State of the art:understanding and integration of the social context in diabetes care

We review the past 25 years of research addressing challenges people living with diabetes experience in their daily lives related to social contexts, i.e. in their family, at work and in society at large, and identify research gaps. We found that young people with diabetes, as they develop through to adulthood, are exposed to considerable risks to their physical and mental health. Family-system interventions have had mixed outcomes. Research in this area would benefit from attention to ethnic/cultural diversity, and involving fathers and other family members. In adults with diabetes, social support relates to better diabetes outcomes. While family member involvement in care is likely to affect health and psychosocial outcomes of the person with diabetes, key elements and mediators of effective family interventions need to be identified. The challenges of diabetes management at work are under-researched; distress and intentional hyperglycaemia are common. When depression is comorbid with diabetes, there are increased work-related risks, e.g. unemployment, sickness absence and reduced income. Research to support people with diabetes at work should involve colleagues and employers to raise awareness and create supportive environments. Stigma and discrimination have been found to be more common than previously acknowledged, affecting self-care, well-being and access to health services. Guidance on stigma-reducing choice of language has been published recently. Resilience, defined as successful adaptation to adversity such as stigma and discrimination, requires studies relevant to the specific challenges of diabetes, whether at diagnosis or subsequently. The importance of the social context for living well with diabetes is now fully recognized, but understanding of many of the challenges, whether at home or work, is still limited, with much work needed to develop successful interventions

The Multiple Process Model of Goal-Directed Reaching Revisited

Recently our group forwarded a model of speed-accuracy relations in goal-directed reaching. A fundamental feature of our multiple process model was the distinction between two types of online regulation: impulse control and limb-target control. Impulse control begins during the initial stages of the movement trajectory and involves a comparison of actual limb velocity and direction to an internal representation of expectations about the limb trajectory. Limb-target control involves discrete error-reduction based on the relative positions of the limb and the target late in the movement. Our model also considers the role of eye movements, practice, energy optimization and strategic behavior in limb control. Here, we review recent work conducted to test specific aspects of our model. As well, we consider research not fully incorporated into our earlier contribution. We conclude that a slightly modified and expanded version of our model, that includes crosstalk between the two forms of online regulation, does an excellent job of explaining speed, accuracy, and energy optimization in goal-directed reaching

Drivers and Barriers of Social Sustainable Development and Growth of Online Higher Education: The Roles of Perceived Ease of Use and Perceived Usefulness

Data Availability Statement: The research data used in the article are based on end-of-course feedback from students, staff meetings, and emails from university management. Therefore, they are confidential and were used with anonymization for data protection.Copyright © 2023 by the authors. Online and distance learning classes have been touted for the last several years as an innovation in higher education that should help improve the entrepreneurial growth mindset of students. However, the reported negative online learning experience of many college students worldwide during the COVID-19 epidemic has shown that many opportunities remain to improve the sustainable development and growth of online visual instruction practices. In this study, we outline and investigate a set of hypotheses related to the perceived usefulness and perceived ease of use (from TAM) of online video instruction in higher education courses during the pandemic. We employ grounded theory using autoethnographic case studies as a data source. We found that (a) synchronous broadcast lectures improve participant attitude (H1) and motivation (H2) toward online instruction, (b) prerecorded video instruction increases participant perceived “ease of use” (H3) and perceived behavioral control (H4) of online instruction, but (c) indicators of recorded dates on pre-recorded video instruction decreases participant perceived “usefulness” (H5) and “certainty” (H6) of online instruction. We enrich the insights of popular motivation models for organizations and the higher education industry by outlining a set of emotional elements originating in neuroscience leadership research (SCARF) that might either amplify or diminish the perceived the ease of use and perceived usefulness to technology usage relationships when participations engage in online learning situations.This research received no external funding

How a Diverse Research Ecosystem Has Generated New Rehabilitation Technologies: Review of NIDILRR’s Rehabilitation Engineering Research Centers

Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a “total approach to rehabilitation”, combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970’s, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program

Acute Kawasaki Disease: Not Just for Kids

Kawasaki Disease is a small-to-medium-vessel vasculitis that preferentially affects children. Kawasaki Disease can occur in adults, but the presentation may differ from that observed in children. Typical findings in both adults and children include fever, conjunctivitis, pharyngitis, and skin erythema progressing to a desquamating rash on the palms and soles. Adults more frequently present with cervical adenopathy (93% of adults vs. 15% of children), hepatitis (65% vs. 10%), and arthralgia (61% vs. 24–38%). In contrast, adults are less frequently affected by meningitis (10% vs. 34%), thrombocytosis (55% vs. 100%), and coronary artery aneurysms (5% vs. 18–25%). We report a case of acute Kawasaki Disease in a 24-year-old man who presented with rash, fever, and arthritis. He was successfully treated with high-dose aspirin and intravenous immunoglobulin (IVIG). Our case highlights the importance of considering Kawasaki Disease in adults presenting with symptoms commonly encountered in a general medical practice

Self-Organization, Layered Structure, and Aggregation Enhance Persistence of a Synthetic Biofilm Consortium

Microbial consortia constitute a majority of the earth’s biomass, but little is known about how these cooperating communities persist despite competition among community members. Theory suggests that non-random spatial structures contribute to the persistence of mixed communities; when particular structures form, they may provide associated community members with a growth advantage over unassociated members. If true, this has implications for the rise and persistence of multi-cellular organisms. However, this theory is difficult to study because we rarely observe initial instances of non-random physical structure in natural populations. Using two engineered strains of Escherichia coli that constitute a synthetic symbiotic microbial consortium, we fortuitously observed such spatial self-organization. This consortium forms a biofilm and, after several days, adopts a defined layered structure that is associated with two unexpected, measurable growth advantages. First, the consortium cannot successfully colonize a new, downstream environment until it selforganizes in the initial environment; in other words, the structure enhances the ability of the consortium to survive environmental disruptions. Second, when the layered structure forms in downstream environments the consortium accumulates significantly more biomass than it did in the initial environment; in other words, the structure enhances the global productivity of the consortium. We also observed that the layered structure only assembles in downstream environments that are colonized by aggregates from a previous, structured community. These results demonstrate roles for self-organization and aggregation in persistence of multi-cellular communities, and also illustrate a role for the techniques of synthetic biology in elucidating fundamental biological principles

Explosive Nucleosynthesis: What we learned and what we still do not understand

This review touches on historical aspects, going back to the early days of nuclear astrophysics, initiated by B$^2$FH and Cameron, discusses (i) the required nuclear input from reaction rates and decay properties up to the nuclear equation of state, continues (ii) with the tools to perform nucleosynthesis calculations and (iii) early parametrized nucleosynthesis studies, before (iv) reliable stellar models became available for the late stages of stellar evolution. It passes then through (v) explosive environments from core-collapse supernovae to explosive events in binary systems (including type Ia supernovae and compact binary mergers), and finally (vi) discusses the role of all these nucleosynthesis production sites in the evolution of galaxies. The focus is put on the comparison of early ideas and present, very recent, understanding.Comment: 11 pages, to appear in Springer Proceedings in Physics (Proc. of Intl. Conf. "Nuclei in the Cosmos XV", LNGS Assergi, Italy, June 2018

A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios

[EN] Ecuador is worldwide considered as one of the main natural flower producers and exporters ¿being roses the most salient ones. Such a fact has naturally led the emergence of small and medium sized companies devoted to the production of quality roses in the Ecuadorian highlands, which intrinsically entails resource usage optimization. One of the first steps towards optimizing the use of resources is to forecast demand, since it enables a fair perspective of the future, in such a manner that the in-advance raw materials supply can be previewed against eventualities, resources usage can be properly planned, as well as the misuse can be avoided. Within this approach, the problem of forecasting the supply of roses was solved into two phases: the first phase consists of the macro-forecast of the total amount to be exported by the Ecuadorian flower sector by the year 2020, using multi-layer neural networks. In the second phase, the monthly demand for the main rose varieties offered by the study company was micro-forecasted by testing seven models. In addition, a Bayesian network model is designed, which takes into consideration macroeconomic aspects, the level of employability in Ecuador and weather-related aspects. This Bayesian network provided satisfactory results without the need for a large amount of historical data and at a low-computational cost.Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS ¿Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems¿ (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCA-RISE-2015. In addition, the authors are greatly grateful by the support given by the SDAS Research Group (www.sdas-group.com)Herrera-Granda, ID.; Lorente-Leyva, LL.; Peluffo-Ordóñez, DH.; Alemany Díaz, MDM. (2021). A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios. Lecture Notes in Computer Science. 12566:245-258. https://doi.org/10.1007/978-3-030-64580-9_21S24525812566Asociación de Productores y Exportadores de Flores: Inicio – Expoflores. https://expoflores.com/Palacios, J., Rosero, D.: Análisis de las condiciones climáticas registradas en el Ecuador continental en el año 2013 y su impacto en el sector agrícola. Estud. e Investig. meteorológicas. Ina. Inst. Nac. Meteorol. e Hidrol. Ecuador, 28, p. (2014)Hidalgo-Proaño, M.: Variabilidad climática interanual sobre el Ecuador asociada a ENOS. CienciAmérica 6, 42–47 (2017)Ritchie, J.W., Abawi, G.Y., Dutta, S.C., Harris, T.R., Bange, M.: Risk management strategies using seasonal climate forecasting in irrigated cotton production: a tale of stochastic dominance. Aust. J. Agric. Resour. Econ. 48, 65–93 (2004). https://doi.org/10.1111/j.1467-8489.2004.t01-1-00230.xLetson, D., Podesta, G.P., Messina, C.D., Ferreyra, R.A.: The uncertain value of perfect ENSO phase forecasts: Stochastic agricultural prices and intra-phase climatic variations. Clim. Change 69, 163–196 (2005). https://doi.org/10.1007/s10584-005-1814-9Weber, E.U., Laciana, C., Bert, F., Letson, D.: Agricultural decision making in the argentine Pampas: Modeling the interaction between uncertain and complex environments and heterogeneous and complex decision makers (2008)Loy, J.-P., Pieniadz, A.: Optimal grain marketing revisited a german and polish perspective. Outlook Agric. 38, 47–54 (2009). https://doi.org/10.5367/000000009787762761Wang, Q.J., Robertson, D.E., Haines, C.L.: A Bayesian network approach to knowledge integration and representation of farm irrigation: 1. Model development. WATER Resour. Res. 45 (2009). https://doi.org/10.1029/2006wr005419Keesman, K.J., Doeswijk, T.: uncertainty analysis of weather controlled systems (2010). https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960073961&doi=10.1007%2F978-3-642-03735-1_12&partnerID=40&md5=210525584472097e996a9f124f96fddbSchnepf, R.: U.S. livestock and poultry feed use and availability: background and emerging issues. In: Feed Market Dynamics and U.S. Livestock Implications. pp. 1–36. Nova Science Publishers, Inc., CRS, United States (2012)Medellín-Azuara, J., Howitt, R.E., MacEwan, D.J., Lund, J.R.: Economic impacts of climate-related changes to California agriculture. Clim. Change 109, 387–405 (2011). https://doi.org/10.1007/s10584-011-0314-3McCown, R.L., Carberry, P.S., Dalgliesh, N.P., Foale, M.A., Hochman, Z.: Farmers use intuition to reinvent analytic decision support for managing seasonal climatic variability. Agric. Syst. 106, 33–45 (2012). https://doi.org/10.1016/j.agsy.2011.10.005Scott, S.L., Varian, H.R.: Predicting the present with bayesian structural time series. Available SSRN 2304426 (2013)Prudhomme, C., Shaffrey, L., Woollings, T., Jackson, C., Fowler, H., Anderson, B.: IMPETUS: Improving predictions of drought for user decision-making. International Conference on Drought: Research and Science-Policy Interfacing, 2015. pp. 273–278. CRC Press/Balkema, Centre for Ecology and Hydrology, Wallingford, Oxfordshire, United Kingdom (2015)Wiles, P., Enke, D.: A hybrid neuro-fuzzy model to forecast the Soybean complex. International Annual Conference of the American Society for Engineering Management 2015, ASEM 2015. pp. 1–5. American Society for Engineering Management, Missouri University of Science and Technology, Engineering Management and Systems Engineering Department, United States (2015)Hansen, B.G., Li, Y.: An analysis of past world market prices of feed and milk and predictions for the future. Agribusiness 33, 175–193 (2017). https://doi.org/10.1002/agr.21474Johnson, M.D., Hsieh, W.W., Cannon, A.J., Davidson, A., Bedard, F.: Crop yield forecasting on the Canadian Prairies by remotely sensed vegetation indices and machine learning methods. Agric. For. Meteorol. 218, 74–84 (2016). https://doi.org/10.1016/j.agrformet.2015.11.003Chen, J., Yang, J., Zhao, J., Xu, F., Shen, Z., Zhang, L.: Energy demand forecasting of the greenhouses using nonlinear models based on model optimized prediction method. Neurocomputing 174, 1087–1100 (2016). https://doi.org/10.1016/j.neucom.2015.09.105Fodor, N., et al.: Integrating plant science and crop modeling: assessment of the impact of climate change on soybean and maize production. Plant Cell Physiol. 58, 1833–1847 (2017). https://doi.org/10.1093/pcp/pcx141Chapman, R., et al.: Using Bayesian networks to predict future yield functions with data from commercial oil palm plantations: a proof of concept analysis. Comput. Electron. Agric. 151, 338–348 (2018). https://doi.org/10.1016/j.compag.2018.06.006Lara-Estrada, L., Rasche, L., Sucar, L.E., Schneider, U.A.: Inferring Missing Climate Data for Agricultural Planning Using Bayesian Networks. LAND. 7 (2018). https://doi.org/10.3390/land7010004Abdelaal, H.S.A., Thilmany, D.: Grains production prospects and long run food security in Egypt. Sustain. 11 (2019). https://doi.org/10.3390/su11164457Kusunose, Y., Ma, L., Van Sanford, D.: User responses to imperfect forecasts: findings from an experiment with Kentucky wheat farmers. Weather. Clim. Soc. 11, 791–808 (2019). https://doi.org/10.1175/wcas-d-18-0135.1Kadigi, I.L., et al.: Forecasting yields, prices and net returns for main cereal crops in Tanzania as probability distributions: a multivariate empirical (MVE) approach. Agric. Syst. 180 (2020). https://doi.org/10.1016/j.agsy.2019.102693McGrath, G., Rao, P.S.C., Mellander, P.-E., Kennedy, I., Rose, M., van Zwieten, L.: Real-time forecasting of pesticide concentrations in soil. Sci. Total Environ. 663, 709–717 (2019). https://doi.org/10.1016/j.scitotenv.2019.01.401Yang, B., Xie, L.: Bayesian network modelling for “direct farm” mode based agricultural supply chain risk. Ekoloji 28, 2361–2368 (2019)Zaporozhtseva, L.A., Sabetova, T. V, Yu Fedulova, I.: Assessment of the uncertainty factors in computer modelling of an agricultural company operation. International Conference on Information Technologies in Business and Industries, ITBI 2019. Institute of Physics Publishing, Voronezh State Agrarian University, Michurina Str. 30, Voronezh, 394087, Russian Federation (2019)Box, G.E.P., Jenkins, G.M., Reinsel, G.C., Ljung, G.M.: Time series analysis: forecasting and control. Wiley (2015)Hanke, J., Wichern, D.: Business forecast. Pearson Educación (2010)Novagric: Invernaderos para Cultivo de Rosas. https://www.novagric.com/es/invernaderos-rosasWeather Spark: Clima promedio en Quito, Ecuador, durante todo el año - Weather Spark. https://es.weatherspark.com/y/20030/Clima-promedio-en-Quito-Ecuador-durante-todo-el-añoInstituto Nacional de Estadísticas y Censos-INEC: Encuesta Nacional de Empleo, Desempleo y subempleo-ENEMDU. https://www.ecuadorencifras.gob.ec/empleo-diciembre-2019/Central Bank of Ecuador: Central Bank of Ecuador. www.bce.fin.ecHyndman, R., Athnasopoulos, G.: Forecasting: Principles and Practice. OTexts, Australia (2018)Herrera-Granda, I.D., et al.: Artificial neural networks for bottled water demand forecasting: a small business case study. In: Rojas, I., Joya, G.C.A. (eds.) International Work-Conference on Artificial Neural Networks, pp. 362–373. Springer, Canaria (2019

Backbone and side-chain 1H, 13C and 15N assignments of the ubiquitin-associated domain of human X-linked inhibitor of apoptosis protein

X-linked inhibitor of apoptosis protein (XIAP), a leading member of the family of inhibitor of apoptosis (IAP) proteins, is considered as the most potent and versatile inhibitor of caspases and apoptosis. It has been reported that XIAP is frequently overexpressed in cancer and its expression level is implicated in contributing to tumorigenesis, disease progression, chemoresistance and poor patient-survival. Therefore, XIAP is one of the leading targets in drug development for cancer therapy. Recently, based on bioinformatics study, a previously unrecognized but evolutionarily conserved ubiquitin-associated (UBA) domain in IAPs was identified. The UBA domain is found to be essential for the oncogenic potential of IAP, to maintain endothelial cell survival and to protect cells from TNF-α-induced apoptosis. Moreover, the UBA domain is required for XIAP to activate NF-κB. In the present study, we report the near complete resonance assignments of the UBA domain-containing region of human XIAP protein. Secondary structure prediction based on chemical shift index (CSI) analysis reveals that the protein is predominately α-helical, which is consistent with the structures of known UBA proteins