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      Real Time Monitoring of Children, and Adults with Mental Disabilities Using a Low-Cost Non-Invasive Electronic Device

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          Abstract

          There are a growing number of small children—as well as adults—with mental disabilities (including elderly citizens with Alzheimer’s disease or other forms of age-related dementia) that are getting lost in rural and urban areas for various reasons. Establishing their location within the first 72 h is crucial because lost people are exposed to all kinds of adverse conditions and in the case of the elderly, this is further aggravated if prescribed medication is needed. Herein we describe a non-invasive, low-cost electronic device that operates constantly, keeping track of time, the geographical location and the identification of the subject using it. The prototype was made using commercial low-cost electronic components. This electronic device shows high connectivity in open and closed areas and identifies the geographical location of a lost subject. We freely provide the software and technical diagrams of the prototypes.

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          Most cited references 39

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          Nanoparticle-based bio-bar codes for the ultrasensitive detection of proteins.

          An ultrasensitive method for detecting protein analytes has been developed. The system relies on magnetic microparticle probes with antibodies that specifically bind a target of interest [prostate-specific antigen (PSA) in this case] and nanoparticle probes that are encoded with DNA that is unique to the protein target of interest and antibodies that can sandwich the target captured by the microparticle probes. Magnetic separation of the complexed probes and target followed by dehybridization of the oligonucleotides on the nanoparticle probe surface allows the determination of the presence of the target protein by identifying the oligonucleotide sequence released from the nanoparticle probe. Because the nanoparticle probe carries with it a large number of oligonucleotides per protein binding event, there is substantial amplification and PSA can be detected at 30 attomolar concentration. Alternatively, a polymerase chain reaction on the oligonucleotide bar codes can boost the sensitivity to 3 attomolar. Comparable clinically accepted conventional assays for detecting the same target have sensitivity limits of approximately 3 picomdar, six orders of magnitude less sensitive than what is observed with this method.
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            Poverty and common mental disorders in developing countries.

            A review of English-language journals published since 1990 and three global mental health reports identified 11 community studies on the association between poverty and common mental disorders in six low- and middle-income countries. Most studies showed an association between indicators of poverty and the risk of mental disorders, the most consistent association being with low levels of education. A review of articles exploring the mechanism of the relationship suggested weak evidence to support a specific association with income levels. Factors such as the experience of insecurity and hopelessness, rapid social change and the risks of violence and physical ill-health may explain the greater vulnerability of the poor to common mental disorders. The direct and indirect costs of mental ill-health worsen the economic condition, setting up a vicious cycle of poverty and mental disorder. Common mental disorders need to be placed alongside other diseases associated with poverty by policy-makers and donors. Programmes such as investment in education and provision of microcredit may have unanticipated benefits in reducing the risk of mental disorders. Secondary prevention must focus on strengthening the ability of primary care services to provide effective treatment.
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              An Overview on Wireless Sensor Networks Technology and Evolution

              Wireless sensor networks (WSNs) enable new applications and require non-conventional paradigms for protocol design due to several constraints. Owing to the requirement for low device complexity together with low energy consumption (i.e., long network lifetime), a proper balance between communication and signal/data processing capabilities must be found. This motivates a huge effort in research activities, standardization process, and industrial investments on this field since the last decade. This survey paper aims at reporting an overview of WSNs technologies, main applications and standards, features in WSNs design, and evolutions. In particular, some peculiar applications, such as those based on environmental monitoring, are discussed and design strategies highlighted; a case study based on a real implementation is also reported. Trends and possible evolutions are traced. Emphasis is given to the IEEE 802.15.4 technology, which enables many applications of WSNs. Some example of performance characteristics of 802.15.4-based networks are shown and discussed as a function of the size of the WSN and the data type to be exchanged among nodes.
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                Author and article information

                Journal
                Micromachines (Basel)
                Micromachines (Basel)
                micromachines
                Micromachines
                MDPI
                2072-666X
                28 September 2017
                October 2017
                : 8
                : 10
                Affiliations
                [1 ]Department of Mathematics, Faculty of Sciences, Universidad Nacional Autónoma de Mexico, Mexico City 04510, Mexico
                [2 ]Escuela Superior de Ingeniería Mećanica y Eléctrica, Instituto Politécnico Nacional, Mexico City 07738, Mexico; nachoislas@ 123456yahoo.com
                [3 ]Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City 07738, Mexico; nanobiomex@ 123456hotmail.com
                [4 ]Department of Computer Science, Instituto Nacional de Astrofísica, Óptica y Electrónica, Puebla 72840, Mexico; ariasmo@ 123456inaoep.mx
                [5 ]Centro de Investigaciones Químicas, Universidad Autónoma del Estado de Morelos, Morelos 62209, Mexico; buhse@ 123456uaem.mx
                [6 ]Department of Infectious Diseases, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City 14080, Mexico; juanjcalva@ 123456gmail.com
                [7 ]Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán/Instituto Tecnológico y de Estudios Superiores de Monterrey TecSalud, Mexico City 14080, Mexico; caguilarsalinas@ 123456yahoo.com
                [8 ]Unidad de Apoyo a la Investigación Clínica, Instituto Nacional de Pediatría, Mexico City 04530, Mexico; clauspim@ 123456hotmail.com
                [9 ]Department of Molecular Medicine and USF Health Byrd Alzheimer’s Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL 33647, USA; vuversky@ 123456health.usf.edu
                [10 ]Institute for Biological Instrumentation, Russian Academy of Sciences, 142290 Moscow Region, Russia
                Author notes
                [* ]Correspondence: polanco@ 123456unam.mx
                Article
                micromachines-08-00292
                10.3390/mi8100292
                6190192
                2217b96b-b9ce-446e-8340-7388c2e03e0a
                © 2017 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

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