Internet of Things for Mental Health: Open Issues in Data Acquisition, Self-Organization, Service Level Agreement, and Identity Management

The increase of mental illness cases around the world can be described as an urgent and serious global health threat. Around 500 million people suffer from mental disorders, among which depression, schizophrenia, and dementia are the most prevalent. Revolutionary technological paradigms such as the Internet of Things (IoT) provide us with new capabilities to detect, assess, and care for patients early. This paper comprehensively survey works done at the intersection between IoT and mental health disorders. We evaluate multiple computational platforms, methods and devices, as well as study results and potential open issues for the effective use of IoT systems in mental health. We particularly elaborate on relevant open challenges in the use of existing IoT solutions for mental health care, which can be relevant given the potential impairments in some mental health patients such as data acquisition issues, lack of self-organization of devices and service level agreement, and security, privacy and consent issues, among others. We aim at opening the conversation for future research in this rather emerging area by outlining possible new paths based on the results and conclusions of this work.Consejo Nacional de Ciencia y Tecnologia (CONACyT)Sonora Institute of Technology (ITSON) via the PROFAPI program PROFAPI_2020_0055Spanish Ministry of Science, Innovation and Universities (MICINN) project "Advanced Computing Architectures and Machine Learning-Based Solutions for Complex Problems in Bioinformatics, Biotechnology and Biomedicine" RTI2018-101674-B-I0

Analysis of objectives relationships in multiobjective problems using trade-off region maps

Understanding the relationships between objectives in many-objective optimisation problems is desirable in order to develop more effective algorithms. We propose a techniquefor the analysis and visualisation of complex relationships between many (three or more) objectives. This technique looks at conflicting, harmonious and independent objectives relationships from different perspectives. To do that, it uses correlation, trade-off regions maps and scatter-plots in a four step approach. We apply the proposed technique to a set of instances of the well-known multiobjective multidimensional knapsack problem. The experimental results show that with the proposed technique we can identify local and complex relationships between objectives, trade-offs not derived from pairwise relationships, gaps in the fitness landscape, and regions of interest. Such information can be used to tailor the development of algorithms

Optimizing the Compression Stress Relief Process for 7050AL Forgings

Structural components machined from aluminum forgings can exhibit distortion and poor dimensional quality due to residual stresses formed primarily during heat treatment. To alleviate these problems, mechanically stress-relieved tempers are used in which a small amount of plastic strain is introduced after solution heat treatment and prior to aging. For hand-forged billets and die forgings, this strain is introduced by compression. Process specifications for compression stress relief typically allow a range of strains, and this process variability can in turn lead to inconsistent forging performance in machining. In addition, since cold work is known to accelerate the aging response and decrease the peak strength in alloys such as 7050Al, it is important to control the compression stress relief process to achieve the stress relief while maintaining acceptable mechanical properties. The purpose of this investigation was to experimentally characterize the influence of compressive strain on the mechanical properties achieved after subsequent aging treatment in aluminum alloy 7050. We have also used finite element modeling of the residual stress state in a typical forging to predict optimum compression parameters for stress relief

Patterns of subnet usage reveal distinct scales of regulation in the transcriptional regulatory network of Escherichia coli

The set of regulatory interactions between genes, mediated by transcription factors, forms a species' transcriptional regulatory network (TRN). By comparing this network with measured gene expression data one can identify functional properties of the TRN and gain general insight into transcriptional control. We define the subnet of a node as the subgraph consisting of all nodes topologically downstream of the node, including itself. Using a large set of microarray expression data of the bacterium Escherichia coli, we find that the gene expression in different subnets exhibits a structured pattern in response to environmental changes and genotypic mutation. Subnets with less changes in their expression pattern have a higher fraction of feed-forward loop motifs and a lower fraction of small RNA targets within them. Our study implies that the TRN consists of several scales of regulatory organization: 1) subnets with more varying gene expression controlled by both transcription factors and post-transcriptional RNA regulation, and 2) subnets with less varying gene expression having more feed-forward loops and less post-transcriptional RNA regulation.Comment: 14 pages, 8 figures, to be published in PLoS Computational Biolog

Systems Thinking Approach to Sustainable Performance in RAMSAR Sites

This article explores and validates the integrated use of the Viable System Model (VSM) and the Partial Least Squares Path Modeling (PLS-PM) approach to assess the sustainable management of RAMSAR sites carrying out economic activities. This work adopts a systems- thinking approach integrating systemic methodologies in three phases: 1) the VSM was first used to develop a conceptual model of the organisational problem; 2) PLS-PM was used to propose a construct to outline a solution, as well as to statistically validate the relationships proposed in the conceptual model; finally, 3) through the VSM, the relationships between actors were rethought in order to promote sustainable performance. The obtained results suggest that the joint use of VSM and PLS-PM is an effective approach that aids to the identification of relational and structural pathologies affecting the observed RAMSAR systems. It also proved useful to suggest that relationships can lead to the sustainable performance of the sites under study. It should be noted that the framework of systemic tools is constrained in its application to the organisational domain: assessing two RAMSAR areas in Mexico. Methodologically, this is the first application of the integrated use of VSM and PLS-PM to analyse the management and viability/sustainability of RAMSAR areas from an organisational perspective, opening a new avenue for the analysis and optimisation of management of such areas. This study provides tools to support actors and academics related to RAMSAR sites and opens up a discussion on how to rethink the organisational interactions in order to improve RAMSAR sites adaptive capabilities

Control over phase separation and nucleation using a laser-tweezing potential

Control over the nucleation of new phases is highly desirable but elusive. Even though there is a long history of crystallization engineering by varying physicochemical parameters, controlling which polymorph crystallizes or whether a molecule crystallizes or forms an amorphous precipitate is still a poorly understood practice. Although there are now numerous examples of control using laser-induced nucleation, the absence of physical understanding is preventing progress. Here we show that the proximity of a liquid–liquid critical point or the corresponding binodal line can be used by a laser-tweezing potential to induce concentration gradients. A simple theoretical model shows that the stored electromagnetic energy of the laser beam produces a free-energy potential that forces phase separation or triggers the nucleation of a new phase. Experiments in a liquid mixture using a low-power laser diode confirm the effect. Phase separation and nucleation using a laser-tweezing potential explains the physics behind non-photochemical laser-induced nucleation and suggests new ways of manipulating matter

Oportunidades de negocio en las cadenas de valor sostenibles para carne y leche

Oportunidades de negocio en las cadenas de valor sostenibles para carne y lech

Tuning a Circular p-n Junction in Graphene from Quantum Confinement to Optical Guiding

The motion of massless Dirac-electrons in graphene mimics the propagation of photons. This makes it possible to control the charge-carriers with components based on geometrical-optics and has led to proposals for an all-graphene electron-optics platform. An open question arising from the possibility of reducing the component-size to the nanometer-scale is how to access and understand the transition from optical-transport to quantum-confinement. Here we report on the realization of a circular p-n junction that can be continuously tuned from the nanometer-scale, where quantum effects are dominant, to the micrometer scale where optical-guiding takes over. We find that in the nanometer-scale junction electrons are trapped in states that resemble atomic-collapse at a supercritical charge. As the junction-size increases, the transition to optical-guiding is signaled by the emergence of whispering-gallery modes and Fabry-Perot interference. The creation of tunable junctions that straddle the crossover between quantum-confinement and optical-guiding, paves the way to novel design-architectures for controlling electronic transport.Comment: 16 pages, 4 figure

Monitoring occurrence of SARS-CoV-2 in school populations: A wastewater-based approach

Clinical testing of children in schools is challenging, with economic implications limiting its frequent use as a monitoring tool of the risks assumed by children and staff during the COVID-19 pandemic. Here, a wastewater-based epidemiology approach has been used to monitor 16 schools (10 primary, 5 secondary and 1 post-16 and further education) in England. A total of 296 samples over 9 weeks have been analysed for N1 and E genes using qPCR methods. Of the samples returned, 47.3% were positive for one or both genes with a detection frequency in line with the respective local community. WBE offers a low cost, non-invasive approach for supplementing clinical testing and can provide longitudinal insights that are impractical with traditional clinical testing