed circuit boards (PCBs) are essential components in various electronic devices, playing a vital role in their functionality. Over time, PCBs have evolved significantly, becoming smaller, more complex, and multi-layered to meet the demands of advancing technology and consumer preferences. The quality of solder paste deposits is measured by circularity, volume, positioning, and the number of satellites. Mycronic is a supplier of jet printing machines for PCB manufacturers and needs to investigate and counteract an unwanted variation in volume and positioning within the first dot of the solder paste strip, and its so-called “sea saw” effect for the following three dots. This master’s thesis has two aims. The first aim is to develop and evaluate an experimental method to reduce variation between the dots in the strip. The second aim is to reduce the variation between the 1st dot and the following three dots by finding a combination of pre-feed, first, second, and third waveforms to obtain improved precision, volume, circularity, and reduced volume variation. Using an experimental design a full factorial design was used, examining six experimental factors. The design was further augmented with a central composite design to describe the second-order model. The knowledge from the experiment was used to optimize and improve the quality factors of jet printing, which were verified with an additional experiment. The results of the study provided compelling evidence that only the selected experimental factors had a significant impact on improving the volume metric. It was observed that the presence or absence of satellites during the experiment did not have any effect on the results, and neither did the positioning and circularity factors contribute to any improvement or deterioration. Specifically, the most significant difference in volume between 1st and following three dots for the optimized solution is 0.5 nl, and the currently used settings have a difference of 2.6

The incorporation of drug-loaded mesoporous materials in dosage forms prepared with fused deposition modeling (FDM) has shown the potential to solve challenges relating to additive manufacturing techniques, such as the stability of poorly-soluble drugs in the amorphous state. However, the addition of these non-melting mesoporous materials significantly affects the mechanical properties of the filament used in FDM, which in turn affects the printability of the feedstock material. Therefore, in this study a full-factorial experimental design was utilized to investigate different processing parameters of the hot melt extrusion process, their effect on various mechanical properties and the potential correlation with the filaments' printability. The thermolabile, poorly-soluble drug ibuprofen was utilized as a model drug to assess the potential of two mesoporous materials, Mesoporous Magnesium Carbonate (MMC) and a silica-based material (MCM-41), to thermally protect the loaded drug. Factorial and principal components analysis displayed a correlation between non-printable MCM-41 filaments and their mechanical properties where printable filaments had a maximum stress >7.5 MPa and a Young's modulus >83 MPa. For MMC samples there was no clear correlation, which was in large part attributed to the filaments' inconsistencies and imperfections. Finally, both mesoporous materials displayed a thermal protective feature, as the decomposition due to the thermal degradation of a significant portion of the thermolabile drug was shifted to higher temperatures post-loading. This highlights the potential capability of such a system to be implemented for thermosensitive drugs in FDM applications.

Selective ion separation is a fundamental challenge with applications ranging from the manufacturing of pharmaceuticals & industrial salts to water desalination. In particular, the separation of formate, a primary product of electrochemical carbon dioxide reduction, has attracted attention not only to reduce carbon emissions and energy costs but to provide new routes to value-added chemicals. In the present study, selective formate separation from an aqueous solution is demonstrated using an electrochemical flow cell with symmetric redox-active polyvinyl ferrocene electrodes. An electrosorption system equipped with an electrosorption cell, inline conductivity, and pH sensors was constructed to provide real-time measurements of the formate adsorption performance in continuous flow mode while varying operating conditions such as the flow rate, cell voltage, and electrolyte concentration. These parameters were optimized using a Box–Behnken experimental design to improve the formate adsorption selectivity. The flow cell results showed a selectivity higher than 6.0 toward the removal of formate in an electrolyte containing a 30-fold excess of perchlorate under optimal operation conditions (i.e., 0.5 mL/min flow rate, 1.0 V, and 15 mM electrolyte concentration). The performance of the flow cell was also tested using a solution that contained different liquid CO2 reduction products, and formate separation was achieved. The results suggest that the proper design of the electrochemical cell and efficient operation of the flow platform pave the way for scaling up the technology for selective formate separation., Complex Fluid Processing, Large Scale Energy Storage

Several recent works in human-robot-interaction (HRI) have begun to highlight the importance of the replication crisis and open science practices for our field. Yet, suggestions and recommendations tailored to child-robot-interaction (CRI) research, which poses its own additional set of challenges, remain limited. There is also an increased need within both HRI and CRI for inter and crossdisciplinary collaborations, where input from multiple different domains can contribute to better research outcomes. Consequently, this workshop aims to facilitate discussions between researchers from diverse disciplines within CRI. The workshop will open with a panel discussion between CRI researchers from different disciplines, followed by 3-minute flash talks of the accepted submissions. The second half of the workshop will consist of breakout group discussions, where both senior and junior academics from different disciplines can share their experiences of conducting CRI research. Through this workshop, we hope to create a common ground for addressing shared challenges in CRI, as well as identify a set of possible solutions going forward.

Experimental design plays a critical role in ensuring the safety and reliability of systems in various domains. Bayesian belief networks (BBNs) have been widely used as a decision-making tool for probabilistic modeling and analysis of complex systems. This thesis presents an approach for using a BBN to model an assurance case and predict the likelihood of its claims. This can be used to evaluate changes to the experiments that will generate the evidence needed for the assurance case. We present two examples as case studies in the software engineering domain to demonstrate the effectiveness of our approach. The results show that our framework can effectively capture the changes in the degree of belief in a claim under uncertainties and risks associated with the experimental design and provide decision-makers with a more comprehensive understanding of the system under investigation.

The incorporation of drug-loaded mesoporous materials in dosage forms prepared with fused deposition modeling (FDM) has shown the potential to solve challenges relating to additive manufacturing techniques, such as the stability of poorly-soluble drugs in the amorphous state. However, the addition of these non-melting mesoporous materials significantly affects the mechanical properties of the filament used in FDM, which in turn affects the printability of the feedstock material. Therefore, in this study a full-factorial experimental design was utilized to investigate different processing parameters of the hot melt extrusion process, their effect on various mechanical properties and the potential correlation with the filaments' printability. The thermolabile, poorly-soluble drug ibuprofen was utilized as a model drug to assess the potential of two mesoporous materials, Mesoporous Magnesium Carbonate (MMC) and a silica-based material (MCM-41), to thermally protect the loaded drug. Factorial and principal components analysis displayed a correlation between non-printable MCM-41 filaments and their mechanical properties where printable filaments had a maximum stress >7.5 MPa and a Young's modulus >83 MPa. For MMC samples there was no clear correlation, which was in large part attributed to the filaments' inconsistencies and imperfections. Finally, both mesoporous materials displayed a thermal protective feature, as the decomposition due to the thermal degradation of a significant portion of the thermolabile drug was shifted to higher temperatures post-loading. This highlights the potential capability of such a system to be implemented for thermosensitive drugs in FDM applications.

Background: The purpose was to investigate if participation in a three-month electronic tracking outdoor physical activity and a motivational interviewing (MI) intervention led to positive behavioural, psychological, and physiological outcomes. Methods: Based on a two-group pre-post design, 12 middle-aged women and 6 men were randomly assign to an experimental and a control group. Physical activity data were collected by wrist-worn activity sensors, and pre-post data were collected on the GHQ-12, the BREQ-2, body mass, body fat mass and total body muscle. Measures of cardiovascular fitness were taken pre to post. The experimental group was supported through individual MI coaching sessions and resistance-training for use in an outdoor gym. Magnitude based inferences (MBI) were calculated based on the disposition of the confidence limits for the mean differences to the smallest worthwhile changes. Results: The experimental group had a beneficial increase in its physical activity behaviour (steps). The control group had a medium decrease in identified regulation, the experimental group maintained the same level at the post-measure. Conclusion: Few studies have investigated how the combination of MI and the use of activity-tracking devices effect physical and mental health. This study investigates the use of both MI and activity-tracking devices on psychological well-being, motivation, and physical health in an outdoor context. Future research recommendations are given. © 2022 ACAPS, Introduction: L'objectif était de déterminer si la participation à une intervention d'activité physique extérieure avec suivi électronique et d'entretiens motivationnels (MI) d'une durée de trois mois conduisait à des résultats positifs sur les plans comportementaux, psychologiques et physiologiques. Méthodes: Suivant un design d'étude pré-post à deux groupes, 12 femmes d'âge moyen et 6 hommes ont été assignés par randomisation à un groupe expérimental ou à un groupe contrôle. Les données relatives à l'activité physique ont été collectées au moyen de capteurs d'activité portés au poignet. Les données pré- et post-intervention concernaient le GHQ-12, le BREQ-2, la masse corporelle, la masse grasse et la masse musculaire. La condition cardiovasculaire a également été mesurée pré- et post-intervention. Le groupe expérimental a bénéficié de MI individuels et d'ateliers de renforcement musculaire en plein air. Des magnitude based inferences (MBI) ont été calculées à partir de la disposition des limites de confiance concernant les différences moyennes des plus petits changements significatifs. Résultats: Le groupe expérimental présentait une augmentation bénéfique du comportement d'activité physique (nombre de pas). Le groupe contrôle présentait une diminution moyenne de la régulation identifiée, tandis que cette valeur est restée stable dans le groupe expérimental. Conclusion: Peu d'études ont examiné comment la combinaison de MI et de dispositifs de suivi de l'activité affectent la santé physique et mentale. Cette étude a examiné l'influence de l'utilisation conjointe de MI et de dispositifs de suivi d'activité sur le bien-être psychologique, la motivation et la santé physique dans un contexte de pratique extérieure. Des recommandations relatives aux recherches futures ont été formulées. © 2022 ACAPS, Titel på franska: Une étude sur les avantages de la participation à un programme de suivi électronique de l’activité physique et d’entretiens motivationnels pendant une période de trois mois

Printed circuit boards (PCBs) are essential components in various electronic devices, playing a vital role in their functionality. Over time, PCBs have evolved significantly, becoming smaller, more complex, and multi-layered to meet the demands of advancing technology and consumer preferences. The quality of solder paste deposits is measured by circularity, volume, positioning, and the number of satellites. Mycronic is a supplier of jet printing machines for PCB manufacturers and needs to investigate and counteract an unwanted variation in volume and positioning within the first dot of the solder paste strip, and its so-called “sea saw” effect for the following three dots. This master’s thesis has two aims. The first aim is to develop and evaluate an experimental method to reduce variation between the dots in the strip. The second aim is to reduce the variation between the 1st dot and the following three dots by finding a combination of pre-feed, first, second, and third waveforms to obtain improved precision, volume, circularity, and reduced volume variation. Using an experimental design a full factorial design was used, examining six experimental factors. The design was further augmented with a central composite design to describe the second-order model. The knowledge from the experiment was used to optimize and improve the quality factors of jet printing, which were verified with an additional experiment. The results of the study provided compelling evidence that only the selected experimental factors had a significant impact on improving the volume metric. It was observed that the presence or absence of satellites during the experiment did not have any effect on the results, and neither did the positioning and circularity factors contribute to any improvement or deterioration. Specifically, the most significant difference in volume between 1st and following three dots for the optimized solution is 0.5 nl, and the currently used settings have a difference of 2.6

The incorporation of drug-loaded mesoporous materials in dosage forms prepared with fused deposition modeling (FDM) has shown the potential to solve challenges relating to additive manufacturing techniques, such as the stability of poorly-soluble drugs in the amorphous state. However, the addition of these non-melting mesoporous materials significantly affects the mechanical properties of the filament used in FDM, which in turn affects the printability of the feedstock material. Therefore, in this study a full-factorial experimental design was utilized to investigate different processing parameters of the hot melt extrusion process, their effect on various mechanical properties and the potential correlation with the filaments' printability. The thermolabile, poorly-soluble drug ibuprofen was utilized as a model drug to assess the potential of two mesoporous materials, Mesoporous Magnesium Carbonate (MMC) and a silica-based material (MCM-41), to thermally protect the loaded drug. Factorial and principal components analysis displayed a correlation between non-printable MCM-41 filaments and their mechanical properties where printable filaments had a maximum stress >7.5 MPa and a Young's modulus >83 MPa. For MMC samples there was no clear correlation, which was in large part attributed to the filaments' inconsistencies and imperfections. Finally, both mesoporous materials displayed a thermal protective feature, as the decomposition due to the thermal degradation of a significant portion of the thermolabile drug was shifted to higher temperatures post-loading. This highlights the potential capability of such a system to be implemented for thermosensitive drugs in FDM applications.

Almond (Prunus amygdalus) is one of the most common tree nuts on a worldwide basis. This nut is highly regarded in the food and cosmetic industries. However, for all these applications, almonds are used without their shell protection, which is industrially removed contributing approximately 35-75% of the total fruit weight. This residue is normally incinerated or dumped, causing several environmental problems. In this study, a novel cellulose nanocrystal (CNCs) extraction procedure from almond shell (AS) waste by using microwave-assisted extraction was developed and compared with the conventional approach. A three-factor, three-level Box-Behnken design with five central points was used to evaluate the influence of extraction temperature, irradiation time, and NaOH concentration during the alkalization stage in crystallinity index (CI) values. A similar CI value (55.9 +/- 0.7%) was obtained for the MAE process, comprising only three stages, compared with the conventional optimized procedure (55.5 +/- 1.0%) with five stages. As a result, a greener and more environmentally friendly CNC extraction protocol was developed with a reduction in time, solvent, and energy consumption. Fourier transform infrared (FTIR) spectra, X-ray diffractogram (XRD), atomic force microscopy (AFM), and scanning electron microscopy (SEM) images, and thermal stability studies of samples confirmed the removal of non-cellulosic components after the chemical treatments. TEM images revealed a spherical shape of CNCs with an average size of 21 +/- 6 nm, showing great potential to be used in food packaging, biological, medical, and photoelectric materials. This study successfully applied MAE for the extraction of spherical-shaped CNCs from AS with several advantages compared with the conventional procedure, reducing costs for industry.

Introduction. Whey is the residual liquid product of the manufacture of cheese with useful nutritional value. It contains 95 % of the lactose, 25 % of the proteins and 8 % of fat of the total milk components. Objective. To elaborate a refreshing whey drink with the addition of rice flour and orange concentrate. Materials and methods. The experimental work was realized at Food Department laboratories belongs to Pharmacy and Foods Institute from Universidad de La Habana-Cuba, between January and May 2021. The raw materials: whey, rice flower, and orange concentrated juice were characterized. A mix design was applied using Design–expert version 8.0 program to get the better formulation (combination of ingredients). The independent variables in percentage were: whey (79.95 to 84.15), concentrated orange juice (7 to 11), and guar gum stabilizer (from 0.1 to 0.3), and as response variables, acceptability and stability of the obtained drink. The best combination of ingredients was evaluated by a panel of judges based on the intensity of the odor, orange flavor, and consistency, using the attibutes “light”, “moderate” and “marked”. Results. The best formulation was composed of whey (84.15 %), orange concentrate (7 %), refined sugar (5 %), rice flour (3.75 %), and guar gum stabilizer (0.1 %). The sensorial acceptability criteria given by the training judges was “I like it”. Regarding the intensity of the orange smell, the whey beverage received a balanced criteria between the “light” and “moderate” ratings and the consistency was qualified as “light”. Conclusions. All formulations tested showed good stability and adequate sensory acceptability. The best combination showed no phase separation at 24 hours after processing and was characterized by twenty tasters., Introducción. El lactosuero es el residuo líquido obtenido de la fabricación de quesos con valor nutricional aprovechable. Contiene el 95 % de la lactosa, 25 % de las proteínas y 8 % de la materia grasa del total de componentes de la leche. Objetivo. Elaborar una bebida refrescante de suero lácteo con la adición de harina de arroz y concentrado de naranja. Materiales y métodos. El trabajo experimental se desarrolló en los laboratorios del Departamento de Alimentos del Instituto de Farmacia y Alimentos de la Universidad de La Habana-Cuba, entre enero y mayo de 2021. Se caracterizaron las materias primas: lactosuero, harina de arroz y jugo concentrado de naranja. Se aplicó un diseño de mezcla con base en el programa Design–expert versión 8.0, para seleccionar la mejor formulación (combinación de ingredientes). Las variables independientes en porcentaje fueron: suero (79, 95 a 84,15), jugo concentrado de naranja (7 a 11) y estabilizante goma guar (de 0,1 a 0,3) y como variables de respuesta aceptabilidad y estabilidad de la bebida obtenida. La mejor combinación de ingredientes fue evaluada por un panel de jueces con base en la intensidad de los atributos olor, sabor a naranja y consistencia, mediante los atributos “ligero”, “moderado” y “marcado”. Resultados. La mejor formulación estuvo compuesta por suero (84,15 %), concentrado de naranja (7 %), azúcar refino (5 %), harina de arroz (3,75 %) y estabilizante goma guar (0,1 %). Los catadores otorgaron a la bebida la evaluación integral de “me gusta”, según sus criteros la intensidad del olor a naranja fue ligero y moderado, el sabor a naranja moderado y la consistencia ligera. Conclusión. Todas las formulaciones ensayadas mostraron buena estabilidad y aceptabilidad sensorial adecuada. La mejor combinación no presentó separación de fases a las 24 horas de elaborada y fue caracterizada por veinte catadores.

A microgrid is a group of interconnected loads and distributed energy resources that can fill the gap between the dependence on a bulk power grid and the transition to renewable energies. The islanded mode presents itself as the most interesting scenario, when local controllers should maintain the power quality standards based on several parameters. A tool specifically focused on the process of parameter tuning of the secondary consensus-based control for inverter-based islanded microgrids was proposed in this paper. One often-quoted drawback in this process is the great number of parameters that must be tuned, even for a very simple microgrid structure. To manage such a large number of parameters, the design of experiments was used in this study. The main motivation for this work was to present an optimized way to define the correct parameters for the secondary consensus control for inverter-based islanded microgrids. The study shows how experimental design methodology can be an efficient tool to tune microgrid parameters, which are typically multi-objective-based experiments. From the results, it is correct to state that the design of experiments is able to reach the optimal setting with a minimal number of experiments, which would be almost impossible to obtain with the trial-and-error method., This work was supported by the Brazilian agencies of the Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Education Personnel (CAPES), and Research Support Foundation of the Minas Gerais State (FAPEMIG). This publication is part of the R&D project PID2021-122835OB-C21, financed by MCIN/AEI/10.13039/ 501000011033 and FEDER “Una manera de hacer Europa”., Peer Reviewed, Postprint (published version)

Almond (Prunus amygdalus) is one of the most common tree nuts on a worldwide basis. This nut is highly regarded in the food and cosmetic industries. However, for all these applications, almonds are used without their shell protection, which is industrially removed contributing approximately 35-75% of the total fruit weight. This residue is normally incinerated or dumped, causing several environmental problems. In this study, a novel cellulose nanocrystal (CNCs) extraction procedure from almond shell (AS) waste by using microwave-assisted extraction was developed and compared with the conventional approach. A three-factor, three-level Box–Behnken design with five central points was used to evaluate the influence of extraction temperature, irradiation time, and NaOH concentration during the alkalization stage in crystallinity index (CI) values. A similar CI value (55.9 ± 0.7%) was obtained for the MAE process, comprising only three stages, compared with the conventional optimized procedure (55.5 ± 1.0%) with five stages. As a result, a greener and more environmentally friendly CNC extraction protocol was developed with a reduction in time, solvent, and energy consumption. Fourier transform infrared (FTIR) spectra, X-ray diffractogram (XRD), atomic force microscopy (AFM), and scanning electron microscopy (SEM) images, and thermal stability studies of samples confirmed the removal of non-cellulosic components after the chemical treatments. TEM images revealed a spherical shape of CNCs with an average size of 21 ± 6 nm, showing great potential to be used in food packaging, biological, medical, and photoelectric materials. This study successfully applied MAE for the extraction of spherical-shaped CNCs from AS with several advantages compared with the conventional procedure, reducing costs for industry.

De productie van groene waterstof door elektrolyse van zeewater is economisch een stuk aantrekkelijker geworden. Wageningse wetenschappers hebben met een proefopstelling bewezen dat het mogelijk is om via membraandestillatie Ultra Puur Water (UPW) te winnen uit zeewater. De energie daarvoor komt uit de restwarmte van de elektrolyser.

Populations with a migration background have a higher prevalence of mental health problems than their native counterparts. They are also more likely to have unmet medical needs and are less frequently referred to mental health services. One potential explanation for this is that physicians, such as general practitioners (GPs), may unintentionally discriminate against migrant patients, particularly when they lack humanization. To date, no experimental study has investigated this hypothesis. This paper assesses the influence of humanization on GPs’ discriminatory decisions regarding migrant patients with depression. A balanced 2 × 2 factorial experiment was carried out with Belgian GPs (N = 797) who received video-vignettes depicting either a native patient or a migrant patient with depression. Half of the respondents were exposed to a text that humanized the patient by providing more details about the patient’s life story. Decisions related to diagnosis, treatment and referral werecollected, as well as the time spent on each video and text, and were analysed using ANOVA. Migrant patients’ symptoms were judged to be less severe than those of native patients (F = 7.71, p < 0.05). For almost all treatments, the decision was less favourable for the migrant patient. Humanization had little effect on medical decisions. We observed that GPs spent significantly more time on the vignette with the humanization intervention, especially for the migrant patients. The results indicate that ethnic differences in the management of depression persist in primary care. Humanization, however, does not mitigate those differences in medical decisions.

The incorporation of drug-loaded mesoporous materials in dosage forms prepared with fused deposition modeling (FDM) has shown the potential to solve challenges relating to additive manufacturing techniques, such as the stability of poorly-soluble drugs in the amorphous state. However, the addition of these non-melting mesoporous materials significantly affects the mechanical properties of the filament used in FDM, which in turn affects the printability of the feedstock material. Therefore, in this study a full-factorial experimental design was utilized to investigate different processing parameters of the hot melt extrusion process, their effect on various mechanical properties and the potential correlation with the filaments' printability. The thermolabile, poorly-soluble drug ibuprofen was utilized as a model drug to assess the potential of two mesoporous materials, Mesoporous Magnesium Carbonate (MMC) and a silica-based material (MCM-41), to thermally protect the loaded drug. Factorial and principal components analysis displayed a correlation between non-printable MCM-41 filaments and their mechanical properties where printable filaments had a maximum stress >7.5 MPa and a Young's modulus >83 MPa. For MMC samples there was no clear correlation, which was in large part attributed to the filaments' inconsistencies and imperfections. Finally, both mesoporous materials displayed a thermal protective feature, as the decomposition due to the thermal degradation of a significant portion of the thermolabile drug was shifted to higher temperatures post-loading. This highlights the potential capability of such a system to be implemented for thermosensitive drugs in FDM applications.

Over the past decades the field of family business has witnessed a surge in publications and experienced meaningful changes that have served to increase its legitimacy and establish the field as an independent area of academic inquiry. Along with these advancements, scholars have called for experimental research designs that can reveal the influence of individual-level, microfoundational phenomena underlying macro-level family business phenomena. Given the challenge of conducting such studies, the event-sampling method with experimental design (ESME) approach is highlighted as a new opportunity for family business scholars to further enrich their methodological toolbox. Fundamentally, the ESME approach is a longitudinal, repeated-sampling method with experimental design that provides researchers with the opportunity to investigate the effects of various micro-level phenomena within the family business. By facilitating the incorporation of familial variables and processual elements in family business research, the ESME approach can account for the longitudinal and dynamic interplay of family and family business phenomena. Overall, ESME is a method with the potential to help researchers answer many of the “how” questions that remain unanswered in the field of family business. A description of ESME is offered, relevant challenges and opportunities in family business research are identified, and best practices for ESME are shared to support the work of family business scholars.

Prior research on networks has established that tensions might arise between organizational structures and processes and network goals. This study investigates the role that network managers can play in mitigating these tensions through network orchestration. Based on an experimental design involving students and practitioners from the social domain, the combined effects of network orchestration and organizational formalization on goal orientation were examined. Results show that a negative effect of organizational formalization on network goal orientation is mitigated by network orchestration. Thereby, this study contributes to our understanding of the role of network orchestration in coping with tensions inherent to networks.

Double-blind randomized controlled trials are traditionally seen as the gold standard for causal inferences as the difference-in-means estimator is an unbiased estimator of the average treatment effect in the experiment. The fact that this estimator is unbiased over all possible randomizations does not, however, mean that any given estimate is close to the true treatment effect. Similarly, while predetermined covariates will be balanced between treatment and control groups on average, large imbalances may be observed in a given experiment and the researcher may therefore want to condition on such covariates using linear regression. This article studies the theoretical properties of both the difference-in-means and OLS estimators conditional on observed differences in covariates. By deriving the statistical properties of the conditional estimators, we can establish guidance for how to deal with covariate imbalances.

Double-blind randomized controlled trials are traditionally seen as the gold standard for causal inferences as the difference-in-means estimator is an unbiased estimator of the average treatment effect in the experiment. The fact that this estimator is unbiased over all possible randomizations does not, however, mean that any given estimate is close to the true treatment effect. Similarly, while predetermined covariates will be balanced between treatment and control groups on average, large imbalances may be observed in a given experiment and the researcher may therefore want to condition on such covariates using linear regression. This article studies the theoretical properties of both the difference-in-means and OLS estimators conditional on observed differences in covariates. By deriving the statistical properties of the conditional estimators, we can establish guidance for how to deal with covariate imbalances.

Double-blind randomized controlled trials are traditionally seen as the gold standard for causal inferences as the difference-in-means estimator is an unbiased estimator of the average treatment effect in the experiment. The fact that this estimator is unbiased over all possible randomizations does not, however, mean that any given estimate is close to the true treatment effect. Similarly, while predetermined covariates will be balanced between treatment and control groups on average, large imbalances may be observed in a given experiment and the researcher may therefore want to condition on such covariates using linear regression. This article studies the theoretical properties of both the difference-in-means and OLS estimators conditional on observed differences in covariates. By deriving the statistical properties of the conditional estimators, we can establish guidance for how to deal with covariate imbalances.

Double-blind randomized controlled trials are traditionally seen as the gold standard for causal inferences as the difference-in-means estimator is an unbiased estimator of the average treatment effect in the experiment. The fact that this estimator is unbiased over all possible randomizations does not, however, mean that any given estimate is close to the true treatment effect. Similarly, while predetermined covariates will be balanced between treatment and control groups on average, large imbalances may be observed in a given experiment and the researcher may therefore want to condition on such covariates using linear regression. This article studies the theoretical properties of both the difference-in-means and OLS estimators conditional on observed differences in covariates. By deriving the statistical properties of the conditional estimators, we can establish guidance for how to deal with covariate imbalances.

Recently, there has been increasing interest in the use of heavily restricted randomization designs which enforce balance on observed covariates in randomized controlled trials. However, when restrictions are strict, there is a risk that the treatment effect estimator will have a very high mean squared error (MSE). In this article, we formalize this risk and propose a novel combinatoric-based approach to describe and address this issue. First, we validate our new approach by re-proving some known properties of complete randomization and restricted randomization. Second, we propose a novel diagnostic measure for restricted designs that only use the information embedded in the combinatorics of the design. Third, we show that the variance of the MSE of the difference-in-means estimator in a randomized experiment is a linear function of this diagnostic measure. Finally, we identify situations in which restricted designs can lead to an increased risk of getting a high MSE and discuss how our diagnostic measure can be used to detect such designs. Our results have implications for any restricted randomization design and can be used to evaluate the trade-off between enforcing balance on observed covariates and avoiding too restrictive designs.

The workflow and process of graphic design is today streamlined by the usage of our tools such as softwares. However, this doesn’t mean that designers must restrict themselves from working outside an established practice largely determined by such software. Implementing programming and generative design as a method in the development of graphic design can lead to new insights and different perspectives. Proven to be an asset in the creation of visual material the method falls short as generative design is co-dependent on both the designer and user. Though complicated and expensive, generative design proves useful when working with realtime data and as a tool for generating new ideas. Working experimentally with under-utilized tools can help the development of new trends and methods within the field of graphic design.

Background: Teamwork skills are essential to the quality of care and patient safety; nevertheless, team training is limited in Bachelor of Nursing degree programs in Norway. Objectives: The objective of this study was to explore the impact of implementing a TeamSTEPPS® team training intervention on Bachelor of Nursing students' attitudes toward teamwork in health care. Design: A longitudinal quasi-experimental design with pre- and posttests was used. Settings: One intervention group and one control group were recruited from two campuses at a Norwegian university offering a Bachelor of Nursing degree. Participants: Subjects were recruited from a population of 423 students. Methods: For 26 months, the intervention group was exposed to the TeamSTEPPS® team training program with various learning activities to enhance teamwork skills. The intervention group and the control group responded to the Norwegian version of the TeamSTEPPS® Teamwork Attitude Questionnaire (T-TAQ) before the intervention (T0), after ten months (T1), and after 24 months (T2). The students participated in survey T0 and T1 was defined as Sample 1 and students participated in survey T0 and T2 was defined as Sample 2 The data were analyzed with parametric and nonparametric statistics. Results: At T0 there was a significant difference between the intervention and control group. The intervention group showed a significant positive change in the Total T-TAQ score from T0 to T1 and from T0 to T2. The change in mean score differed significantly between the intervention and control group in favor of the intervention group. Conclusions: This study showed that a team training program improved Bachelor of Nursing students' attitudes toward teamwork. Therefore, we recommend that the TeamSTEPPS® team training program be implemented in Bachelor of Nursing programs to facilitate a culture of teamwork.

Recently, there has been increasing interest in the use of heavily restricted randomization designs which enforce balance on observed covariates in randomized controlled trials. However, when restrictions are strict, there is a risk that the treatment effect estimator will have a very high mean squared error (MSE). In this article, we formalize this risk and propose a novel combinatoric-based approach to describe and address this issue. First, we validate our new approach by re-proving some known properties of complete randomization and restricted randomization. Second, we propose a novel diagnostic measure for restricted designs that only use the information embedded in the combinatorics of the design. Third, we show that the variance of the MSE of the difference-in-means estimator in a randomized experiment is a linear function of this diagnostic measure. Finally, we identify situations in which restricted designs can lead to an increased risk of getting a high MSE and discuss how our diagnostic measure can be used to detect such designs. Our results have implications for any restricted randomization design and can be used to evaluate the trade-off between enforcing balance on observed covariates and avoiding too restrictive designs.

Background: Teamwork skills are essential to the quality of care and patient safety; nevertheless, team training is limited in Bachelor of Nursing degree programs in Norway. Objectives: The objective of this study was to explore the impact of implementing a TeamSTEPPS® team training intervention on Bachelor of Nursing students' attitudes toward teamwork in health care. Design: A longitudinal quasi-experimental design with pre- and posttests was used. Settings: One intervention group and one control group were recruited from two campuses at a Norwegian university offering a Bachelor of Nursing degree. Participants: Subjects were recruited from a population of 423 students. Methods: For 26 months, the intervention group was exposed to the TeamSTEPPS® team training program with various learning activities to enhance teamwork skills. The intervention group and the control group responded to the Norwegian version of the TeamSTEPPS® Teamwork Attitude Questionnaire (T-TAQ) before the intervention (T0), after ten months (T1), and after 24 months (T2). The students participated in survey T0 and T1 was defined as Sample 1 and students participated in survey T0 and T2 was defined as Sample 2 The data were analyzed with parametric and nonparametric statistics. Results: At T0 there was a significant difference between the intervention and control group. The intervention group showed a significant positive change in the Total T-TAQ score from T0 to T1 and from T0 to T2. The change in mean score differed significantly between the intervention and control group in favor of the intervention group. Conclusions: This study showed that a team training program improved Bachelor of Nursing students' attitudes toward teamwork. Therefore, we recommend that the TeamSTEPPS® team training program be implemented in Bachelor of Nursing programs to facilitate a culture of teamwork.

Recently, there has been increasing interest in the use of heavily restricted randomization designs which enforce balance on observed covariates in randomized controlled trials. However, when restrictions are strict, there is a risk that the treatment effect estimator will have a very high mean squared error (MSE). In this article, we formalize this risk and propose a novel combinatoric-based approach to describe and address this issue. First, we validate our new approach by re-proving some known properties of complete randomization and restricted randomization. Second, we propose a novel diagnostic measure for restricted designs that only use the information embedded in the combinatorics of the design. Third, we show that the variance of the MSE of the difference-in-means estimator in a randomized experiment is a linear function of this diagnostic measure. Finally, we identify situations in which restricted designs can lead to an increased risk of getting a high MSE and discuss how our diagnostic measure can be used to detect such designs. Our results have implications for any restricted randomization design and can be used to evaluate the trade-off between enforcing balance on observed covariates and avoiding too restrictive designs.

Background: Teamwork skills are essential to the quality of care and patient safety; nevertheless, team training is limited in Bachelor of Nursing degree programs in Norway. Objectives: The objective of this study was to explore the impact of implementing a TeamSTEPPS® team training intervention on Bachelor of Nursing students' attitudes toward teamwork in health care. Design: A longitudinal quasi-experimental design with pre- and posttests was used. Settings: One intervention group and one control group were recruited from two campuses at a Norwegian university offering a Bachelor of Nursing degree. Participants: Subjects were recruited from a population of 423 students. Methods: For 26 months, the intervention group was exposed to the TeamSTEPPS® team training program with various learning activities to enhance teamwork skills. The intervention group and the control group responded to the Norwegian version of the TeamSTEPPS® Teamwork Attitude Questionnaire (T-TAQ) before the intervention (T0), after ten months (T1), and after 24 months (T2). The students participated in survey T0 and T1 was defined as Sample 1 and students participated in survey T0 and T2 was defined as Sample 2 The data were analyzed with parametric and nonparametric statistics. Results: At T0 there was a significant difference between the intervention and control group. The intervention group showed a significant positive change in the Total T-TAQ score from T0 to T1 and from T0 to T2. The change in mean score differed significantly between the intervention and control group in favor of the intervention group. Conclusions: This study showed that a team training program improved Bachelor of Nursing students' attitudes toward teamwork. Therefore, we recommend that the TeamSTEPPS® team training program be implemented in Bachelor of Nursing programs to facilitate a culture of teamwork.