Stephansen Holman (coalpaper37)

Around 5% of the world population suffers from hearing impairment. One of its main barriers is communication with others since it could lead to their social exclusion and frustration. To overcome this issue, this paper presents a system to interpret the Spanish sign language alphabet which makes the communication possible in those cases, where it is necessary to sign proper nouns such as names, streets, or trademarks. For this, firstly, we have generated an image dataset of the signed 30 letters composing the Spanish alphabet. Then, given that there are static and in-motion letters, two different kinds of neural networks have been tested and compared convolutional neural networks (CNNs) and recurrent neural networks (RNNs). A comparative analysis of the experimental results highlights the importance of the spatial dimension with respect to the temporal dimension in sign interpretation. So, CNNs obtain a much better accuracy, with 96.42% being the maximum value.In order to achieve the controlled release of curcumin, HPMC (hydroxypropyl methyl cellulose) was spray dried with curcumin and lactose. The spray-dried materials were pressed into tablets with a diameter of 8 mm, and their release characteristics in vitro were measured. In vitro experiments showed that the release of curcumin from the HPMC mixture was significantly slower due to the sustained-release property of HPMC as a typical excipient. Methylβcyclodextrin The release profile of curcumin from the HPMC mixture was relatively stable for a controlled release. SEM images show that the HPMC co-spray-dried powders have crumpled surfaces due to the large molecular weight of HPMC. DSC, XRD, FTIR, N2 adsorption, and TGA have been measured for the spray-dried curcumin materials. This work indicates that HPMC can be used as a controlled-release excipient for curcumin preparations. Determine and characterize potential risk areas for the occurrence of cutaneous leishmaniasis (CL) in Latin America (LA). Ecological observational study with observation units defined by municipalities with CL transmission between 2014-2018. Environmental and socioeconomic variables available for at least 85% of the municipalities were used, combined in a single database, utilizing the R software. The principal component analysis methodology was combined with a hierarchical cluster analysis to group clusters of municipalities based on their similarity. The V-test was estimated to define the positive or negative association of the variables with the clusters and separation by natural breaks was used to determine which ones contributed the most to each cluster. Information on cases was also incorporated in the analyses to attribute CL risk for each cluster. This study included 4,951 municipalities with CL transmission (36.5% of the total in LA) and seven clusters were defined by their association with 18 environmental and socioeconomic variables. The historical risk of CL is positively associated with the Amazonian, Andean and Savannah clusters in a decreasingly manner; and negatively associated with the Forest evergreen, Forest/crop and Forest/populated clusters. The Agricultural cluster did not reveal any association with the CL cases. The study made it possible to identify and characterize the CL risk by clusters of municipalities and to recognize the epidemiological distribution pattern of transmission, which provides managers with better information for intersectoral interventions to control CL. The study made it possible to identify and characterize the CL risk by clusters of municipalities and to recognize the epidemiological distribution pattern of transmission, which provides managers with better information for intersectoral interventions to control CL.Access to information and intercultural approaches in the field of health are essential for the elimination of inequities in health access and care. Intercultural models such as traditional, co