Types Of Spots Research Articles

Dependence of electron and neutral vapor density distributions on anode mode of high current vacuum arc

The vacuum arc discharge makes transition to a footpoint mode, anode spot type 1 (type 1) mode and anode spot type 2 (type 2) mode under high current conditions. The mode dependence of the electron and metal vapor densities were experimentally quantified using dichroic Shack–Hartmann type laser wavefront sensors. In the type 1 mode, the electron and metal vapor densities were about 2.5 times higher than the footpoint mode. The electron density of the type 2 mode was three times higher than that of the type 1 mode, while significant difference was not found in the metal vapor density. Such higher electron density for the type 2 mode than the type 1 mode was coherent with a previous result obtained by Stark broadening. The present electron and metal vapor density measurement demonstrated that the amount of the electrode erosion was in the following order: footpoint mode < type 1 mode < type 2 mode, which agreed with a previous study.

Multiclass Classification of Paddy Leaf Diseases Using Random Forest Classifier

With increase in population, improving the quality and quantity of food is essential. Paddy is a vital food crop serving numerous people in various continents of the world. The yield of paddy is affected by numerous factors. Early diagnosis of disease is needed to prevent the plants from successive stage of disease. Manual diagnosis by naked eye is the traditional method widely adopted by farmers to identify leaf diseases. However, when the task involves manual disease diagnosis, problems like the hiring of domain experts, time consumption, and inaccurate results will arise. Inconsistent results may lead to improper treatment of plants. To overcome this problem, automatic disease diagnosis is proposed by researchers. This will help the farmers to accurately diagnose the disease swiftly without the need for expert. This manuscript develops model to classify four types of paddy leaf diseases bacterial blight, blast, tungro and brown spot. To begin with, the image is preprocessed by resizing and conversion to RGB Red, Green and Blue (RGB) and Hue, Saturation and Value (HSV) color space. Segmentation is done. Global features namely: hu moments, Haralick and color histogram are extracted and concatenated. Data is split in to training part and testing part in 70:30 ratios. Images are trained using multiple classifiers like Logistic Regression, Random Forest Classifier, Decision Tree Classifier, K-Nearest Neighbor (KNN) Classifier, Linear Discriminant Analysis (LDA),Support Vector Machine (SVM) and Gaussian Naive Bayes. This study reports Random Forest classifier as the best classifier. The Accuracy of the proposed model gained 92.84% after validation and 97.62% after testing using paddy disordered samples. 10 fold cross validation is performed. Performance of classification algorithms is measured using confusion matrix with precision, recall, F1- score and support as parameters.

High-fidelity simulations for Turing pattern formation in multi-dimensional Gray–Scott reaction-diffusion system

In this study, the authors present high-fidelity numerical simulations for capturing the Turing pattern in a multi-dimensional Gray–Scott reaction-diffusion system. For this purpose, an explicit mixed modal discontinuous Galerkin (DG) scheme based on multi-dimensional structured meshes is employed. This numerical scheme deals with high-order derivatives in diffusion, and highly nonlinear functions in reaction terms. Spatial discretization is accomplished using hierarchical basis functions based on scaled Legendre polynomials. A new reaction term treatment is also detailed, showing an intrinsic property of the DG scheme and preventing incorrect solutions due to excessively nonlinear reaction terms. The system is reduced to a set of time-dependent ordinary differential equations, which are solved with an explicit third-order Total Variation Diminishing (TVD) Runge–Kutta method. The Saddle-Node, Hopf, and Turing bifurcations’ boundary conditions are also examined for the system, and subsequently, Turing space is identified. The developed numerical scheme is applied to various multidimensional Gray–Scott systems to assess its ability to capture Turing pattern formation. Several test problems, such as stationary and non-stationary waves, pulse-splitting waves, self-replicating waves, and different types of spots, are chosen from the literature to demonstrate the different Turing patterns.

Study on cathode spot expansion process in vacuum arc with high di/dt

The study on cathode spot under high di/dt condition promotes the application of vacuum circuit breaker in DC transmission and aerospace technology. Cathode spot, as a source of microscopic particles, directly affects the breaking capacity of vacuum circuit breaker. In this paper, vacuum arc with high di/dt was generated in L-C oscillating circuit. The cathode spot behavior was obtained by a high-speed camera. There are two types of cathode spots with different size, different expansion velocity and brightness. The difference in the size of different types of cathode spots leads to the difference in the thermal diffusion velocity of the spots, which is also the main reason for the difference in the expansion velocity of the two types of spots. The influence of spot current density on temperature and electric field is discussed. With the increase of di/dt, the phenomenon of unstable expansion of cathode spots is observed. A new cathode spot is generated in the cold electrode area far away from the previous cathode spot area, resulting in a significant increase in the arc voltage. The expansion characteristics of cathode spot under different current amplitude, frequency and di/dt conditions are obtained.

Diseases and pests of clematis from the collection of the Botanical Garden-Institute of VSUT (Yoshkar-Ola)

Clematis is one of the highly ornamental plants used in landscaping, but they are often susceptible to diseases as a result of abiotic and biotic factors action. The article presents an overview of diseases and pests of clematis. Among them, wilt is especially dangerous, which leads to a sharp withering of plants. Also, clematis can be affected by rust, powdery mildew, gray rot, various types of spotting, etc., as well as pests nematode, worm, aphids, spider mite, slugs, etc. Information on pest control and diseases of clematis is presented. Possible signs of weakening of non-infectious plants are indicated. The diseases identified during the visual examination of clematis in the Botanical Garden-Institute of VSUT (Yoshkar-Ola) are given. The plants grow on the lianas site of the Fruticetum exposition. Wilting was observed in plants older than 20 years: symptoms were detected in 1/3 of plants. Most of the collection plants showed signs of spotting. In some varietal clematis, small-leaved was observed. Damage by leaf-eating insects and mice, as well as mechanical damage from hail and rain were revealed. Agrotechnical measures carried out for the prevention of diseases are presented. The obtained data can be used in the practice of growing clematis at the landscaping facilities of settlements in the region.

Spatiotemporal clusters of Kawasaki disease in South Korea from 2008 to 2017: A municipal-level ecological study.

As the etiology of Kawasaki disease (KD) remains unknown, identifying spatiotemporal clusters with proper stratification of KD could provide further evidence for investigating the triggers of KD. However, spatiotemporal distributions of KD with sex stratification have never been reported. Therefore, we aimed to analyze the spatiotemporal patterns of KD by sex in South Korea. We extracted epidemiologic week (Epiweek)-based KD cases in patients <5 years of age (ICD-10-CM code: M303) from 2008 to 2017 national health insurance service data at the 250 municipal level. To determine whether spatial autocorrelation and persistent municipal-level clusters exist, year- and sex-stratified global Moran's I statistics, Getis-Ord Gi* statistics, and emerging hotspot analysis on KD incidence were conducted. A total of 72,510 KD cases were reported between 2008 and 2017 (male-to-female ratio = 1.40:1). Incidence has increased since 2008, with the highest incidence in 2016 (396.8 per 100,000 population). KD had seasonality of winter and summer but different by sex. Positive spatial autocorrelation was consistently reported in every stratum, with the 2011-2014 period having the strongest index value (total sex I = 0.286, p < 0.001; male I = 0.242, p < 0.001; female I = 0.213, p < 0.001). Hot spots were consistently detected in the northern parts, and cold spots were in the southern part for 9 years in both sexes. The emerging hot spot analysis showed new, consecutive, and sporadic hot spots on the northwestern and eastern coasts and new and sporadic cold spots in the southwestern part. However, the distribution and proportion of hot or cold spot types differed according to sex. The spatiotemporal features of KD had limits to concluding that only infectious triggers result in KD occurrence. Therefore, our findings support the notion that KD is a syndrome with multiple factors, including infectious, genetic, and environmental factors, that are associated with sex differences.

AGM and Jellyfish Swarms of Elliptic Curves

The classical produces wonderful infinite sequences of arithmetic and geometric means with common limit. For finite fields with we introduce a finite field analogue that spawns directed finite graphs instead of infinite sequences. The compilation of these graphs reminds one of a jellyfish swarm, as the 3D renderings of the connected components resemble jellyfish (i.e., tentacles connected to a bell head). These swarms turn out to be more than the stuff of child’s play; they are taxonomical devices in number theory. Each jellyfish is an isogeny graph of elliptic curves with isomorphic groups of -points, which can be used to prove that each swarm has at least jellyfish. This interpretation also gives a description of the class numbers of Gauss, Hurwitz, and Kronecker which is akin to counting types of spots on jellyfish.

Applying OHSA to Detect Road Accident Blackspots

With increasing numbers of crashes and injuries, understanding traffic accident spatial patterns and identifying blackspots is critical to improve overall road safety. This study aims at detecting blackspots using optimized hot spot analysis (OHSA). Traffic accidents were classified by their participants and severity to explore the relationship between blackspots and different types of accidents. Based on the outputs of incremental spatial autocorrelation, OHSA was then implemented on different types of accidents. Finally, the performance of OHSA in evaluating the road safety level of the proposed RBT index are examined using a binary correlation analysis (i.e., R2 = 0.89). The results show that: (1) The optimal scale distance varies from 0.6 km to 2.8 km and is influenced by the distance of the travel mode. (2) Central cities, with 54.6% of the total accidents, experiences more rigorous challenges regarding traffic safety than satellite cities. (3) There are many types of black spots in vulnerable communities, but in some specific areas, there are only black spots of non-motor vehicle accidents. Considering the practical significance of the above results, policy makers and traffic engineers are expected to give higher attention to central cities and vulnerable communities or prioritize the implementation of relevant optimization measures.

Proposal of facial pigmentary unit and facial hyperpigmentation type for Fitzpatrick skin types II-IV.

Studies on facial hyperpigmentation across different facial units are limiting. We aimed to analyze melanin pigmentation images to observe facial pigmentary demarcation lines (FPDLs) and suggest facial hyperpigmentation types for normal individuals. 3D facial melanin pigmentation images of 173 volunteers were obtained and analyzed for the presence of FPDLs. Pigmentation severity was assessed for each of the thirteen facial pigment units. The images were then grouped according to a pattern of hyperpigmentation to suggest three facial hyperpigmentation types-dark spot, photoaging and post-inflammatory hyperpigmentation. Four groups of FPDLs including a novel group I were observed. Nasal, frontal, auricular were the darkest pigmented facial pigment unit, and the anterior neck was the least pigmented. The dark spot type was the most common facial hyperpigmentation type. The photoaging type and the PIH type showed age-dependent distribution, as the photoaging type was more common among the subjects over 40s, and the PIH type was more common in younger subjects. Facial hyperpigmentation among healthy individuals with Fitzpatrick skin types II-IV is often accompanied by FPDLs and categorized into three types. Each type is modeled after the pattern of pigmentation associated with certain dermatological disorders. The practical implications of facial hyperpigmentation types can be resourceful in various fields including prevention and treatment of pigmentary disorders.

Early warning of Diaporthe infection in kiwifruit soft rot by plasmonic dimer-enhanced Raman spectroscopy.

Diaporthe genus is the dominant pathogens of kiwifruit soft rot with long incubation period and rapid onset and very hard to detect in advance. It is of great significance to develop point-of-care tests for disease prevention and field management. Here we screen a pair of genus-level primers for constructing plasmonic dimer Rayleigh/Raman spectroscopy, which enables rapid, specific, and sensitive detection of Diaporthe genus in real kiwifruits. Dark-filed Rayleigh scattering clearly visualizes the target-induced dimer assembly of nanoprobes. Plasmonic dimer-enhanced Raman spectroscopy has high specificity for 12 common isolates of Diaporthe genus in one batch samples with highly accurate results and much higher sensitivity than polymerase chain reaction (PCR). It realizes the recognition of Diaporthe infection at an early stage of 24h when the kiwifruits do not have any noticeable symptoms. It demonstrates a bright prospect of point-of-care tests for early warning of kiwifruit soft rot infection and quality control.

Uncommonly known change characteristics of land use pattern in Guangdong Province–Hong Kong–Macao, China: Space time pattern, terrain gradient effects and policy implication

Previous studies on land use have largely focused on characteristics of quota allocation and spatial distribution based on time series analysis. However, indwelling patterns, combined space–time characteristics and terrain gradient effects are often hidden from the regional territorial spatial planning process. By using spatial econometric techniques, including hot spot analysis, landscape theory, a space–time cube model and a terrain–niche index, this paper aimed to assist regional planning by revealing these hidden characteristics in Guangdong Province, China. The results were as follows: urban construction land had formed an agglomerated region at the center of the study area, surrounded by many smaller satellite cities, which resembled a mainland–island metapopulation pattern. Three hot spot types—oscillating (32.45 % of the region), sporadic (1.85 %) and persistent (6.83 %)—formed the main space–time pattern throughout the study period. The main patterns included persistent hot spots in the Pearl River Delta, approximating a strip pattern of sporadic and oscillating hot spots from the east to west, with persistent cold spots in the north. Dry land cropping showed an increase in area at terrain levels 3–6 while in other terrains the area of dry land cropping decreased over time. These findings indicate that more attention needs to be paid to maintaining or adjusting the shape and equilibrium between the mainland and the island cities in the future. Steeper terrain is normally considered for cropland when conflicts exist for land use, which might decrease cropland quality to some extent. Hence, current territorial and spatial planning should focus on changing spatial disequilibrium and the reduction in cropland quality, which might result from the land policy of “superior occupation and inferior compensation”, to slow regional differences and to achieve sustainable development.

Blind spots in medical education: how can we envision new possibilities?

As human beings, we all have blind spots. Most obvious are our visual blind spots, such as where the optic nerve meets the retina and our inability to see behind us. It can be more difficult to acknowledge our other types of blind spots, like unexamined beliefs, assumptions, or biases. While each individual has blind spots, groups can share blind spots that limit change and innovation or even systematically disadvantage certain other groups. In this article, we provide adefinition of blind spots in medical education, and offer examples, including unfamiliarity with the evidence and theory informing medical education, lack of evidence supporting well-accepted and influential practices, significant absences in our scholarly literature, and the failure to engage patients in curriculum development and reform. We argue that actively helping each other see blind spots may allow us to avoid pitfalls and take advantage of new opportunities for advancing medical education scholarship and practice. When we expand our collective field of vision, we can also envision more "adjacent possibilities," future states near enough to be considered but not so distant as to be unimaginable. For medical education to attend to its blind spots, there needs to be increased participation among all stakeholders and acommitment to acknowledging blind spots even when that may cause discomfort. Ultimately, the better we can see blind spots and imagine new possibilities, the more we will be able to adapt, innovate, and reform medical education to prepare and sustain aphysician workforce that serves society's needs.

Points of persuasion: Truth spots in future city development

Geographers and historians have contributed to a well-established literature on how places become repositories of inherited meanings and contested memories. Much less attention has been afforded to space and place as future-making resources. In this article, we consider how extant places feature in the imagination, planning and development of ex novo cities. Focusing on three new administrative capitals in Southeast Asia – Putrajaya (in Malaysia), Naypyidaw (in Myanmar) and Nusantara (in Indonesia) – we show how places have been mobilized as points of persuasion, or what sociologist Thomas Gieryn has termed “truth spots”. Drawing and building upon Gieryn’s work, we identify three heuristic types of truth spots: aspirational truth spots that demonstrate progressive developmental possibilities for emulation; antithetical truth spots signaling past failures to avoid in planning and developing the future city; and anticipatory truth spots that articulate future expectations, justifying forms of (in)action in the present. While existing work on truth spots emphasizes powers of persuasion associated with physical, in-person experiences of place, our emphasis and contribution centres on the narrative mobilization of place references.

Sustainability reporting nexus to corporate governance in scholarly literature

Sustainability reporting has become a practice of the majority and is decided by boards of directors as the supreme governing body in the decision-making process of companies. The paper provides a high-view picture and visualizes research to portray the historical shifts in sustainability reporting nexus to corporate governance through an analysis utilizing CiteSpace software on 935 articles published in Web of Science Core Collection from 2009 to 2021.The number of papers in the area has expanded, especially since 2013 (a branching point), while the study determines a type of bifurcation spot (the year 2017) that evinces the SR-CG field maturity. The study determined the dominant countries through affiliated to them researchers (the United Kingdom, Spain, Italy, China and Australia), the most esteemed journals (Journal of Business Ethics, Business Strategy and the Environment and Accounting, Auditing &amp;amp;amp; Accountability Journal), and the major co-occurrence of hot keywords (carbon disclosure project, environmental disclosure quality, integrated reporting, financial performance, foreign director, environmental reporting, public sector, sustainability assurance statement). The paper identifies principal issues where SR-CG research lags (dearth of those research in developing economies and geographical limitation of research) and unravels uncharted so far domains (jurisdictions-related studies) in the realm. Future research in the realm is likely to focus on ESG, disclosures and governance performance, as well as on specific areas (geography, industry, etc.), and will explore in depth the role of multiple factors together. This papers indicate the growing convergence between SR and CG in literature, and given predominance of ‘SR as a function of CG’ approach a more stalwart and sound CG framework could bring about more tenable SR practices. The paper puts forward an agenda for advancing forthcoming research in the realm of SR-CG interdependence. AcknowledgmentThis paper is co-funded by European Union through the European Education and Culture Executive Agency (EACEA) within the project “EU BEST PRACTICE OF LIFE CYCLE ASSESSMENT, SOCIAL, ENVIRONMENTAL ACCOUNTING AND SUSTAINABILITY REPORTING” 101047667 — EULASTING — ERASMUS-JMO-2021-HEI-TCH-RSCH https://bit.ly/3Bbvquw

Appearance quality classification method of Huangguan pear under complex background based on instance segmentation and semantic segmentation.

The 'Huangguan' pear disease spot detection and grading is the key to fruit processing automation. Due to the variety of individual shapes and disease spot types of 'Huangguan' pear. The traditional computer vision technology and pattern recognition methods have some limitations in the detection of 'Huangguan' pear diseases. In recent years, with the development of deep learning technology and convolutional neural network provides a new solution for the fast and accurate detection of 'Huangguan' pear diseases. To achieve automatic grading of 'Huangguan' pear appearance quality in a complex context, this study proposes an integrated framework combining instance segmentation, semantic segmentation and grading models. In the first stage, Mask R-CNN and Mask R-CNN with the introduction of the preprocessing module are used to segment 'Huangguan' pears from complex backgrounds. In the second stage, DeepLabV3+, UNet and PSPNet are used to segment the 'Huangguan' pear spots to get the spots, and the ratio of the spot pixel area to the 'Huangguan' pear pixel area is calculated and classified into three grades. In the third stage, the grades of 'Huangguan' pear are obtained using ResNet50, VGG16 and MobileNetV3. The experimental results show that the model proposed in this paper can segment the 'Huangguan' pear and disease spots in complex background in steps, and complete the grading of 'Huangguan' pear fruit disease severity. According to the experimental results. The Mask R-CNN that introduced the CLAHE preprocessing module in the first-stage instance segmentation model is the most accurate. The resulting pixel accuracy (PA) is 97.38% and the Dice coefficient is 68.08%. DeepLabV3+ is the most accurate in the second-stage semantic segmentation model. The pixel accuracy is 94.03% and the Dice coefficient is 67.25%. ResNet50 is the most accurate among the third-stage classification models. The average precision (AP) was 97.41% and the F1 (harmonic average assessment) was 95.43%.In short, it not only provides a new framework for the detection and identification of 'Huangguan' pear fruit diseases in complex backgrounds, but also lays a theoretical foundation for the assessment and grading of 'Huangguan' pear diseases.

Study of the impact of the power dimming and lighting modes of LED lamps on the near magnetic field

The LED represents the hot topic has many traditional lighting systems because of their high energy efficiency and lifetime. Nevertheless, if the emissions of harmonic currents are relatively present in the literature because presenting problems on the grid, the measurements of emissions radiated by LED lamps have rarely been carried out. This work studies the magnetic field above LED Lamp Spot Type with different probes, for the three directions (HX, HY, HZ), in the frequency domain (FD) using a spectrum analyzer by the technique of near-field scan (NFS). The scan step is 0.5 cm, the LED lamps are powered directly by the electrical network 220 V/ 50 Hz, then quantify the magnetic field above the center of the inductor depending on the variation of the mode of lighting for each lamp. We used two lamps of power P = 6 W and P = 12 W, the lighting modes for each lamp are: mode 1 (white), mode 2 (colored), mode 3 (white + colored), to understand the impact of variation power and mode of lighting on the magnetic field.

Investigation on anode modes of vacuum arc under different contact opening speeds

This paper aims to investigate the anode modes of vacuum arc at different opening speeds, especially at a high opening speed that exceeds 3 m/s. The butt contacts made of CuCr30 and CuCr50 with a diameter of 15 mm are used. Experiments are conducted at the current of 3.3, 4.4, 5.5, and 6.3 kA with a frequency of 50 Hz. An electromagnetic repulsion actuator provides the average opening speed from 1.7 to 3 m/s. The experimental results show that the number of droplets splashing into electrodes increases as the arc current increases, while a higher opening speed decreases the droplets. A higher opening speed will reduce the transferred charge before the anode spot type 2, and a higher Cr content increases the transferred charge before the anode spot type 2. Increasing opening speed will decrease the starting time of anode spot type 2, but it increases the gap distance when anode spot type 2 appears. Meanwhile, the increase in Cr content delays the formation of anode spot type 2.

Evaluation of the spatial distribution of scenic resources based on 3S technology: A case study of the Yesanpo National Park.

Evaluation of scenic resources is imperative in national park planning, and 3S technology has been applied for this purpose because it effectively leverages modern geo-informatics technology. We investigated the scenic resources in the Yesanpo National Park based on 3S technology. The Nearest-Neighbor Index, Kernel density estimation, imbalance index, and geographical concentration index in modern geography were introduced into the spatial distribution evaluation of scenic resources, and here, for the first time, the spatial combination index of scenic resources was proposed as one of the quantitative analysis indices of spatial distribution of scenic resources. Moreover, the spatial combination distribution characteristics of scenic resources were analyzed quantitatively and graphically. The characteristics of the spatial distribution of scenic resources in the Yesanpo National Park were as follows: The spatial distribution type of scenic spots in the Yesanpo National Park is a clustered type. The spatial distribution of the scenic resource groups in the Yesanpo National Park was extremely imbalanced and highly concentrated. Based on the identification of scenic resources, we evaluated the scenic resources of each area and propose sustainable development plans for each area. This evaluation method can be applied to similar national parks to promote the quantitative and graphical evaluation of the spatial distribution of scenic resources and provide support for the decision-making processes related to national park planning and management.

Spatial Distribution and Accessibility of High Level Scenic Spots in Inner Mongolia

Based on the data of high-level scenic spots in Inner Mongolia, the methods of the nearest neighbor index, kernel density, accessibility, and spatial autocorrelation are used to systematically sort out the spatial distribution pattern, accessibility, and influencing factors of various types of scenic spots. The following conclusions are drawn from the analysis. The spatial distribution of different types of tourist attractions in Inner Mongolia is in a state of “small agglomeration and large dispersion”. The spatial accessibility of different types of tourist attractions in Inner Mongolia is generally poor, and the temporal accessibility presents an inverted U-shaped distribution over time. The county-level accessibility of different types of scenic spots in Inner Mongolia is relatively poor, basically showing an oblique distribution pattern of low in the west and high in the east. The influencing factors of the spatial distribution pattern and accessibility of various scenic spots in Inner Mongolia mainly include the natural environment, transportation network, resource endowment, and economic level. This study proposes an optimal path for accessibility according to the aspects of the design of tourism scenic areas in a circle and the construction of tourist traffic and facilities, as well as the linkage design of tourist routes.

Integrated Reservoir Model and Differential Stimulation Modes of Low Permeability Porous Carbonate Reservoir: A Case Study of S Reservoir in X Oilfield in Iraq

The S reservoir in the X Oilfield in Iraq has great development potential due to its rich geological reserves. However, the low permeability and strong heterogeneity of the reservoir lead to great differences in reservoir stimulation performance. In this study, an integrated reservoir model and differential stimulation mode are put forward to solve the above problems. First, the feasibility of fracturing is evaluated by laboratory experiments. Second, an integrated reservoir model is established, which mainly includes a rock mechanics model, fracturing simulation model, and numerical simulation model, and correct the integrated model by fracturing operation curves and production dynamic curves. Third, three types of stimulation areas are classified according to the combination of sweet spot types, and three different stimulation modes are proposed. In conclusion, a small-scale stimulation mode should be applied in the Type I area to maximize economic benefits. In the Type II area, the medium-scale stimulation mode should be performed to ensure certain productivity while achieving certain economic benefits. In the Type III area, the large-scale stimulation mode should be employed to obtain certain productivity while economic benefits must be above a limit. The differential stimulation model proposed in this paper has made a great reference for the efficient development of low-permeability carbonate rocks.