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Today, the daily life of citizens is affected by the occurrence of a type of violation of regulations that occur as a motivation to live in cities, and its continuation and high rate, in addition to depriving citizens of their comfort, requires dealing with them and criminal intervention, which itself creates a complex social problem in cities. has brought. This violation of regulations, which are called urban crimes and violations, has drawn an unacceptable future for cities that is not worthy of continuation. As a way out, the use of the criminal justice system and harsh and coercive actions are on the agenda. The resulting consequences involve a significant part of the citizens in criminal procedures and involve heavy costs. Using the descriptive-analytical method and based on library sources and law analysis, this article concludes that the approach of responsive regulation has criteria that can work more effectively, and based on the design method of the pyramid of responsive regulatio، suitable pyramid with this approach Suggests and explains. [ABSTRACT FROM AUTHOR]

In recent years, various stakeholders and political decision-makers have recognized the significance of high-quality urban sound environments, stressing the need for user-centered trajectories. Despite the rising interest in this field, the soundscape approach has not yet fully permeated urban planning and design, possibly due to a lack of comprehensible guidelines on how to implement and curate successful soundscape designs, attributed to on-going developments on this subject. In the course of the Catalogue of Soundscape Interventions (CSI) Project, a taxonomy of eight dimensions was developed to serve as an orientation aid for practitioners, describing important aspects of soundscape-related measures that can be used as a brief to facilitate communication between authorities, consultants, and researchers. This study describes the theoretical framework and, in particular, the sequential coding process involved in deriving these dimensions, which is based on grounded theory. It lists observations and limitations of the resulting taxonomy and builds upon these findings to critically review and revisit existing nomenclature and concepts. Finally, a qualitative distinction in the form of a design pyramid according to ascending levels of epistemic rigor is proposed, to differentiate between documented practices, which may serve as a reference point for future harmonization and standardization.

Five different solar stills (SSs) have been tested in this experimental study. Hemispherical SS, tubular SS, pyramid SS, double slope SS, and conventional SS are the five SS systems. The primary goal is to determine which SS will perform more effectively at the testing location. Initially, the SSs were evaluated with no changes and the outcomes were contrasted with those of the conventional SS. Secondly, exterior reflectors have been added to four SSs. Third, hemispherical SS and tubular SS with reflectors have been utilized with phase change material (PCM) combined with Ag-Nanoparticles. Lastly, tests using reflectors, fan, and external condensers have been conducted on the hemispherical SS and tubular SS. The findings showed that the increase in productivity for hemispherical SS, tubular SS, pyramid SS, and double slope SS without modifications are 107 %, 97 %, 66.5 %, and 30 % greater than that of conventional SS, respectively. Furthermore, the results depicted that employing reflectors improved the productivity rise for tubular SS, hemispherical SS, pyramid SS, and double slope SS to be higher than conventional SS's productivity by 168 %, 153 %, 113 %, and 85 %, respectively. Besides, the effect of employing PCM-Ag with hemispherical SS and tubular SS (with reflector) is increasing their productivity to be 202 % and 212 % higher than conventional SS's production, respectively. Also, the hemispherical SS and tubular SS with reflector, fan, and a condenser showed 217 % and 236 % higher productivity than conventional SS. The actual cost of producing water for the conventional SS, hemispherical SS, and tubular SS with reflectors and fan is 0.0244, 0.012, and 0.013 $/L, respectively.

Background: Evidence-based medicine (EBM), as originally conceived, used all types of peer-reviewed evidence to guide medical practice and decision-making. During the SARS-CoV-2 Coronavirus disease (COVID-19) pandemic, the standard usage of EBM, modeled by the Evidence-Based Medicine Pyramid, undermined EBM by incorrectly using pyramid levels to assign relative quality. The resulting pyramid-based thinking is biased against reports both in levels beneath randomized control trials (RCTs) and those omitted from the pyramid entirely. Thus, much of the evidence was ignored. Our desire for a more encompassing and effective medical decision-making process to apply to repurposed drugs led us to develop an alternative to the EBM Pyramid for EBM. Herein, we propose the totality of evidence (T-EBM) wheel. Objectives: To create an easily understood graphic that models EBM by incorporating all peer-reviewed evidence that applies to both new and repurposed medicines, and to demonstrate its potential utility using ivermectin as a case study. Methods: The graphics were produced using Microsoft Office Visio Professional 2003 except for part of the T-EBM wheel sunburst chart, which was produced using Microsoft 365 Excel. For the case study, PubMed® was used by searching for peer-reviewed reports containing "ivermectin" and either "covid" or "sars" in the title. Reports were filtered for those using ivermectin-based protocols in the treatment of COVID-19. The resulting 265 reports were evaluated for their study design types and treatment outcomes. The three-ringed graphical T-EBM wheel was composed of two inner rings showing all types of reports and an outer ring showing outcomes for each type. Findings-Conclusions: The T-EBM wheel avoids the biases of the EBM Pyramid and includes all types of reports in the pyramid along with reports such as population and mechanistic studies. In both early and late stages of medical emergencies, pyramid-based thinking may overlook indications of efficacy in regions of the T-EBM wheel beyond RCTs. This is especially true when searching for ways to prevent and treat a novel disease with repurposed therapeutics before RCTs, safety assessments, and mechanisms of action of novel therapeutics are established. As such, T-EBM Wheels should replace the EBM Pyramids in medical decision-making and education. T-EBM Wheels can be expanded upon by implementing multiple outer rings, one for each different kind of outcome (efficacy, safety, etc.). A T-EBM Wheel can be created for any proprietary or generic medicine. The ivermectin (IVM) T-EBM Wheel displays the efficacy of IVM-based treatments of COVID-19 in a color-coded graphic, visualizing each type of evidence and the proportions of each of their outcomes (positive, inconclusive, negative). [ABSTRACT FROM AUTHOR]

Crowd counting provides an important foundation for public security and urban management. Due to the existence of small targets and large density variations in crowd images, crowd counting is a challenging task. Mainstream methods usually apply convolution neural networks (CNNs) to regress a density map, which requires annotations of individual persons and counts. Weakly-supervised methods can avoid detailed labeling and only require counts as annotations of images, but existing methods fail to achieve satisfactory performance because a global perspective field and multi-level information are usually ignored. We propose a weakly-supervised method, DTCC, which effectively combines multi-level dilated convolution and transformer methods to realize end-to-end crowd counting. Its main components include a recursive swin transformer and a multi-level dilated convolution regression head. The recursive swin transformer combines a pyramid visual transformer with a fine-tuned recursive pyramid structure to capture deep multi-level crowd features, including global features. The multi-level dilated convolution regression head includes multi-level dilated convolution and a linear regression head for the feature extraction module. This module can capture both low- and high-level features simultaneously to enhance the receptive field. In addition, two regression head fusion mechanisms realize dynamic and mean fusion counting. Experiments on four well-known benchmark crowd counting datasets (UCF_CC_50, ShanghaiTech, UCF_QNRF, and JHU-Crowd++) show that DTCC achieves results superior to other weakly-supervised methods and comparable to fully-supervised methods. [ABSTRACT FROM AUTHOR]

Abstract Crowd counting provides an important foundation for public security and urban management. Due to the existence of small targets and large density variations in crowd images, crowd counting is a challenging task. Mainstream methods usually apply convolution neural networks (CNNs) to regress a density map, which requires annotations of individual persons and counts. Weakly-supervised methods can avoid detailed labeling and only require counts as annotations of images, but existing methods fail to achieve satisfactory performance because a global perspective field and multi-level information are usually ignored. We propose a weakly-supervised method, DTCC, which effectively combines multi-level dilated convolution and transformer methods to realize end-to-end crowd counting. Its main components include a recursive swin transformer and a multi-level dilated convolution regression head. The recursive swin transformer combines a pyramid visual transformer with a fine-tuned recursive pyramid structure to capture deep multi-level crowd features, including global features. The multi-level dilated convolution regression head includes multi-level dilated convolution and a linear regression head for the feature extraction module. This module can capture both low- and high-level features simultaneously to enhance the receptive field. In addition, two regression head fusion mechanisms realize dynamic and mean fusion counting. Experiments on four well-known benchmark crowd counting datasets (UCF_CC_50, ShanghaiTech, UCF_QNRF, and JHU-Crowd++) show that DTCC achieves results superior to other weakly-supervised methods and comparable to fully-supervised methods.

The third part of the article proceeds from the starting points in the decision-making problem (DMP) specified in the first stages of research [1, 2]. Here, we continue to compare the predominance (first of all, quality) of autoclave and non-autoclave alternative technological processes (ATP) as part of the stages of TP(e) with a linear algorithm of end-to-end action in the manufacture of carbon fiber (CF) aircraft structures (AC) such as highly loaded wing stringer panels (HLS) of B787, A350, MC-21, CSeries mainline aircraft as a component of hierarchical systems. To describe and study them, the following were involved: initial technological and verbal models, technological and mathematical model of an autonomous dynamic system (ADS) and a number of two-dimensional manifolds (topology) to it in the form of technological and geometric models. The article continues the study of development in this direction by approximating manifolds by polyhedra. Including co-cellular and double-formed structures - pentagonal pyramids and bipyramids, as well as bodies of revolution around them - cone and bicon. Examples of schematic and technological interpretive modeling are presented. The methodological basis is the main provisions of decision-making theory, factor analysis and system-process approach with the involvement of practice results (expert analysis), first of all, the definition of technological factors of processes with criterion assessments of the advantages, components of alternatives in their competitive strategies. [ABSTRACT FROM AUTHOR]

We prove that eight dihedral angles in a pyramid with an arbitrary quadrilateral base always sum up to a number in the interval (3π, 5π). Moreover, for any number in (3π, 5π) there exists a pyramid whose dihedral angle sum is equal to this number, which means that the lower and upper bounds are tight. Furthermore, the improved (and tight) upper bound 4π is derived for the class of pyramids with parallelogramic bases. This includes pyramids with rectangular bases, often used in finite element mesh generation and analysis. [ABSTRACT FROM AUTHOR]

Background: Evidence-based medicine (EBM), as originally conceived, used all types of peer-reviewed evidence to guide medical practice and decision-making. During the SARS-CoV-2 Coronavirus disease (COVID-19) pandemic, the standard usage of EBM, modeled by the Evidence-Based Medicine Pyramid, undermined EBM by incorrectly using pyramid levels to assign relative quality. The resulting pyramid-based thinking is biased against reports both in levels beneath randomized control trials (RCTs) and those omitted from the pyramid entirely. Thus, much of the evidence was ignored. Our desire for a more encompassing and effective medical decision-making process to apply to repurposed drugs led us to develop an alternative to the EBM Pyramid for EBM. Herein, we propose the totality of evidence (T-EBM) wheel. Objectives: To create an easily understood graphic that models EBM by incorporating all peer-reviewed evidence that applies to both new and repurposed medicines, and to demonstrate its potential utility using ivermectin as a case study. Methods: The graphics were produced using Microsoft Office Visio Professional 2003 except for part of the T-EBM wheel sunburst chart, which was produced using Microsoft 365 Excel. For the case study, PubMed® was used by searching for peer-reviewed reports containing “ivermectin” and either “covid” or “sars” in the title. Reports were filtered for those using ivermectin-based protocols in the treatment of COVID-19. The resulting 265 reports were evaluated for their study design types and treatment outcomes. The three-ringed graphical T-EBM wheel was composed of two inner rings showing all types of reports and an outer ring showing outcomes for each type. Findings-Conclusions: The T-EBM wheel avoids the biases of the EBM Pyramid and includes all types of reports in the pyramid along with reports such as population and mechanistic studies. In both early and late stages of medical emergencies, pyramid-based thinking may overlook indications of efficacy in regions of the T-EBM wheel beyond RCTs. This is especially true when searching for ways to prevent and treat a novel disease with repurposed therapeutics before RCTs, safety assessments, and mechanisms of action of novel therapeutics are established. As such, T-EBM Wheels should replace the EBM Pyramids in medical decision-making and education. T-EBM Wheels can be expanded upon by implementing multiple outer rings, one for each different kind of outcome (efficacy, safety, etc.). A T-EBM Wheel can be created for any proprietary or generic medicine. The ivermectin (IVM) T-EBM Wheel displays the efficacy of IVM-based treatments of COVID-19 in a color-coded graphic, visualizing each type of evidence and the proportions of each of their outcomes (positive, inconclusive, negative).

A novel wafer-scale silicon fractal fabrication method is presented here for forming pyramids only in the lateral direction using the crystal orientation of silicon. Fractals are fabricated in silicon by masking only the corners (corner lithography) of a cavity in silicon with silicon nitride, where the shape is determined by the crystal {111} planes of the silicon. The octahedral cavity shaped by the {111} planes was previously only used for forming octahedral fractals in all directions, but by using a planar silicon dioxide hard-mask on a silicon (100) wafer, the silicon octahedral cavity is "cut in half". This creates a pyramid with sharper edges and vertices at its base than those determined by just the {111} planes. This allows selective corner lithography patterning at the vertices of the base while leaving the apex unpatterned, leading to lateral growing of pyramidal fractals. This selective patterning is shown mathematically and then demonstrated by creating a fractal of four generations, with the initial pyramid being 8 µm and the two final generations being of submicron size. [ABSTRACT FROM AUTHOR]

To solve the ghosting artifacts problemin dynamic scenemulti-scale exposure fusion, an improvedmulti-exposure fusionmethod has been proposed without ghosting based on the exposure fusion framework and the color dissimilarity feature of this study. This fusion method can be further applied to power system monitoring and unmanned aerial vehicle monitoring. In this study, first, an improved exposure fusion framework based on the camera responsemodel was applied to preprocess the input image sequence. Second, the initial weight map was estimated bymultiplying four weight items. In removing the ghosting weight term, an improved color dissimilarity feature was used to detect the object motion features in dynamic scenes. Finally, the improved pyramid model as adopted to retain detailed information about the poor exposure areas. Experimental results indicated that the proposed method improves the performance of images in terms of sharpness, detail processing, and ghosting artifacts removal and is superior to the five existing multi-exposure image fusion (MEF) methods in quality evaluation. [ABSTRACT FROM AUTHOR]

At schools, many teachers generally applied a conventional way of teaching mathematics. Students were only required to achieve cognitive learning success. This study aimed to develop mathematics learning media for lessons related to pyramids using the Reflective Pedagogical Paradigm (RPP) and Van Hiele theory, including the development steps and student and teacher responses to the learning process. The researchers used the research and development procedures by Borg and Gall that include (1) Preliminary studies; (2) Planning Research; (3) Design Development; (4) Limited Trial; (5) Revision of Limited Field Test Results. The learning tools developed were syllabus, lesson plans, modules, worksheets, formative tests, and attitude assessments. The data collection techniques used were observation, distributing questionnaires, interviews, and tests. Based on the validation results, the learning media got 4.19, thus categorized as "good," and students' response to the learning process reached 128.23, thus categorized as "good" as well. Students and teachers carried out learning happily and actively.

Background: The emergence of wireless capsule endoscopy (WCE) has presented a viable non-invasive mean of identifying gastrointestinal diseases in the field of clinical gastroenterology. However, to overcome its extended time of manual inspection, a computer aided automatic detection system is getting vast popularity. In this case, major challenges are low resolution and lack of regional context in images extracted from WCE videos. Methods: For tackling these challenges, in this paper a convolution neural network (CNN) based architecture, namely RAt-CapsNet, is proposed that reliably employs regional information and attention mechanism to classify abnormalities from WCE video data. The proposed RAt-CapsNet consists of two major pipelines: Compression Pipeline and Regional Correlative Pipeline. In the compression pipeline, an encoder module is designed using a Volumetric Attention Mechanism which provides 3D enhancement to feature maps using spatial domain condensation as well as channel-wise filtering for preserving relevant structural information of images. On the other hand, the regional correlative pipeline consists of Pyramid Feature Extractor which operates on image driven feature vectors to generalize and propagate local relationships of pixels from WCE abnormalities with respect to the normal healthy surrounding. The feature vectors generated by the pipelines are then accumulated to formulate a classification standpoint. Results: Promising computational accuracy of mean 98.51% in binary class and over 95.65% in multi-class are obtained through extensive experimentation on a highly unbalanced public dataset with over 47 thousand labelled. Conclusion: This outcome in turn supports the efficacy of the proposed methodology as a noteworthy WCE abnormality detection as well as diagnostic system.

Megaproject social responsibility (MSR) has received a great deal of attention from both academics and practitioners. However, as a very broad and complex concept, MSR requires an in-depth investigation of its components, driving forces, and contingent factors. Thus, this study aims to explore the climbing process across different levels of MSR from the perspectives of external stakeholders and project complexity. This study first establishes a pyramid framework for analyzing the different components and levels of MSR by leveraging stakeholder theory. Then, drawing upon attention- and capability-based views, theoretical development and empirical analyses are carried out to validate the influence of external stakeholders on participating organizations' MSR and the moderating effects of project complexity. Using a set of survey data from Chinese megaprojects, the empirical findings demonstrate that the positive influence of external stakeholders and the negative moderating effect of project complexity become salient when ascending the pyramid of MSR. The value of this study lies in the way in which it considers the climbing process based on a hierarchical framework of MSR. The theoretical framework and empirical findings offer both project managers and policy makers with new insights into how to govern the diverse social responsibility issues in megaproject construction and management. [ABSTRACT FROM AUTHOR]

This study aims to develop and produce a mathematics student worksheet based on guided discovery to facilitate the understanding concept and the curiosity of eighth grade students on prism and pyramid material. The type of research is research and development using the Richey and Klein development procedure, which consists of the planning, production, and evaluation. Mathematics student worksheet assessment for material and media experts. Material and media experts fill out the mathematics student worksheet assessment. The research data analysis technique is product quality analysis. According to the evaluation of material experts and media experts, the mathematics student worksheet is very good. Based on the results of the study, it found that the quality of the mathematics student worksheet based on guided discovery was classified as very good with the specification of the average score of the material expert validator assessment of 194.5 from the ideal maximum score of 208 and classified in the very good category with the specification of the average score of the media expert validator assessment of 57 from the ideal maximum score of 72. Based on this, the product of the guided discovery-based math worksheets is declared valid and can use in the learning process.

This work deals with real conditions testing of two Fresnel lens-based optical concentrators for concentrator photovoltaic systems (CPV). Particular attention is paid to validate the performances of the secondary optical elements (SOEs), namely pyramid and cone, both made from highly transparent fused silica and mounted with a poly methyl methacrylate (PMMA) Fresnel lens as a primary optical element (POE). The effet of the focal distance of the POE on the main optical characteristics is analyzed by simulation and the corresponding results and behavior are discussed in details. Prototypes based on Fresnel lens having 75 and 100mm in diameter and pyramid- and cone-based secondary optical elements have been simulated, fabricated and tested. Optical and electrical characterization procedures are described in details. The optical efficiency, acceptance angle, spatial homogeneity of the output power and electrical performances of the fabricated CPV units are measured and are in a good agreement with simulation data. Results show that the pyramid-type concentrator gives the best optical and electrical performances. The electric efficiency achieved by the pyramid-based concentrators reaches 30% which make it able to reach the highest standards of CPV technology performances. A large acceptance angle of 1.35° is measured as one of the highest value reported in the literature for systems with pyramid as a SOE. A good agreement between simulation and experiment results has been obtained, confirming the performance expected from a CPV system having the same secondary optical element with a larger primary optical element.

Damage identification in post-earthquake reinforced concrete (RC) structures based on semantic segmentation has been recognized as a promising approach for rapid and non-contact damage localization and quantification. In damage segmentation tasks, damage regions are often set against complex backgrounds, featuring irregular geometric boundaries and intricate textures, posing significant challenges to model segmentation performance. Additionally, the absence of public datasets exacerbates these challenges, hindering advancements in this field. In this paper, a pyramid Haar wavelet downsampling attention UNet (PHA-UNet) semantic segmentation network is proposed, and a database containing 1400 images of damaged RC components (PEDRC-Dataset) with pixel-level annotations is established. In the proposed PHA-UNet, attention mechanisms, multiscale feature fusion, Haar wavelet downsampling, and transfer learning are introduced to address above challenges. Finally, the proposed PHA-UNet is compared with four existing image segmentation architectures on both the Cityspace and the PEDRC-Dataset. • A pyramid Haar wavelet downsampling attention UNet (PHA-UNet) semantic segmentation network is proposed. • A database containing 1400 images of damaged RC components with pixel-level annotations is established. • In the proposed PHA-UNet, attention mechanisms, multiscale feature fusion, and Haar wavelet downsampling are introduced. • Ablation studies highlight the importance of attention mechanism in damage segmentation task of RC components. [ABSTRACT FROM AUTHOR]

Although graph convolutional networks (GCNs) have shown their demonstrated ability in skeleton-based action recognition, both the spatial and the temporal connections rely too much on the predefined skeleton graph, which imposes a fixed prior knowledge for the aggregation of high-level semantic information via the graph-based convolution. Some previous GCN-based works introduced dynamic topology (vertex connection relationships) to capture flexible spatial correlations from different actions. Then, the local relationships from both the spatial and temporal domains can be captured by diverse GCNs. This paper introduces a more straightforward and more effective backbone to obtain the spatial-temporal correlation between skeleton joints with a local-global alternation pyramid architecture for skeleton-based action recognition, namely the pyramid spatial-temporal graph transformer (PGT). The PGT consists of four stages with similar architecture but different scales: graph embedding and transformer blocks. We introduce two kinds of transformer blocks in our work: the spatial-temporal transformer block and joint transformer block. In the former, spatial-temporal separated attention (STSA) is proposed to calculate the connection of the global nodes of the graph. Due to the spatial-temporal transformer block, self-attention can be performed on skeleton graphs with long-range temporal and large-scale spatial aggregation. The joint transformer block flattens the tokens in both the spatial and temporal domains to jointly capture the overall spatial-temporal correlations. The PGT is evaluated on three public skeleton datasets: the NTU RGBD 60, NTU RGBD 120 and NW-UCLA datasets. Better or comparable performance with the state of the art (SOTA) shows the effectiveness of our work. [ABSTRACT FROM AUTHOR]

Although transformer has achieved great progress on computer vision tasks, the scale variation in dense image prediction is still the key challenge. Few effective multi-scale techniques are applied in transformer and there are two main limitations in the current methods. On the one hand, self-attention module in vanilla transformer fails to sufficiently exploit the diversity of semantic information because of its rigid mechanism. On the other hand, it is difficult to build attention and interaction among different levels due to the heavy computational burden. To alleviate this problem, we first revisit multi-scale problem in dense prediction, verifying the significance of diverse semantic representation and multi-scale interaction, and exploring the adaptation of transformer to pyramidal structure. Inspired by these findings, we propose a novel Semantic-aware Decoupled Transformer Pyramid (SDTP) for dense image prediction, consisting of Intra-level Semantic Promotion (ISP), Cross-level Decoupled Interaction (CDI) and Attention Refinement Function (ARF). ISP explores the semantic diversity in different receptive space through more flexible self-attention strategy. CDI builds the global attention and interaction among different levels in decoupled space which also solves the problem of heavy computation. Besides, ARF is further added to refine the attention in transformer. Experimental results demonstrate the validity and generality of the proposed method, which outperforms the state-of-the-art by a significant margin in dense image prediction tasks. Furthermore, the proposed components are all plug-and-play, which can be embedded in other methods. [ABSTRACT FROM AUTHOR]

Fast and accurate MRI image reconstruction from undersampled data is crucial in clinical practice. Deep learning based reconstruction methods have shown promising advances in recent years. However, recovering fine details from undersampled data is still challenging. In this paper, we introduce a novel deep learning based method, Pyramid Convolutional RNN (PC-RNN), to reconstruct images from multiple scales. Based on the formulation of MRI reconstruction as an inverse problem, we design the PC-RNN model with three convolutional RNN (ConvRNN) modules to iteratively learn the features in multiple scales. Each ConvRNN module reconstructs images at different scales and the reconstructed images are combined by a final CNN module in a pyramid fashion. The multi-scale ConvRNN modules learn a coarse-to-fine image reconstruction. Unlike other common reconstruction methods for parallel imaging, PC-RNN does not employ coil sensitive maps for multi-coil data and directly model the multiple coils as multi-channel inputs. The coil compression technique is applied to standardize data with various coil numbers, leading to more efficient training. We evaluate our model on the fastMRI knee and brain datasets and the results show that the proposed model outperforms other methods and can recover more details. The proposed method is one of the winner solutions in the 2019 fastMRI competition. [ABSTRACT FROM AUTHOR]

Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is one of the most economically destructive pathogens. The soybean line Zhongpin03-5373 (ZP), which combines resistance genes from several donors, is highly resistant to SCN race 3 (SCN3). In our previous study, two QTL (rhg1 and GmSNAP11) were identified in a population of recombinant inbred lines derived from a cross between ZP and the susceptible parent Zhonghuang 13. The two QTL explained around one-third of the resistance, suggesting the presence of further QTL contributing to SCN resistance. In the present study, we used an improved version of the genetic map comprising the previously applied 1062 molecular markers and 47 newly developed InDel (insertion-deletion) markers. The improved map revealed a novel locus contributing to SCN3 resistance: qSCN3-1, flanked by InDel marker InDel1-7 and SNP marker Map-0047, explained 4.55% of the phenotypic variance for resistance to SCN3 and was not involved in digenic epistatic interaction with rhg1 and GmSNAP11. Haplotypes of Map-0047_CAPS (a CAPS marker developed for Map-0047) and InDel1-7 were significantly associated with SCN3 resistance in a panel of 209 resistant and susceptible accessions. Using further allele-combination analysis for three functional markers representing three cloned resistance genes (rhg1, Rhg4, and GmSNAP11) and two markers flanking qSCN3-1, we found that adding the resistance allele of qSCN3-1 greatly increased soybean resistance to SCN, even in diverse genetic backgrounds. The qSCN3-1 locus will be useful for marker-assisted polygene pyramid breeding and should be targeted for the future identification of candidate genes.

Monocular depth estimation is an undirected problem, so constructing a network to predict better image depth information is an important research topic. This paper proposes a mixed-scale Unet network (MAPUnet) with a dense atrous pyramid based on the coder-decoder structure widely used in computer vision. We innovatively introduce the Unet++ structure of the image segmentation network for depth estimation. We reset the number of convolutional layers of the network under the framework of the Unet++ network and innovatively connect the decoders densely. Moreover, by choosing the appropriate size of the atrous radius, we form a dense atrous pyramid based on different feature layers to better connect the features in the deep and shallow layers of the network. To verify the effectiveness of the proposed algorithm, we test the network on the KITTI dataset and the NYU Depth V2 dataset. We compare the network with the current state-of-the-art methods. The proposed method has higher accuracy and has steadily improved relative to the threshold of accuracy and root-mean-square error. We also conduct ablation studies, studies targeting the effectiveness of the network framework, and discussions on the convergence time and parameter complexity of the network. We will open-source the code at https://github.com/yang-yi-fan/MAPUnet.

The wheat multi-pest resistance genes Lr67 and Lr34 are similar in that they both condition resistance to many diseases, in a non-race-specific manner, and code for cellular transporters. Lr34 plays a critical role in breeding wheat for disease resistance in large part because it interacts with other resistance genes to result in effective and durable resistance. To determine if Lr67 interacts with other resistance genes in a similar manner as Lr34 six different doubled haploid populations were developed which segregated for either Lr67 or Lr34 along with a second resistance gene, either Lr13 , Lr16 , or Lr32. The presence or absence of each of these genes in the progeny lines was determined by molecular marker analysis. These six populations were tested for leaf rust field resistance in the same environments to compare the effects of Lr34 and Lr67 alone, and in combination with Lr13 , Lr16 or Lr32. Lr67 and Lr34 significantly reduced the levels of rust severity, Lr34 showed a significant interaction with Lr13 but Lr67 did not. Both genes interacted with Lr16 , and Lr67 had a significant interaction with Lr32. This analysis demonstrates the similar effect of Lr67 , as seen with Lr34 , on the interaction with other resistance genes to give a better level of resistance than with single resistance genes. While Lr67 is not widely deployed in agriculture, it could play an important role in disease resistance in future wheat cultivars. [ABSTRACT FROM AUTHOR]

This work studied the physical-chemical characteristics of two lime-based stucco samples extracted from the “El Cerrito” archeological site in Querétaro, Mexico. Their compositional analyses are consistent with calcite, labradorite (clay mineral), sand size quartz and volcanic lithics, and organic compounds. Scanning Electron Microscopy (SEM) images confirmed the use of micro and submicron natural fibers. Energy Dispersive Spectroscopy semi-quantitative analysis (EDS-SEM) showed Al, Mg, Ca, C, Si, K, and O as the major element components. Inductively Coupled Plasma (ICP) quantitative analysis found Ca, Al, Fe, Mg, and K as the major components, and Ba, P, S, Sr, Mn, Cr, and V, as minor and trace elements that produce a compelling fingerprint. X-ray diffraction patterns reveal that these stuccoes are formed by calcite and labradorite crystalline phases. These analyses were used to develop and reproduce a new stucco formulation that can be used to conserve and restore archeological buildings and as modern wall finishing. The new stucco is a heterogeneous mixture of calcium hydroxide, pozzolan (alunite-kaolinite), fine quartz sand, and volcanic lithics as an aggregate, and soluble and insoluble natural fibers obtained from nopal pads as additives. A step-by-step methodology to prepare and apply the newly formulated stucco in a modern house as a wall finishing is reported. Pozzolan, calcium hydroxide, and water react to produce the pozzolanic effect acting as a non-hydraulic cement, while calcium hydroxide reacts with the atmospheric CO2 to form calcium carbonate. Portlandite conversion to calcite and the pozzolanic effect to obtain labradorite were shown by X-ray analysis and high-resolution SEM images of the newly applied stucco.

The wheat multi-pest resistance genes Lr67 and Lr34 are similar in that they both condition resistance to many diseases, in a non-race-specific manner, and code for cellular transporters. Lr34 plays a critical role in breeding wheat for disease resistance in large part because it interacts with other resistance genes to result in effective and durable resistance. To determine if Lr67 interacts with other resistance genes in a similar manner as Lr34 six different doubled haploid populations were developed which segregated for either Lr67 or Lr34 along with a second resistance gene, either Lr13, Lr16, or Lr32. The presence or absence of each of these genes in the progeny lines was determined by molecular marker analysis. These six populations were tested for leaf rust field resistance in the same environments to compare the effects of Lr34 and Lr67 alone, and in combination with Lr13, Lr16 or Lr32. Lr67 and Lr34 significantly reduced the levels of rust severity, Lr34 showed a significant interaction with Lr13 but Lr67 did not. Both genes interacted with Lr16, and Lr67 had a significant interaction with Lr32. This analysis demonstrates the similar effect of Lr67, as seen with Lr34, on the interaction with other resistance genes to give a better level of resistance than with single resistance genes. While Lr67 is not widely deployed in agriculture, it could play an important role in disease resistance in future wheat cultivars.

Wavefront sensing is one of the key elements of an Adaptive Optics System. As an alternative to the commonlyencountered, commercially available Shack-Hartmann WFS (SH-WFS), the more recent Pyramid-WFS (P-WFS) isproving to be a very attractive technology, thanks to its high-sensitivity and robustness against aliasing. At INO, centerfor applied research in optics and technology transfer in Quebec City, Canada, we have developed a compact andflexible P-WFS prototype that can be integrated into an AO system. This P-WFS prototype includes a fast piezo-electricmodulation mirror and a high-sensitivity EMCCD camera. Our P-WFS was installed on the experimental AO systemdeveloped by Laval University in Quebec for the 1.6-m Mont-Mégantic telescope, which also includes a commercialhigh-speed SH-WFS. The architecture is such that both WFSs can take measurements simultaneously, and either one canbe used to drive the deformable mirror. Here we present the on-sky results obtained with the INO P-WFS module.

Sometime after coming to Mexico City in the early twentieth century, the Concheros gradually became involved in the growing cultural interest in the Aztec past. By the last decades, however, they found themselves in an antagonistic situation with those dancers who called themselves the Mexica who, although they performed the same dances, espoused mexicanidad a strong neo-nationalistic and neo-indianist ideology. The Mexica reject Spanish colonialism and have discarded the clearly Catholic ritual practices of the Concheros who habitually dance outside Churches: the Mexica’s preference is for pyramids. The article, using historical and fieldwork data, examines the growing use of archaeological sites as they have slowly been refurbished, focusing on two: Teotihuacan and Cholula. Importantly, in the last two decades, a gradual rapprochement between the Concheros and the Mexica has occurred as the overall ethos of the dance has been changing once again.

Background: Hirayama disease (HD) is a motor neuron disease and occasionally is associated with lower limb hyper-reflexia. Corticospinal tract dysfunction can be evaluated by diffusion tensor imaging (DTI), but there is paucity of study in HD.Objective: We report corticospinal tract functions using DTI in the patients with HD and correlate with clinical findings.Materials and Methods: The patients with HD diagnosed on the basis of clinical and electromyography findings were included. Their age, duration of illness, side of initial involvement, and progression were noted. Presence of lower limb hyper-reflexia, and cervical spine magnetic resonance imaging (MRI) findings were noted. Cranial MRI was done and DTI findings at internal capsule, cerebral peduncle, pons, and pyramid were noted.Results: In total, 10 patients with HD and 5 matched controls were evaluated. The apparent diffusion coefficient (7.03 ± 0.27 vs 6.83 ± 0.36), fractional anisotropy (0.79 ± 0.04 vs 0.82 ± 0.05), axial diffusivity (5.08 ± 0.08 vs 5.04 ± 0.07), and radial diffusivity (3.79 ± 0.05 vs 3.76 ± 0.05) between HD patients and controls were not different in internal capsule. These values were also not significantly different in cerebral peduncle, pons, and pyramid. These values were also not significantly different between the severe and less severely affected sides. The fractional anisotropy did not correlate with lower limb hyper-reflexia (P = 1.00) and spinal cord atrophy (P = 0.60).Conclusion: DTI study in HD patients did not reveal corticospinal tract involvement in brain. [ABSTRACT FROM AUTHOR]

Although graph convolutional networks (GCNs) have shown their demonstrated ability in skeleton-based action recognition, both the spatial and the temporal connections rely too much on the predefined skeleton graph, which imposes a fixed prior knowledge for the aggregation of high-level semantic information via the graph-based convolution. Some previous GCN-based works introduced dynamic topology (vertex connection relationships) to capture flexible spatial correlations from different actions. Then, the local relationships from both the spatial and temporal domains can be captured by diverse GCNs. This paper introduces a more straightforward and more effective backbone to obtain the spatial-temporal correlation between skeleton joints with a local-global alternation pyramid architecture for skeleton-based action recognition, namely the pyramid spatial-temporal graph transformer (PGT). The PGT consists of four stages with similar architecture but different scales: graph embedding and transformer blocks. We introduce two kinds of transformer blocks in our work: the spatial-temporal transformer block and joint transformer block. In the former, spatial-temporal separated attention (STSA) is proposed to calculate the connection of the global nodes of the graph. Due to the spatial-temporal transformer block, self-attention can be performed on skeleton graphs with long-range temporal and large-scale spatial aggregation. The joint transformer block flattens the tokens in both the spatial and temporal domains to jointly capture the overall spatial-temporal correlations. The PGT is evaluated on three public skeleton datasets: the NTU RGBD 60, NTU RGBD 120 and NW-UCLA datasets. Better or comparable performance with the state of the art (SOTA) shows the effectiveness of our work.

This paper conducts a systematic study on the role of spatial and temporal attention mechanism in the video salient object detection (VSOD) task. We present a two-stage spatial-temporal attention network, named STA-Net, which makes two major contributions. In the first stage, we devise a Multi-Scale-Spatial-Attention (MSSA) module to reduce calculation cost on non-salient regions while exploiting multi-scale saliency information. Such a sliced attention method offers an individual way to efficiently exploit the high-level features of the network with an enlarged receptive field. The second stage is to propose a Pyramid-Saliency-Shift-Aware (PSSA) module, which puts emphasis on the importance of dynamic object information since it offers a valid shift cue to confirm salient object and capture temporal information. Such a temporal detection module is able to encourage precise salient region detection. Exhaustive experiments show that the proposed STA-Net is effective for video salient object detection task, and achieves compelling performance in comparison with state-of-the-art. [ABSTRACT FROM AUTHOR]

The aim of this paper is to forecast the methodology by which Cheops Pyramid as a historic building was built, based on notions of modular patterns discovered within the following planar illustrations, starting at the apex and descending to its grand base.Some of Cheops’ heritage in terms of form and function has existed for millennia, as its mark was recapped with a front line that was constructed thousands of years before. Such a voyage through the missing captures of the building techniques wouldn’t have occurred without the incidental outcome that resulted from overlaying the various pixelated plans of block arrangements on the floor maps of Cheops. This building is believed to exhibit norms similar to those governing the balance between matter and void in the universe.By assessing this historical masonry structure of Giza, we have come to find some regulatory approaches concerning how to asses the construction of such a building by predicting their interiors, spatial definitions, customs, and layouts. As there are no major records of their plans, the best practice anticipated in this paper is to modularize the figurative appearance of such buildings, by imitating themes of the repetitive patterns of past regional Egyptian architecture seen as pixels. This led to the fundamental solution to such a dilemma in building construction.

The subject of our interest is to analyze the significance of Russia-Egypt relations undervVladimir Putin. The main purpose of our studies is to present the most important conditions and dependencies that characterize political, economic and military relations between the two countries.In the beginning, we would like to discuss the history of relations between the abovementioned states, dating back to the times of the USSR. The key issue is the description of diplomatic relations between the two countries under the rule of Gamal Abdel Nasser in Egypt and Anwar Sadat, after which for many years there had been a freeze in mutual relations up to the turn of the 21st century. In the next part of the discussion we present the most important goals and assumptions of political relations between Moscow and Cairo, implemented from the beginning of Putin’s rule in 2000 and by subsequent ruling elites in Egypt. We are mainly talking about Egypt gradually turning away from the United States, Russia’s slow return to the Middle East, the conflicts in Libya, Syria and tensions between the rulers of Egypt and Qatar, which harbors followers of the Muslim Brotherhood persecuted by Cairo. In addition, we examine the importance of economic issues in bilateral relations, focusing on the growing cooperation in the field of energy. We also describe the significance of military aspect and the related maritime doctrine of the Russian Federation, in which Egypt was mentioned as one of the most important partners of Russia in the Middle East.In the summary, we present possible forecasts for the future in mutual relations, at the same time trying to answer the question of how real is the significant weakening of the Egyptian-American relations and Egypt’s turn to Russia in the future.

Sometime after coming to Mexico City in the early twentieth century, the Concheros gradually became involved in the growing cultural interest in the Aztec past. By the last decades, however, they found themselves in an antagonistic situation with those dancers who called themselves the Mexica who, although they performed the same dances, espoused mexicanidad a strong neo-nationalistic and neo-indianist ideology. The Mexica reject Spanish colonialism and have discarded the clearly Catholic ritual practices of the Concheros who habitually dance outside Churches: the Mexica's preference is for pyramids. The article, using historical and fieldwork data, examines the growing use of archaeological sites as they have slowly been refurbished, focusing on two: Teotihuacan and Cholula. Importantly, in the last two decades, a gradual rapprochement between the Concheros and the Mexica has occurred as the overall ethos of the dance has been changing once again. [ABSTRACT FROM AUTHOR]

We investigate two crucial and closely-related aspects of CNNs for optical flow estimation: models and training. First, we design a compact but effective CNN model, called PWC-Net, according to simple and well-established principles: pyramidal processing, warping, and cost volume processing. PWC-Net is 17 times smaller in size, 2 times faster in inference, and 11 percent more accurate on Sintel final than the recent FlowNet2 model. It is the winning entry in the optical flow competition of the robust vision challenge. Next, we experimentally analyze the sources of our performance gains. In particular, we use the same training procedure for PWC-Net to retrain FlowNetC, a sub-network of FlowNet2. The retrained FlowNetC is 56 percent more accurate on Sintel final than the previously trained one and even 5 percent more accurate than the FlowNet2 model. We further improve the training procedure and increase the accuracy of PWC-Net on Sintel by 10 percent and on KITTI 2012 and 2015 by 20 percent. Our newly trained model parameters and training protocols are available on https://github.com/NVlabs/PWC-Net. [ABSTRACT FROM AUTHOR]

The effect of apex and attack angles to the flow around a pyramid obstacle was investigated with flow visualization and laser Doppler velocimetry. The flow visualization was performed by dye injection and electrolytic etching methods. The Reynolds number based on the height of the pyramid is 600. The apex angle, 2α, is in the range of 15 through135 degrees, and the attack angle,γ, is 0 and 45 degrees. It seems like the flow in upstream region of the pyramid is divided into two patterns; two and four vortex systems. The height of the primary vortex of horseshoe vortices takes a maximum value around 2α=90 degree for γ=0 degree, but 2α=45 degree for γ=45 degree. The height for γ=45 degree is lower compared with the result for γ=0 degree. The dependency on 2α and γ of the additional stain rate due to the obstacle can be formulated with the spanwise component of fluid velocity along the obstacle surfaces and the streamwise projected base width. The maximum vorticity, |Ω|maxδ*us /U∞ where U∞ is free stream velocity and δ*us is the displacement thickness near the upstream separation point, of the primary vortex varies depending on the magnitude of the vortex stretching due to the additional strain rate multiplied by time scale that the fluid passes through the obstacle. The vortex system is two vortices for |Ω|maxδ*us /U∞ 1.5.

The paper presents applications developed for teaching descriptive geometry – representation of solids and development of the surface of the solids. The purpose of the applications presented is to enable the development and improvement of the spatial ability of the students such as to understand the methods used in descriptive geometry for constructing and developing the surfaces of the solids.

In this paper, a new method for manufacturing flexible and repeatable sensors made of silicon solar cells is reported. The method involves depositing the noble metal film directly onto the Si template and stripping out the substrate with a pyramid morphology by using an adhesive polymer. In order to evaluate the enhancement ability of the substrate, Rhodamine 6G (R6G) were used as surface-enhanced Raman scattering (SERS) probe molecules, and the results showed a high sensitivity and stability. The limit of detection was down to 10−12 M for R6G. The finite-difference time domain (FDTD) was used to reflect the distribution of the electromagnetic field, and the electric field was greatly enhanced on the surface of the inverted pyramidal substrate, especially in pits. The mechanism of Raman enhancement of two types of pyramidal SERS substrate, before and after stripping of the noble metal film, is discussed. By detecting low concentrations of plasmid DNA, the identification of seven characteristic peaks was successfully realized using a noble metallic pyramidal substrate.

In this paper, we propose a novel multiple pyramids based image inpainting method using local patch statistics and geometric feature-based sparse representation to maintain texture consistency and structure coherence. First, we approximate each patch in the target region (region to be inpainted) by statistically dominant local candidate patches to preserve local consistency. Then each approximated patch is refined by a sparse representation of candidate patches based on local steering kernel (LSK) feature to retain texture quality. We also propose a multiple pyramids based approach to generate several inpainted versions of the input image, one for each of the pyramids. Finally, we combine the inpainted images by gradient-based weighted average to produce the final inpainted image. This approach helps to maintain structure coherence and to remove artifacts which may appear in the inpainted images due to different initial scales of the individual pyramids. The proposed method is tested on a wide range of natural images for scratch and blob/object removal. We have presented both quantitative and qualitative comparison with the existing methods to demonstrate the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Since the 1970s, archaeology has been very rapidly professionalized with the evolution of the French administration and the explosion of preventive archaeology positions. The benefits of this rapid evolution must now take into account the non-professional actors (volunteers, amateurs and citizens) whose diversity has also evolved. Indeed, the distance taken by professionals towards the latter is increasing a little more every day. Yet, for a long time, learned societies and associations have fuelled scientific production. Some have even led to the creation of research centres, sometimes associated with the creation of a museum. These large-scale initiatives from legal entities may also be found in the case of individuals. To very different degrees, many other volunteer archaeologists, sometimes defining themselves as independent researchers, have contributed to knowledge about human beings through an archaeological approach. Some have even become professionals. Through the presentation of the contributions and limitations of the various non-professional research actors (in particular volunteer archaeologists and amateur researchers), we highlight the importance of strengthening the link between professionals and non-professionals for tomorrow's archaeological research in mode³ science 4.0. [ABSTRACT FROM AUTHOR]

Several muon telescopes have been developed in the last years at CEA-Saclay. Benefitting from 15 years of R&D on Micro-Pattern Gaseous Detectors (MPGDs) and from several recent innovations, these telescopes yield unprecedented resolution for real-time instruments, and allow for high-definition muography imaging. As a first application, three of them were deployed around Khufu's Pyramid from 2015 to 2017, showing very good performance and stability in harsh conditions. They also provided the first-ever detection of internal structures of a pyramid from the outside, and participated in the discovery of a large void above the Grand Gallery. [ABSTRACT FROM AUTHOR]

The paper presents applications developed for teaching descriptive geometry -- representation of solids and development of the surface of the solids. The purpose of the applications presented is to enable the development and improvement of the spatial ability of the students such as to understand the methods used in descriptive geometry for constructing and developing the surfaces of the solids. [ABSTRACT FROM AUTHOR]