Classification Of Units Research Articles

Prospective study on the analysis of intestinal microflora changes and prediction on metabolic function in severe burn patients at early stage by 16S ribosomal RNA high-throughput sequencing

Objective: To analyze the changes of intestinal microflora and to predict the metabolic function of intestinal microflora in severe burn patients at early stage by 16S ribosomal RNA (rRNA) high-throughput sequencing. Methods: In this prospective observational study, 48 patients with severe burns who met the inclusion criteria were admitted to Department of Burns and Plastic Surgery of Affiliated Hospital of Jiangsu University from January 2018 to December 2019 were included in burn group, and 40 healthy volunteers who met the inclusion criteria and underwent physical examination at the Physical Examination Center of Affiliated Hospital of Jiangsu University in the same period were included in healthy group. Fecal samples were collected from patients in burn group in about 1 week after admission and from volunteers in healthy group on the day of physical examination. The 16S rRNA V4 gene sequencing was performed in the feces of patients in burn group and volunteers in healthy group to analyze the relative abundance of various bacteria. The operational classification unit (OTU) was divided by Mothur software to analyze the dominant bacteria. The OTU number, Chao1 index, Ace index, and Shannon index of fecal microflora were analyzed by QIIME1.9.0 software. The principal component analysis for relative abundance of fecal microflora was performed by Canoco Software 5.0. The metabolic function of fecal microflora was predicted by Kyoto Encyclopedia of Genes and Genomes. Data were statistically analyzed with independent sample t test, and Mann-Whitney U test, and Bonferroni correction. Results: The relative abundance of Bacteroides, Enterococcus, Acinetobacter, Macrococcus, and Staphylococcus in feces of patients in burn group was significantly higher than that of volunteers in healthy group (Z=-5.20, -2.37, -5.17, -4.41, -6.03, P<0.05 or P<0.01), and the relative abundance of unclassified-Helicobacillae, Prevotella, Cecobacteria, unclassified-Rumencocci, Pseudobutyrivibrio, Brautia, and unclassified-Digiestive Streptococcaceae (Z=-8.03, -3.21, -7.63, -5.88, -8.05, -8.05, -6.77, P<0.01) and other 12 species of bacteria in the feces of volunteers in healthy group was significantly higher than that of patients in burn group. The diversity of fecal microflora of volunteers in healthy group was better than that of patients in burn group, the main dominant microflora of volunteers in healthy group were Bacteroides, unclassified-Helicobacillae, Prevotella, unclassified- Enterobacteriaceae, Brautia, Parabacteroides, Escherichia coli, etc., and the main dominant microflora of patients in burn group were Bacteroides, Prevotella, unclassified-Enterobacteriaceae, and Parabacteroides. The OTU number, Ace index, Chao1 index, and Shannon index of fecal microflora of patients in burn group were 149±47, 199±45, 190±45, 2.0±0.9, which were significantly lower than 266±57, 323±51, 318±51, 3.8±0.5 of volunteers in healthy group (t=10.325, 11.972, 12.224, 11.662, P<0.01). The relative abundance of fecal microflora of patients in burn group and volunteers in healthy group was clearly divided into two groups by principal component 1, and the contribution rate of principal component 1 was 32.50%, P<0.01. The fecal microflora of volunteers in healthy group were more concentrated on principal component 2, the fecal microflora of patients in burn group were dispersed in principal component 2, and the contribution rate of principal component 2 was 13.44%, P>0.05. The metabolic levels of alanine-aspartate-glutamate, arginine- proline, cysteine-methionine, glycine-serine-threonine, phenylalanine, tryptophan, and tyrosine in amino acid, tricarboxylic acid cycle, glucose and mannose, galactolipin, glycolysis/gluconiogenesis, starch and sucrose in carbohydrate of fecal microflora of patients in burn group were significantly lower than those of volunteers in healthy group (Z=-4.75, -4.54, -4.75, -4.62, -3.71, -3.28, -4.19, -3.82, -4.72, -4.35, -4.75, -4.71, P<0.01). The levels of lipoic acid metabolism and coenzyme Q synthesis of fecal microflora of patients in burn group were significantly higher than those of volunteers in healthy group (Z=-6.07, -4.51, P<0.01). The metabolic level of arachidonic acid of fecal microflora of patients in burn group was similar to that of volunteers in healthy group (P>0.05). Conclusions: There are significant differences in intestinal microflora between severe burn patients at the early stage and healthy people, and the species and diversity of microflora are decreased, and the nutrient metabolism level is decreased in burn patients by 16S rRNA high-throughput sequencing.

Типификация и коррекция синтаксонов лесной растительности Западного Кавказа

The article presents the typification and correction of mountain forests’ syntaxa established by one of the authors for the Western Caucasus. Unvalid classification units are validated according to the International Code of the Phytosociological Nomenclature (Theurillat et al., 2021): 2 associations of mesophytic deciduous forests of the order Lathyro–Carpinetalia and 3 associations of fir-beech forests of the order Rhododendro pontici–Fagetalia orientalis of the Carpino–Fagetea class, as well as 2 associations of oak pubescent forests and juniper woodland communities of the class Quercetea pubescentis. The main reasons of the invalidity of original publications are the absence of a nomenclature type or the ineffectiveness of the publication.

Восстановительные сукцессии повреждений почвенного покрова при проведении рубок ухода в ельнике черничном северной тайги

Damage to the top soil layers during logging operations can be of various forms (compaction, mixing, pressing, etc.) and of a long-term character. The recovery of the morphological characters and the structure of the soil profile of the native soil can take decades or have irreversible effect. We have studied the soil damage during two-stage (1973 and 2002) conversion thinning operations in the spruce forest with blueberry cover in the northern taiga (tree-length log skidding, TDT-55 tractor). The types of damage that stay during the progressive succession for 50 years and have signs of disturbances due to the logging operations were identified. The mosaic structure of the mixed bedrocks still continues to exist. The forest litter pressed by the heavy machines is replaced by the newly formed one. And at the same time, the organic bedrock of the medium degree of decomposition, which is untypical for the native podzolic soil, is preserved. Mixing by tractor tracks and the formation of mixed bedrock is the most common disturbance of the upper bedrock during logging operations due to insufficient coverage of the skid roads by felling residues. The amount of such damage to the soil is 77 % and 79 % in the skid roads of 1973 and 2002, respectively. But the depth of damage is small, which is 10 cm on average, with fluctuations up to 22 cm. In nano- and micro-depressions, the processes of peat formation and gleying develop. The number of locations with the genesis of bog soils is gradually increasing. On the skid roads of 1973 the proportion of wetlands is 2,5 times higher than in the skid roads of 2002 (86,9 % and 37,3 %, respectively). The long-term soil disturbance in the structure of the soil profile makes it necessary to develop classification approaches to improve the analysis of anthropogenic disturbed soils in cutting areas. The classification units are suggested

Russian Approaches to the Forest Type Classification

The results of researches characterizing the geographical distribution of forest-ecological, phytocoenotic, and genetic classifications of forest types in the Russian Federation nowadays are presented in the thesis. A comparative analysis was carried out for the following items: the inclusive concept of a classification unit (a type of habitat conditions; a type of forest); features of distinguishing the border of the classification units; classification features used to determine the type of habitat conditions; features of the classification of phytocoenoses used to determine the forest type; the degree to which the successional dynamics of forest stands are taken into consideration; the degree to which the influence of anthropogenic factors are taken into consideration; the level of implementation in forest management and forestry practice; regions of implementation. In the process of development of forest typologies, the concept of a forest type changed from understanding it as a forest area homogeneous by composition, structure, and appearance (homogeneity in space) in natural classifications to the concepts of a forest type, in which priority is given to homogeneity in origin (genesis), as well as developmental processes and dynamics (homogeneity in time) in genetic and dynamic typologies. Currently, there is the following forest type classification in the Russian Federation: forest-ecological, phytocoenotic, genetic, and dynamic. When classifying forest areas within the forest-ecological direction provided by E.V. Alekseev – P.S. Pogrebnyak, the priority is given to the characteristics of the habitat conditions. Within the phytocoenotic direction provided by V.N. Sukachev, the priority is given to the phytocoenosis characteristics. Within the genetic approach provided by B.A. Ivashkevich – B.P. Kolesnikov, a forest type is considered as a series of alternating phases – types of phytocoenosis within the same type of habitat conditions. In this case, phytocoenotic classifications can be a part of the genetic classifications for the climax forest phytocoenosis. And the dynamic approach provided by I.S. Melekhov is very close to the genetic one and is a superstructure over the classical phytocoenotic forest typology provided by V.N. Sukachev. The current use of forest typological classifications by forest inventory management enterprises in the Russian Federation was studied. A map of the geographical distribution of forest typologies of the above-listed directions of forest typology researches was created. Forest-ecological classifications are used mainly in the southern regions of the European part of Russia and the North Caucasus. Forest typologies created based on a genetic approach to the forest type classification are used in Western Siberia, in the south of the Far East and Eastern Siberia, and in some regions of the Urals. Phytocoenotic classifications of forest types are used in other regions of the Russian Federation.

Health service use and costs among migrants in an irregular situation: Cross-sectional register-based study from a voluntary-based clinic.

As few data based on actual demand for healthcare services in vulnerable migrant populations exist, we studied service use and healthcare costs in a cohort of migrants in an irregular situation. In this single-centre retrospective register study, we examined the reasons for encounter, diagnoses, service use and costs of healthcare among patients at a voluntary clinic for migrants in an irregular situation in Helsinki, Finland. ICPC-2 classification and national unit costs for primary healthcare were used for the cost estimation. A total of 546 patient visits accounted for 620 ICPC-2 coded reasons for encounter, diagnoses and process codes. The most common health problems were teeth/gum disease (10%), acute upper respiratory infection (5%) and oesophageal disease (3%). Visits seldom led to complementary investigations (2%), follow-up visits (5%) or referrals (11%). The total cost of treatment, excluding dental health costs, was 71 euros per visit. Migrants in an irregular situation present with a variety of health concerns, the majority of which can be treated in a basic primary healthcare facility at a relatively low cost. This encourages research to evaluate the health and cost effects of extending public healthcare for migrants in an irregular situation beyond emergency care.

Индекс на локализация на земеделските стопанство в периода 2008-2016 г. в селските райони на Южен централен район

The rural development policy in Bulgaria is dictated by the accompanying facts, with approximately 45% of the population living in them, covering 85% of the territory. The study and analysis of the socio-economic processes in agriculture of smaller administrative units of the NUTS classification gives an accurate picture of the real situation. The operation of farms ensures the production of different types of agricultural production. Contributing to the formation of Gross Domestic Product and the fulfillment of commitments in relation to the EU Common Agricultural Policy. The application of the localization index for agricultural holdings in the rural areas of the South-Central Region in Bulgaria reveals their real economic status. The study of the specialization factor for agricultural holdings covers an eight-year period 2008-2016. The localization index is the basis for an analysis of the different types of economic processes and phenomena. It is also applicable in smaller administrative areas, namely in the rural municipalities of the South-Central Region.

Local soil classification [soil association/soil slope–soil series], world reference base, and USDA soil taxonomy: roles in soil survey execution

The objective was to do a comparative assessment of the best roles of three classification systems, [the “USDA-Soil Taxonomy”; the “World Reference Base (WRB)”; and the presumably Soil Association/Soil Series Concept of Nigeria] in Soil Survey execution from Soil Mapping through to Soil Survey Report. In this instance the concern of this paper is mostly what is best applicable when mapping legend is being defined during field research and/or field activities for mapping and publication purposes. The soils used are derived from basement complex rocks (Ilero at 08.05N/03.22E) and the coastal sediments (Igbodu at 6.28’13’’N/4.19’30” E) in the sub-humid and humid parts of southwest Nigeria respectively. The soils pattern reflects the topo-sequence and/or litho-sequence concepts with a typical sequence of soils on the crest, shoulder and/or upper slope, middle slope, lower slope, fringe and/or valley bottom positions. At the mapping phase, the WRB nearly corroborates the intrinsic qualities of the Soil Association-Soil Series concept. This comparison is fully developed when the characteristics of the different classification units are compared to the morphological expression as shown in the Soil Association-Soil Series concept. However, it should be noted that the philosophy behind these two systems only slightly overlap as classification systems adaptable for soil mapping purposes [field and post field] at the level of soil management requirements – large scale ; while USDA Soil Taxonomy is best at small scale and for better understanding of soil genesis of the mapping units.

Intra-annual land cover mapping and dynamics analysis with dense satellite image time series: a spatiotemporal cube based spatiotemporal contextual method

ABSTRACT Land covers provide essential information for understanding and detecting ecosystem, resources, and environmental dynamics. However, they are generally mapped at coarser temporal scales to study the inter-annual changes, while scant attention has been paid to map intra-annual land cover dynamics at finer temporal scales. Moreover, existing studies are still limited in intra-annual land cover mapping with dense satellite image time series (SITS). Accordingly, this study proposed a novel approach to accurately classify dense SITS for mapping intra-annual land cover dynamics. First, dense SITS is segmented at multiple spatiotemporal scales to generate optimal spatiotemporal cubes (ST-cubes), which are chosen as classification units. Second, the ST-cubes based on spectral, textural, spatial, and temporal features are integratively defined and employed in SITS classification. Third, the spatiotemporal context is modeled by a spatiotemporally extended conditional random field model that measures both spatiotemporal features and semantic correlation between geographic objects. Finally, the proposed method is applied to map the intra-annual land cover dynamics. Comparative experiments of SITS classification are carried out between our method and three existing competitors in a suburban area in Beijing, China, with a dense Sentinel-2 SITS. Moreover, based on the classification results, we analyzed the quantitative intra-annual dynamics of land cover. The result shows that our approach achieves significant improvements in classification accuracy over existing methods, indicating the effectiveness and superiority of the proposed method in mapping intra-annual land cover dynamics with dense SITS.

DNA Barcoding for Identification and Detection of Species

Identification is a very important part of the taxonomy. Since a species represents the basic unit of biological classification, identifying species is important to understand the systematics and the precise phylogenetic position of particular species. In recent years, species identification and delimitation have seen major improvements because of the incorporation of DNA sequence data. This review provides a comprehensive list of commonly employed nuclear and chloroplast regions used for the barcoding of plants.

Streptomyces luteolifulvus sp. nov., a novel actinomycete isolated from soil in Nanjing, China.

During the investigation of exploring potential sources of novel species and natural bioactives, a novel actinomycete, designated strain HIT-DPA4T, was isolated from a soil sample, which was collected from Nanjing, Jiangsu Province, PR China and characterized using a polyphasic approach. On the basis of 16S rRNA gene sequence similarities and the result of phylogenetic analysis, strain HIT-DPA4T was most closely related to Streptomyces cyaneus CGMCC 4.1671T, and shared the highest sequence similarity of 98.76%. In addition, the cell walls of the species HIT-DPA4T contained LL-diaminopimelic acid as the diagnostic diamino acid and the whole-cell hydrolysates were identified as glucose and ribose, and the principal phospholipids were found to be diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylinositol mannoside and phosphatidylmonomethylethanolamine. MK-9(H6) and MK-9(H4) were predominant menaquinones; and C16:0, anteiso-C15:0 and C15:0 as major cellular fatty acids of the organism HIT-DPA4T. Gene Ontology database analysis and antiSMASH server predicted results displayed that strain HIT-DPA4T was a promising classification units, which has various types of functions and contains multiple biosynthetic gene clusters with the similarity more than 80%. Multilocus sequence analysis (MLSA) of five housekeeping genes (atpD, gyrB, recA, rpoB and trpB) illustrated that Streptomyces luteolifulvus formed a separate branch in the genus Streptomyces. However, a combination of low level of DNA-DNA relatedness and physiological properties indicated that strain HIT-DPA4T can be distinguished from its phylogenetically related species Streptomyces cyaneus CGMCC 4.1671T. Moreover, gene synteny research could be further differed organism HIT-DPA4T from similarity species. Therefore, the strain is concluded to represent a novel species of the genus Streptomyces, for which the name Streptomyces luteolifulvus sp. nov. is proposed. The type strain is HIT-DPA4T (= CGMCC 4.7558T = TISTR 2751T).

Типификация и коррекция синтаксонов луговой растительности класса Molinio–Arrhenatheretea Tx. 1937 Южного Нечерноземья России

The article presents the typification and correction of the syntaxa of grass vegetation, established at different times for the Southern Nechernozemye of Russia. 3 associations and 5 subassociations are validated according to the requirements of the International Code of Phytosociological Nomenclature (Theurillat et al., 2021). The description of syntaxa is given according to the plan: name, synonyms, nomenclature type (holotype or lectotype), diagnostic species (their single blocks were used without dividing into characteristic, differential and constant), definition (verbal diagnosis). The belonging of associations and subassociations to the highest classification units is indicated in accordance with the modern hierarchical system of floristic classification of vegetation in Europe (Mucina et al., 2016). All of these units belong to the group of Intrazonal boreo-temperate grasslands and heath.

The safety and efficacy of modifying the admission protocol to the epilepsy monitoring unit in response to the COVID-19 pandemic

PurposeThe coronavirus disease 2019 (COVID-19) pandemic has impacted admission to epilepsy monitoring units (EMUs) for classification and presurgical evaluation of patients with refractory epilepsy. We modified the EMU admission protocol via anti-seizure medications (ASM) withdrawal implemented one day before admission; thus, we aimed to evaluate the efficacy and safety of this modified protocol. MethodsIn January 2021, we initiated ASM tapering 24 h before—rather than on the first day after—EMU admission, contrasting with the previous protocol. We retrospectively reviewed EMU admissions between January and April of 2018, 2019, and 2021, and identified the time required to record the first seizure, and EMU yield to confirm or change the epilepsy classification. We also evaluated the safety of the modified protocol, by monitoring the seizure frequency for up to 5 months after the discharge from the hospital. ResultsOne hundred four patients were included (mean age: 30 years, men: 43%); excluding a longer disease duration and abundance of normal routine electro-encephalogram (EEG) in patients admitted before the pandemic, no differences were observed in patients' characteristics. On average, it took 41 h and 21 h to record the first seizure using the standard and modified protocols, respectively (p < 0.001, 95% CI: 10–30). Other characteristics were investigated both before and after the COVID-19 pandemic, and epilepsy classifications were confirmed twice using the modified protocol (OR = 2.4, p = 0.04, 95% CI: 1.1–5.5). Multivariate regression analysis confirmed the shorter time to record the first seizure using the modified admission protocol (23 h less, p < 0.001; 95% CI: 12–34). Finally, 36 (86%) patients admitted during the pandemic exhibited no increase in seizure frequency after the discharge from the hospital. ConclusionsInitiating ASM withdrawal one day before EMU admission was deemed to be an efficient and safe way to confirm epilepsy classification and significantly decrease the length of hospital stay. Ultimately, this will shorten the long waiting list for EMU admission created by the COVID-19 pandemic.

ТОПОНИМИК ТАДҚИҚОТЛАРДА ТАСНИФЛАШ МУАММОЛАРИ ВА УЛАРДА ЭТНОТОПОНИМЛАРНИНГ ТУТГАН ЎРНИ

This article examines the problems of classification of toponymy of the Uzbek people in the research conducted in the 60s of the XX century to the beginning of the XXI century and the role of ethnotoponyms as a separate classification unit. We know that toponyms also include place names formed based on the names of people, nation, tribe, ethnic group, tribe. The field of scientific and practical study of these names is called ethnotoponymy. Ethnotoponyms, on the other hand, are the name of an ethnos, that is, they are the result of the interaction of an ethnonym and a system of toponyms. In this regard, the study of ethnotoponyms as a separate form of classification unit is extremely relevant

Mapping essential urban land use categories with open big data: Results for five metropolitan areas in the United States of America

Urban land-use maps outlining the distribution, pattern, and composition of various land use types are critically important for urban planning, environmental management, disaster control, health protection, and biodiversity conservation. Recent advances in remote sensing and social sensing data and methods have shown great potentials in mapping urban land use categories, but they are still constrained by mixed land uses, limited predictors, non-localized models, and often relatively low accuracies. To inform these issues, we proposed a robust and cost-effective framework for mapping urban land use categories using openly available multi-source geospatial “big data”. With street blocks generated from OpenStreetMap (OSM) data as the minimum classification unit, we integrated an expansive set of multi-scale spatially explicit information on land surface, vertical height, socio-economic attributes, social media, demography, and topography. We further proposed to apply the automatic ensemble learning that leverages a bunch of machine learning algorithms in deriving optimal urban land use classification maps. Results of block-level urban land use classification in five metropolitan areas of the United States found the overall accuracies of major-class (Level-I) and minor-class (Level-II) classification could be high as 91% and 86%, respectively. A multi-model comparison revealed that for urban land use classification with high-dimensional features, the multi-layer stacking ensemble models achieved better performance than base models such as random forest, extremely randomized trees, LightGBM, CatBoost, and neural networks. We found without very-high-resolution National Agriculture Imagery Program imagery, the classification results derived from Sentinel-1, Sentinel-2, and other open big data based features could achieve plausible overall accuracies of Level-I and Level-II classification at 88% and 81%, respectively. We also found that model transferability depended highly on the heterogeneity in characteristics of different regions. The methods and findings in this study systematically elucidate the role of data sources, classification methods, and feature transferability in block-level land use classifications, which have important implications for mapping multi-scale essential urban land use categories.

New segetal communities of sunflower crops in the Orenburg Region

The diversity of weed-field communities of sunflower crops within the forest-steppe zone of the Orenburg Region (Abdulinskiy, Matveevskiy, Oktyabrskiy, Aleksandrovskiy, Sharlykskiy districts) was studied. The communities in the system of ecological-floristic classification units are assigned to the new variant Orobanche cumana of the Amarantho blitoides Lactucetum tataricae Khasanova et al. 2019. In the core of the cenoflora of communities juvenile weed species prevail. The most active of them are late spring annuals (Amaranthus blitoides, Panicum miliaceum, Amaranthus retroflexus, Setaria viridis) and early spring annuals (Chenopodium album, Fallopia convolvulus, Camelina microcarpa). Root perennials such as Lactuca tatarica, Convolvulus arvensis, Euphorbia virgata, Cirsium arvense have also a high proportion. A distinctive feature of the communities is the participation in their floristic composition of a dangerous quarantine species Sunflower broomrape (Orobanche cumana). Modeling the area of the association under a moderate scenario of climate change shows that the distribution of communities by 2050 can cover almost the entire territory of the Cis-Urals (within the Republic of Bashkortostan). It is necessary to organize a monitoring system for the range of these communities in the Southern Urals.

Noise Exposure Levels in Black Tea Processing Factories and Its Effects on Employees

The aim of this study was to determine the daily noise exposure levels in black tea processing factories and to evaluate its effects on employees' occupational health and safety. In the study, the sound pressure level dBA values were measured at the ear levels of the employees in each production unit in three tea factories operating in Artvin Province. These factories where the measurements were made consist of withering, curling, oxidation, drying (boiler and stove) and classification units. These units include various systems and mechanisms formed by conveyors, fans, steam heaters, boilers, reducers, pallets, hoods, screens, gears, and drums. In the measurements performed considering the ISO 9612:2009 (Acoustics Determination of Occupational Noise Exposure Engineering Method) standard, a sound pressure level meter in Type-2 class complying with the requirements of the IEC 61672-1: 2002 was used. A weighted equivalent sound pressure levels were determined using the measured values. Considering these values and working times, personal daily noise exposure levels were calculated. It was determined that the equivalent sound pressure levels and daily personal noise exposure levels at the employee ear level were in the range of 77-87 dBA and 74-83 dBA, respectively. Curling units have the highest equivalent sound pressure level (86.81 dBA) and daily personal noise exposure level value (83.10 dBA) compared to other units, while boilers have the lowest equivalent sound pressure level (76.75 dBA) and daily personal noise exposure level value (73.55 dBA). Considering the regulation on protection of employees from noise related risks, it was concluded that the daily noise exposure level reached the lower exposure action value (80 dBA) in these factories. The study showed that the health and work efficiency of the employees could be adversely affected by noise in tea factories, considering various research results and Regulations on noise.

Automated brain tumor detection and classification using weighted fuzzy clustering algorithm, deep auto encoder with barnacle mating algorithm and random forest classifier techniques

AbstractMagnetic resonance imaging (MRI) scan analysis is an effective tool that accurately detects abnormal brain tissue. This manuscript proposes the strategy of segmentation of brain tumors in MRI images and uses the technique of weighted fuzzy factor based on kernel metrics. Here, a deep auto encoder (DAE) with barnacle mating algorithm (BMOA) and random forest (RF) classifier are used to tumor stage classification to enhance the accuracy of prediction. This manuscript presents a deep‐neural network structure, integrating DAE and RF, with a classification unit, which is used for the classification of brain MRI. Finally, the segmented features are graded by the DAE with BMOA and RF. The proposed method is executed in MATLAB site and the performance is analyzed with existing methods. The experimental outcomes of the proposed method are assessed and validated in MR brain images depending on accuracy, sensitivity, and specificity for performance with quality analysis.

A comparative study and analysis of LSTM deep neural networks for heartbeats classification

Heart diseases and their diagnosis has become a predominant topic in Healthcare systems as the heart is one of the pivotal parts of the human body. Electrocardiogram (ECG) signal-based diagnosis and classification have been experimented with various computational techniques which have demonstrated early detection and treatment of heart disease. Deep learning (DL) is the current interest of different Healthcare applications that includes the heartbeat classification based on ECG signals. There are various studies conducted with different DL models, such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and Gated Recurrent Unit (GRU) for the heartbeat classification using MIT-BIH arrhythmia dataset. This paper aims to provide a comprehensive analysis of Long-Short Term Memory (LSTM) based DL models with multiple performance metrics on the MIT-BIH arrhythmia dataset for the heartbeat classification. The different variants of the LSTM DL model are proposed for the purpose of the classification. Among the variants, the bi-directional LSTM DL model shows high accuracy in the classification of Normal beats (97%), Premature ventricular contractions (PVC) beats (98%), Atrial Premature Complex (APC) beats (98%), and Paced Beats (PB) beats (99%). The comparative analysis of the bi-directional LSTM DL model with the existing works shows 95% sensitivity and 98% specificity in the classification of heartbeats. The results evidently show that the LSTM DL models are appropriate for the classification of heartbeats.

DYNAMIC STOP LIST FOR THE GUJARATI LANGUAGE USING RULE BASED APPROACH

Text classification, document cluster, and similar endeavors area unit important analysis spaces underpinning a large vary of problems and applications within the area of internet intelligence. A typical approach, once cluster or otherwise classifying documents algorithmically, is to represent an online document as a vector of numbers derived from the frequencies of words therein document, wherever the words area unit taken from the complete assortment of documents into consideration. A tried approach is to use an inventory of “stop” words (also known as a ‘stop list’), that establish frequent words like ‘and’ and ‘or’ which might be unlikely to Words within the stop list area unit thus not enclosed within the vector that represents a document. Current stop lists area unit arguably noncurrent within the lightweight of fluctuations in word usage, and conjointly arguably innocent of sure candidate generic stop lists, thus delivery into question that we tend to explore this by developing new stop lists in an exceedingly rule based method.

Mapping Paddy Rice with Sentinel-1/2 and Phenology-, Object-Based Algorithm—A Implementation in Hangjiahu Plain in China Using GEE Platform

In tropical/subtropical monsoon regions, accurate rice mapping is hampered by the following factors: (1) The frequent occurrence of clouds in such areas during the rice-growing season interferes strongly with optical remote sensing observations; (2) The agro-landscape in such regions is fragmented and scattered. Rice maps produced using low spatial resolution data cannot well delineate the detailed distribution of rice, while pixel-based mapping using medium and high resolutions has significant salt-and-pepper noise. (3) The cropping system is complex, and rice has a rotation schedule with other crops. Therefore, the Phenology-, Object- and Double Source-based (PODS) paddy rice mapping algorithm is implemented, which consists of three steps: (1) object extraction from multi-temporal 10-m Sentinel-2 images where the extracted objects (fields) are the basic classification units; (2) specifying the phenological stage of transplanting from Savitzky–Golay filtered enhanced vegetation index (EVI) time series using the PhenoRice algorithm; and (3) the identification of rice objects based on flood signal detection from time-series microwave and optical signals of the Sentinel-1/2. This study evaluated the potential of the combined use of the Sentinel-1/2 mission on paddy rice mapping in monsoon regions with the Hangzhou-Jiaxin-Huzhou (HJH) plain in China as the case study. A cloud computing approach was used to process the available Sentinel-1/2 imagery from 2019 and MODIS images from 2018 to 2020 in the HJH plain on the Google Earth Engine (GEE) platform. An accuracy assessment showed that the resultant object-based paddy rice map has a high accuracy with a producer (user) accuracy of 0.937 (0.926). The resultant 10-m paddy rice map is expected to provide unprecedented detail, spatial distribution, and landscape patterns for paddy rice fields in monsoon regions.