Minimum Map Research Articles

Maximum radial pattern matching for minimum star map identification

This paper proposes an all-sky star map identification algorithm that can simultaneously achieve high identification probability, low algorithm complexity, and small databases for well photometric and intrinsic parameters-calibrated star sensors. The proposed algorithm includes three main steps. First, a binary radial pattern table is constructed offline. Then, the maximum value matching of the radial pattern is performed between the star spots and the guide stars, and the star pairs (i.e., the minimum star map) after radial pattern matching undergo a coarse matching through angular distance cross-validation. Finally, a reference star map is designed based on the identified star pairs, and the matching of all the star spots in the field of view is realized. Simulation and analysis results show that the database required by the proposed algorithm for 5,000 guide stars is not larger than 200 KB. Also, when false and missing star spots account for 50% of all guide stars and the star spot extraction error is 0.5 pixel (the corresponding pointing error is 26″), the average star map identification time of the proposed algorithm is less than 2 ms, and its identification probability is higher than 98%. The results demonstrate that the proposed algorithm performs better than similar algorithms.

Rhythmic Gymnastics Therapy Has an Effect on Reducing Blood Pressure in Hypertension Sufferers

Background: Rhythmic exercise therapy for blood pressure in hypertensive sufferers is one of the non-pharmacological intervention techniques that can be used by hypertensive sufferers. Objective: This research aims to determine the effect of rhythmic exercise therapy on blood pressure in hypertension sufferers in Cisalak Village, Cibeber District, Cianjur Regency in 2022. Method: The design of this research is a Quasy Experiment design, non-equivalent pre-test and post-test with a control group design. The population in this study were all residents of Cisalak village, Cibeber subdistrict, Cianjur district with a sample of 32 respondents (16 intervention and 16 controls). The instrument used in this research was an observation sheet. Data collection techniques by observation. The analysis used is Univariate and Bivariate using the Wilcoxon test. Results: The blood pressure of hypertensive patients before being given rhythmic exercise therapy provided information on the value (Mean Arterial Pressure) with a mean value of MAP of 113 mmHg before the intervention from 16 intervention respondents with a minimum MAP of 106 mmHg and a maximum MAP of 120 mmHg. After conducting research, the results of the mean value were MAP 103 mmHg, minimum MAP 96 mmHg, and maximum MAP 113 mmHg. The results of the Wilcoxon Signed Rank T-Test test between the values ​​of the Intervention Group and the Control Group showed that the P-value was 0.001, and the Intervention p-value <0.005. Conclusion: That there is an effect of rhythmic exercise therapy on patients suffering from hypertension in Cisalak village, Cibeber subdistrict, Cianjur district in the intervention group.

Determination of Black Sea Coastline Length with Oblique Stereographic Projection Using Affine Transformation

The Black Sea basin has rich oil and natural gas resources. As a result, determining the continental shelf in international relations and maritime law is a critical issue for countries with a shoreline on the Black Sea, which is a semi-enclosed sea. Global projections are generally used for the projection of satellites used to image the earth. The use of global projections causes increased deformation in applications in local areas. For this reason, the deformation of satellite images used as a base can be reduced by converting them to the appropriate projection. In this study, the coastline lengths of the countries neighboring the Black Sea were calculated by using remote sensing images and selecting the appropriate cartographic projection due to the aim of minimum map deformation. By using different numbers of control points to determine the six parameters of the 2D Affine transformation used for coordinate transformation, the change in the accuracy of the transformation depending on the number of control points was examined. The Black Sea coastline, which was digitized in the local coordinate system via the MODIS satellite image, was transformed into coordinates in the oblique stereographic projection system with 2D affine transformation. 11 test points were used in the affine transformation parameters calculated using different control points, and root mean square error (RMSE) of approximately 6 km on the X axis and approximately 10 km on the Y axis was achieved using 25 control points. As a result of the transformation, the coastline lengths of each country bordering the Black Sea were determined in oblique stereographic projection.

Joint simplification of various types spatial objects while preserving topological relationships

Cartographic generalization includes the process of graphically reducing information from reality or larger scaled maps to display only the information that is necessary at a specific scale. After generalization, maps can show the main things and essential characteristics. The scale, use and theme of maps, geographical features of cartographic regions and graphic dimensions of symbols are the main factors affecting cartographic generalization. Geometric simplification is one of the core components of cartographic generalization. The topological relations of spatial features also play an important role in spatial data organization, queries, updates, and quality control. Various map transformations can change the relationships between features, especially since it is common practice to simplify each type of spatial feature independently (first administrative boundaries, then road network, settlements, hydrographic network, etc.). In order to detect the spatial conflicts a refined description of topological relationships is needed. Considering coverings and mesh structures allows us to reduce the more general problem of topological conflict correction to the problem of resolving topological conflicts within a single mesh cell. In this paper, a new simplification algorithm is proposed. Its peculiarity is the joint simplification of a set of spatial objects of different types while preserving their topological relations. The proposed algorithm has a single parameter — the minimum map detail size (usually it is equal to one millimeter in the target map scale). The first step of the algorithm is the construction of a special mesh data structure. On its basis for each spatial object a sequence of cells is formed, to which points of this object belong. If a cell contains points of only one object, its geometric simplification is performed within the bounding cell using the sleeve-fitting algorithm. If a cell contains points of several objects, geometric simplification is performed using a special topology-preserving procedure.

Rede de suporte social, capacidade funcional e saúde mental em pessoas idosas

Abstract This study aimed to describe the characteristics of the social networks of older adults and to assess associations between social support, functional capacity and mental health. The sample consisted of 134 community-dwelling older adults, assessed in terms of their social network through the Minimum Map of Older Adult Relationships; functional capacity for performance in activities of daily living; depressive symptoms, assessed through the Geriatric Depression Scale and; anxiety, assessed through the Beck Anxiety Inventory. Cluster analyses were performed. The social network was characterized by being informal, functioning as affective support that occurs through visits. Social support perceived as insufficient was more frequent in men, in those who were dependent regarding instrumental activities of daily living, and in those with anxiety and depressive symptoms. Reduced social support networks and lack of support were associated with limitations in functional capacity and worse mental health, sparking debate about the centrality of the family in the provision of support.

Rapid estimation of minimum depth-to-bedrock from lidar leveraging deep-learning-derived surficial material maps

Previously glaciated landscapes often share similar surficial characteristics, including large areas of exposed bedrock, blankets of till deposits, and alluvium-floored valleys. These materials play significant roles in geologic and hydrologic resources, geohazards, and landscape evolution; however, the vast extents of many previously glaciated landscapes have rendered comprehensive, detailed field mapping difficult. While recent advances in remote sensing have facilitated mapping of surficial materials and landforms, manual map creation has remained a time-intensive task.The development of convolutional neural networks (CNNs) for image classification has provided a new opportunity for rapid characterization of digital elevation models, thus enabling efficient mapping of surficial materials and landforms. We have developed a methodology that leverages existing geologic maps and high-resolution (1–3 m) lidar data to train a U-Net CNN to classify alluvium and exposed bedrock in previously glaciated regions. Coupled with U.S. Geological Survey-developed geomorphometry tools capable of approximating stream incision depths, these classifications can be used to estimate the minimum thicknesses of stream-proximal hillslope sediments in areas where streams have undergone minimal incision into bedrock.We validate this approach in the context of the Neversink River watershed, a subbasin of the Delaware River Basin and significant water source for New York City. Evaluation of deep learning model performance demonstrates substantial agreement with manually drawn maps of alluvium and exposed bedrock. Validation of the minimum sediment thickness map using borehole data and passive seismic measurements shows the greatest performance for shallow materials and decreased performance in deep sediments, as well as in areas where bedrock exposures were too small to be resolved by lidar. To resolve these issues and create more accurate surficial maps, we are training new CNNs with additional geologic data and exploring advanced approaches for estimating depths of stream incision.

Abstract Number ‐ 150: Association of 24‐hour Blood Pressure Parameters Post‐thrombectomy with Mortality in Anemic and Non‐anemic Patients

Introduction Higher blood pressure (BP) is considered to be harmful in patients who undergo mechanical thrombectomy (MT), however, the impact of BP post‐MT based on comorbidities like anemia has not been well studied. We aim to determine the association of 24‐h post‐MT BP parameters with mortality depending on the anemia status. Methods We conducted a retrospective chart review of patients who underwent MT at a comprehensive stroke center from 7/2014 to 12/2020. Patients were dichotomized into anemic and non‐anemic groups based on the World Health Organization’s definition of anemia [hemoglobin < 12.0 g/dL in women and < 13.0 g/dL in men]. We performed a binary logistic regression analysis controlling for baseline parameters, with the 24‐h post‐MT BP parameters as predictors. The primary outcome was 3‐month mortality. Results 220 patients met the inclusion criteria. The 3‐month mortality rate was 27.27%. In the multivariable analysis, the 24‐h parameters of a lower mean DBP (65.53±9.73 vs. 71.94±10.16; OR, 0.92; 95% CI, 0.86‐0.98; P 0.007), lower mean MAP (85.7±8.65 vs. 91.38±10; OR, 0.93; 95% CI, 0.86‐0.99; P 0.02), a lower minimum DBP (49.27±10.51 vs. 55.1±11.23; OR, 0.93; 95% CI, 0.88‐0.99; P 0.019), a lower minimum MAP (68.96±9.54 vs. 74.73±10.47; OR, 0.93; 95% CI, 0.87‐0.99; P 0.023) were significantly associated with mortality in patients with anemia. There was no association between 24‐hour BP Parameters post‐MT and mortality in non‐anemic patients. Conclusions In our study, lower BP parameters were associated with higher 3‐month mortality in anemic patients, however, this effect was not found in non‐anemic patients. Anemia induces a relative hypoxic state in target tissue in the event of an increase in metabolic demand such as stroke. Higher BP post‐MT can potentially promote perfusion and thus is not associated with worse outcomes in anemic patients post‐MT, whereas in non‐anemic patients it may potentially lead to reperfusion injury.

Low-Light Image Enhancement with Contrast Increase and Illumination Smooth

In image enhancement, maintaining the texture and attenuating noise are worth discussing. To address these problems, we propose a low-light image enhancement method with contrast increase and illumination smooth. First, we calculate the maximum map and the minimum map of RGB channels, and then we set maximum map as the initial value for illumination and introduce minimum map to smooth illumination. Second, we use the histogram-equalized version of the input image to construct the weight for the illumination map. Third, we propose an optimization problem to obtain the smooth illumination and refined reflectance. Experimental results show that our method can achieve better performance compared to the state-of-the-art methods.

1293: ENTERAL VASOPRESSOR USE IN CRITICALLY ILL TRAUMA PATIENTS

Introduction: Enteral vasopressor (EV) therapies have been used to facilitate the weaning of IV vasopressors in critically ill patients. Studies have shown mixed results in the medically critically ill population; however this practice is still common. The use of EVs in the critically ill trauma population is less well described. The purpose of this medication use evaluation was to describe the use of EV therapy in our trauma and surgical ICU and to identify subpopulations which may benefit from EV therapy. Methods: This was an IRB approved single-center, retrospective medication use evaluation at a Level 1 trauma center. Inclusion criteria included: adult patients admitted from January 1st, 2020 to March 15th, 2022 to the trauma and surgical ICU; received IV continuous vasopressor(s) for more than 24 hours; and concomitant use of IV and EV(s). EV therapy was defined as midodrine and/or pseudoephedrine. The primary endpoint was overall success in weaning of IV continuous infusion vasopressors and successful weaning at < 24 hour and < 48 hour post-EV initiation. Secondary endpoints were bradycardiac events (HR < 50 bpm) and IV continuous infusion vasopressor free days in patients requiring a defined duration of vasopressor support. Results: 106 patients were included in the evaluation with 83.0% receiving midodrine and 13.2% receiving pseudoephedrine with or without midodrine. 3.8% of patients were transitioned between agents. Among the whole ICU cohort, 56.7% of patients had spinal cord injury and 54.7% had defined minimum MAP goal and duration. Overall success of IV vasopressor weaning was 78.3%. Weaning of IV vasopressors at < 24 hours and < 48 hours from EV initiation was 28.3% and 48.1%, respectfully. Bradycardia occurred in 41.5% of patients; however symptomatic bradycardia was 6.6%. Among patients with spinal cord injury and defined MAP goal duration, EV therapy was associated with a median of 3 IV vasopressor free days (interquartile range: 0-4). Conclusions: EV therapy can be used to facilitate weaning of IV vasopressor therapy in the traumatic, critically ill patients. Midodrine and pseudoephedrine use may benefit spinal cord injury patients by reducing IV vasopressor days. Future prospective studies are needed to confirm this finding.

Local extreme map guided multi-modal brain image fusion.

Multi-modal brain image fusion targets on integrating the salient and complementary features of different modalities of brain images into a comprehensive image. The well-fused brain image will make it convenient for doctors to precisely examine the brain diseases and can be input to intelligent systems to automatically detect the possible diseases. In order to achieve the above purpose, we have proposed a local extreme map guided multi-modal brain image fusion method. First, each source image is iteratively smoothed by the local extreme map guided image filter. Specifically, in each iteration, the guidance image is alternatively set to the local minimum map of the input image and local maximum map of previously filtered image. With the iteratively smoothed images, multiple scales of bright and dark feature maps of each source image can be gradually extracted from the difference image of every two continuously smoothed images. Then, the multiple scales of bright feature maps and base images (i.e., final-scale smoothed images) of the source images are fused by the elementwise-maximum fusion rule, respectively, and the multiple scales of dark feature maps of the source images are fused by the elementwise-minimum fusion rule. Finally, the fused bright feature map, dark feature map, and base image are integrated together to generate a single informative brain image. Extensive experiments verify that the proposed method outperforms eight state-of-the-art (SOTA) image fusion methods from both qualitative and quantitative aspects and demonstrates great application potential to clinical scenarios.

Local Voltage Mapping of Solar Cells in the Presence of Localized Radiative Defects.

Hyperspectral electroluminescence and photoluminescence imaging of photovoltaic materials and devices produces three-dimensional spatially and spectrally resolved luminescence data, which can be calibrated to an absolute scale, enabling the extraction of high resolution maps of quantities such as the local voltage (quasi-Fermi-level splitting). This extraction requires supplemental measurements of external quantum efficiency (EQE), but these do not have the same spatial resolution. Previously, assumptions have been made to overcome this limitation. In this work, we evaluate these assumptions for InGaAs solar cells with significant spatial variation in the luminescence spectrum shape due to small regions with elevated concentrations of radiative defects. Although appropriate for small variations in spectral shape, we find that with more significant variation, these assumptions can result in non-physical EQEs and too-low voltages. Combining multiple methods can help alleviate this, or a minimum voltage map can be extracted, which will be similar to the actual voltage when EQE is high.

Ferroelectric HfO2 and the importance of strain

Ferroelectric oxides based on ${\mathrm{HfO}}_{2}$ show tremendous promise for the next generation of memory and logic devices. The ferroelectric polymorph is one of several that can be derived from the high symmetry cubic fluorite structure of ${\mathrm{HfO}}_{2}$. A single grain of ${\mathrm{HfO}}_{2}$ may consist of a coherent mixture of multiple orientational and translational variants of different polymorphs. Here, we use symmetry-adapted strain-order parameters to elucidate the relationship between the different ${\mathrm{HfO}}_{2}$ polymorphs and their symmetrically equivalent variants. We use first-principles electronic structure methods to identify minimum energy pathways and map them in subspaces of the symmetry-adapted strain order parameters. We next investigate the atomic structure of domain boundaries that separate coexisting variants of ferroelectric ${\mathrm{HfO}}_{2}$. We rely on Gibbsian excess quantities and a precise specification of mechanical boundary conditions to describe the thermodynamic properties of domain boundaries. Our first-principles calculations show that the O and Hf shuffle arrangement within a domain boundary is closely related to the intermediate shuffle patterns of the homogeneous pathways between ferroelectric variants. Furthermore, the preferred structure within a boundary is very sensitive to local strain constraints imposed by the adjacent ferroelectric variants, leading to highly anisotropic domain boundary energies.

Technical challenges in the treatment of mediastinal lymphomas by proton pencil beam scanning and deep inspiration breath-hold

PurposeTo comprehensively describe the treatment of mediastinal lymphoma by pencil beam scanning (PBS) proton therapy. MethodsFourteen patients underwent PBS proton treatment in a supine position in deep inspiration breath-hold (DIBH). Three DIBH computed tomography (CT) scans were acquired for each patient to delineate the Internal Target Volume (ITV). Intensity-modulated proton therapy (IMPT) was planned by min–max robust optimization on the ITV, with a 6 mm setup and 3.5% range uncertainties. Robustness analysis was performed and dose coverage was visually inspected on the corresponding voxel-wise minimum map. Layer repainting was set equal to 5 to compensate for cardiac motion. Intra-fraction reproducibility during treatment was assessed by repeated daily DIBH X-ray imaging. Finally, an additional CT was acquired at half treatment to estimate the impact of inter-fraction dosimetric reproducibility. ResultsIMPT guaranteed robust mediastinal target coverage and organs-at-risk sparing. However, visual voxel-wise robustness evaluation showed that in five patients a second optimization with focused objectives in the cost-function was necessary to achieve a robust coverage of the target regions at the interface between lungs and soft tissue. In six patients, repainting was not used due to excessive treatment time length and poor patient compliance. Intra-fraction average reproducibility was within 1 mm/1degree. On repeated CT scans, inter-fraction setup errors and/or anatomical changes showed minimal dosimetric differences in CTV coverage. ConclusionIMPT in DIBH is effective and reproducible to treat mediastinal lymphomas. Caution is recommended to guarantee robust dose delivery to high-risk regions at the interface between lungs and soft tissue.

Robust Registration Algorithm for Optical and SAR Images Based on Adjacent Self-Similarity Feature

Because optical and synthetic aperture radar (SAR) images are complementary, their registration has received extensive attention in joint applications. However, robust optical and SAR image registration is challenging due to substantial geometric and radiometric differences. To address this problem, we propose a fast and robust registration algorithm for optical and SAR images based on a novel feature type known as the adjacent self-similarity (ASS). The ASS feature of the pixelwise feature representation is defined to quickly and finely capture the structural features of the image. The ASS feature is extracted by using an optimized offset mean filtering method in a neighborhood of the unit pixel radius to accelerate and refine calculations and the local statistics weighted difference operation to suppress coherent speckles. Based on the ASS feature, we extract the minimum self-similarity map (SSM) and the index map, which are robust against radiometric differences and speckles. Then, based on the excellent characteristics of the two maps, we propose a feature detector based on suppressing the local nonmaximum on the minimum SSM and a novel feature descriptor based on calculating the distribution histogram of the index map in a log-polar grid. In addition, we design a rotation invariance enhancement method for the descriptor to improve the rotation invariance robustness of the algorithm. We conduct experiments with both synthetic and real image pairs. The registration results demonstrate that the proposed algorithm has good scale and rotation invariance, as well as good antinoise ability, and that the algorithm performs better than existing state-of-the-art algorithms in terms of registration robustness, accuracy, and efficiency. The registration results on two real optical and SAR image pairs with complex image scenes show the adaptability of the proposed algorithm. The source code of ASS is publicly available¹.

New Stereo Vision Algorithm Composition Using Weighted Adaptive Histogram Equalization and Gamma Correction

This work presents the composition of a new algorithm for a stereo vision system to acquire accurate depth measurement from stereo correspondence. Stereo correspondence produced by matching is commonly affected by image noise such as illumination variation, blurry boundaries, and radiometric differences. The proposed algorithm introduces a pre-processing step based on the combination of Contrast Limited Adaptive Histogram Equalization (CLAHE) and Adaptive Gamma Correction Weighted Distribution (AGCWD) with a guided filter (GF). The cost value of the pre-processing step is determined in the matching cost step using the census transform (CT), which is followed by aggregation using the fixed-window and GF technique. A winner-takes-all (WTA) approach is employed to select the minimum disparity map value and final refinement using left-right consistency checking (LR) along with a weighted median filter (WMF) to remove outliers. The algorithm improved the accuracy 31.65% for all pixel errors and 23.35% for pixel errors in nonoccluded regions compared to several established algorithms on a Middlebury dataset.

Identifying the best spatial interpolation method for estimating spatial distribution of PM2.5 in Jakarta

Nowadays, many researchers are focused on analyzing the association between PM2.5 concentration and respiratory diseases. PM2.5 is one of the most threatening air pollutant for human health in cities and causes an increasing number of deaths. However, obtaining detailed PM2.5 concentration data constitutes one of the problems in analyzing its relationship with the human health effect. This study aims to select the best model for predicting PM2.5, spatially explicit in Jakarta, and estimate its spatial distribution in this region over the 2019-2020 period. The observation data of PM2.5 measurement results were in eight points spread across Jakarta. Furthermore, the data is a two-year daily time series from 2019-2020, which was then be processed into annual average data. Seven spatial interpolations of different methods were selected to identify which is most realistic in generating the estimated concentration value of PM2.5. From the results, we conclude that the Spline with Tension was the best interpolation method based on 2D visualization and model evaluation. Based on the model evaluation, the Spline with Tension method generated the best model with minimum error, where RMSE, MSE, MAE, and MAP had values of 0.0533,0.0028, 0.0400, 0.0008, respectively. Meanwhile, Ordinary Kriging with spherical had the most significant.

ДИАГНОСТИКА КОММУНИКАТИВНЫХ УЧЕБНЫХ ДЕЙСТВИЙ ОБУЧАЮЩИХСЯ МЛАДШЕГО ШКОЛЬНОГО ВОЗРАСТА С ЛЕГКОЙ УМСТВЕННОЙ ОТСТАЛОСТЬЮ

Statement of the problem. In terms of the concept of development of education for students with disabilities for the period of 2020-2030 and according to the Federal State Educational Standard for students with intellectual disabilities, the harmonious development of both academic educational results and life competence necessary for a student with special educational needs in various social situations is declared one of the main strategic directions for the development of children of early school age. The Basic Learning Action Program (BLAP), as a structural element of the Federal Standard, does not contradict the indicated idea and aims not only at the formation and development of mentally retarded students, but also at ensuring the conditions for their socialization, including their life competence development. The analysis of educational theory and practice made it possible to distinguish a contradiction between the development of the basic provisions of active and differentiated approaches and the insufficient theoretical development of the criteria and levels of formation of communicative learning activities (CLA) of students of early school age with mild mental retardation in order to form the phenomenon under research. The problem solved in the article is the search for theoretical grounds for revealing the essence, structure of CLA of students of early school age with a mild degree of intellectual disabilities in order to develop the diagnostics of the phenomenon under research. The purpose of the article is to disclose the essence, structure of CLA of students of early school age with mild intellectual disabilities; to identify and characterize formation levels of the investigated phenomenon in order to develop diagnostics of CLA formation in the context of the research subject. Methodology (materials and methods) is based on the active and differentiated approaches to education of students with intellectual disabilities; analysis of official documents, scientific psychological and pedagogical literature on the problem of development of basic learning activities in students with intellectual disabilities. Research results. Based on the analysis of scientific works of Russian and foreign researchers and the regulatory and legal framework, the essence and structure of CLA of students of early school age with mild intellectual disabilities was revealed; minimum evaluation and diagnostic map of formation of the investigated phenomenon has been developed; variable communicative situations in which CLA of students of early school age with mild intellectual disabilities are manifested and formed are identified. Conclusion. The developed diagnosis of CLA of students of primary school age with intellectual disabilities will allow tracking their dynamics and making timely adjustments in the organization and implementation of their formation at the level of primary general education and with appropriate modification actions at subsequent educational levels.

AutoTICI: Automatic Brain Tissue Reperfusion Scoring on 2D DSA Images of Acute Ischemic Stroke Patients.

The Thrombolysis in Cerebral Infarction (TICI) score is an important metric for reperfusion therapy assessment in acute ischemic stroke. It is commonly used as a technical outcome measure after endovascular treatment (EVT). Existing TICI scores are defined in coarse ordinal grades based on visual inspection, leading to inter- and intra-observer variation. In this work, we present autoTICI, an automatic and quantitative TICI scoring method. First, each digital subtraction angiography (DSA) acquisition is separated into four phases (non-contrast, arterial, parenchymal and venous phase) using a multi-path convolutional neural network (CNN), which exploits spatio-temporal features. The network also incorporates sequence level label dependencies in the form of a state-transition matrix. Next, a minimum intensity map (MINIP) is computed using the motion corrected arterial and parenchymal frames. On the MINIP image, vessel, perfusion and background pixels are segmented. Finally, we quantify the autoTICI score as the ratio of reperfused pixels after EVT. On a routinely acquired multi-center dataset, the proposed autoTICI shows good correlation with the extended TICI (eTICI) reference with an average area under the curve (AUC) score of 0.81. The AUC score is 0.90 with respect to the dichotomized eTICI. In terms of clinical outcome prediction, we demonstrate that autoTICI is overall comparable to eTICI.

Elevation trend in bacterial functional gene diversity decouples from taxonomic diversity

Elevational patterns in taxonomic diversity have been widely studied, but there has been little attention given to patterns in functional gene diversity. We used a metagenomic approach – along with amplicon data - to study trends in functional gene diversity in bacteria along a 2,300 m elevational gradient on Mt. Norikura, Japan. We hypothesized that in accordance with a global scale study by Bahram et al. (2018), functional gene diversity would show a mid-elevation minimum, due to a pH minimum pH and MAP maximum in the mid-elevations. Instead, we observed a mid-elevation maximum in functional gene diversity, and a decrease with increasing pH values from acidic to near neutral. We also found a weak negative relationship between OTU diversity and functional diversity. There appear to be no obvious ecological mechanisms to explain why the observed mid-elevation peak in functional diversity occurs. The trends observed here demonstrate that it is also necessary to consider more complex localised trends that would largely remain hidden from broad global studies. The fact that functional gene diversity in bacteria is decoupled from taxonomic diversity emphasizes that each should be treated as separate dimensions of diversity.

SAR Image Registration Based on ROEWA-Blocks and Multiscale Circle Descriptor

Given the imaging characteristics of synthetic aperture radar (SAR) images and the inherent speckle noise in them, scale-invariant feature transform based algorithms are unable to perform satisfactorily. To improve registration efficiency between SAR images, we propose a robust and efficient registration method with three main contributions. First, considering sudden dark patches appearing in SAR images, we propose the ratio of exponentially weighted average blocks to suppress the sudden dark patches and better adapt to different test images. This new operator called blocks of the ratio of exponentially weighted averages (ROEWA-B) divides the processing windows of ROEWA into blocks, which can not only reduce speckle noise but also retain more edge details compared to ROEWA when sudden dark patches appear. Second, for outlier removal, we present an approach using the minimum moment map to remove erroneous keypoints. Finally, based on the gradient location orientation histogram descriptor, we propose a novel multiscale circle descriptor, which combines scale change information to give weights to feature points at different scales. Experimental results for various thresholds and evaluations demonstrate the advantage and robustness of our method in registration.