Onealrindom1182

This paper presents a wireless traffic flow detection system, mainly focused on conditions in which the traffic flow is slow or stopped, which increases the risk of highway accidents. To achieve this goal, a Low Power Wide Area Network (LPWAN) based on LoRa called Short LoRa has been developed. This LoRa sub-network complies with the European Telecommunications Standards Institute (ETSI) harmonized standard for its compatibility in Europe countries. In addition, the development of the devices has allowed them to also work on a LoRaWAN network. The introduced development has been compared to a reference system mounted with laser barriers that provided a high accurate comparison. Field tests of the system have been carried out and the data obtained in the measurement has been analyzed with two different methods, and both of them were valid for the application. The results can determine vehicle speed with adequate precision at low speeds. The attenuating behavior of the communication signal is also analyzed through the Radio Signal Strength Indicator (RSSI). The relationship between vehicle speed, gate distances and RSSI attenuation has been studied. The system is proven to have efficient results in detecting traffic flow under the conditions for which it has been developed.With the rapid development of the global navigation satellite system (GNSS), high-rate GNSS has been widely used for high-precision GNSS coseismic displacement retrieval. In recent decades, relative positioning (RP) and precise point positioning (PPP) are mainly adopted to retrieve coseismic displacements. this website However, RP can only obtain relative coseismic displacements with respect to a reference station, which might be subject to quaking during a large seismic event. While PPP needs a long (re)convergence period of tens of minutes. There is no convergence time needed in the variometric approach for displacements analysis standalone engine (VADASE) but the derived displacements are accompanied by a drift. Temporal point positioning (TPP) method adopts temporal-differenced ionosphere-free phase measurements between a reference epoch and the current epoch, and there is almost no drift in the displacement derived from TPP method. Nevertheless, the precise orbit and clock products should be applied in the TPP methodction during the whole period of 15-min. The latter gives an accuracy of 1.2 cm and 2.4 cm in the horizontal and vertical components, respectively.This study's objective was to examine the characteristics of patients with chronic obstructive pulmonary disease (COPD) presenting with various exercise tolerance levels. A total of 235 patients with stable COPD were classified into 4 groups (1) LoFlo + HiEx-patients with a six-minute walking distance (6MWD) ≥350 m and percentage of predicted forced expiratory volume in 1 s (%FEV1.0) less then 50%; (2) HiFlo + HiEx-patients with a 6MWD ≥350 m and a %FEV1.0 ≥50%; (3) LoFlo + LoEx-patients with a 6MWD less then 350 m and %FEV1.0 less then 50%; and (4) HiFlo + LoEx-patients with a 6MWD less then 350 m and %FEV1.0 ≥ 50%. Aspects of physical ability in the HiFlo + LoEx group were significantly lower than those in the HiFlo + HiEx group. The HiFlo + LoEx group was characterized by a history of hospitalization for respiratory illness within the past year, treatment with at-home oxygen therapy, and lacking daily exercise habits. Following three months of pulmonary rehabilitation, the LoFlo + HiEx group significantly improved in the modified Medical Research Council dyspnea score, maximum gait speed, and 6MWD, while the HiFlo + LoEx group significantly improved in the percentage of maximal expiratory pressure, maximum gait speed, 6MWD, incremental shuttle walking distance, and St. George's Respiratory Questionnaire score. The HiFlo + LoEx group had the greatest effect of three-month pulmonary rehabilitation compared to other groups.This research studied a new material named modified infrared powder (MIRP) for decreasing the high temperature of asphalt pavements which can help alleviate the urban heat island effect to some extent. Based on the physical apparent density tests of materials and infrared thermal radiation test, the cooling performance of MIRP was obtained. link2 X-ray diffraction analysis and scanning electron microscopy test (SEM) were conducted to analyze the chemical composition and the microstructure of MIRP, respectively. According to the radiant heat transfer theory, a thermal radiation model of the pavement equilibrium temperature was established by microscopic and chemical analysis to study the influence of thermal radiation asphalt mixture and reveal its cooling performance. The results show that the main components of MIRP are metal oxides and nonmetallic oxides which improve its infrared emissivity. Compared with limestone mineral powder asphalt mortar, the asphalt mortar with MIRP had a more compact structure and uniform distribution, and enhanced the overall structural performance of the mixture. The thermal radiation model reveals that the pavement equilibrium temperature combined with the MIRP in asphalt mixture decreases with the increase of the longwave emissivity, and it diminishes with the decrease of the shortwave absorptivity.The accuracy of dryland crop classification using satellite-based synthetic aperture radar (SAR) data is often unsatisfactory owing to the similar dielectric properties that exist between the crops and their surroundings. link3 The main objective of this study was to improve the accuracy of dryland crop (maize and cotton) classification by combining multitype features and multitemporal polarimetric SAR (PolSAR) images in Hebei plain, China. Three quad-polarimetric RADARSAT-2 scenes were acquired between July and September 2018, from which 117 features were extracted using the Cloude-Pottier, Freeman-Durden, Yamaguchi, and multiple-component polarization decomposition methods, together with two polarization matrices (i.e., the coherency matrix and the covariance matrix). Random forest (RF) and support vector machine (SVM) algorithms were used for classification of dryland crops and other land-cover types in this study. The accuracy of dryland crop classification using various single features and their combinations wis study provides an important reference for timely and accurate classification of dryland crop in Hebei plain, China.During metastasis, cancer cells undergo phenotype changes in the epithelial-mesenchymal transition (EMT) process. Extracellular vesicles (EVs) released by cancer cells are the mediators of intercellular communication and play a role in metastatic process. Knowledge of factors that influence the modifications of the pre-metastatic niche for the migrating carcinoma cells is important for prevention of metastasis. We focus here on how cancer progression is affected by EVs released from either epithelial-like HT29-cells or from cells that are in early EMT stage triggered by Snail transcription factor (HT29-Snail). We found that EVs released from HT29-Snail, as compared to HT29-pcDNA cells, have a different microRNA profile. We observed the presence of interstitial pneumonias in the lungs of mice injected with HT29-Snail cells and the percent of mice with lung inflammation was higher after injection of HT29-Snail-EVs. Incorporation of EVs released from HT29-pcDNA, but not released from HT29-Snail, leads to the increased secretion of IL-8 from macrophages. We conclude that Snail modifications of CRC cells towards more invasive phenotype also alter the microRNA cargo of released EVs. The content of cell-released EVs may serve as a biomarker that denotes the stage of CRC and EVs-specific microRNAs may be a target to prevent cancer progression.Most engineering structures are composed of basic components such as plates, shells, and beams, and their dynamic characteristics under explosion load determine the impact resistance of the structure. In this paper, a three-dimensional composite steel structure was designed using a beam, plate, and other basic elements to study its mechanical behavior under explosion load. Subsequently, experiments on the composite steel structure under explosion load were carried out to study its mechanical behavior, and the failure mode and deformation data of the composite steel structure were obtained, which provided important experimental data regarding the dynamic response and mechanical behavior of the composite steel structure under explosion load. Then, we independently developed a parallel program with the coupled calculation method to solve the numerical simulation of the dynamic response and failure process of the composite steel structure under explosion load. This program adopts the Euler method as a whole, and Lagrange particles are used for materials that need to be accurately tracked. The numerical calculation results are in good agreement with the experimental data, indicating that the developed parallel program can effectively deal with the large deformation problems of multi-medium materials and the numerical simulation of the complex engineering structure failures subjected to the strong impact load.In this paper, an overlapping-resistant Internet of Things (IoT) solution for a Bluetooth Low Energy (BLE)-based indoor tracking system (BLE-ITS) is presented. The BLE-ITS is a promising, inexpensive alternative to the well-known GPS. It can be used in human traffic analysis, such as indoor tourist facilities. Tourists or other customers are tagged by a unique MAC address assigned to a simple and energy-saving BLE beacon emitter. Their location is determined by a distributed and scalable network of popular Raspberry Pi microcomputers equipped with BLE and WiFi/Ethernet modules. Only simple triggered messages in the form of login records (LRs) are sent to a server, where the so-called path vectors (PVs) and interest profile (IPr) are set. The authors implemented the prototype and demonstrated its usefulness in a controlled environment. As it is shown in the paper, the solution is highly overlap-resistant and mitigates the so-called multilocation problem.Deep learning is one of the most effective approaches to medical image processing applications. Network models are being studied more and more for medical image segmentation challenges. The encoder-decoder structure is achieving great success, in particular the Unet architecture, which is used as a baseline architecture for the medical image segmentation networks. Traditional Unet and Unet-based networks still have a limitation that is not able to fully exploit the output features of the convolutional units in the node. In this study, we proposed a new network model named TMD-Unet, which had three main enhancements in comparison with Unet (1) modifying the interconnection of the network node, (2) using dilated convolution instead of the standard convolution, and (3) integrating the multi-scale input features on the input side of the model and applying a dense skip connection instead of a regular skip connection. Our experiments were performed on seven datasets, including many different medical image modalities such as colonoscopy, electron microscopy (EM), dermoscopy, computed tomography (CT), and magnetic resonance imaging (MRI). The segmentation applications implemented in the paper include EM, nuclei, polyp, skin lesion, left atrium, spleen, and liver segmentation. The dice score of our proposed models achieved 96.43% for liver segmentation, 95.51% for spleen segmentation, 92.65% for polyp segmentation, 94.11% for EM segmentation, 92.49% for nuclei segmentation, 91.81% for left atrium segmentation, and 87.27% for skin lesion segmentation. The experimental results showed that the proposed model was superior to the popular models for all seven applications, which demonstrates the high generality of the proposed model.