Readiness for implementation of novel digital health interventions for postoperative monitoring:a systematic review and clinical innovation network analysis

An increasing number of digital health interventions (DHIs) for remote postoperative monitoring have been developed and evaluated. This systematic review identifies DHIs for postoperative monitoring and evaluates their readiness for implementation into routine health care. Studies were defined according to idea, development, exploration, assessment, and long-term follow-up (IDEAL) stages of innovation. A novel clinical innovation network analysis used coauthorship and citations to examine collaboration and progression within the field. 126 DHIs were identified, with 101 (80%) being early stage innovations (IDEAL stage 1 and 2a). None of the DHIs identified had large-scale routine implementation. There is little evidence of collaboration, and there are clear omissions in the evaluation of feasibility, accessibility, and the health-care impact. Use of DHIs for postoperative monitoring remains at an early stage of innovation, with promising but generally low-quality supporting evidence. Comprehensive evaluation within high-quality, large-scale trials and real-world data are required to definitively establish readiness for routine implementation

An Annotated Bibliography of Financial Therapy Research: 2010 to 2018

The purpose of this paper is to expand upon Mentzer, Britt, Samuelson, and Herrera’s (2010) annotated bibliography of research conducted in the field of financial therapy prior to 2010 and provide readers with a current overview of financial therapy research published since that time. Annotated bibliographies are categorized by topics and future research in each area is suggested. In addition, two tables were developed to provide readers a snapshot of the current landscape of financial therapy. The first table provides a list of journals of published articles featuring financial therapy or related topics. The second table provides an overview of types of research, population studies, key topics, as well as highlighting whether theory and financial therapy are overtly referred to within the article

NASA Tech Briefs, November 2010

Topics covered include: Portable Handheld Optical Window Inspection Device; Salience Assignment for Multiple-Instance Data and Its Application to Crop Yield Prediction; Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems ; Predicting Long-Range Traversability from Short-Range Stereo-Derived Geometry; Browser-Based Application for Telemetry Monitoring of Robotic Assets; Miniature Low-Noise G-Band I-Q Receiver; Methods of Using a Magnetic Field Response Sensor Within Closed, Electrically Conductive Containers; Differential Resonant Ring YIG Tuned Oscillator; Microfabricated Segmented-Involute-Foil Regenerator for Stirling Engines; Reducing Seal Adhesion in Low Impact Docking Systems; Optimal Flow Control Design; Corrosion-Resistant Container for Molten-Material Processing; Reusable Hot-Wire Cable Cutter; Deployment of a Curved Truss; High-Volume Airborne Fluids Handling Technologies to Fight Wildfires; Modeling of Alkane Oxidation Using Constituents and Species; Fabrication of Lanthanum Telluride 14-1-11 Zintl High-Temperature Thermoelectric Couple; A Computer Model for Analyzing Volatile Removal Assembly; Analysis of Nozzle Jet Plume Effects on Sonic Boom Signature; Optical Sidebands Multiplier; Single Spatial-Mode Room-Temperature-Operated 3.0 to 3.4 micrometer Diode Lasers; Self-Nulling Beam Combiner Using No External Phase Inverter; Portable Dew Point Mass Spectrometry System for Real-Time Gas and Moisture Analysis; Maximum Likelihood Time-of-Arrival Estimation of Optical Pulses via Photon-Counting Photodetectors; Handheld White Light Interferometer for Measuring Defect Depth in Windows; Decomposition Algorithm for Global Reachability on a Time-Varying Graph; Autonomous GN and C for Spacecraft Exploration of Comets and Asteroids; Efficient Web Services Policy Combination; Using CTX Image Features to Predict HiRISE-Equivalent Rock Density; Isolation of the Paenibacillus phoenicis, a Spore-Forming Bacterium; Monolithically Integrated, Mechanically Resilient Carbon-Based Probes for Scanning Probe Microscopy; Cell Radiation Experiment System; Process to Produce Iron Nanoparticle Lunar Dust Simulant Composite; Inversion Method for Early Detection of ARES-1 Case Breach Failure; Use of ILTV Control Laws for LaNCETS Flight Research;and Evaluating Descent and Ascent Trajectories Near Non-Spherical Bodies

Application of web 3.0 technologies in distance education (by levels of higher education)

The purpose of the survey is to identify the need for Web 3.0-technologies in distance education among higher education seekers initial level (short cycle), first (bachelor's) level, second (master's) level, third (educational-scientific/educational-creative) level, scientific level among 438 applicants for higher education. Features (open source software (OSS) for developing, sharing and configuring programs for global use and application, built-in algorithms for analyzing and interpreting large amounts of data) and the benefits of Web 3.0 in higher education (the ability to organize collaboration on a social network, encourage globalization, improve data management, stimulate creativity and innovation, support the availability of mobile Internet). The correlation between the functions of Web 3.0-technologies in distance education and learning outcomes at all levels of higher education is established. Intelligence indicates a lack of comprehensive scientific research in the relevant field. The practical significance of the results of intelligence lies in the correlation of the functions of Web 3.0-technologies in distance education and learning outcomes at all levels of higher education

Metabolomics Data Processing and Data Analysis—Current Best Practices

Metabolomics data analysis strategies are central to transforming raw metabolomics data files into meaningful biochemical interpretations that answer biological questions or generate novel hypotheses. This book contains a variety of papers from a Special Issue around the theme “Best Practices in Metabolomics Data Analysis”. Reviews and strategies for the whole metabolomics pipeline are included, whereas key areas such as metabolite annotation and identification, compound and spectral databases and repositories, and statistical analysis are highlighted in various papers. Altogether, this book contains valuable information for researchers just starting in their metabolomics career as well as those that are more experienced and look for additional knowledge and best practice to complement key parts of their metabolomics workflows

El efecto de la convergencia de los medios de comunicación en el aprovechamiento de oportunidades empresariales

This paper sheds light on specific aspect of Media Convergence which is not only about convergence and similarity, but about divergence in different aspects and opportunities which bring up for entrepreneurial activities. Problem area of this study is to understand how media convergence provides new business opportunities in media markets and how media entrepreneurs can exploit those opportunities for proposing value to target customers. This paper follows a quantitative research design. Therefore, 119 cofounders of small and medium media firms answered an online questionnaire, and the data was analyzed by SPSS. Regression analysis was used to analyze the data. The findings reveal that four types of divergence, including media distribution channels, media content producers, audiences, and advertisers, affect exploitation of entrepreneurial opportunities in small and medium sized media firms.Este documento arroja luz sobre aspectos específicos de la convergencia de los medios de comunicación, que se trata solamente de convergencia y similitud, sino de divergencia en diferentes aspectos y oportunidades que se presentan en las actividades empresariales. El área problemática de este estudio es comprender cómo la convergencia de los medios de comunicación brinda nuevas oportunidades de negocio en los mercados de los medios de comunicación y cómo los empresarios de los medios pueden aprovechar esas oportunidades para proponer valor a sus clientes objetivo. Este trabajo realiza un diseño de investigación cuantitativa. Por lo tanto, 119 cofundadores de pequeñas y medianas empresas de medios respondieron un cuestionario en línea, y los datos fueron analizados a través del programa estadístico SPSS. El análisis de regresión se utilizó para analizar los datos. Los hallazgos revelan que cuatro tipos de divergencias, que incluyen los canales de distribución de medios, los productores de contenido de medios, las audiencias y los anunciantes, afectan el aprovechamiento de oportunidades empresariales en pequeñas y medianas empresas de medios

The state of web accessibility for people with cognitive disabilities: a rapid evidence assessment

Increased digitisation of day-to-day activities was occurring prior to the COVID-19 pandemic. The pandemic only accelerated the virtual shift, making web accessibility an urgent issue, especially for marginalised populations. Despite decades of work to develop, refine, and implement web accessibility standards, people with cognitive disabilities regularly experience many barriers to web accessibility. To inform ongoing work to improve web accessibility for people with cognitive disabilities, a systematic review was conducted. The main question guiding this review is: what are the state-of-the-art of interventions that support web accessibility for citizens, 9 years of age and up, living with cognitive impairment? A set of 50 search strings were entered into three academic databases: SCOPUS, ProQuest, and Web of Science. Systematic screening procedures narrowed the search returns to a total of 45 included papers. A data analysis revealed themes associated with the lived experiences of people with cognitive disabilities, tools for improving web accessibility, and methodological best practices for involving people with cognitive disabilities in research. These findings have immediate implications for ongoing research and the development of meaningful solutions to the problem of web accessibility for people with cognitive disabilities.info:eu-repo/semantics/publishedVersio

The experience of body image for people with a left ventricular assist device

This thesis is comprised of a systematic literature review, an empirical paper and a critical appraisal. Firstly, a systematic review and metasynthesis of qualitative studies exploring psychological experiences of adult heart transplant recipients was conducted. A metaethnographic approach was used to synthesise the findings of 12 papers. The results demonstrated that recipients underwent a process of making sense of their identity following transplantation. Recipients perceived that their psychological adjustment was impacted by the expectations of medical professionals, friends, family and wider society. They experienced fluctuating positive and negative emotions such as anxiety, grief and gratitude. Physical, social and psychological factors influenced coping and adaptation, contributing to better psychological wellbeing. Clinical implications are discussed. Secondly, the empirical paper explores experiences of body image for adults implanted with a left ventricular assist device (LVAD). Nine participants were interviewed, and the data were analysed using interpretative phenomenological analysis. The findings highlighted the importance of social, functional and appearance-related aspects of body image for LVAD-users. Participants re-evaluated their body with the LVAD and perceived that it, and themselves were “different”. They perceived their body as restricted and had a constant awareness of their body and device, which led to feelings of anxiety. LVAD-users used practical and psychological strategies to adjust to their changed body and perceive themselves as more “normal”. Clinical implications and limitations of the study are discussed, and further research is recommended. Finally, the critical appraisal offers a reflection on the process of conducting LVAD research including strengths and limitations. It also compares the findings of the review and empirical papers and recommends further areas for research

Optimization of Fluid Bed Dryer Energy Consumption for Pharmaceutical Drug Processes through Machine Learning and Cloud Computing Technologies

[ES] Los altos costes energéticos, las constantes medidas regulatorias aplicadas por las administraciones para mantener bajos los costes sanitarios, así como los cambios en la normativa sanitaria que se han introducido en los últimos años, han tenido un impacto significativo en la industria farmacéutica y sanitaria. El paradigma Industria 4.0 engloba cambios en el modelo productivo tradicional de la industria farmacéutica con la inclusión de tecnologías que van más allá de la automatización tradicional. El objetivo principal es lograr medicamentos más rentables mediante la incorporación óptima de tecnologías como la analítica avanzada. El proceso de fabricación de las industrias farmacéuticas tiene diferentes etapas (mezclado, secado, compactado, recubrimiento, envasado, etc.) donde una de las etapas más costosas energéticamente es el proceso de secado. El objetivo durante este proceso es extraer el contenido de líquidos como el agua mediante la inyección de aire caliente y seco en el sistema. Este tiempo de secado normalmente está predeterminado y depende del volumen y el tipo de unidades de producto farmacéutico que se deben deshidratar. Por otro lado, la fase de precalentamiento puede variar dependiendo de varios parámetros como la experiencia del operador. Por lo tanto, es posible asumir que una optimización de este proceso a través de analítica avanzada es posible y puede tener un efecto significativo en la reducción de costes en todo el proceso de fabricación. Debido al alto coste de la maquinaria involucrada en el proceso de producción de medicamentos, es una práctica común en la industria farmacéutica tratar de maximizar la vida útil de estas máquinas que no están equipados con los últimos sensores. Así pues, es posible implementar un modelo de aprendizaje automático que utilice plataformas de analítica avanzada, como la computación en la nube, para analizar los posibles ahorros en el consumo de energía. Esta tesis está enfocada en mejorar el consumo de energía en el proceso de precalentamiento de un secador de lecho fluido, mediante la definición e implementación de una plataforma de computación en la nube IIOT (Industrial Internet of Things)-Cloud, para alojar y ejecutar un algoritmo de aprendizaje automático basado en el modelo Catboost, para predecir cuándo es el momento óptimo para detener el proceso y reducir su duración y, en consecuencia, su consumo energético. Los resultados experimentales muestran que es posible reducir el proceso de precalentamiento en un 45% de su duración en tiempo y, en consecuencia, reducir el consumo de energía hasta 2.8 MWh por año.[CAT] Els elevats costos energètics, les constants mesures reguladores aplicades per les administracions per mantenir uns costos assistencials baixos, així com els canvis en la normativa sanitària que s'han introduït en els darrers anys, han tingut un impacte important en el sector farmacèutic i sanitari. El paradigma de la indústria 4.0 engloba els canvis en el model de producció tradicional de la indústria farmacèutica amb la inclusió de tecnologies que van més enllà de l'automatització tradicional. L'objectiu principal és aconseguir fàrmacs més rendibles mitjançant la incorporació òptima de tecnologies com l'analítica avançada. El procés de fabricació de les indústries farmacèutiques té diferents etapes (mescla, assecat, compactació, recobriment, envasat, etc.) on una de les etapes més costoses energèticament és el procés d'assecat. L'objectiu d'aquest procés és extreure el contingut de líquids com l'aigua injectant aire calent i sec al sistema. Aquest temps de procediment d'assecat normalment està predeterminat i depèn del volum i del tipus d'unitats de producte farmacèutic que cal deshidratar. D'altra banda, la fase de preescalfament pot variar en funció de diversos paràmetres com l'experiència de l'operador. Per tant, podem assumir que una optimització d'aquest procés mitjançant analítiques avançades és possible i pot tenir un efecte significatiu de reducció de costos en tot el procés de fabricació. A causa de l'elevat cost de la maquinària implicada en el procés de producció de fàrmacs, és una pràctica habitual a la indústria farmacèutica intentar maximitzar la vida útil d'aquestes màquines que no estan equipats amb els darrers sensors. Així, es pot implementar un model d'aprenentatge automàtic que utilitza plataformes de analítiques avançades com la computació en núvol, per analitzar l'estalvi potencial del consum d'energia. Aquesta tesis està enfocada a millorar el consum d'energia en el procés de preescalfament d'un assecador de llit fluid, mitjançant la definició i implementació d'una plataforma IIOT (Industrial Internet of Things)-Cloud computing, per allotjar i executar un algorisme d'aprenentatge automàtic basat en el modelatge Catboost, per predir quan és el moment òptim per aturar el procés i reduir-ne la durada, i en conseqüència el seu consum energètic. Els resultats de l'experiment mostren que és possible reduir el procés de preescalfament en un 45% de la seva durada en temps i, en conseqüència, reduir el consum d'energia fins a 2.8 MWh anuals.[EN] High energy costs, the constant regulatory measures applied by administrations to maintain low healthcare costs, and the changes in healthcare regulations introduced in recent years have all significantly impacted the pharmaceutical and healthcare industry. The industry 4.0 paradigm encompasses changes in the traditional production model of the pharmaceutical industry with the inclusion of technologies beyond traditional automation. The primary goal is to achieve more cost-efficient drugs through the optimal incorporation of technologies such as advanced analytics. The manufacturing process of the pharmaceutical industry has different stages (mixing, drying, compacting, coating, packaging, etc..), and one of the most energy-expensive stages is the drying process. This process aims to extract the liquid content, such as water, by injecting warm and dry air into the system. This drying procedure time usually is predetermined and depends on the volume and the kind of units of a pharmaceutical product that must be dehydrated. On the other hand, the preheating phase can vary depending on various parameters, such as the operator's experience. It is, therefore, safe to assume that optimization of this process through advanced analytics is possible and can have a significant cost-reducing effect on the whole manufacturing process. Due to the high cost of the machinery involved in the drug production process, it is common practice in the pharmaceutical industry to try to maximize the useful life of these machines, which are not equipped with the latest sensors. Thus, a machine learning model using advanced analytics platforms, such as cloud computing, can be implemented to analyze potential energy consumption savings. This thesis is focused on improving the energy consumption in the preheating process of a fluid bed dryer by defining and implementing an IIOT (Industrial Internet of Things) Cloud computing platform. This architecture will host and run a machine learning algorithm based on Catboost modeling to predict when the optimum time is reached to stop the process, reduce its duration, and consequently its energy consumption. Experimental results show that it is possible to reduce the preheating process by 45% of its time duration, consequently reducing energy consumption by up to 2.8 MWh per year.Barriga Rodríguez, R. (2023). Optimization of Fluid Bed Dryer Energy Consumption for Pharmaceutical Drug Processes through Machine Learning and Cloud Computing Technologies [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/19584