Improving Indoor Localization Using Mobile UWB Sensor and Deep Neural Networks

Accurate localization in indoor environments with ultra-wideband (UWB) technology has long attracted much attention. However, due to the presence of multipath components or non-line of sight (NLOS) propagation of the radio signals, it has been converted to a critical challenge. Existing solutions use many fixed anchors in the indoor environment. Particularly, large areas require many anchor points and in the case of unexpected events that lead to the destruction of existing infrastructures, the fixed anchor points cannot be used. In this paper, a novel localization framework based on the transmitting signal from a mobile UWB sensor on the outside of the building and its received signal regarding the modified Saleh Valenzuela (SV) channel model is presented. After preprocessing the received signals, two new procedures to reduce the ranging error caused by multipath components are proposed. In the first procedure, two machine learning algorithms including multi-layer perceptron (MLP) and support vector machine (SVM) using the extracted features from the received UWB signal time and power vectors are implemented. Moreover, in the second procedure, two deep learning algorithms including MLP and convolutional neural networks (CNNs) using the received UWB signal time and power vectors are implemented to improve the performance of the indoor localization system. The simulation results show that the architecture designed for the convolutional neural network based on the hybrid dataset (the combination of the dataset related to received UWB signal time and power vectors) provides a mean absolute error (MAE) of about 3 cm

Glutaraldehyde-crosslinking for improved copper absorption selectivity and chemical stability of polyethyleneimine coatings

Nano-thin coatings of glutaraldehyde (GA)-crosslinked polyethyleneimine (PEI) are extremely selective and effective in binding copper from seawater. Here it was demonstrated that GA-PEI performs significantly different from PEI. The copper-selectivity of self-assembled PEI coatings on silicon substrates was greatly improved by GA-crosslinking. After submersion in artificial seawater containing 200 ppb copper and equimolar amounts of 11 competing ions only copper and trace amounts of Zn were detected in the GA-crosslinked coatings, while for non-crosslinked PEI there was about 30% Zn present relative to copper. The coatings were demonstrated to be highly stable under acidic conditions and retained their copper-binding selectivity after repeated cycles of binding and acid-mediated elution. After self-assembly of the GA-crosslinked coating on mesoporous diatomaceous earth particles, significant amounts of copper could be extracted from 200 ppb in artificial seawater and eluted under acidic pH

Incarceration and mortality in the United States

The ongoing COVID-19 pandemic has spotlighted the role of America's overcrowded prisons as vectors of ill health, but robust analyses of the degree to which high rates of incarceration impact population-level health outcomes remain scarce. In this paper, we use county-level panel data from 2927 counties across 43 states between 1983 and 2014 and a novel instrumental variable technique to study the causal effect of penal expansion on age-standardised cause-specific and all-cause mortality rates. We find that higher rates of incarceration have substantively large effects on deaths from communicable, maternal, neonatal, and nutritional diseases in the short and medium term, whilst deaths from non-communicable disease and from all causes combined are impacted in the short, medium, and long run. These findings are further corroborated by a between-unit analysis using coarsened exact matching and a simulation-based regression approach to predicting geographically anchored mortality differences

Fruit set and seed traits affected by N-phenyl-phetalamic acid in four grapevine (Vitis vinifera L.) cultivars

Grapes are an important horticultural crop that is popularly consumed in a variety of different forms; the fruit is eaten in at its immature stage, as ripe fruit and dried as raisins and vine leaves are also consumed. Therefore any research on ways to improve production of Iranian grapes in terms of quality and quantity is valuable. The main purpose of this study was to test the use of Phenyl Phetalamic Acid (PPA) to improve fruit set and quality. The experiment was designed as a factorial for four grapevine cultivars; 'Razeghi', 'Askari', 'Sefidaly' and 'Rishbaba' and three concentrations of PPA (0, 500, 1000 mg∙L-1). Treatments were arranged in a completely randomized design with three replications. The experiment was done in the Kashmar vineyard (Khorasan Razavi province) during 2010 spring. PPA treatment was applied by foliar spraying at the stage of 50 % anthesis. Results showed that PPA levels had a significant effect on evaluated cluster traits (weight, length and number) and berry (number, weight, length and diameter). Fruit set index (number of berries per cluster) was 263.11 for 'Sefidaly' followed by 113, 109.89 and 76.11 for 'Askari', 'Razeghi' and 'Rishbaba', respectively. 'Askari' and 'Razeghi' cultivars showed similar and insignificant reactions but their difference was significant compared to 'Rishbaba'. The effect was significant for interactions of traits for cluster, berry and seed except for number of berries per cluster. Based on these results, cluster characters were significantly and positively affected by PPA treatment at the concentration of 1000 mg∙L-1. This concentration increased fruit set by 26.2 % compared to the control in all cultivars except for Askari. The PPA concentration 500 mg∙L-1, observed as the most effective treatment for improved berry characters, provided its non-significant difference with 1000 mg∙L-1. Seed number per berry decreased significantly in 'Askari' and 'Rishbaba' at 500 mg∙L-1, which was considered positive in terms of quality. In summary, results determined that PPA had a positive effect on fruit as an auxin synergist. These improved berry characteristics are hypothesized to occur through a decrease in the dominance of apical buds that would allow more metabolites to be directed to development of fruit clusters, although further research is required.

Unhealthy lifestyles and ischaemic electrocardiographic abnormalities: the Persian Gulf Healthy Heart Study

We assessed prevalence of cardiovascular risk factors, ischaemic heart disease (IHD) and unhealthy lifestyles in 3723 participants aged ≥ 25 years in the northern Persian Gulf region; 96.0% had ≥ 1 cardiovascular risk factor. Over 60% had unhealthy body weight, only 8.3% ate the recommended amount of fruits and vegetables, 70.6% were physically inactive and 19.0% were current smokers. Prevalence of electrocardiogram (ECG) with evidence of IHD was 12.7%. Present or past smoking and truncal obesity were independently associated with IHD ECGs in men, and past or present smoking and obesity in women. Hypertension and diabetes were independently associated with increased risk of IHD EC

Comparison performance of visible-nir and near-infrared hyperspectral imaging for prediction of nutritional quality of goji berry (Lycium barbarum l.)

The potential of hyperspectral imaging for the prediction of the internal composition of goji berries was investigated. The prediction performances of models obtained in the Visible-Near Infrared (VIS-NIR) (400–1000 nm) and in the Near Infrared (NIR) (900–1700 nm) regions were compared. Analyzed constituents included Vitamin C, total antioxidant, phenols, anthocyanin, soluble solids content (SSC), and total acidity (TA). For vitamin C and AA, partial least square regression (PLSR) combined with different data pretreatments and wavelength selection resulted in a satisfactory prediction in the NIR region obtaining the R2pred value of 0.91. As for phenols, SSC, and TA, a better performance was obtained in the VIS-NIR region yielding the R2pred values of 0.62, 0.94, and 0.84, respectively. However, the prediction of total antioxidant and anthocyanin content did not give satisfactory results. Conclusively, hyperspectral imaging can be a useful tool for the prediction of the main constituents of the goji berry (Lycium barbarum L.)

The association between income and life expectancy revisited: deindustrialization, incarceration and the widening health gap

BACKGROUND: The health gap between the top and the bottom of the income distribution is widening rapidly in the USA, but the lifespan of America’s poor depends substantially on where they live. We ask whether two major developments in American society, deindustrialization and incarceration, can explain variation among states in life expectancy of those in the lowest income quartile. METHODS: life expectancy estimates at age 40 of those in the bottom income quartile were used to fit panel data models examining the relationship with deindustrialization and incarceration between 2001 and 2014 for all US states. RESULTS: A one standard deviation (s.d.) increase in deindustrialization (mean = 11.2, s.d. = 3.5) reduces life expectancy for the poor by 0.255 years [95% confidence interval (CI): 0.090–0.419] and each additional prisoner per 1000 residents (mean = 4.0, s.d. = 1.5) is associated with a loss of 0.468 years (95% CI: 0.213–0.723). Our predictors explain over 20% of the state-level variation in life expectancy among the poor and virtually the entire increase in the life expectancy gap between the top and the bottom income quartiles since the turn of the century. CONCLUSIONS: In the USA between 2001 and 2014, deindustrialization and incarceration subtracted roughly 2.5 years from the lifespan of the poor, pointing to their role as major health determinants. Future research must remain conscious of the upstream determinants and the political economy of public health. If public policy responses to growing health inequalities are to be effective, they must consider strengthening industrial policy and ending hyper-incarceration

Fingerprinting sub-basin spatial sediment sources in a large Iranian catchment under dry-land cultivation and rangeland farming: combining geochemical tracers and weathering indices

Study region: The Kamish River catchment (308 km2); a mountainous agricultural catchment under dry-land and rangeland farming located in Kermanshah province, in western Iran. Study focus: The main objective of this study was to apportion sub-basin spatial source relative contributions to target channel bed sediment samples using a composite fingerprinting procedure including a Bayesian un-mixing model. In total, thirty-four geochemical tracers, eleven elemental ratios and different weathering indices were measured or estimated for 43 tributary sediment samples collected to characterise three sub-basin spatial sediment sources and eleven target bed sediment samples collected at the outlet of the main basin. Statistical analysis was used to select three different composite signatures. New hydrological insights for the region: Using a composite signature based on KW-H and DFA, the respective relative contributions (with uncertainty ranges) from tributary sub-basins 1, 2 and 3 were estimated as 54.3% (47.8–62.0), 11.4% (4.2–18.7) and 34.3% (27.6–39.9), compared to 72.0% (61.6–82.7), 13.6% (9.0–18.5) and 14.2% (3.1–25.4) using a combination of KW-H and data mining, and 50.8% (42.8–59.9), 28.7% (20.2–37.3) and 20.3% (12.7–27.2) using a fingerprint selected by KW-H and PCCA. The root mean square difference between these source estimates highlighted sensitivity to the composite signatures. Evaluation of the un-mixing model predictions using virtual mixture tests confirmed agreement between modelled and known source proportions

Enhancing nonclassical bosonic correlations in a quantum walk network through experimental control of disorder

The presence of disorder and inhomogeneities in quantum networks has often been unexpectedly beneficial for both quantum and classical resources. Here we experimentally realize a controllable inhomogenous quantum walk (QW) dynamics, which can be exploited to investigate the effect of coherent disorder on the quantum correlations between two indistinguishable photons. Through the imposition of suitable disorder configurations, we observe two-photon states that exhibit an enhancement in the quantum correlations between two selected modes of the network, compared to the case of an ordered QW. Different configurations of disorder can steer the system toward different realizations of such an enhancement, thus allowing spatial and temporal manipulation of quantum correlations between remote modes of QW networks