Circular Scanning Research Articles

Instrument Design and In-Flight Performance of an Airborne Terahertz Ice Cloud Imager

The Airborne Terahertz Ice Cloud Imager (ATICI) is an airborne demonstration prototype of an ice cloud imager (ICI), which will be launched on the next generation of Fengyun satellites and plays an important role in heavy precipitation detection, typhoon, and medium-to-short-term meteorological/ocean forecasting. At present, it has 13 frequency channels covering 183–664 GHz, which are sensitive to scattering by cloud ice. This paper provides an overview of ATICI and proposes a receiving front-end design scheme using a planar mirror and a quasi-optical feed network which improves the main beam efficiency of each frequency band, with measured values better than 95.5%. It can detect factors such as ice particle size, ice water path, and ice water content in clouds by rotating the circular scanning of the antenna feed system. A high-sensitivity receiver system has been developed and tested for verification. The flight verification results show that the quasi-optical feed network subsystem works well and performs stably under vibration and temperature changes. The system sensitivity is better than 1.5 K, and the domestically produced high-frequency receiver has stable performance, which can meet the conditions of satellite applications. The ATICI performs well and meets expectations, verifying the feasibility of the Fengyun-5 ICI payload.

LidPose: Real-Time 3D Human Pose Estimation in Sparse Lidar Point Clouds with Non-Repetitive Circular Scanning Pattern.

In this paper, we propose a novel, vision-transformer-based end-to-end pose estimation method, LidPose, for real-time human skeleton estimation in non-repetitive circular scanning (NRCS) lidar point clouds. Building on the ViTPose architecture, we introduce novel adaptations to address the unique properties of NRCS lidars, namely, the sparsity and unusual rosetta-like scanning pattern. The proposed method addresses a common issue of NRCS lidar-based perception, namely, the sparsity of the measurement, which needs balancing between the spatial and temporal resolution of the recorded data for efficient analysis of various phenomena. LidPose utilizes foreground and background segmentation techniques for the NRCS lidar sensor to select a region of interest (RoI), making LidPose a complete end-to-end approach to moving pedestrian detection and skeleton fitting from raw NRCS lidar measurement sequences captured by a static sensor for surveillance scenarios. To evaluate the method, we have created a novel, real-world, multi-modal dataset, containing camera images and lidar point clouds from a Livox Avia sensor, with annotated 2D and 3D human skeleton ground truth.

Study on circular scanning for cross-scale micro/nanoscratching machining

Large-scale scanning probe can facilitate fabricating cross-scale micro/nano structures. However, the processing of complex two-dimensional patterns usually encounters challenges including numerous machining feature points and probe jumps, which results in low efficiency, as well as poor machining quality. Therefore, a circular scanning method based on corner point extraction (CSCE) was proposed in this study for programming the probe path and reducing the number of probe jumps. Before the machining, the target structures or images were converted into raw data points through image processing, and then the data was refined by corner point extraction for obtaining the machining points. Subsequently, the machining points were arranged in the order of a circular scanning algorithm to get the probe path. Using CSCE, the probe jump was only 1 time for processing an H-shaped pattern. By comparison with the circular scanning method based on intersection point extraction (CSIE) for the H pattern, the number of machining points in CSCE was reduced from 82 to 12, and the machining time was shortened from 17.15 s to 3.17 s. Consequently, CSCE can enable efficient and high-quality fabrication of cross-scale micro/nanostructures.

THE EFFECT OF LASER OSCILLATING WELDING ON FORMATION AND PROPERTIES OF TITANIUM ALLOY

Titanium alloys are widely used in aerospace and other fields due to their advantages of low density, high specific strength and good corrosion resistance. Laser oscillating welding is an innovative process in the realm of welding technology. In this study, two laser oscillating welding methods (circular and linear) were employed to analyze the influence of different oscillation parameters on the formation of titanium alloy. The results indicate that the oscillation frequency has a significant impact on weld formation. The laser scanning trajectory also affects weld formation, with circular and linear scanning trajectories resulting in better weld quality. Finally, the effects of oscillation modes on the microstructure and properties of laser oscillating welding titanium alloy were investigated based on optimized process parameters. Among them, circular laser oscillating welding of titanium alloy exhibits higher tensile strength, with a maximum tensile strength of up to 1188.3[Formula: see text]MPa.

Photothermal Hydrogel Composites Featuring G4-Carbon Nanomaterial Networks for Staphylococcus aureus Inhibition.

Microbial infections represent a significant health risk, often leading to severe complications and, in some cases, even fatalities. As a result, there is an urgent need to explore innovative drug delivery systems and alternative therapeutic techniques. The photothermal therapy has emerged as a promising antibacterial approach and is the focus of this study. Herein, we report the successful synthesis of two distinct supramolecular composite hydrogels by incorporating graphene oxide (GO) and single-walled carbon nanotubes (SWNTs) into guanosine quadruplex (G4) based hydrogels containing covalently bound β-cyclodextrin (β-CD). The G4 matrix was synthesized through a two-step process, establishing a robust network between G4 and β-CDs, followed by the encapsulation of either GO or SWNTs. Comprehensive characterization of these composite hydrogels were conducted using analytical techniques, including circular dichroism, Raman spectroscopy, rheological investigations, X-ray diffraction, and scanning electron microscopy. A notable discovery from the conducted research is the differential photothermal responses exhibited by the hydrogels when exposed to near-infrared laser irradiation. Specifically, SWNT-based hydrogels demonstrated superior photothermal performance, achieving a remarkable temperature increase of up to 52 °C, in contrast to GO-based hydrogels, which reached a maximum of 34 °C. These composite hydrogels showed good cytotoxicity evaluation results and displayed synergistic antibacterial activity against Staphylococcus aureus, positioning them as promising candidates for antibacterial photothermic platforms, particularly in the context of wound treatment. This study offers a valuable contribution to the development of advanced and combined therapeutic strategies for combating microbial infections and highlights the potential of carbon nanomaterial-enhanced supramolecular hydrogels in photothermal therapy applications.

One small step for a robot, one giant leap for habitat monitoring: A structural survey of EU forest habitats with Robotically-mounted Mobile Laser Scanning (RMLS)

EU States are mandated by the 92/43/EEC Habitats Directive to generate recurring reports on the conservation status and functionality of habitats at the national level. This assessment is based on their floristic and, especially for forest habitats, structural characterization. Currently, habitat field monitoring efforts are carried out only by trained human operators. The H2020 Project “Natural Intelligence for Robotic Monitoring of Habitats – NI” aims to develop quadrupedal robots able to move autonomously in the unstructured environment of forest habitats. In this work, we tested the locomotion performance, efficiency and the accuracy of a robot performing structural habitat monitoring, comparing it with traditional field survey methods inside selected stands of Luzulo-Fagetum beech forests (9110 Annex I Habitat). We used a quadrupedal robot equipped with a Mobile Laser Scanning system (MLS), implementing for the first time a structural monitoring of EU forest habitats with a Robotically-mounted Mobile Laser Scanning (RMLS) platform. Two different scanning trajectories were used to automatically map individual tree locations and extract tree Diameter at Breast Height (DBH) from point clouds. Results were compared with field human measurements in terms of accuracy and efficiency of the survey. The robot was able to successfully execute both scanning trajectories, for which we obtained a tree detection rate of 100 %. Circular scanning trajectory performed better in terms of battery consumption, Root Mean Square Error (RMSE) of the extracted DBH (2.43 cm or 10.73 %) and prediction power (R2adj = 0.72, p < 0.001). The RMLS platform improved survey efficiency with 19.31 m2/min or 1.77 trees/min in comparison with 3.45 m2/min or 0.32 trees/min of traditional survey. Finally, a processing script was developed to allow the repeatability of RMLS surveys in similar habitat monitoring missions. In the future, a human-robotic monitoring framework might represent an accurate support for those repetitive and time-consuming activities in habitat monitoring, offering a valuable benefit for biodiversity conservation.

Tree Diameter at Breast Height (DBH) Estimation Using an iPad Pro LiDAR Scanner: A Case Study in Boreal Forests, Ontario, Canada

The aim of this study was to determine whether the iPad Pro 12th generation LiDAR sensor is useful to measure tree diameter at breast height (DBH) in natural boreal forests. This is a follow-up to a previous study that was conducted in a research forest and identified the optimal method for (DBH) estimation as a circular scanning and fitting ellipses to 4 cm stem cross-sections at breast height. The iPad Pro LiDAR scanner was used to acquire point clouds for 15 sites representing a range of natural boreal forest conditions in Ontario, Canada, and estimate DBH. The secondary objective was to determine if tested stand (species composition, age, density, understory) or tree (species, DBH) factors affected the accuracy of estimated DBH. Overall, estimated DBH values were within 1 cm of actual DBH values for 78 of 133 measured trees (59%). An RMSE of 1.5 cm (8.6%) was achieved. Stand age had a large effect (&gt;0.15) on the accuracy of estimated DBH values, while density, understory, and DBH had moderate effects (0.05–0.14). No trend was identified between accuracy and stand age. Accuracy improved as understory density decreased and as tree DBH increased. Inertial measurement unit (IMU) and positional accuracy errors with the iPad Pro scanner limit the feasibility of using this device for forest inventories.

Estimating Tree Diameter at Breast Height (DBH) Using iPad Pro LiDAR Sensor in Boreal Forests

Traditional Diameter at Breast Height (DBH) mensuration is labor-intensive and costly. This scoping study explored the possibility of using the Apple iPad Pro Light Detection And Ranging (LiDAR) sensor to estimate DBH. Three plots were scanned in a research plantation near Thunder Bay, Canada. Sites consisted of either Black Spruce (Picea mariana) or Red Pine (Pinus resinosa) planted with different initial densities. DBH was manually measured for validation. Point clouds were acquired for each plot using three scanning patterns; circular, figure-8, and transect. Single and five cross sections of 4 or 10 cm in thickness were extracted from each point cloud, centered at 1.3 m above the ground. Two circle fitting algorithms (Pratt, Taubin) and two ellipse fitting algorithms (Taubin, Szpak) were applied to the extracted cross-sections to estimate DBH. Scanning pattern and curve-fitting formula significantly impacted DBH estimate accuracy (p-value ≤ 0.001), while cross-section count and thickness did not. The circular scanning pattern with a single 4 cm cross-section and a combination of circle- and ellipse-fitting formulas was the most accurate DBH estimation method (RMSE = 1.1 cm; 6.17%).

Utilizing semantic-level computer vision for fracture trace characterization of hard rock pillars in underground space

This study utilizes a semantic-level computer vision-based detection to characterize fracture traces of hard rock pillars in underground space. The trace images captured by photogrammetry are used to establish the database for training two convolutional neural network (CNN)-based models, i.e., U-Net (University of Freiburg, Germany) and DeepLabV3+ (Google, USA) models. Chain code technology, polyline approximation algorithm, and the circular window scanning approach are combined to quantify the main characteristics of fracture traces on flat and uneven surfaces, including trace length, dip angle, density, and intensity. The extraction results indicate that the CNN-based models have better performances than the edge detection methods-based Canny and Sobel operators for extracting the trace and reducing noise, especially the DeepLabV3+ model. Furthermore, the quantization results further prove the reliability of extracting the fracture trace. As a result, a case study with two types of traces (i.e., on flat and uneven surfaces) demonstrates that the applied semantic-level computer vision detection is an accurate and efficient approach for characterizing the fracture trace of hard rock pillars.

Characterization of the genesis and spatial variability in tectonic fractures in the Gaosong ore field (South China).

This study examines fractures in the Gaosong ore field to determine the main factors affecting the spatial variability in the fracture structure. The attributes of fractures, including the fracture orientation, intensity and intersection density, in the Wuzishan anticline and near the Lotus mountain fault in the Gaosong ore field in the GeJiu ore district were extracted by using a modified circular scanning line method. The fracture intensity and intersection density were analyzed based on the semivariance geostatistics function by using the volume of variation and the amount of relative variability. These parameters quantitatively describe the spatial variability in the fracture structure. The mean and standard variance of fracture intensity and intersection density in the ore field decrease with distance from the Lotus mountain fault, while the coefficient of variation increases. The spatial anisotropy is closely related to the axial direction of the Wuzishan anticline and the orientation of the Lotus mountain fault. The main factors affecting the spatial variability in the fault structure can be determined with the semivariance geostatistics function, and the results are useful for studying the geology of the mining area and can help to construct an accurate structural model to serve the needs of mine production.

Impurity-free and high-efficiency modification for 30CrMo steel

It is still difficult to simultaneously achieve surface polishing and purity-free modification of 30CrMo steel by conventional treatment technologies. Herein, the continuous circular scanning electron beam process (CCSEBP), a novel route, for direct surface modification of 30CrMo steel is proposed. The changes regularity in microstructure, surface roughness, microhardness and wear resistance after electron beam treatment was investigated. Results indicated that the modified layer was primarily composed of typical acicular and lath martensite. After polishing, the surface roughness was decreased from 2.2 μm to 0.9 μm and microhardness improved significantly, which is closely associated with martensitic transformation. Moreover, the wear amount of the 30CrMo steel after modification is reduced by 50% compared to the pristine specimen. Following appropriate treatment, 30CrMo steel exhibited an extraordinary combination of hardness and finish. This study shed light on the development of high-efficiency modification for electron beam scanning 30CrMo steel.

Impact of Beam Deflection Geometry on the Surface Architecture and Mechanical Properties of Electron-Beam-Modified TC4 Titanium Alloy.

This paper aims to investigate the impact of beam deflection geometry on the structure, surface architecture, and friction coefficient of electron-beam-modified TC4 titanium alloys. During the experiments, the electron beam was deflected in the form of different scanning geometries, namely linear, circular, and matrix. The structure of the treated specimens was investigated in terms of their phase composition by employing X-ray diffraction experiments. The microstructure was studied by scanning electron microscopy (SEM). The surface architecture was examined by atomic force microscopy (AFM). The friction coefficient was studied by a mechanical wear test. It was found that the linear and circular deflection geometries lead to a transformation of the phase composition, from double-phase α + β to α' martensitic structure. The application of a linear manner of scanning leads to a residual amount of beta phase. The use of a matrix does not tend to structural changes on the surface of the TC4 alloy. In the case of linear geometry, the thickness of the modified zone is more than 800 μm while, in the case of EBSM using circular scanning, the thickness is about 160 μm. The electron-beam surface modification leads to a decrease in the surface roughness to about 27 nm in EBSM with linear deflection geometry and 31 nm in circular deflection geometry, compared to that of the pure TC4 substrate (about 160 nm). The electron-beam surface modification of the TC4 alloy leads to a decrease in the coefficient of friction (COF), with the lowest COF values obtained in the case of linear deflection geometry (0.32). The results obtained in this study show that beam deflection geometry has a significant effect on the surface roughness and friction coefficient of the treated surfaces. It was found that the application of a linear manner of scanning leads to the formation of a surface with the lowest roughness and friction coefficient.

Two-Step CFAR-Based 3D Point Cloud Extraction Method for Circular Scanning Ground-Based Synthetic Aperture Radar

Ground-Based Synthetic Aperture Radar (GBSAR) has non-contact, all-weather, high resolution imaging and microdeformation sensing capabilities, which offers advantages in applications such as building structure monitoring and mine slope deformation retrieval. The Circular Scanning Ground-Based Synthetic Aperture Radar (CS-GBSAR) is one of its newest developed working mode, in which the radar rotates around an axis in a vertical plane. Such nonlinear observation geometry brings the unique advantage of three-dimensional (3D) imaging compared with traditional GBSAR modes. However, such nonlinear observation geometry causes strong sidelobes in SAR images, which makes it a difficult task to extract point cloud data. The Conventional Cell Averaging Constant False Alarm Rate (CA-CFAR) algorithm can extract 3D point cloud data layer-by-layer at different heights, which is time consuming and is easily influenced by strong sidelobes to obtain inaccurate results. To address these problems, this paper proposes a new two-step CFAR-based 3D point cloud extraction method for CS-GBSAR, which can extract accurate 3D point cloud data under the influence of strong sidelobes. It first utilizes maximum projection to obtain three-view images from 3D image data. Then, the first step CA-CFAR is applied to obtain the coarse masks of three-views. Then, the volume mask in the original 3D image is obtained via inverse projection. This can remove strong sidelobes outside the potential target region and obtain potential target area data by intersecting it with the SAR 3D image. Then, the second step CA-CFAR is applied to the potential target area data to obtain 3D point clouds. Finally, to further eliminate the residual strong sidelobes and output accurate 3D point clouds, the modified Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm is applied. The original DBSCAN method uses a spherical template to cluster. It covers more points, which is easily influenced by the strong sidelobe. Hence, the clustering results have more noise points. Meanwhile, modified DBSCAN clusters have a cylindrical template to accommodate the data’s features, which can reduce false clustering. The proposed method is validated via real data acquired by the North China University of Technology (NCUT)-developed CS-GBSAR system. The laser detection and ranging (LiDAR) data are used as the reference ground truth to demonstrate the method. The comparison experiment with conventional method shows that the proposed method can reduce 95.4% false clustered points and remove the strong sidelobes, which shows the better performance of the proposed method.

Nonlinear Dynamics of Large-Angle Circular Scanning With an Aluminum Nitride Micro-Mirror

This paper introduces a model for nonlinear dynamics of a resonant micro-mirror designed for large-angle circular scanning. The mirror is driven by aluminum nitride thin-films within a chip-scale vacuum package, which permits large scan angles to be achieved at low voltages, but with substantial nonlinearity in the mirror’s dynamic response. A nonlinear mirror model is proposed and analyzed to identify major trends in mirror performance and implications for mirror design. Analysis focuses on coupling between two axes, which has not been closely examined for multi-axis micro-mirrors. Coupling between axes is found to be capable of augmenting scan amplitude or causing mirror response to collapse from a circular scan patter to an ellipse or line scan, depending on relative strength of model parameters. Good agreement is achieved between modeled and experimental micro-mirror response, with scan amplitudes near <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\pm$</tex-math> </inline-formula> 13 degrees under 1.5 V excitation.2022-0181

Curved Synthetic Aperture Radar for Near-Field Terahertz Imaging

High resolution imaging technique will play an essential role in the future smart imaging applications to provide potential solutions for accurate detection, monitoring and classification of the target. The potential of synthetic aperture radar (SAR) systems to acquire high resolution images has opened new frontiers and led to its exploration in new applications. The conventional microwave radar imaging suffers limited range resolution in the sub-millimeter wave range and optical imaging methods are constrained by the diffraction limit. In the terahertz (THz) regime of the spectrum, the SAR systems could be operated in all the weather, all the time and are capable of penetrating through clouds, smoke, dust etc. to achieve high resolution images beyond the diffraction limit. The curved SAR presents a SAR system created by circularly encircling the target scene. The Circular SAR and Spiral SAR which are based on a circular and cylindrical spiral scanning trajectory, respectively are the scanning methods used for curved SAR. In this paper, we have explored a new toolbox that enables the rapid development of near-field THz-SAR imaging systems and generation of large near-field THz imaging scenarios with the goal to support and facilitate data driven research such as deep learning in the THz community through synthetically generated SAR images as well as its potential for THz based high resolution and 2D/3D near-field imaging application. Initially, the potential advantages of THz-SAR over Microwave SAR and optical imaging methods are presented. Further, a frequency modulated continuous wave (FMCW) radar testbed is simulated in multi-input multi-output (MIMO) configuration for the target frequency band. Moreover, the circular and cylindrical SAR scanning methods are explored for near-field imaging of point targets to obtain 2D and 3D THz-SAR images, respectively. Also, the radar images are reconstructed using the Back Propagation and Polar Formatting Algorithms, focusing on short range applications like indoor environments. Finally, the SAR performance evaluation metrics are reported and a roadmap for future work is presented.

Circularly Polarized Metasurface Phased Array Antenna System With Wide Axial-Ratio Beamwidth for LEO Mobile Satellite Communication

In this paper a millimeter waves LHCP 1×32 with dummy on both sides phased array antenna is proposed. Multi-layer structure and single feed are employed. The antenna patch adopts 3×3 metasurface. The measured impedance bandwidth is 20%, ranging from 22.5 to 27.5 GHz. The axial ratio bandwidth with an axial-ratio (AR) level < 3 dB achieves 3.35 GHz ranging from 24.15 GHz to 27.5 GHz. Relative 3 dB axial ratio bandwidth reaches 13.4%. A total of 37 beams were measured in the anechoic chamber. The results show that whether the phased array antenna system serves as transmitter or receiver, the 3dB beam angle coverage at 26 GHz reaches -42°-45° at φ= 0° and -42°-42° at φ= 90°. The 3 dB axial ratio beam angle ranges from -80° to 89° at φ= 0°, and from -45° to 45° at φ= 90°. Based on this linear array, it is easy to expand to circular polarization planar wide-angle scanning phased array. The antenna system realizes circular polarization with wide angle wide axial ratio beam scanning, which can be used in LEO satellite communication system.

Local Bit-Plane Domain 3D Oriented Arbitrary and Circular Shaped Scanning Patterns for Bio-Medical Image Retrieval

A new feature descriptor called local bit-plane domain 3D oriented arbitrary and circular shaped scanning pattern (LB-3D-OACSP) is proposed for biomedical image retrieval in this study. Unlike the circular, zigzag and other scanning structures, the LB-3D-OACSP descriptor calculates the association between reference-pixel and its surrounding pixels in bit-plane domain in a 3D plane using multi-directional 3D arbitrary and 3D circular shaped scanning patterns. In contrast to other scanning structures, the multi-directional 3-D arbitrary shaped patterns provide more continual angular dissimilarity among the sampling positions with the aim to capture more frequent changes in the local textures. The total of sixteen number of discriminative 3D arbitrary and 3D circular shaped patterns oriented in various directions are applied on a 3D plane constructed using respective bit-planes of three multi-scale images which ensures the maximum extraction of inter-scale geometrical information across the scales which very effectively captures not only the uniform but non-uniform textures too. The multi-scale images are generated by processing the input image with Gaussian filter banks generating three multi-scale images. The LB-3D-OACSP descriptor is able to capture most of the very fine to coarse image textures through encoding of bit-planes. The performance of LB-3D-OACSP is tested on three popular biomedical image databases both in terms of % average retrieval precision (ARP) and % average retrieval recall (ARR). The experiments demonstrate an encouraging enhancement in terms of %ARP and %ARR as compared to many existing state of the art descriptors.

ST-DepthNet: A Spatio-Temporal Deep Network for Depth Completion Using a Single Non-Repetitive Circular Scanning Lidar

In this paper, we propose a novel depth image completion technique based on sparse consecutive measurements of a non-repetitive circular scanning (NRCS) Lidar, demonstrating the capabilities of a new, compact, and accessible sensor technology for dense range mapping of highly dynamic scenes. Our deep network called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ST-DepthNet</i> is composed of a spatio-temporally (ST) extended U-Net architecture, which accepts a very sparse range data sequence as input and produces a dense depth image stream of the same field-of-view ensuring a high level of spatial details and accuracy. For evaluation, we have constructed a new urban dataset, that – to our best knowledge as the first open Benchmark in this field – comprises various simulated and real-world NRCS Lidar data samples, allowing us to simultaneously train our model on synthetic data with Ground Truth, and to validate the result via real NRCS Lidar measurements. Using this new dataset, we have shown the superiority of our method against a densified depth map obtained from the raw sensor stream, and against two independent state-of-the-art deep-learning based Lidar-only depth completion methods.

A spatial analysis of co-circulating dengue and chikungunya virus infections during an epidemic in a region of Northeastern Brazil

The aim of this study was to describe, through spatial analysis, the cases of arboviruses (dengue and chikungunya), including deaths, during the first epidemic after the circulation of the chikungunya virus (CHIKV) in the state of Pernambuco, Northeastern Brazil. This was an ecological study in both Pernambuco and the state capital, Recife, from 2015 to 2018. The odds ratios (OR) were estimated, and the statistical significance was considered p≤0.05. For the spatial analysis, Kulldorff's space-time scan statistics method was adopted to identify spatial clusters and to provide the relative risk (RR). In order to assess the significance at a level of p < 0.01 of the model, the number of Monte Carlo replications was 999 times. To perform the scan statistics we used the Poisson probability model, with a circular scanning window; annual temporal precision and retrospective analysis. A total of 227 deaths and 158,728 survivors from arboviruses was reported during the study period, with 100 deaths from dengue and 127 from CHIKV. The proportion of deaths from dengue was 0.08% and from chikungunya was 0.35%. The proportion of all those infected (deaths plus survivors) with dengue was 77.42% and with chikungunya was 22.58%. Children aged 0 to 9 years were around 3 times more likely to die than the reference group (OR 2.84; CI95% 1.16–5.00). From the age of 40, the chances of death increased significantly: 40–49 (OR 2.52; CI95% 1.19–5.29), 50–59 (OR 5.55; CI95% 2.76–11.17) and 60 or more (OR 14.90; CI95% 7.79–28.49). Males were approximately twice as likely to die as females (OR 1.77; CI95% 1.36–2.30). White-skinned people were less likely to die compared to non-white (OR 0.60; CI95% 0.41–0.87). The space-time analysis of prevalence in the state of Pernambuco revealed the presence of four clusters in the years 2015 and 2016, highlighting the Metropolitan Macro-region with a relative risk=4 and the Agreste and Hinterland macro-regions with a relative risk=3.3. The spatial distribution of the death rate in the municipality of Recife smoothed by the local empirical Bayesian estimator enabled a special pattern to be identified in the southwest and northeast of the municipality. The spatiotemporal analysis of the death rate revealed the presence of two clusters in the year 2015. In the primary cluster, it may be noted that the aforementioned aggregate presented a RR=7.2, and the secondary cluster presented a RR=6.0. The spatiotemporal analysis with Kulldorff's space-time scan statistics method, proved viable in identifying the risk areas for the occurrence of arboviruses, and could be included in surveillance routines so as to optimize prevention strategies during future epidemics.

Controlling the Structure and Morphology of Organic Nanofilaments Using External Stimuli.

In our continuing pursuit to generate, understand, and control the morphology of organic nanofilaments formed by molecules with a bent molecular shape, we here report on two bent-core molecules specifically designed to permit a phase or morphology change upon exposure to an applied electric field or irradiation with UV light. To trigger a response to an applied electric field, conformationally rigid chiral (S,S)-2,3-difluorooctyloxy side chains were introduced, and to cause a response to UV light, an azobenzene core was incorporated into one of the arms of the rigid bent core. The phase behavior as well as structure and morphology of the formed phases and nanofilaments were analyzed using differential scanning calorimetry, cross-polarized optical microscopy, circular dichroism spectropolarimetry, scanning and transmission electron microscopy, UV-vis spectrophotometry, as well as X-ray diffraction experiments. Both bent-core molecules were characterized by the coexistence of two nanoscale morphologies, specifically helical nanofilaments (HNFs) and layered nanocylinders, prior to exposure to an external stimulus and independent of the cooling rate from the isotropic liquid. The application of an electric field triggers the disappearance of crystalline nanofilaments and instead leads to the formation of a tilted smectic liquid crystal phase for the material featuring chiral difluorinated side chains, whereas irradiation with UV light results in the disappearance of the nanocylinders and the sole formation of HNFs for the azobenzene-containing material. Combined results of this experimental study reveal that in addition to controlling the rate of cooling, applied electric fields and UV irradiation can be used to expand the toolkit for structural and morphological control of suitably designed bent-core molecule-based structures at the nanoscale.