Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical Acid Base Balance

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Survey on Pre-Processing Techniques for Text Mining

Data Mining is a versatile sublet in the field of computer science. It is the computational evolution mode of detecting patterns in large data sets. This paper give an indication on the different pre-processing techniques to mine text data. Text mining applications include – Information Retrieval, Information Extraction, Categorization, and Natural Language Processing. The pre-processing of text mining starts with Tokenization, followed by Stop-word removal and finally stemming. This paper evaluates Porter’s and Krovetz algorithm, highlighting their applications and drawbacks.
An Efficient Adaptive Switching Median Filter Architecture for Removal of Impulse Noise in Images

— The median filter performs well as long as the spatial density of the impulse noise is not large. However the adaptive switching median filtering can handle impulse noise with probabilities even larger than these. An additional benefit of the adaptive switching median filter is that it seeks to preserve edges while smoothing nonimpulse noise. Considering the high level of noise, the adaptive algorithm performs quite well. The choice of maximum allowed window size depends on the application. In which it compares each pixel with surrounding neighbour pixels. If a pixel is different from neighbourhood is labelled as impulse noise. those noise pixels are replaced by median pixel value. Such that edges are preserved and it smoothens the other noises also.
Functions Of Mathematical Physics

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Starch Granules in Tissues of Rice Plants and Their Changes in Relation to Plant Growth

The rice plant is a conspicuous cereal which accumulates many starch granules in its tissues.3> The author carried out a series of studies on starch granules in rice plants in a period from 1954 to 1981.1-10> Some of the major results will be presented in this paper. Accumulation and distribution of starch granules in the tissues were microscopically observed after staining starch granules with I-KI solution or by using the Pass reaction . ** For leaf sheaths and stem-internodes, where a large amount of starch granules accumulate in parenchyma, histochemical methods shown in Fig. 1 were employed to estimate the relative amount of starch in these organs. >
New Downy Mildew Disease Caused by Hyaloperonospora brassicae on Pak choi (Brassica rapa) in Korea

Pak choi (or a Bok choy; Brassica rapa subsp. chinensis) is a popular brassicaceous vegetable worldwide. In January 2019, a downy mildew symptom on pak choi was found at a farm located in Yongin, Korea. Based on morphological characteristics and molecular phylogenetic inference, the pathogenic oomycete was identified as Hyaloperonospora brassicae. To our knowledge, this is the first report of downy mildew disease occurring on pak choi in Korea. Considering the increasing demand for this crop, this pathogen would be a potentially new threat to the cultivation of pak choi in Korea.
Reciprocity and behavioral heterogeneity govern the stability of social networks

Significance In animal societies, social partnerships form a dynamic network that can change over time. Why are some social network structures more stable than others? We addressed this question by studying a cooperative bird species in which social behavior is important for fitness, similar to humans. We found that stable social networks are characterized by more frequent interactions but sparser connectivity throughout the network. Using a simulation, we show how both results can be explained by a simple model of reciprocity. These findings indicate that social stability is governed by a trade-off whereby individuals can either maintain a few high-quality partners or increase partner number. This fundamental trade-off may govern the dynamics and stability of many societies, including in humans. The dynamics of social networks can determine the transmission of information, the spread of diseases, and the evolution of behavior. Despite this broad importance, a general framework for predicting social network stability has not been proposed. Here we present longitudinal data on the social dynamics of a cooperative bird species, the wire-tailed manakin, to evaluate the potential causes of temporal network stability. We find that when partners interact less frequently and when social connectedness increases, the network is subsequently less stable. Social connectivity was also negatively associated with the temporal persistence of coalition partnerships on an annual timescale. This negative association between connectivity and stability was surprising, especially given that individual manakins who were more connected also had more stable partnerships. This apparent paradox arises from a within-individual behavioral trade-off between partnership quantity and quality. Crucially, this trade-off is easily masked by behavioral variation among individuals. Using a simulation, we show that these results are explained by a simple model that combines among-individual behavioral heterogeneity and reciprocity within the network. As social networks become more connected, individuals face a trade-off between partnership quantity and maintenance. This model also demonstrates how among-individual behavioral heterogeneity, a ubiquitous feature of natural societies, can improve social stability. Together, these findings provide unifying principles that are expected to govern diverse social systems.
Global community breaks at 60 m on mesophotic coral reefs

Aim: Mesophotic coral ecosystems (MCEs) are unique communities that support a high proportion of depth-endemic species distinct from shallow-water coral reefs. However, there is currently little consensus on the boundaries between shallow and mesophotic coral reefs and between upper versus lower MCEs because studies of these communities are often site specific. Here, we examine the ecological evidence for community breaks, defined here as species loss, in fish and benthic taxa between shallow reefs and MCEs globally. Location: Global MCEs. Time period: 1973–2017. Major taxa studied: Macrophytes, Porifera, Scleractinia, Hydrozoa, Octocorallia, Antipatharia and teleost fishes. Methods: We used random-effects models and breakpoint analyses on presence/absence data to identify regions of higher than expected species loss along a depth gradient of 1–69 m, based on a meta-analysis of 26 studies spanning diverse photoautotrophic and heterotrophic taxa. We then investigated the extent to which points of high faunal turnover can be explained by environmental factors, including light, temperature and nutrient availability. Results: We found evidence for a community break, indicated by a significant loss of shallow-water taxa, at ~ 60 m across several taxonomically and functionally diverse benthic groups and geographical regions. The breakpoint in benthic composition is best explained by decreasing light, which is correlated with the optical depths between 10 and 1% of surface irradiance. A concurrent shift in the availability of nutrients, both dissolved and particulate organic matter, and a shift from photoautotroph to heterotroph-dominated assemblages also occurs at ~ 60 m depth. Main conclusions: We found evidence for global community breaks across multiple benthic taxa at ~ 60 m depth, indicative of distinct community transitions between shallow and mesophotic coral ecosystems. Changes in the underwater light environment and the availability of trophic resources along the depth gradient are the most parsimonious explanations for the observed patterns.
A lag in the advancement of biotechnology: reliable control of maize stem borers in Africa

The future of food security in Africa is being severely threatened due to an exponential increase in population, which is almost three times the increase of food production. Maize production is constrained by stem borers which cause significant yield losses. Yield losses can be further compounded by higher temperatures due to climate changes, which are expected to increase the population of maize stem borers. While several methods have been employed in stem borer management, there is still significant damage caused by maize stem borers. This necessitates better control methods including the adoption of recent biotechnological advancement in RNA interference (RNAi) technology. This review highlights evidence of an increase in the stem borer population as well as the foreseen decline in maize production worldwide due to the effects of climatic changes. Furthermore, we have drawn attention to improved methods that have been used to control stem borers in maize production as well as a reluctant acceptance of traditional biotechnology in Africa. Finally, we suggest the application of alternative RNA interference techniques to breed maize for efficient pest control in order to achieve food security, improve nutrition and promote sustainable maize production.
Text classification algorithm based on hidden Markov model

A number of sophisticated automatic text classification algorithms have been proposed in recent years, but those algorithms are mainly based on the probability and statistical models and have not established a relationship with the syntax and semantic of text. In this paper, a new automatic text classification algorithm using Hidden Markov Model ( HMM) was proposed. At first, a feature set was built to distinguish the document types. Then the different sequences of feature words were regarded as the different observations generated by HMM classifiers. The state transition sequence of a specific HMM classifier implied the process of document's formation and evolution in a specific document type. When a document was classified, the result was created by the HMM classifier which could get the greatest generation probability according to the document. To some extent, some syntactic and semantic features of different document were represented by the classification model. The model can be applied to automatic multi-category text classification, and it has high classification efficiency.
Road traffic accidents prediction based on optimal weighted combined model

The prediction of traffic accident is the basis of transportation safety, assessment and decision-making. Aimed at solving the limitations in various single grey forecasting methods, a combined forecasting model of road traffic accidents based on optimal weighted method is put forward. According to the characteristics of traffic accident in China, a model combining GM(1,1), Verhulst and SCGM(1,1)c is established and the weight coefficients of combined forecasting model are determined by optimal weighted method. The deaths of traffic accident in China from 2001 to 2007 are taken as original data to establish forecasting model predicting the deaths of traffic accident from 2008 to 2010. The results demonstrate that the forecast accuracy of combined model is better than that of GM(1,1)model,Verhulst model and SCGM(1,1)c model.
Rhetorical Structure Annotation of Chinese News Commentaries

This paper reports a rhetorical structure annotation project to a Chinese news commentary corpus Caijingpinglun(CJPL) for the purpose of natural language processing.The elementary discourse unit(EDU) in this project is defined as a string between two selected punctuation marks.And altogether 47 Chinese rhetorical relations are defined to mark the nuclarity according to the classic rhetorical structure theory(RST). A 60-page annotation manual with detailed rules of EDU segmentation,EDU combination,relation and scheme tagging protocols are composed.Analysis on the first manually annotated set of 97 texts shows that the RST has good cross-language transferability to Chinese,and the data obtained from this project may be further exploited in Chinese discourse processing.
Perceived direction of deformation flow

In everyday circumstances, human observers can easily discriminate the direction of transparent liquid flow. However, the mechanism of direction discrimination is not so straightforward. The present study focused on the flow of image deformation, which is closely related to the flow of transparent liquid in the natural world. To determine what image information is important in discriminating the direction of deformation flow, a natural image in a stimulus clip was deformed by using a deformation vector map that translated leftward or rightward. The task of the observers was to judge whether the transparent liquid in the clip flowed leftward or rightward. Manipulating the amplitude of deformation, we found that the discrimination performance improved with the amplitude. Interestingly, the observers’ performance was high overall only when shearing deformation was applied to the stimuli, while the observers reported an opposite-motion direction when only compressive deformation was applied. We computationally analyzed motion statistics of stimuli and found that the combination of mean and skewness of horizontal motion vectors reliably predicted the performance. The results indicate that human observers use global motion directions in order to determine the direction of deformation flow.
Droughts and the ecological future of tropical savanna vegetation

Climate change is expected to lead to more frequent, intense and longer droughts in the future, with major implications for ecosystem processes and human livelihoods. The impacts of such droughts are already evident, with vegetation dieback reported from a range of ecosystems, including savannas, in recent years. Most of our insights into the mechanisms governing vegetation drought responses have come from forests and temperate grasslands, while responses of savannas have received less attention. Because the two life forms that dominate savannas—C3 trees and C4 grasses—respond differently to the same environmental controls, savanna responses to droughts can differ from those of forests and grasslands. Drought‐driven mortality of savanna vegetation is not readily predicted by just plant drought‐tolerance traits alone, but is the net outcome of multiple factors, including drought‐avoidance strategies, landscape and neighborhood context, and impacts of past and current stressors including fire, herbivory and inter‐life form competition. Many savannas currently appear to have the capacity to recover from moderate to severe short‐term droughts, although recovery times can be substantial. Factors facilitating recovery include the resprouting ability of vegetation, enhanced flowering and seeding and post‐drought amelioration of herbivory and fire. Future increases in drought severity, length and frequency can interrupt recovery trajectories and lead to compositional shifts, and thus pose substantial threats, particularly to arid and semi‐arid savannas. Synthesis. Our understanding of, and ability to predict, savanna drought responses is currently limited by availability of relevant data, and there is an urgent need for campaigns quantifying drought‐survival traits across diverse savannas. Importantly, these campaigns must move beyond reliance on a limited set of plant functional traits to identifying suites of physiological, morphological, anatomical and structural traits or “syndromes” that encapsulate both avoidance and tolerance strategies. There is also a critical need for a global network of long‐term savanna monitoring sites as these can provide key insights into factors influencing both resistance and resilience of different savannas to droughts. Such efforts, coupled with site‐specific rainfall manipulation experiments that characterize plant trait–drought response relationships, and modelling efforts, will enable a more comprehensive understanding of savanna drought responses.
Comparative study of anthropometric measurements, liver function tests, hemoglobin and plasma glucose levels between individuals with alcohol abuse and controls

Background: Alcohol abuse is global burden to families as well as society. On the ‘years of life lost scale’, which is based on alcohol attributable years of life lost, India has been rated 4 on a scale of 1 to 5. This implies that the alcohol consuming population of our country loses most of the years of their life because of drinking and its consequences. The aim of this research is to compare anthropometric measurements, liver function tests, haemoglobin and plasma glucose levels in individuals with alcohol abuse and normal population.Methods: The study was conducted in the Department of General Medicine, Civil Hospital, Aizawl. 84 cases of individuals with alcohol abuse (as per DSM-IV criteria) within the age group of 18-70 years and 70 age, sex, height and weight matched lifetime abstainers, healthy individuals were taken as controls from medicine department. They underwent a detailed clinical examination, anthropometric measurements, liver function tests, haemoglobin and plasma glucose levels.Results: 15.5% of the individuals with alcohol abuse had hypertension. The mean post prandial glucose among the individuals with alcohol abuse was 116.8±12.3 mg/dl and among the controls was 121.1±11.0 mg/dl. Mean serum bilirubin 1.1 mg/dl, AST 79 IU/l & ALT was 79.6 in alcoholics. The mean serum bilirubin 0.8 mg/dl, AST 27.2 IU/l and ALT was 29.4 in non-alcoholics.Conclusions: The individuals with alcohol abuse have raised serum bilirubin, AST and ALT levels compared to the non-alcoholics. Prevalence of hypertension is higher in the individuals with alcohol abuse compared to normal population.
Inhibition Controls Receptive Field Size, Sensitivity, and Response Polarity of Direction Selective Ganglion Cells Near the Threshold of Vision

Information about motion is encoded by direction-selective retinal ganglion cells (DSGCs). These cells reliably transmit this information across a broad range of light levels, spanning moonlight to sunlight. Previous work indicates that adaptation to low light levels causes heterogeneous changes to the direction tuning of ON-OFF (oo)DSGCs and suggests that superior-preferring ON-OFF DSGCs (s-DSGCs) are biased toward detecting stimuli rather than precisely signaling direction. Using a large-scale multi-electrode array, we measured the absolute sensitivity of ooDSGCs and found that s-DSGCs are ten-fold more sensitive to dim flashes of light than other ooDSGCs. We measured their receptive field sizes and found that s-DSGCs also have larger receptive fields than other ooDSGCs, however, the size difference does not fully explain the sensitivity difference. Using a conditional knockout of gap junctions and pharmacological manipulations, we demonstrate that GABA-mediated inhibition contributes to the difference in absolute sensitivity and receptive field size at low light levels, while the connexin36-mediated gap junction coupling plays a minor role. We further show that GABA-mediated inhibition masks the OFF response of ooDSGCs under scotopic conditions, restricting their responses to increases in light. These results reveal that GABAergic inhibition controls and differentially modulates the responses of ooDSGCs under scotopic conditions. Significance Statement Light adaptation and parallel processing are two major functions of retina. Here we show that parallel processing is differentially regulated between photopic and scotopic conditions across DSGCs. This differential adaptation alters the absolute sensitivity and RF size of s-DSGCs relative to other ooDSGC types. These results point to novel mechanisms and possibly new circuit elements that shape retinal processing of motion under rod-mediated light levels.
Diversity and pathogenicity of microbial communities causing grape sour rot in eastern coastal areas of China

Background As a polymicrobial disease, grape sour rot can lead to the decrease in the yield of grape berries and wine quality. The diversity of microbial communities in sour rot-infected grapes depends on the planting location of grapes and the identified methods. The east coast of China is one of the most important grape and wine regions in China and even in the world. Methods To identify the pathogenic microorganism s causing sour rot in table grapes of eastern coastal areas of China, the diversity and abundance of the bacteria and fungi were assessed based on two methods, including traditional culture-methods, and 16S rRNA and ITS gene high-throughput sequencing . Then the pathogenicity of cultivable microorganisms was determined in laboratory. Results Based on traditional culture-methods, we identified 15 cultivable bacterial species and 10 fungal species from sour rot-infected grapes. The p athogenicity assay confirmed five cultivated fungi species (three Aspergillus species, Alternaria tenuissima, and Fusarium proliferatum), and four bacteria species (two Cronobacter species, Serratia marcescens and Lysinibacillus fusiformis) as mainly pathogenic on grape. A. tenuissima, and F. proliferatum were the firstly discovered as pathogens on harvesting grape. Moreover, high-throughput sequencing revealed the OTUs numbers of bacteria and fungi were 1343.33 and 1038.67 respectively. Proteobacteria (72.15%) and Firmicutes (26.83%) were dominant phylums among the 19 bacterial phyla identified, while Ascomycota (93.86%) was the dominant fungal phylum. Then, bacteria such as Acetobacter sp. , Gluconobacter sp. , Bacillus sp. , and Lactococcus sp. and fungi such as Incertae sedis sp. , Issatchenkia terricola, Colletotrichum viniferum, Hanseniaspora vineae, Saprochaete gigas, and Candida diversa took the vast majority ofmicrobial species in sour rot-infected grapes. Therefore, more accurate and abundant microbial communities in sour rot-infected grapes could be identified using the traditional culture-methods and high-throughput sequencing.