Fall prevention strategy for an active orthotic system

Dissertação de mestrado integrado em Engenharia Biomédica (especialização em Eletrónica Médica)Todos os anos, são reportadas cerca de 684,000 quedas fatais e 37.3 milhões de quedas não fatais que requerem atenção médica, afetando principalmente a população idosa. Assim, é necessário identificar eficientemente indivíduos com alto risco de queda, a partir da população alvo idosa, e prepará los para superar perturbações da marcha inesperadas. Uma estratégia de prevenção de queda capaz de eficientemente e atempadamente detetar e contrariar os eventos de perdas de equilíbrio (PDE) mais frequentes pode reduzir o risco de queda. Como slips foram identificados como a causa mais prevalente de quedas, estes eventos devem ser abordados como foco principal da estratégia. No entanto, há falta de estratégias de prevenção de quedas por slip. Esta dissertação tem como objetivo o design de uma estratégia de prevenção de quedas de slips baseada na conceção das etapas de atuação e deteção. A estratégia de atuação foi delineada com base na resposta biomecânica humana a slips, onde o joelho da perna perturbada (leading) apresenta um papel proeminente para contrariar LOBs induzidas por slips. Quando uma slip é detetada, a estratégia destaca uma ortótese de joelho que providencia um torque assisstivo para prevenir a queda. A estratégia de deteção considerou as propriedades atrativas dos controladores Central Pattern Generator (CPG) para prever parâmetros da marcha. Algoritmos baseados em threshold monitorizam o erro de previsão do CPG, que aumenta após uma perturbação inesperada na marcha, para a deteção de slips. O ângulo do joelho e a velocidade angular da canela foram selecionados como os parâmetros de monitorização da marcha. Um protocolo experimental concebido para provocar perturbações de slip a sujeitos humanos permitiu a recolha de dados destas variáveis para posteriormente validar o algoritmo de deteção de perturbações. Algoritmos CPG foram capazes de produzir aproximações aceitáveis dos sinais de marcha em estado estacionário do ângulo do joelho e da velocidade angular da canela com sucesso. Além disso, o algoritmo de threshold adaptativo detetou LOBs induzidas por slips eficientemente. A melhor performance global foi obtida usando este algoritmo para monitorizar o ângulo do joelho, que detetou quase 80% (78.261%) do total de perturbações com um tempo médio de deteção (TMD) de 250 ms. Além disso, uma média de 0.652 falsas perturbações foram detetadas por cada perturbação corretamente identificada. Estes resultados sugerem uma performance aceitável de deteção de perturbações do algoritmo, de acordo com os requisitos especificados para a deteção.Every year, an estimated 684,000 fatal falls and 37.3 million non-fatal falls requiring medical attention are reported, mostly affecting the older population. Thus, it is necessary to effectively screen high fall risk individuals from targeted elderly populations and prepare them to successfully overcome unexpected gait perturbations. A fall prevention strategy capable of effectively and timely detect and counteract the most frequent loss of balance (LOB) events may reduce the fall risk. Since slips were identified as the main contributors to falls, these events should be addressed as a main focus of the strategy. Nonetheless, there is a lack of slip-induced fall prevention strategies. This dissertation aims the design of a slip-related fall prevention strategy based on the conception of an actuation and a detection stage. The actuation strategy was delineated based on the human biomechanical reactions to slips, where the perturbed (leading) leg’s knee joint presents a prominent role to counteract slip-induced LOBs. Thereby, upon the detection of a slip, this strategy highlighted a knee orthotic device that provides an assistive torque to prevent the falls. The detection strategy considered the attractive properties of biological-inspired Central Pattern Generator (CPG) controllers to predict gait parameters. Threshold-based algorithms monitored the CPG’s prediction error produced, which increases upon an unexpected gait perturbation, to perform slip detection. The knee angle and shank angular velocity were selected as the monitoring gait parameters. An experimental protocol designed to provoke slip perturbations to human subjects allowed to collect data from these variables to further validate the perturbation detection algorithm. CPG algorithms were able to successfully produce acceptable estimations of the knee angle and shank angular velocity signals during steady-state walking. Furthermore, an adaptive threshold algorithm effectively detected slip-induced LOBs. The best overall performance was obtained using this algorithm to monitor the knee angle from the perturbed leg, which detected almost 80% (78.261%) of the total perturbations with a mean detection time (MDT) of 250 ms. In addition, a mean of 0.652 false perturbations were detected for each correct perturbation identified. These results suggest an acceptable perturbation detection performance of the algorithm implemented in light of the detection requirements specified

A New Spatial Criteria Method to Delimit Rural Settlements towards Boundaries Equity: Land Use Optimization for Decision Making in Galicia, NW Spain

[Abstract] Rural settlements (RS) are a reality of rural areas. They consist of cluster of buildings and ways of life mainly associated with activities related to agriculture. As economic policies applied in rural development have evolved, the physical delimitation of rural areas has become more important because such areas are recipients of financial support, which depends on an area’s characteristics. Thus, it is necessary to formulate a new spatial approach for RS delimitation. The objective of this study is to define spatial criteria for identification and delimitation of the RS to recognize the morphological context of each RS. With respect to methodology, RS in the community of Galicia, Northwestern Spain were studied, and factors for spatial characterization were defined according to experts’ evaluations. Subsequently, spatial restrictions and conditions were identified for the delimitation of boundaries. The criteria that this research proposes reveal numerically adjustable factors that can recognize and interpret the morphological characteristics of each RS, which is also evidenced by the results of RS delimitations. It can be concluded that the numerically defined criteria associated with a spatial operation allow the adaptation to the morphological characteristics of any RS, as well as spatial equity by recognizing the differentiation of building structures and land uses of each RS, rather unlike the criteria defined by the law.This study was funded by the research project “Geographic information systems for urban planning and planning by optimisation techniques on multicore processors” by Xunta de Galicia and FEDER funds of the European Union (Centro de Investigación de Galicia accreditation 2019–2022, ref. ED431G 2019/01; Consolidation Program of Competitive Reference Groups, ref. ED431C 2021/30)Xunta de Galicia; ED431G 2019/01Xunta de Galicia; ED431C 2021/3

Growth and biomass production of prickly pear in the second cycle irrigated with treated domestic sewage

This study aimed to evaluate, in the second cycle, the growth and production of ‘Orelha-de-elefante Mexicana’ prickly pear (Opuntia sp.) under complementary irrigation with treated domestic sewage. The experiment was carried out in the Milagre Settlement, municipality of Apodi-RN, Brazil, from June 2016 to February 2017. Five treatments were evaluated, corresponding to four irrigation frequencies (2.3, 7.0, 14.0 and 21.0 days) to apply an effluent depth of 3.5 mm, and the control, rainfed cultivation (without irrigation). The experimental design was randomized blocks, with four replicates. After preliminary-primary treatment, the domestic sewage showed acceptable chemical and physical characteristics for fertigation under the conditions adopted in the prickly pear cultivation. 234 days after the 1st cut in the plants, the following morphometric characteristics were measured: plant height and length, width, perimeter, thickness and number of primary and secondary cladodes, and biomass accumulation. Complementary irrigation with treated domestic sewage effluent applied at intervals of 2.3, 7.0, 14.0 and 21.0 days allowed satisfactory growth and production of ‘Orelha-de-elefante Mexicana’ prickly pear; without irrigation, its development was substantially hampered during the dry period. Complementary irrigation with 3.5 mm of domestic sewage effluent applied at intervals of 2.3, 7.0 and 14.0 days led to highest growth and biomass accumulation in ‘Orelha-de-elefante Mexicana’ prickly pear

Photobiomodulation reduces the cytokine storm syndrome associated with Covid-19 in the zebrafish model

Although the exact mechanism of the pathogenesis of COVID-19 is not fully understood, oxidative stress and the release of pro-inflammatory cytokines have been highlighted as playing a vital role in the pathogenesis of the disease. In this sense, alternative treatments are needed to reduce the inflammation caused by COVID-19. Therefore, this study aimed to investigate the potential effect of red PBM as an attractive therapy to downregulate the cytokine storm caused by COVID-19 from a zebrafish model. RT-PCR analyses and protein-protein interaction prediction among SARS-CoV-2 and Danio rerio proteins showed that rSpike was responsible for generating systemic inflammatory processes with significantly increased pro-inflammatory (il1b, il6, tnfa, and nfkbiab), oxidative stress (romo1) and energy metabolism (slc2a1a, coa1) mRNA markers, with a pattern like those observed in COVID-19 cases in humans. On the other hand, PBM treatment decreased the mRNA levels of these pro-inflammatory and oxidative stress markers compared with rSpike in various tissues, promoting an anti-inflammatory response. Conversely, PBM promotes cellular and tissue repair of injured tissues and significantly increases the survival rate of rSpike-inoculated individuals. Additionally, metabolomics analysis showed that the most impacted metabolic pathways between PBM and the rSpike-treated groups were related to steroid metabolism, immune system, and lipids metabolism. Together, our findings suggest that the inflammatory process is an incisive feature of COVID-19, and red PBM can be used as a novel therapeutic agent for COVID-19 by regulating the inflammatory response. Nevertheless, the need for more clinical trials remains, and there is a significant gap to overcome before clinical trials.publishedVersio

Immunodominant antibody responses directed to SARS-CoV-2 hotspot mutation sites and risk of immune escape

IntroductionConsidering the likely need for the development of novel effective vaccines adapted to emerging relevant CoV-2 variants, the increasing knowledge of epitope recognition profile among convalescents and afterwards vaccinated with identification of immunodominant regions may provide important information.MethodsWe used an RBD peptide microarray to identify IgG and IgA binding regions in serum of 71 COVID-19 convalescents and 18 vaccinated individuals. ResultsWe found a set of immunodominant RBD antibody epitopes, each recognized by more than 30% of the tested cohort, that differ among the two different groups and are within conserved regions among betacoronavirus. Of those, only one peptide, P44 (S415-429), recognized by 68% of convalescents, presented IgG and IgA antibody reactivity that positively correlated with nAb titers, suggesting that this is a relevant RBD region and a potential target of IgG/IgA neutralizing activity.DiscussionThis peptide is localized within the area of contact with ACE-2 and harbors the mutation hotspot site K417 present in gamma (K417T), beta (K417N), and omicron (K417N) variants of concern. The epitope profile of vaccinated individuals differed from convalescents, with a more diverse repertoire of immunodominant peptides, recognized by more than 30% of the cohort. Noteworthy, immunodominant regions of recognition by vaccinated coincide with mutation sites at Omicron BA.1, an important variant emerging after massive vaccination. Together, our data show that immune pressure induced by dominant antibody responses may favor hotspot mutation sites and the selection of variants capable of evading humoral response

Ebola: an international public health emergency

The outbreak of Ebola in West Africa could become one of the worst infectious-disease-driven humanitarian crises of recent times. With more than 3000 deaths since the first case was confirmed in March 2014, the international community has recognized Ebola as a public health emergency of international concern and a clear threat to global health security. The complexity of dealing with this Ebola outbreak has highlighted the need for traditional actors, such as WHO and the CDC, to embrace the wider health and humanitarian community. The epidemic reinforces the need for nations to investment in health infrastructure and disease surveillance to keep pace with other developments in Africa. If Ebola arrives in high-income and middleincome nations, it should be contained quickly. The crisis shows the importance of sufficient levels of multilateral funding for WHO. The world needs a strong WHO, with the financing and political influence to fulfil its historic mission

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio