User's Guide Research Articles

Technical note: A volumetric method for measuring the longitudinal arch of human tracks and feet.

Fossil footprints (i.e., tracks) were believed to document arch anatomical evolution, although our recent work has shown that track arches record foot kinematics instead. Analyses of track arches can thereby inform the evolution of human locomotion, although quantifying this 3-D aspect of track morphology is difficult. Here, we present a volumetric method for measuring the arches of 3-D models of human tracks and feet, using both Autodesk Maya and Blender software. The method involves generation of a 3-D object that represents the space beneath the longitudinal arch, and measurement of that arch object's geometry and spatial orientation. We provide relevant tools and guidance for users to apply this technique to their own data. We present three case studies to demonstrate potential applications. These include, (1) measuring the arches of static and dynamic human feet, (2) comparing the arches of human tracks with the arches of the feet that made them, and (3) direct comparisons of human track and foot arch morphology throughout simulated track formation. The volumetric measurement tool proved robust for measuring 3-D models of human tracks and feet, in static and dynamic contexts. This tool enables researchers to quantitatively compare arches of fossil hominin tracks, in order to derive biomechanical interpretations from them, and/or offers a different approach for quantifying foot morphology in living humans.

Nurses’ records on guidance for users with tuberculosis in Primary Health Care

Resumo Objetivo Avaliar a completude dos registros de enfermeiros sobre as orientações dadas a usuários com tuberculose (TB) acompanhados na Atenção Primária à Saúde (APS). Métodos Estudo documental e retrospectivo, cuja população foi constituída por todos prontuários dos casos novos de TB notificados em Unidades de Saúde da Família de um município da Paraíba entre 2015 e 2019. O estudo foi desenvolvido entre julho e setembro de 2020, com uma amostra de 190 prontuários selecionados por amostragem proporcional e probabilística sistemática. Utilizou-se o software R para análise estatística, com nível de significância de 5%, empregando estatística descritiva, Diagrama de Pareto e análise de tendência. Resultados Do total, 60% dos indicadores foram classificados como muito ruins (orientações sobre alimentação, tratamento e consultas) na avaliação da completude do registro sobre as orientações de enfermeiros a respeito das orientações à TB. O Diagrama de Pareto destacou as orientações relacionadas a alimentação e tratamento como os principais problemas no registro, representando mais de 50% da incompletude total. Os modelos de tendência apresentaram evidências estatísticas crescentes para a incompletude do indicador ‘orientações sobre consultas’ (p=0,016) e tendência crescente para os indicadores ‘orientações sobre exames e consultas’. Em contrapartida, as orientações sobre alimentação e exames mostraram tendência decrescente de incompletude. Conclusão Os registros mostraram uma completude inadequada, acompanhada por uma tendência crescente de incompletude no registro de orientações aos usuários com TB na APS. Esse cenário aponta para a urgência de medidas de intervenção na saúde pública, para aprimorar o acompanhamento da TB na APS.

Region-Aware Portrait Retouching With Sparse Interactive Guidance

Portrait retouching aims to improve the aesthetic quality of input portrait photos and especially requires human-region priority. The deep learning-based methods largely elevate the retouching efficiency and provide promising retouched results. However, existing portrait retouching methods focus on automatic retouching, which treats all human-regions equally and ignores users' preferences for specific individuals, thus suffering from limited flexibility in interactive scenarios. In this work, we emphasize the importance of users' intents and explore the interactive portrait retouching task. Specifically, we propose a region-aware retouching framework with two branches: an automatic branch and an interactive branch. The automatic branch involves an encoding-decoding process, which searches region candidates and performs automatic region-aware retouching without user guidance. The interactive branch encodes sparse user guidance into a priority condition vector and modulates latent features with a region selection module to further emphasize the user-specified regions. Experimental results show that our interactive branch effectively captures users' intents and generalizes well to unseen scenes with sparse user guidance, while our automatic branch also outperforms the state-of-the-art retouching methods due to improved region-awareness.

Conceptualizing Patient as an Organization With the Adoption of Digital Health.

This study aimed to identify the factors affecting adoption intention using the TAM (Technology Acceptance Model), HB (Health Belief model), and the UTAUT (Unified Theory of Acceptance and Use of Technology). The argument is made that the adoption of the technology enables patients to create resources (ie, data), transforming patients from mere consumers to producers as well. PLS analysis showed that health beliefs and perceived ease of use had positive effects on the perceived usefulness of digital healthcare, and system capabilities positively impacted perceived ease of use. Furthermore, perceived service, the customer's willingness to change and reference group influence significantly impacted adoption intention (b > 0.1, t > 1.96, P < .05). However, privacy protection and data security, online healthcare resources, and user guidance were not positively associated with perceived usefulness. Perceived usefulness, the customer's willingness to change, and the influence of the reference group are decisive variables affecting adoption intention among the general population, whereas privacy protection and data security are indecisive variables. Online resources and user guides do not support adoption intentions.

Challenges for Future Robotic Sorters of Mixed Industrial Waste: A Survey

To achieve recycling of mixed industrial waste toward an advanced sustainable society, waste sorting automation through robots is crucial and urgent. For this purpose, a robot is required to recognize the category, shape, pose, and condition of different waste items and manipulate them according to the category to be sorted. This survey considers three potential difficulties in the sorting automation: 1) End-effector: to robustly grasp and manipulate different waste items with dirt and deformations; 2) Sensor: to recognize the category, shape, and pose of existing objects to be manipulated and the wet and dirty conditions of their surfaces; and 3) Planner: to generate feasible and efficient sequences and trajectories. This survey includes 76 references to studies related to automatic waste sorting and 159 references to worldwide waste recycling attempts. This pioneering investigation reveals the possibility and limitations of conventional systems; thus, providing insights on open issues and potential technologies to achieve a robot-incorporated sorter for the chaotic mixed waste is one of its contributions. This paper further presents a system design policy for readers and discusses future advanced sorters, thereby contributing to the field of robotics and automation. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Most automated sorting systems operate for limited target waste items. This study is motivated by the automation of mixed industrial waste treatment facilities using advanced robotic sorters. Emerging advances and increasing functionalities of robot system components will widen system applicability and increase use cases in the chaotic mixed industrial waste domain. This paper surveys the research conducted to date, discusses open issues and potential approaches, and presents user guides that provide practitioners with a system design policy. The user guides created according to the strengths and weaknesses of each system configuration provide future researchers and developers with a useful a priori design policy that has been thus far validated on efficiency, quality, productivity, and reliability. A question-and-answer style guide and a sorting-target-aware previous study reference list allows users to find the desired system configuration, including the investigated components according to their purpose.

Body MRI Pulse Sequences: Atlas and User Guide.

Body MRI Pulse Sequences: Atlas and User Guide.

A Model of Science, Technology, Engineering, and Mathematics Remote Research-Based Learning

Opportunities for research-based learning at the high school level are limited, and with the COVID-19 pandemic, these have been further reduced. Such opportunities are particularly scarce for authentic research experiences (AREs), which allow students to identify as scientists by collecting data that contributes to scientists’ research. In response to the COVID-19 pandemic, we adapted two of our AREs for classroom settings, as remote independent research experiences for students to conduct from home. User guides and protocols from the AREs, Genotype-to-Phenotype Research with Corn and Discover Volvox Development, were adapted to instruct high school students to work on their own with the guidance of scientists and ARE coordinators. These independent authentic research experiences (IAREs) were implemented in the summer of 2020 and have since been available to students. Student responses to reflection questions and the Laboratory Course Assessment Survey indicate that IAREs provide students with significant gains including learning science content and research practices, collaborating with scientists, facing and resolving challenges, and contributing to scientific research.

Selecting the Appropriate User Experience Questionnaire and Guidance for Interpretation: the UEQ Family

Selecting the Appropriate User Experience Questionnaire and Guidance for Interpretation: the UEQ Family

Beyond Correlation: Incorporating Counterfactual Guidance to Better Support Exploratory Visual Analysis.

Providing effective guidance for users has long been an important and challenging task for efficient exploratory visual analytics, especially when selecting variables for visualization in high-dimensional datasets. Correlation is the most widely applied metric for guidance in statistical and analytical tools, however a reliance on correlation may lead users towards false positives when interpreting causal relations in the data. In this work, inspired by prior insights on the benefits of counterfactual visualization in supporting visual causal inference, we propose a novel, simple, and efficient counterfactual guidance method to enhance causal inference performance in guided exploratory analytics based on insights and concerns gathered from expert interviews. Our technique aims to capitalize on the benefits of counterfactual approaches while reducing their complexity for users. We integrated counterfactual guidance into an exploratory visual analytics system, and using a synthetically generated ground-truth causal dataset, conducted a comparative user study and evaluated to what extent counterfactual guidance can help lead users to more precise visual causal inferences. The results suggest that counterfactual guidance improved visual causal inference performance, and also led to different exploratory behaviors compared to correlation-based guidance. Based on these findings, we offer future directions and challenges for incorporating counterfactual guidance to better support exploratory visual analytics.

Registros de enfermeiros sobre orientações aos usuários com tuberculose na Atenção Primária

Abstract Objective To evaluate the completeness of nurses’ records on guidance given to users with tuberculosis (TB) followed in Primary Health Care (PHC). Methods This was a documentary and retrospective study whose population consisted of all records of new TB cases reported in Family Health Units in a municipality (State of Paraíba) in the period 2015-2019. The study was conducted from July to September 2020 with a sample of 190 medical records selected by systematic proportional and probabilistic sampling. The R software for statistical analysis was used with a 5% significance level, employing descriptive statistics, Pareto Chart, and trend analysis. Results In assessing the completeness of the guidance record about nutrition, treatment, and consultations given by nurses for patients with TB, 60% of the indicators were classified as very poor. The Pareto Chart highlighted guidance on food and treatment as the main problems in the record, representing more than 50% of the total incompleteness. The trend models showed increasing statistical evidence for the incompleteness of the guidance on consultations indicator (p=0.016) and a growing statistical trend for the incompleteness of the guidance on exams and consultations indicators. In contrast, guidance on nutrition and exams showed a decreasing trend in incompleteness. Conclusion Records showed inadequate completeness accompanied by an increasing trend for incompleteness in the registration of guidance for users with TB in PHC. This scenario points to the urgency of intervention measures in Public Health to improve TB monitoring in PHC.

CAISeg: A Clustering-Aided Interactive Network for Lesion Segmentation in 3D Medical Imaging.

Accurate lesion segmentation in medical imaging is critical for medical diagnosis and treatment. Lesions' diverse and heterogeneous characteristics often present a distinct long-tail distribution, posing difficulties for automatic methods. Currently, interactive segmentation approaches have shown promise in improving accuracy, but still struggle to deal with tail features. This triggers a demand of effective utilizing strategies of user interaction. To this end, we propose a novel point-based interactive segmentation model called Clustering-Aided Interactive Segmentation Network (CAISeg) in 3D medical imaging. A customized Interaction-Guided Module (IGM) adopts the concept of clustering to capture features that are semantically similar to interaction points. These clustered features are then mapped to the head regions of the prompted category to facilitate more precise classification. Meanwhile, we put forward a Focus Guided Loss function to grant the network an inductive bias towards user interaction through assigning higher weights to voxels closer to the prompted points, thereby improving the responsiveness efficiency to user guidance. Evaluation across brain tumor, colon cancer, lung cancer, and pancreas cancer segmentation tasks show CAISeg's superiority over the state-of-the-art methods. It outperforms the fully automated segmentation models in accuracy, and achieves results comparable to or better than those of the leading point-based interactive methods while requiring fewer prompt points. Furthermore, we discover that CAISeg possesses good interpretability at various stages, which endows CAISeg with potential clinical application value.

Density functional theory methods applied to homogeneous and heterogeneous catalysis: a short review and a practical user guide.

The application of density functional theory (DFT) methods in catalysis has been growing fast in the last few decades thanks to both the availability of more powerful high computing resources and the development of new efficient approximations and approaches. DFT calculations allow for the understanding of crucial catalytic aspects that are difficult or even impossible to access by experiments, thus contributing to faster development of more efficient and selective catalysts. Depending on the catalytic system and properties under investigation, different approaches should be used. Moreover, the reliability of the obtained results deeply depends on the approximations involved in both the selected method and model. This review addresses chemists, physicists and materials scientists whose interest deals with the application of DFT-based computational tools in both homogeneous catalysis and heterogeneous catalysis. First, a brief introduction to DFT is presented. Then, the main approaches based on atomic centered basis sets and plane waves are discussed, underlining the main differences, advantages and limitations. Eventually, guidance towards the selection of the catalytic model is given, with a final focus on the evaluation of the energy barriers, which represents a crucial step in all catalytic processes. Overall, the review represents a rational and practical guide for both beginners and more experienced users involved in the wide field of catalysis.

A Mediated Moderation Analysis Of The Efficacy Of E-Hrm

The aim of this paper is to examine the effectiveness of e-HRM by a mediated moderation analysis. This paper used both descriptive and quantitative approaches, while the research unit of analysis consists of Line managers and HR specialists. Purposeful sampling was used for the sampling process in this study while, the research sample consists of 373 Line managers and HR specialists. A questionnaire was used to collect data and PLS-SEM was used to evaluate the study. This study responds to two concerns raised in earlier e-HRM studies; first, to draw attention to the importance of the connection between technology and organisational features; and second, to indicate that the implementation of e-HRM leads to higher-quality HRM services. The main factors affecting the excellent quality of HRM services are the benefits of both traditional HRM and e-HRM. Repeated use of e-HRM and user guidance confirmed their mediating effect, while appropriation of e-HRM and acceptance of the e-HRM system demonstrated their moderating influence. This paper encourage line managers and HR specialists must ensure that e-HRM systems are user-friendly and understandable to the intended audience (e.g. Operational: e-payroll processes, Relational: e-recruitment and selection, Transformational: online talent management). This paper has made a significant contribution to knowledge and to the operationalization of e-HRM literature, which could help to develop theory, model, practice and research in areas of HRM quality of service.

The Impact of ChatGPT on Language Learners’ Motivation

As digital technology advances, its tools and applications are being used both inside and outside the classroom to increase student participation and motivation. One encouraging technology that has freshly seized acceptance is the adoption of artificial intelligence (AI) in language learning. One akin AI structure is ChatGPT. It is a language model matured by OpenAI that can engender human-like chat in return to user guidance. The goal of this study is to explore the effect of combining ChatGPT-generated dialogues into language teaching materials on the motivation of language learners. The participants group of this study were second-year 60 university students. The students' motivational strategies were measured using the 'Motivational Strategies for Learning Questionnaire' (Pintrinch &amp; De Groot, 1990). The outcomes of the present study showed that there were statistically powerful differences between majors on the motivation test subcategories (self-regulation, intrinsic values, and test anxiety). In other words, using ChatGPT technology as a learning material, has increased the motivation of the students.

Exploring the user guidance for more accurate building segmentation from high-resolution remote sensing images

In recent years, the computer vision domain has witnessed a surge of interest in interactive object segmentation, an area of study that seeks to expedite the annotation process for pixel-wise segmentation tasks through user guidance. Despite this growing focus, existing methods mainly focus on a single type of pre-annotation and neglect the quality of boundary prediction, which significantly influences subsequent manual adjustments to segmentation boundaries. To address these limitations, we introduce a novel end-to-end network to facilitate more precise building segmentation using diverse types of user guidance. In our proposed method, a centroid map is generated to provide foreground prior information crucial to the subsequent segmentation procedure, and the boundary correction module automatically refines the segmentation mask from existing segmentation networks. Extensive experiments on two popular building extraction datasets demonstrate that our method outperforms all existing approaches given various user guidance (bounding boxes, inside-outside points, or extreme points), achieving the IoU scores of over 95% on SpaceNet-Vegas dataset and over 93% on Inria-building dataset. The remarkable performance of our method further demonstrates its immense potential to alleviate the labor-intensive annotation process associated with remote sensing datasets. The code of our proposed method is available at https://github.com/StephenDHYang/UGBS-pytorch.

Lean Office: Proposition and Application of a Process-Mapping Method Based on the Shingo Production Mechanism (SPM)

This study proposes a process-mapping method based on the SPM to identify waste in office environments. Design Science Research was used to develop a method (M0) for mapping processes in office environments. This method was subjected to critical analysis by four experts in the field, who sent their contributions. Thus, a new method (M1) was generated, which was instantiated in a company in Brazil in the process of technical publications and user guides. As a result, in the practical application, it was possible to verify the efficiency of the proposed method, and the future flow of the analyzed flow allowed a reduction in the lead time by 75% and an increase in the rate of added value from 4.88% to 19.56%. The method can contribute to the identification of waste more complex than the usual VSM and thus improve office environments. This way, managers and process engineers can understand the activities in detail and propose improvements in these processes, generating greater speed and precision. This method proposal for administrative environments, aims to expand the detailing of waste, allowing greater precision in the identification of waste and, consequently, greater effectiveness in improving the process flow analyzed.

Navigating the Expansive Landscapes of Soft Materials: A User Guide for High-Throughput Workflows.

Synthetic polymers are highly customizable with tailored structures and functionality, yet this versatility generates challenges in the design of advanced materials due to the size and complexity of the design space. Thus, exploration and optimization of polymer properties using combinatorial libraries has become increasingly common, which requires careful selection of synthetic strategies, characterization techniques, and rapid processing workflows to obtain fundamental principles from these large data sets. Herein, we provide guidelines for strategic design of macromolecule libraries and workflows to efficiently navigate these high-dimensional design spaces. We describe synthetic methods for multiple library sizes and structures as well as characterization methods to rapidly generate data sets, including tools that can be adapted from biological workflows. We further highlight relevant insights from statistics and machine learning to aid in data featurization, representation, and analysis. This Perspective acts as a "user guide" for researchers interested in leveraging high-throughput screening toward the design of multifunctional polymers and predictive modeling of structure-property relationships in soft materials.

P36: Intimacy and Sexuality Expression Preference (ISEP) Tool: Usage experience and creation of a practical user guide

AbstractAgeing and dementia affect many aspects of life, including intimate relationships, sex and sexual expression. Older people, including those living with dementia, can have sexual relationships and form new ones. Their sexual and physical health, quality of life, and psychological well-being can be improved by respecting their intimacy and sexuality expression preferences. However, due to ageism and stigma, healthcare professionals often ignore the sexual feelings and needs of those with dementia living in long-term care. Discussions with stakeholders and literature show limited attention paid to understanding the sexual preferences of people living with dementia in health and social care. In 2020, the Intimacy and Sexuality Expression Preference (ISEP) tool was developed for use in long-term care to gather information on intimate and sexual expression preferences of older people, including those living with dementia, to assist in care provision. The ISEP tool was trialled in a Queensland, Australia, nursing home with 14 older residents. This presentation will share insight into the use of the ISEP tool and how it informs the development of ‘ISEP: A Practical User Guide’. This guide provides information on how to (a) use the ISEP tool for assessment; (b) interpret and integrate findings into care (i.e., identify a potential course of action); and (c) evaluate outcomes. Illustrative examples will be included. It will inform how preferences for the expression of sexuality can be practically addressed to improve care practices and care outcomes (i.e., satisfaction and quality of life) for people with dementia.

Joint AAPM Task Group 282/EFOMP Working Group Report: Breast dosimetry for standard and contrast-enhanced mammography and breast tomosynthesis.

Currently, there are multiple breast dosimetry estimation methods for mammography and its variants in use throughout the world. This fact alone introduces uncertainty, since it is often impossible to distinguish which model is internally used by a specific imaging system. In addition, all current models are hampered by various limitations, in terms of overly simplified models of the breast and its composition, as well as simplistic models of the imaging system. Many of these simplifications were necessary, for the most part, due to the need to limit the computational cost of obtaining the required dose conversion coefficients decades ago, when these models were first implemented. With the advancements in computational power, and to address most of the known limitations of previous breast dosimetry methods, a new breast dosimetry method, based on new breast models, has been developed, implemented, and tested. This model, developed jointly by the American Association of Physicists in Medicine and the European Federation for Organizations of Medical Physics, is applicable to standard mammography, digital breast tomosynthesis, and their contrast-enhanced variants. In addition, it includes models of the breast in both the cranio-caudal and the medio-lateral oblique views. Special emphasis was placed on the breast and system models used being based on evidence, either by analysis of large sets of patient data or by performing measurements on imaging devices from a range of manufacturers. Due to the vast number of dose conversion coefficients resulting from the developed model, and the relative complexity of the calculations needed to apply it, a software program has been made available for download or online use, free of charge, to apply the developed breast dosimetry method. The program is available for download or it can be used directly online. A separate User's Guide is provided with the software.

HierVid: Lowering the Barriers to Entry of Interactive Video Making with a Hierarchical Authoring System

Interactive videos have been applied to various areas due to their engagement potential and efficiency improvement of information communication. However, creating interactive videos can be challenging because of a lack of novice-oriented guidance in current platforms, and the logic-building process when authoring interactive videos. To address these challenges, we obtained insights from four creativity support tool designers, proposed a series of hierarchical interactive video structures based on existing narrative structures, and presented the HierVid system. The system is designed as a Template-Module-Unit Mode-based hierarchical authoring platform grounded on three design requirements, and we conducted two user studies to evaluate HierVid. The results showed that novice users could get started to use and understand the functions easily, and the system allowed users to use and explore freely, with an enhanced efficiency compared to the bilibili platform. In conclusion, our research and design of HierVid offer guidance and support for novice users, making interactive video authoring quicker and more accessible.