Enabling Machine Learning Across Heterogeneous Sensor Networks with Graph Autoencoders

Machine Learning (ML) has been applied to enable many life-assisting appli-cations, such as abnormality detection and emdergency request for the soli-tary elderly. However, in most cases machine learning algorithms depend on the layout of the target Internet of Things (IoT) sensor network. Hence, to deploy an application across Heterogeneous Sensor Networks (HSNs), i.e. sensor networks with different sensors type or layouts, it is required to repeat the process of data collection and ML algorithm training. In this paper, we introduce a novel framework leveraging deep learning for graphs to enable using the same activity recognition system across HSNs deployed in differ-ent smart homes. Using our framework, we were able to transfer activity classifiers trained with activity labels on a source HSN to a target HSN, reaching about 75% of the baseline accuracy on the target HSN without us-ing target activity labels. Moreover, our model can quickly adapt to unseen sensor layouts, which makes it highly suitable for the gradual deployment of real-world ML-based applications. In addition, we show that our framework is resilient to suboptimal graph representations of HSNs

Seedless Pattern Growth of Quasi-Aligned ZnO Nanorod Arrays on Cover Glass Substrates in Solution

A hybrid technique for the selective growth of ZnO nanorod arrays on wanted areas of thin cover glass substrates was developed without the use of seed layer of ZnO. This method utilizes electron-beam lithography for pattern transfer on seedless substrate, followed by solution method for the bottom-up growth of ZnO nanorod arrays on the patterned substrates. The arrays of highly crystalline ZnO nanorods having diameter of 60 ± 10 nm and length of 750 ± 50 nm were selectively grown on different shape patterns and exhibited a remarkable uniformity in terms of diameter, length, and density. The room temperature cathodluminescence measurements showed a strong ultraviolet emission at 381 nm and broad visible emission at 585–610 nm were observed in the spectrum

Ultra-fast Microwave Synthesis of ZnO Nanowires and their Dynamic Response Toward Hydrogen Gas

Ultra-fast and large-quantity (grams) synthesis of one-dimensional ZnO nanowires has been carried out by a novel microwave-assisted method. High purity Zinc (Zn) metal was used as source material and placed on microwave absorber. The evaporation/oxidation process occurs under exposure to microwave in less than 100 s. Field effect scanning electron microscopy analysis reveals the formation of high aspect-ratio and high density ZnO nanowires with diameter ranging from 70 to 80 nm. Comprehensive structural analysis showed that these ZnO nanowires are single crystal in nature with excellent crystal quality. The gas sensor made of these ZnO nanowires exhibited excellent sensitivity, fast response, and good reproducibility. Furthermore, the method can be extended for the synthesis of other oxide nanowires that will be the building block of future nanoscale devices

Impacts of household sources on air pollution at village and regional scales in India

Approximately 3 billion people worldwide cook with solid fuels, such as wood, charcoal, and agricultural residues. These fuels, also used for residential heating, are often combusted in inefficient devices, producing carbonaceous emissions. Between 2.6 and 3.8 million premature deaths occur as a result of exposure to fine particulate matter from the resulting household air pollution (Health Effects Institute, 2018a; World Health Organization, 2018). Household air pollution also contributes to ambient air pollution; the magnitude of this contribution is uncertain. Here, we simulate the distribution of the two major health-damaging outdoor air pollutants (PM2:5 and O3) using state-of-thescience emissions databases and atmospheric chemical transport models to estimate the impact of household combustion on ambient air quality in India. The present study focuses on New Delhi and the SOMAARTH Demographic, Development, and Environmental Surveillance Site (DDESS) in the Palwal District of Haryana, located about 80 km south of New Delhi. The DDESS covers an approximate population of 200 000 within 52 villages. The emissions inventory used in the present study was prepared based on a national inventory in India (Sharma et al., 2015, 2016), an updated residential sector inventory prepared at the University of Illinois, updated cookstove emissions factors from Fleming et al. (2018b), and PM2:5 speciation from cooking fires from Jayarathne et al. (2018). Simulation of regional air quality was carried out using the US Environmental Protection Agency Community Multiscale Air Quality modeling system (CMAQ) in conjunction with the Weather Research and Forecasting modeling system (WRF) to simulate the meteorological inputs for CMAQ, and the global chemical transport model GEOS-Chem to generate concentrations on the boundary of the computational domain. Comparisons between observed and simulated O3 and PM2:5 levels are carried out to assess overall airborne levels and to estimate the contribution of household cooking emissions

The summertime Saharan heat low: Sensitivity of the radiation budget and atmospheric heating to water vapour and dust aerosol

The Saharan heat low (SHL) is a key component of the West African climate system and an important driver of the West African Monsoon across a range of timescales of variability. The physical mechanisms driving the variability in the SHL remain uncertain, although water vapour has been implicated as of primary importance. Here, we quantify the independent effects of variability in dust and water vapour on the radiation budget and atmospheric heating of the region using a radiative transfer model configured with observational input data from the Fennec field campaign at the location of Bordj Badji Mokhtar (BBM) in southern Algeria (0.9E, 21.4N), close to the SHL core, for June 2011. Overall, we find dust aerosol and water vapour to be of similar importance in driving variability in the top of atmosphere (TOA) radiation budget and therefore the column integrated heating over the SHL (~7 W m-² per standard deviation of dust AOD). As such we infer that SHL intensity is likely to be similarly enhanced by the effects of dust and water vapour surge events. However, the details of the processes differ. Dust generates substantial radiative cooling at the surface (~11 W m-² per standard deviation of dust AOD), presumably leading to reduced sensible heat flux into the boundary layer, which is more than compensated by direct radiative heating from SW absorption by dust in the dusty boundary layer. In contrast water vapour invokes a longwave radiative warming of at the surface of ~6 W m-² per standard deviation of column integrated water vapour in Kg m-² . Net effects involve a pronounced net atmospheric radiative convergence with heating rates on average of 0.5 K day-¹ and up to 6 K day-¹ during synoptic/meso-scale dust events from monsoon surges and convective cold pool outflows (‘haboobs’). On this basis we make inferences on the processes driving variability in the SHL associated with radiative and advective heating/cooling. Depending on the synoptic context over the region processes driving variability involve both independent effects of water vapour and dust and compensating events in which dust and water vapour are co-varying. Forecast models typically have biases of up to 2 kg m-² in column integrated water vapour (equivalent to a change in 2.6 W m-² TOA net flux) and typically lack variability in dust, and so are expected to poorly represent these couplings. An improved representation dust and water vapour and quantification of associated radiative impact is thus imperative in quest for the answer to what remains to be uncertain related with the climate system of the SHL region

Exploring the diverse definitions of ‘evidence’: a scoping review

OBJECTIVES: To systematically collect and analyse diverse definitions of ‘evidence’ in both health and social sciences, and help users to correctly use the term ‘evidence’ and rethink what is the definition of ‘evidence’ in scientific research. DESIGN: Scoping review. METHODS: Definitions of evidence in the health sciences and social sciences were included. We have excluded the definition of evidence applied in the legal field, abstracts without full text, documents not published in either Chinese or English and so on. We established a multidisciplinary working group and systematically searched five electronic databases including Medline, Web of Science, EBSCO, the Chinese Social Sciences Citation Index and the Chinese Science Citation Database from their inception to 26 February 2022. We also searched websites and reviewed the reference lists of the identified studies. Six reviewers working in pairs, independently, selected studies according to the inclusion and exclusion criteria, and extracted information. Any differences were discussed in pairs, and if there was disagreement, it was resolved via discussion or with the help of a third reviewer. Reviewers extracted document characteristics, the original content for the definitions of ‘evidence’, assessed definitions as either intensional or extensional, and any citations for the given definition. RESULTS: Forty-nine documents were finally included after screening, and 68 definitions were obtained. After excluding duplicates, a total of 54 different definitions of ‘evidence’ were identified. There were 42 intensional definitions and 12 extensional definitions. The top three definiens were ‘information’, ‘fact’ and ‘research/study’. The definition of ‘evidence’ differed between health and social sciences. The term ‘research’ appeared most frequently in the definitions. CONCLUSIONS: The definition of ‘evidence’ has gradually attracted the attention of many scholars and decision-makers in health and social sciences. Nevertheless, there is no widely recognised and accepted definition in scientific research. Given the wide use of the term, we need to think about whether, or under what circumstances, a standardised, clear, meaningful and widely applicable definition of ‘evidence’ might be helpful

Development of a Yoga Program for Type-2 Diabetes Prevention (YOGA-DP) Among High-Risk People in India

Introduction: Many Indians are at high-risk of type-2 diabetes mellitus (T2DM). Yoga is an ancient Indian mind-body discipline, that has been associated with improved glucose levels and can help to prevent T2DM. The study aimed to systematically develop a Yoga program for T2DM prevention (YOGA-DP) among high-risk people in India using a complex intervention development approach. / Materials and Methods: As part of the intervention, we developed a booklet and a high-definition video for participants and a manual for YOGA-DP instructors. A systematic iterative process was followed to develop the intervention and included five steps: (i) a systematic review of the literature to generate a list of Yogic practices that improves blood glucose levels among adults at high-risk of or with T2DM, (ii) validation of identified Yogic practices by Yoga experts, (iii) development of the intervention, (iv) consultation with Yoga, exercise, physical activity, diet, behavior change, and/or diabetes experts about the intervention, and (v) pretest the intervention among Yoga practitioners and lay people (those at risk of T2DM and had not practiced Yoga before) in India. / Results: YOGA-DP is a structured lifestyle education and exercise program, provided over a period of 24 weeks. The exercise part is based on Yoga and includes Shithilikarana Vyayama (loosening exercises), Surya Namaskar (sun salutation exercises), Asana (Yogic poses), Pranayama (breathing practices), and Dhyana (meditation) and relaxation practices. Once participants complete the program, they are strongly encouraged to maintain a healthy lifestyle in the long-term. / Conclusions: We systematically developed a novel Yoga program for T2DM prevention (YOGA-DP) among high-risk people in India. A multi-center feasibility randomized controlled trial is in progress in India

Different atmospheric moisture divergence responses to extreme and moderate El Niños

On seasonal and inter-annual time scales, vertically integrated moisture divergence provides a useful measure of the tropical atmospheric hydrological cycle. It reflects the combined dynamical and thermodynamical effects, and is not subject to the limitations that afflict observations of evaporation minus precipitation. An empirical orthogonal function (EOF) analysis of the tropical Pacific moisture divergence fields calculated from the ERA-Interim reanalysis reveals the dominant effects of the El Niño-Southern Oscillation (ENSO) on inter-annual time scales. Two EOFs are necessary to capture the ENSO signature, and regression relationships between their Principal Components and indices of equatorial Pacific sea surface temperature (SST) demonstrate that the transition from strong La Niña through to extreme El Niño events is not a linear one. The largest deviation from linearity is for the strongest El Niños, and we interpret that this arises at least partly because the EOF analysis cannot easily separate different patterns of responses that are not orthogonal to each other. To overcome the orthogonality constraints, a self-organizing map (SOM) analysis of the same moisture divergence fields was performed. The SOM analysis captures the range of responses to ENSO, including the distinction between the moderate and strong El Niños identified by the EOF analysis. The work demonstrates the potential for the application of SOM to large scale climatic analysis, by virtue of its easier interpretation, relaxation of orthogonality constraints and its versatility for serving as an alternative classification method. Both the EOF and SOM analyses suggest a classification of “moderate” and “extreme” El Niños by their differences in the magnitudes of the hydrological cycle responses, spatial patterns and evolutionary paths. Classification from the moisture divergence point of view shows consistency with results based on other physical variables such as SST

Chalcogenide Glass-on-Graphene Photonics

Two-dimensional (2-D) materials are of tremendous interest to integrated photonics given their singular optical characteristics spanning light emission, modulation, saturable absorption, and nonlinear optics. To harness their optical properties, these atomically thin materials are usually attached onto prefabricated devices via a transfer process. In this paper, we present a new route for 2-D material integration with planar photonics. Central to this approach is the use of chalcogenide glass, a multifunctional material which can be directly deposited and patterned on a wide variety of 2-D materials and can simultaneously function as the light guiding medium, a gate dielectric, and a passivation layer for 2-D materials. Besides claiming improved fabrication yield and throughput compared to the traditional transfer process, our technique also enables unconventional multilayer device geometries optimally designed for enhancing light-matter interactions in the 2-D layers. Capitalizing on this facile integration method, we demonstrate a series of high-performance glass-on-graphene devices including ultra-broadband on-chip polarizers, energy-efficient thermo-optic switches, as well as graphene-based mid-infrared (mid-IR) waveguide-integrated photodetectors and modulators