Effects of a group-deposit prize draw on the step counts of adults

The World Health Organization (WHO, 2016) reports that 3.2 million deaths per year are attributable to physical inactivity, making it the fourth leading risk factor for global mortality. Physical inactivity is also a key risk factor for noncommunicable diseases such as cardiovascular disease, cancer, and diabetes (WHO, 2018). Globally, 1 in 4 adults is not active enough and, therefore, foregoes a myriad of health benefits associated with Physical Activity (PA; WHO, 2018). In the United States, only about 1 in 5 (21%) adults meet the 2008 Physical Activity Guidelines set by the Centers for Disease Control and Prevention (CDC, 2018). The CDC currently recommends adults engage in 150 min of moderate-intensity aerobic activity per week (CDC, 2018). Translated to steps, the recommendation can be met by taking 3,000 steps in 30 min, 5 days per week (Marshall et al., 2009). Physical inactivity is also a major contributor to obesity (WHO, 2018). According to the WHO (2018), worldwide prevalence of obesity almost tripled since 1975. In the United States, the medical costs of obesity were estimated to be $147 billion, or 10% of all medical spending (Finkelstein, Trogdon, Cohen, & Dietz, 2009). To combat the many problems associated with physical inactivity, the CDC (2015), the WHO (2018), and the American Heart Association (2018) prescribe increased PA. Furthermore, increased PA contributes to a variety of other health benefits, including a decreased risk for cardiovascular disease, type 2 diabetes, some cancers, as well as improved mental health, and increased life expectancy (CDC, 2018)

Bin-Picking Solution for Randomly Placed Automotive Connectors Based on Machine Learning Techniques

This paper presents the development of a bin-picking solution based on low-cost vision systems for the manipulation of automotive electrical connectors using machine learning techniques. The automotive sector has always been in a state of constant growth and change, which also implies constant challenges in the wire harnesses sector, and the emerging growth of electric cars is proof of this and represents a challenge for the industry. Traditionally, this sector is based on strong human work manufacturing and the need arises to make the digital transition, supported in the context of Industry 4.0, allowing the automation of processes and freeing operators for other activities with more added value. Depending on the car model and its feature packs, a connector can interface with a different number of wires, but the connector holes are the same. Holes not connected with wires need to be sealed, mainly to guarantee the tightness of the cable. Seals are inserted manually or, more recently, through robotic stations. Due to the huge variety of references and connector configurations, layout errors sometimes occur during seal insertion due to changed references or problems with the seal insertion machine. Consequently, faulty connectors are dumped into boxes, piling up different types of references. These connectors are not trash and need to be reused. This article proposes a bin-picking solution for classification, selection and separation, using a two-finger gripper, of these connectors for reuse in a new operation of removal and insertion of seals. Connectors are identified through a 3D vision system, consisting of an Intel RealSense camera for object depth information and the YOLOv5 algorithm for object classification. The advantage of this approach over other solutions is the ability to accurately detect and grasp small objects through a low-cost 3D camera even when the image resolution is low, benefiting from the power of machine learning algorithms.info:eu-repo/semantics/publishedVersio

A morphospace of functional configuration to assess configural breadth based on brain functional networks

The best approach to quantify human brain functional reconfigurations in response to varying cognitive demands remains an unresolved topic in network neuroscience. We propose that such functional reconfigurations may be categorized into three different types: i) Network Configural Breadth, ii) Task-to-Task transitional reconfiguration, and iii) Within-Task reconfiguration. In order to quantify these reconfigurations, we propose a mesoscopic framework focused on functional networks (FNs) or communities. To do so, we introduce a 2D network morphospace that relies on two novel mesoscopic metrics, Trapping Efficiency (TE) and Exit Entropy (EE), which capture topology and integration of information within and between a reference set of FNs. In this study, we use this framework to quantify the Network Configural Breadth across different tasks. We show that the metrics defining this morphospace can differentiate FNs, cognitive tasks and subjects. We also show that network configural breadth significantly predicts behavioral measures, such as episodic memory, verbal episodic memory, fluid intelligence and general intelligence. In essence, we put forth a framework to explore the cognitive space in a comprehensive manner, for each individual separately, and at different levels of granularity. This tool that can also quantify the FN reconfigurations that result from the brain switching between mental states.Comment: main article: 24 pages, 8 figures, 2 tables. supporting information: 11 pages, 5 figure

The Influence of Education and Experience upon Contextual and Task Performance in Warehouse Operations

Supply chain workers make observable, preventable errors while completing their assigned tasks in the shipping process. Previous research has indicated that individuals with a greater grasp of their work and better system knowledge are less likely to commit interpretation errors. We believe worker-performance may, likewise, be affected by an individuals knowledge of why and where they fit into a larger system defined as mission knowledge. To assess our research objectives, we conduct a controlled experiment with 100 workers in the Air Force supply career field to discern how mission clarity, that is, education, experience and subject characteristics affect pick and pack errors in simulated warehouse order fulfillment tasks. Results indicate that participants who received the experience treatment committed fewer errors, resulting in increased task performance

Managing Solid Waste In School Environment Through Composting Approach

This study aimed at improving solid waste disposal in schools by using the composting approach. The theory that underpinned this study was Reduce, Reuse, and Recycle (3R) theory, while the necessary data were gathered by using a synthesis and integration approach. The following three research questions were framed to guide the conduct of the study: How important is solid waste management in schools? What pedagogical techniques are most effective for promoting environmental sustainability by teaching composting in schools? What are the challenges involved in the composting process at school?  The synthesis and integration approach assisted in integrating concepts from different sources and synthesizing those concepts to create a comprehensive and cogent argument in accordance with emerging themes. It was discovered that solid waste management in schools was particularly crucial since schools produced a lot of rubbish and that waste may affect the environment negatively. Composting is essential to improve school solid waste because it enhances soil health, decreases waste, and encourages sustainable agricultural methods. Three pedagogical techniques that could be utilized to facilitate the teaching and learning of composting in schools have evolved based on the theoretical framework and the literature provided. Project-based learning (PBL), hands-on learning, and inquiry-based learning were some of the new pedagogical strategies. However, some of the challenges with the composting process were identified as follows: difficulty in regulating the moisture level of the compost, keeping the proper balance of carbon and nitrogen in the compost pile, and inability to educate students and staff about the composting process

The Impact of Nurses\u27 Adherence to Sedation Vacations on Ventilator Associated Pneumonia Prevention

Patients who require mechanical ventilation (MV) are at risk for developing ventilator associated pneumonia (VAP). Nurses’ adherence to sedation vacations (SVs) has a direct impact on the development of VAP, because SVs have been shown to reduce patients’ average duration of MV and length of stay (LOS) in the intensive care unit (ICU). The purposes of this study guided by Donabedian’s (1966) model were to quantify nurses’ level of adherence to SVs, in relation to the health outcomes of critically ill patients, and identify the barriers and facilitators to performing SVs. A correlational design was used. The design included three components: abstraction of patient data from the electronic medical record (EMR) (n=79 with VAP and n=79 without VAP), administration of surveys to ICU nurses (N =34), and vignettes related to SVs. Analyses included descriptive statistics, t-tests, correlations, and analyses of covariance. Most nurses held a Bachelors degree (70.6%), had \u3c 9 years of ICU experience (52.9%), worked in a medical ICU (47.1%), and reported high confidence in managing SVs (M =8.88, SD =1.25). The majority of patients (N =158) were Black (58.2%), males (56.3%), and on average middle-aged (M =61.5, SD =14.91), with a long ICU LOS (M =15.5, SD =11.84), extended duration of MV (M =9.5, SD =8.47), and high acuity (APACHE III) (M =70.2, SD =25.42). The nurses’ education, advanced certification, and ICU experience were not associated with the appropriate implementation of SVs in the vignettes. On average nurses’ had low scores on the vignettes (M =6.97, SD =2.21; possible range =0-14). The adherence rate of nurses’ implementation of SVs, determined using EMR data, was also low (M =24%; SD =23%). There were higher rates of SV adherence in patients without VAP (p (p \u3c .01), and a duration of MV \u3c 6 days (p =.04). These findings indicate that even with established protocols, nurses may not consistently implement the evidenced-based interventions that have been shown to prevent nosocomial infections. Future research is needed to improve nursing practice and the quality of care in this patient population

A ROS-based software architecture for a versatile collaborative dual-armed autonomous mobile robot for the manufacturing industry

The industrial context is changing rapidly due to advancements in technology fueled by the Internet and Information Technology. The fourth industrial revolution counts integration, flexibility, and optimization as its fundamental pillars, and, in this context, Human-Robot Collaboration has become a crucial factor for manufacturing sustainability in Europe. Collaborative robots are appealing to many companies due to their low installation and running costs and high degree of flexibility, making them ideal for reshoring production facilities with a short return on investment. The ROSSINI European project aims to implement a true Human-Robot Collaboration by designing, developing, and demonstrating a modular and scalable platform for integrating human-centred robotic technologies in industrial production environments. The project focuses on safety concerns related to introducing a cobot in a shared working area and aims to lay the groundwork for a new working paradigm at the industrial level. The need for a software architecture suitable to the robotic platform employed in one of three use cases selected to deploy and test the new technology was the main trigger of this Thesis. The chosen application consists of the automatic loading and unloading of raw-material reels to an automatic packaging machine through an Autonomous Mobile Robot composed of an Autonomous Guided Vehicle, two collaborative manipulators, and an eye-on-hand vision system for performing tasks in a partially unstructured environment. The results obtained during the ROSSINI use case development were later used in the SENECA project, which addresses the need for robot-driven automatic cleaning of pharmaceutical bins in a very specific industrial context. The inherent versatility of mobile collaborative robots is evident from their deployment in the two projects with few hardware and software adjustments. The positive impact of Human-Robot Collaboration on diverse production lines is a motivation for future investments in research on this increasingly popular field by the industry

Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus

This is an open access book. It gathers the first volume of the proceedings of the 31st edition of the International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022, held on June 19 – 23, 2022, in Detroit, Michigan, USA. Covering four thematic areas including Manufacturing Processes, Machine Tools, Manufacturing Systems, and Enabling Technologies, it reports on advanced manufacturing processes, and innovative materials for 3D printing, applications of machine learning, artificial intelligence and mixed reality in various production sectors, as well as important issues in human-robot collaboration, including methods for improving safety. Contributions also cover strategies to improve quality control, supply chain management and training in the manufacturing industry, and methods supporting circular supply chain and sustainable manufacturing. All in all, this book provides academicians, engineers and professionals with extensive information on both scientific and industrial advances in the converging fields of manufacturing, production, and automation

Wearable Medical Devices in Use: A Study of Insulin Pump Adoption by Young Diabetic Patients In Saudi Arabia

his research belongs to the multi-disciplinary research community concerned with wearable medical technology and branches of sociology and psychology that study its impact. It addresses a real-life problem of Insulin Pump (IP) adoption by Children. This is important for Saudi Arabia, since it is among the top five countries in the world with the highest rate of diabetes. Theories of reasoned action (TRA), technology acceptance model (TAM) and health belief models (HBM) for some of the cases predict that the perception of benefits is the main motivator for the proper use of the technology. This is often not realised in practice, because the main theoretical focus is on the benefits of IP, specifically in the pre-adoption phase. In contrast, this research project is focused on the reasons why some diabetic children patients misuse the IP in spite of the initial perception of its benefits. To find answers to this research question, an empirical study of adoption of IP by children and young adults in Saudi Arabia was carried out. A novel analytical framework was developed in this study in order to unify different perspectives and expectations of the benefits of the IP for a diabetic child and young adult. The analytic framework is applied using empirical study of diabetic children struggling with the IP in the course of the adoption process, with main emphasis on the post-adoption phase. Research methods were predominantly qualitative, involving in-depth interviews and case studies. In the discovery phase, data was collected through interviews of medical personnel and case studies with children and their parents. The analysis was focused on different interactions between medical personnel, patients and their caregivers, the discourses among them in order to explicate the contradictions between them. The main findings are that contradictions show different expectations between the different actors. The medical personnel used medical reasons, whereas the caregiver focus on emotional aspects. However, the diabetic child was concerned with the life-style changes that the use of the IP caused. The different motivations create misunderstandings and result in resistance towards the IP. Age-related and culture-specific factors were also considered, but further research is needed to ensure that the findings can be generalised to other devices, age-groups, cultures and different social contexts. Such studies would also refine the analytical framework and enrich research methodology to make generalisations possible