Crime mapping and spatial analysis

Crime maps are becoming significant tools in crime and justice. Advances in the areas of information technology and Geographic Information Systems (GIS) have opened new opportunities for the use of digital mapping in crime control and prevention programs. Crime maps are also valuable for the study of the ecology and the locational aspects of crime. Maps enable areas of unusually high or low concentration of crime to be visually identified. Maps are however only pictorial representations of the results of more or less complex spatial data analyses. A hierarchical model dealing with crime analysis is proposed and applied to the regional analysis of crime in Tehran, the model helps to identify spatial concentration of crimes in specific area (area based method). In area-based methods, crime data are aggregated into geographical areas such as blocks, precincts, and for each area, the analyst computes a measure of crime value. Multicriteria evaluation concept has been used to assess the crime rate in various blocks a discrete (part) of Tehran city. In this part we used two methods for crime density assessment: • Crime assessment based on crime per block, • Crime assessment based on density of crime per population. After determination of hot spots based on two methods mentioned above spatial function is used to find suitable location to establish new police station or direct patrol to the hot spots to reduce of crime

Effects of Benzo(a)pyrene on the endometrial receptivity and embryo implantation in mice: An experimental study

Background: Benzo(a)pyrene (BaP) as an environmental pollutant is ubiquitous in the environment and it has destructive effects on human health. So far, various studies have demonstrated that BaP can cause adverse effects on the female reproductive system, but the existing information is limited about the effects of BaP on the endometrial receptivity and embryo implantation. Objective: The aim of this study was to investigate the effects of BaP on the endometrial receptivity and implantation in mice. Materials and Methods: In this experimental study, 40 pregnant BALB/c mice were divided into 5 groups (n = 8/each) as follows: experimental groups received the doses of 100 μg/kg, 200 μg/kg, and 500 μg/kg BaP dissolved in corn oil, the control group received normal saline and sham group received corn oil. Pregnant mice administered these solutions from Day 1 to Day 5 of gestation by gavage. On Day 6, the mice were sacrificed. Then their embryos were counted and the hormonal, histomorphological and molecular analyses were performed on themocusa of uterine tube. Results: The data revealed that BaP reduces estrogen and progesterone levels, decreases the number of implantation site, endometrium thickness, uterine lumen diameter, stromal cells and endometrial glands, and blood vessels in the endometrium. However, the expression of Activin receptor-like kinase 5 and E cadherin genes was not changed by BaP with different doses. Conclusion: The finding of this study showed that BaP can change estrogen and progesterone levels, and endometrial morphology leads to impairing the endometrial receptivity and decreasing the number of implantation site. Key words: Benzo(a)pyrene, Embryo implantation, Estrogen, Progesterone, ALK5, E-cadherin

Photogrammetric evaluation of space linear array imagery for medium scale topographic mapping

This thesis is concerned with the 2D and 3D mathematical modelling of satellite-based linear array stereo images and the implementation of this modelling in a general adjustment program for use in sophisticated analytically-based photogrammetric systems. The programs have also been used to evaluate the geometric potential of linear array images in different configurations for medium scale topographic mapping. In addition, an analysis of the information content that can be extracted for topographic mapping purposes has been undertaken. The main aspects covered within this thesis are: - 2D mathematical modelling of space linear array images; - 3D mathematical modelling of the geometry of cross-track and along-track stereo linear array images taken from spacebome platforms; - the algorithms developed for use in the general adjustment program which implements the 2D and 3D modelling; - geometric accuracy tests of space linear array images conducted over high-accuracy test fields in different environments; - evaluation of the geometric capability and information content of space linear array images for medium scale topographic mapping; This thesis concludes that the mathematical modelling of the geometry and the adjustment program developed during the research has the capability to handle the images acquired from all available types of space linear array imaging systems. Furthermore it has been developed to handle the image data from the forthcoming very high-resolution space imaging systems utilizing flexible pointing of their linear array sensors. It also concludes that cross-track and along-track stereo images such as those acquired by the SPOT and MOMS- 02 linear array sensors have the capability for map compilation in 1:50,000 scales and smaller, but only in conjunction with a comprehensive field completion survey to supplement the data acquired from the satellite imagery

Using pixel-based and object-based methods to classify urban hyperspectral features

Object-based image analysis methods have been developed recently. They have since become a very active research topic in the remote sensing community. This is mainly because the researchers have begun to study the spatial structures within the data. In contrast, pixel-based methods only use the spectral content of data. To evaluate the applicability of object-based image analysis methods for land-cover information extraction from hyperspectral data, a comprehensive comparative analysis was performed. In this study, six supervised classification methods were selected from pixel-based category, including the maximum likelihood (ML), fisher linear likelihood (FLL), support vector machine (SVM), binary encoding (BE), spectral angle mapper (SAM) and spectral information divergence (SID). The classifiers were conducted on several features extracted from original spectral bands in order to avoid the problem of the Hughes phenomenon, and obtain a sufficient number of training samples. Three supervised and four unsupervised feature extraction methods were used. Pixel based classification was conducted in the first step of the proposed algorithm. The effective feature number (EFN) was then obtained. Image objects were thereafter created using the fractal net evolution approach (FNEA), the segmentation method implemented in eCognition software. Several experiments have been carried out to find the best segmentation parameters. The classification accuracy of these objects was compared with the accuracy of the pixel-based methods. In these experiments, the Pavia University Campus hyperspectral dataset was used. This dataset was collected by the ROSIS sensor over an urban area in Italy. The results reveal that when using any combination of feature extraction and classification methods, the performance of object-based methods was better than pixel-based ones. Furthermore the statistical analysis of results shows that on average, there is almost an 8 percent improvement in classification accuracy when we use the object-based methods

Cloud detection based on high resolution stereo pairs of the geostationary meteosat images

Due to the considerable impact of clouds on the energy balance in the atmosphere and on the earth surface, they are of great importance for various applications in meteorology or remote sensing. An important aspect of the cloud research studies is the detection of cloudy pixels from the processing of satellite images. In this research, we investigated a stereographic method on a new set of Meteosat images, namely the combination of the high resolution visible (HRV) channel of the Meteosat-8 Indian Ocean Data Coverage (IODC) as a stereo pair with the HRV channel of the Meteosat Second Generation (MSG) Meteosat-10 image at 0° E. In addition, an approach based on the outputs from stereo analysis was proposed to detect cloudy pixels. This approach is introduced with a 2D-scatterplot based on the parallax value and the minimum intersection distance. The mentioned scatterplot was applied to determine/detect cloudy pixels in various image subsets with different amounts of cloud cover. Apart from the general advantage of the applied stereography method, which only depends on geometric relationships, the cloud detection results are also improved because: (1) The stereo pair is the HRV bands of the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) sensor, with the highest spatial resolution available from the Meteosat geostationary platform; and (2) the time difference between the image pairs is nearly 5 s, which improves the matching results and also decreases the effect of cloud movements. In order to prove this improvement, the results of this stereo-based approach were compared with three different reflectance-based target detection techniques, including the adaptive coherent estimator (ACE), constrained energy minimization (CEM), and matched filter (MF). The comparison of the receiver operating characteristics (ROC) detection curves and the area under these curves (AUC) showed better detection results with the proposed method. The AUC value was 0.79, 0.90, 0.90, and 0.93 respectively for ACE, CEM, MF, and the proposed stereo-based detection approach. The results of this research shall enable a more realistic modelling of down-welling solar irradiance in the future

Monitoring Long-Term Spatiotemporal Changes in Iran Surface Waters Using Landsat Imagery

Within water resources management, surface water area (SWA) variation plays a vital role in hydrological processes as well as in agriculture, environmental ecosystems, and ecological processes. The monitoring of long-term spatiotemporal SWA changes is even more critical within highly populated regions that have an arid or semi-arid climate, such as Iran. This paper examined variations in SWA in Iran from 1990 to 2021 using about 18,000 Landsat 5, 7, and 8 satellite images through the Google Earth Engine (GEE) cloud processing platform. To this end, the performance of twelve water mapping rules (WMRs) within remotely-sensed imagery was also evaluated. Our findings revealed that (1) methods which provide a higher separation (derived from transformed divergence (TD) and Jefferies–Matusita (JM) distances) between the two target classes (water and non-water) result in higher classification accuracy (overall accuracy (OA) and user accuracy (UA) of each class). (2) Near-infrared (NIR)-based WMRs are more accurate than short-wave infrared (SWIR)-based methods for arid regions. (3) The SWA in Iran has an overall downward trend (observed by linear regression (LR) and sequential Mann–Kendall (SQMK) tests). (4) Of the five major water basins, only the Persian Gulf Basin had an upward trend. (5) While temperature has trended upward, the precipitation and normalized difference vegetation index (NDVI), a measure of the country’s greenness, have experienced a downward trend. (6) Precipitation showed the highest correlation with changes in SWA (r = 0.69). (7) Long-term changes in SWA were highly correlated (r = 0.98) with variations in the JRC world water map

Spatially and Temporally Distinct Encoding of Muscle and Kinematic Information in Rostral and Caudal Primary Motor Cortex

The organizing principle of human motor cortex does not follow an anatomical body map, but rather a distributed representational structure in which motor primitives are combined to produce motor outputs. Electrophysiological recordings in primates and human imaging data suggest that M1 encodes kinematic features of movements, such as joint position and velocity. However, M1 exhibits well-documented sensory responses to cutaneous and proprioceptive stimuli, raising questions regarding the origins of kinematic motor representations: are they relevant in top-down motor control, or are they an epiphenomenon of bottom-up sensory feedback during movement? Here we provide evidence for spatially and temporally distinct encoding of kinematic and muscle information in human M1 during the production of a wide variety of naturalistic hand movements. Using a powerful combination of high-field functional magnetic resonance imaging and magnetoencephalography, a spatial and temporal multivariate representational similarity analysis revealed encoding of kinematic information in more caudal regions of M1, over 200 ms before movement onset. In contrast, patterns of muscle activity were encoded in more rostral motor regions much later after movements began. We provide compelling evidence that top-down control of dexterous movement engages kinematic representations in caudal regions of M1 prior to movement production

Single-Cell Photothermal Analysis Induced by MoS2 Nanoparticles by Raman Spectroscopy

: Two-dimensional nanomaterials, such as MoS2 nanosheets, have been attracting increasing attention in cancer diagnosis and treatment, thanks to their peculiar physical and chemical properties. Although the mechanisms which regulate the interaction between these nanomaterials and cells are not yet completely understood, many studies have proved their efficient use in the photothermal treatment of cancer, and the response to MoS2 nanosheets at the single-cell level is less investigated. Clearly, this information can help in shedding light on the subtle cellular mechanisms ruling the interaction of this 2D material with cells and, eventually, to its cytotoxicity. In this study, we use confocal micro-Raman spectroscopy to reconstruct the thermal map of single cells targeted with MoS2 under continuous laser irradiation. The experiment is performed by analyzing the water O-H stretching band around 3,400 cm-1 whose tetrahedral structure is sensitive to the molecular environment and temperature. Compared to fluorescence-based approaches, this Raman-based strategy for temperature measurement does not suffer fluorophore instability, which can be significant under continuous laser irradiation. We demonstrate that irradiation of human breast cancer MCF7 cells targeted with MoS2 nanosheets causes a relevant photothermal effect, which is particularly high in the presence of MoS2 nanosheet aggregates. Laser-induced heating is strongly localized near such particles which, in turn, tend to accumulate near the cytoplasmic membrane. Globally, our experimental outcomes are expected to be important for tuning the nanosheet fabrication process

Single-Cell Photothermal Analysis Induced by MoS2 Nanoparticles by Raman Spectroscopy

Two-dimensional nanomaterials, such as MoS2 nanosheets, have been attracting increasing attention in cancer diagnosis and treatment, thanks to their peculiar physical and chemical properties. Although the mechanisms which regulate the interaction between these nanomaterials and cells are not yet completely understood, many studies have proved their efficient use in the photothermal treatment of cancer, and the response to MoS2 nanosheets at the single-cell level is less investigated. Clearly, this information can help in shedding light on the subtle cellular mechanisms ruling the interaction of this 2D material with cells and, eventually, to its cytotoxicity. In this study, we use confocal micro-Raman spectroscopy to reconstruct the thermal map of single cells targeted with MoS2 under continuous laser irradiation. The experiment is performed by analyzing the water O-H stretching band around 3,400 cm−1 whose tetrahedral structure is sensitive to the molecular environment and temperature. Compared to fluorescence-based approaches, this Raman-based strategy for temperature measurement does not suffer fluorophore instability, which can be significant under continuous laser irradiation. We demonstrate that irradiation of human breast cancer MCF7 cells targeted with MoS2 nanosheets causes a relevant photothermal effect, which is particularly high in the presence of MoS2 nanosheet aggregates. Laser-induced heating is strongly localized near such particles which, in turn, tend to accumulate near the cytoplasmic membrane. Globally, our experimental outcomes are expected to be important for tuning the nanosheet fabrication process