Building change detection by W-shape resunet++ network with triple attention mechanism

Building change detection in high resolution remote sensing images is one of the most important and applied topics in urban management and urban planning. Different environmental illumination conditions and registration problem are the most error resource in the bitemporal images that will cause pseudochanges in results. On the other hand, the use of deep learning technologies especially convolutional neural networks (CNNs) has been successful and considered, but usually causes the loss of shape and detail at the edges. Accordingly, we propose a W-shape ResUnet++ network in which images with different environmental conditions enter the network independently. ResUnet++ is a network with residual blocks, triple attention blocks and Atrous Spatial Pyramidal Pooling. ResUnet++ is used on both sides of the network to extract deeper and discriminator features. This improves the channel and spatial inter-dependencies, while at the same time reducing the computational cost. After that, the Euclidean distance between the features is computed and the deconvolution is done. Also, a dual loss function is designed that used the weighted binary cross entropy to solve the unbalance between the changed and unchanged data in change detection training data and in the second part, we used the mask–boundary consistency constraints that the condition of converging the edges of the training data and the predicted edge in the loss function has been added. We implemented the proposed method on two remote sensing datasets and then compared the results with state-of-the-art methods. The F1 score improved 1.52 % and 4.22 % by using the proposed model in the first and second dataset, respectively

Online support vector machine application for model based fault detection and isolation of HVAC system

Abstract—Preventive maintenance plays an important role in Heating, Ventilation and Air Conditioning (HVAC) system. One cost effective strategy is the development of analytic fault detection and isolation (FDI) module by online monitoring the key variables of HAVC systems. This paper investigates realtime FDI for HAVC system by using online Support Vector Machine (SVM), by which we are able to train a FDI system with manageable complexity under real time working conditions. It is also proposed a new approach which allows us to detect unknown faults and updating the classifier by using these previously unknown faults. Based on the proposed approach, a semi unsupervised fault detection methodology has been developed for HVAC system

Developing a smart and clean technology for bioremediation of antibiotic contamination in arable lands

This study presents a smart technological framework to efficiently remove azithromycin from natural soil resources using bioremediation techniques. The framework consists of several modules, each with different models such as Penicillium Simplicissimum (PS) bioactivity, soft computing models, statistical optimisation, Machine Learning (ML) algorithms, and Decision Tree (DT) control system based on Removal Percentage (RP). The first module involves designing experiments using a literature review and the Taguchi Orthogonal design method for cultural conditions. The RP is predicted as a function of cultural parameters using Response Surface Methodology (RSM) and three ML algorithms: Instance-Based K (IBK), KStar, and Locally Weighted Learning (LWL). The sensitivity analysis shows that pH is the most important factor among all parameters, including pH, Aeration Intensity (AI), Temperature, Microbial/Food (M/F) ratio, and Retention Time (RT), with a p-value of <0.0001. AI is the next most significant parameter, also with a p-value of <0.0001. The optimal biological conditions for removing azithromycin from soil resources are a temperature of 32 °C, pH of 5.5, M/F ratio of 1.59 mg/g, and AI of 8.59 m3/h. During the 100-day bioremediation process, RP was found to be an insignificant factor for more than 25 days, which simplifies the conditions. Among the ML algorithms, the IBK model provided the most accurate prediction of RT, with a correlation coefficient of over 95%

Continuous Measurement of Reactive Oxygen Species Inside and Outside of a Residential House during Summer

Reactive oxygen species (ROS) are an important contributor to adverse health effects associated with ambient air pollution. Despite infiltration of ROS from outdoors, and possible indoor sources (eg, combustion), there are limited data available on indoor ROS. In this study, part of the second phase of Air Composition and Reactivity from Outdoor aNd Indoor Mixing campaign (ACRONIM-2), we constructed and deployed an online, continuous, system to measure extracellular gas- and particle-phase ROS during summer in an unoccupied residence in St. Louis, MO, USA. Over a period of one week, we observed that the non-denuded outdoor ROS (representing particle-phase ROS and some gas-phase ROS) concentration ranged from 1 to 4 nmol/m3 (as H2O2). Outdoor concentrations were highest in the afternoon, coincident with peak photochemistry periods. The indoor concentrations of particle-phase ROS were nearly equal to outdoor concentrations, regardless of window-opening status or air exchange rates. The indoor/outdoor ratio of non-denuded ROS (I/OROS) was significantly less than 1 with windows open and even lower with windows closed. Combined, these observations suggest that gas-phase ROS are efficiently removed by interior building surfaces and that there may be an indoor source of particle-phase ROS

The influence of personal care products on ozone-skin surface chemistry

Personal care products are increasingly being marketed to protect skin from the potentially harmful effects of air pollution. Here, we experimentally measure ozone deposition rates to skin and the generation rates and yields of oxidized products from bare skin and skin coated with various lotion formulations. Lotions reduced the ozone flux to the skin surface by 12% to 25%; this may be due to dilution of reactive skin lipids with inert lotion compounds or by reducing ozone diffusivity within the resulting mixture. The yields of volatile squalene oxidation products were 25% to 70% lower for a commercial sunscreen and for a base lotion with an added polymer or with antioxidants. Lower yields are likely due to competitive reactions of ozone with lotion ingredients including some ingredients that are not intended to be ozone sinks. The dynamics of the emissions of squalene ozonation product 6 methyl-2-heptenone (6MHO) suggest that lotions can dramatically reduce the solubility of products in the skin film. While some lotions appear to reduce the rate of oxidation of squalene by ozone, this evidence does not yet demonstrate that the lotions reduce the impact of air pollution on skin health

Constraints on the Persistent Radio Source Associated with FRB 20190520B Using the European VLBI Network

We present very long baseline interferometry (VLBI) observations of a continuum radio source potentially associated with the fast radio burst source FRB 20190520B. Using the European VLBI network, we find the source to be compact on VLBI scales with an angular size of &lt;2.3 mas (3σ). This corresponds to a transverse physical size of &lt;9 pc (at the z = 0.241 redshift of the host galaxy), confirming it to be as fast radio burst (FRB) persistent radio source (PRS) like that associated with the first-known repeater FRB 20121102A. The PRS has a flux density of 201 ± 34 μJy at 1.7 GHz and a spectral radio luminosity of L1.7 GHz = (3.0 ± 0.5) × 1029 erg s−1 Hz−1 (also similar to the FRB 20121102A PRS). Compared to previous lower-resolution observations, we find that no flux is resolved out on milliarcsecond scales. We have refined the PRS position, improving its precision by an order of magnitude compared to previous results. We also report the detection of the FRB 20190520B burst at 1.4 GHz and find the burst position to be consistent with the PRS position, at ≲20 mas. This strongly supports their direct physical association and the hypothesis that a single central engine powers both the bursts and the PRS. We discuss the model of a magnetar in a wind nebula and present an allowed parameter space for its age and the radius of the putative nebula powering the observed PRS emission. Alternatively, we find that an accretion-powered hypernebula model also fits our observational constraints

Effect of iron repletion and correction of iron deficiency on thyroid function in iron-deficient Iranian adolescent girls

The aim of this study was to determine whether iron supplementation in iron-deficient adolescent girls would improve thyroid function. A double-blind clinical trial was performed in a region in southern I.R. Iran. A total of 103 iron deficient participants were chosen. In all, 94 participants successfully completed this study. Participants were randomly assigned to one of two groups and treated with a 300 mg ferrous sulfate 5 times/week (n = 47) and placebo 5 times/week (n = 47) for 12 weeks. Blood samples were collected and assayed for hemoglobin, hematocrit, serum ferritin, iron, total iron binding capacity (TIBC), Thyroid stimulating hormone (TSH), total thyroxine (TT4), total triiodothyronine (TT3), free thyroid hormones (FT4 and FT3), triiodothyronine resin uptake (T3RU), reverse triiodothyronine (rT3), selenium and albumin concentrations. Statistical analysis was performed with parametric and non-parametric methods as appropriate. Data analysis revealed a significant increase in TT4, TT3, T3RU and a significant decrease in rT3 concentration in comparison to initial values in iron treated group (12, p&lt;0.001; 3.5, p&lt;0.001; 16, p&lt;0.05 and 47, p&lt;0.001, respectively). At 12 week there were significant differences between control and placebo in TT4, TT3, T3RU and rT3 concentrations (9.9 vs 8.4 μg dL-1, 145.2 vs 130.4 μg dL-1, 32.5 vs 28.4 and 23 vs 41 μg dL-1, respectively, all p&lt;0.001). Alterations in FT3 and TSH concentration were not significant, but concentration of FT4 revealed a significant difference between the beginning and the end of the study in iron treated group (10.3 vs 11.4, p&lt;0.001). Iron supplementation improves some indices of thyroid function in iron-deficient adolescent girls. © 2007 Asian Network For Scientific Information