scholarly journals Simulasi Sebaran Penyakit Blas Pada Tanaman Padi Menggunakan Model Spatial Multi Criteria Evaluation: Studi Kasus Kabupaten Karawang dan Purwakarta

2019 ◽  
Vol 15 (2) ◽  
pp. 59-68
Author(s):  
Busyairi Latiful Ashar ◽  
Ali Nurmansyah ◽  
Widodo Widodo
Keyword(s):  
Soil Nutrient ◽  
Blast Disease ◽  
Percentage Error ◽  
Model Case ◽  
Multi Criteria Evaluation ◽  
Cultivation Practices ◽  
History Of ◽  
Disease Dispersal ◽  
Irrigation Quality ◽  
Accuracy Of Prediction

Dispersal Simulation of Rice Blast Disease Using Spatial Multi Criteria Evalution Model: Case Study In District of Karawang and PurwakartaRice blast is caused by Pyricularia oryzae. The potential epidemic of this disease can be spatially simulated using the MCA (Multi Criteria Analysis) method based on geographical characteristics, cultivation practices, and eviromental condition. A software that can be used for MCA is SMCE (Spatial Multi Criteria Evaluation). This study was aimed to predict the spatial dispersal of blast disease using SMCE model, and identify the factors that supports the epidemic. The study was conducted in February - August 2018 in Karawang and Purwakarta District. The research methods include observing the severity of blast disease, cultivation practices and environmental conditions, and analyzing SMCE. The SMCE analysis uses rice crop maps from the Sistem Monitoring Pertanaman Padi (Simotandi), which consists of grouping factors, standardizing factors, and weighting factors. The SMCE results are a simulation map of blast disease dispersal which is then compiled with predictions of its severity. Accuracy of prediction results was evaluated by MAPE (Mean Absolute Percentage Error) based on observational data on actual disease severity. The prediction results for Karawang and Purwakarta showed means of accuration 78.16% and 73.95% respectively. In general, factors that have a strong influence on the development of blast disease include altitude, distance from source of the epidemic, history of disease in the fields, number of spores (inoculum) trapped, irrigation quality, application of herbicides, soil nutrient (N, P, K) contents and the level of soil acidity.

AMNIOTIC FLUID SPECTROPHOTOMETRY AND EARLY DELIVERY IN THE MANAGEMENT OF ERYTHROBLASTOSIS FETALIS

PEDIATRICS ◽  
1965 ◽  
Vol 35 (5) ◽  
pp. 815-835
Author(s):  
John M. Bowman ◽  
Janet M. Pollock
Keyword(s):  
Amniotic Fluid ◽  
Antibody Titer ◽  
Severe Disease ◽  
Intrauterine Death ◽  
Perinatal Deaths ◽  
Severity Of Disease ◽  
History Of Disease ◽  
History Of ◽  
Severity Of The Disease ◽  
Accuracy Of Prediction

Accuracy of prediction of intrauterine death in erythroblastosis fetalis, using history of disease and antibody titer alone, is limited (62% accuracy in a series of 121 perinatal deaths and babies who survived only because they were delivered early). Chief sources of error are in first sensitized pregnancies and in isoimmunized pregnancies where the mother has a bad history and a heterozygous husband. Spectrophotometric examination of amniotic fluid obtained transabdominally as early as 24 weeks' gestation has increased our accuracy of prediction of severity of disease to 96.8% in a series of 252 Rh negative isoimmunized pregnancies from whom 402 suitable fluids were obtained and examined. Only one of the eight inaccuracies was of such a degree that the infant's life was threatened. In 32 pregnancies with histories of severe disease on high titers and heterozygous husbands, accuracy of prediction of the Rh status of the fetus was 100 per cent. The procedure carries no risk to the mother, but if the placenta is traversed, her antibody titer may rise and the severity of the disease in the fetus may be increased. Liquor examination allows more accurate timing of induction in threatened intrauterine death and saves less severely affected babies from the hazards of prematurity. It has also proven of value in determining the fetus so severely affected that survival is only possible through intraperitoneal fetal transfusions.

A Bedouin Principle of Freedom for the Risorgimento d’Italia: Michele Amari Integrates Ibn Khaldūn with Vico’s filologia

2020 ◽  
Vol 5 (1) ◽  
pp. 76-96
Author(s):  
Markus Messling
Keyword(s):  
Nineteenth Century ◽  
State Of The Art ◽  
Classical Model ◽  
The State ◽  
Model Case ◽  
Ibn Khaldun ◽  
Giambattista Vico ◽  
New Science ◽  
Human Choice ◽  
History Of

Abstract In the New Science (1744), Giambattista Vico defined filologia as “the doctrine of all the institutions that depend on human choice” of the mondo civile. When nineteenth-century European nationalism was on the rise, supported by narratives of cultural homogeneity and specificity, philological comparatism was the state-of-the-art and it, often, legitimated the obsessions with the purity of origins and genealogies. Italy, characterized by internal plurality and its Mediterranean entanglements, is a model case. Whereas many discourses of the Risorgimento aspired to shape a new Italian nation after the classical model, Michele Amari’s History of the Muslims of Sicily (1854–1872) marked an astonishing exception. For him, going back to Islamic-Sicilian history, its literary, rhetorical and linguistic culture, meant to resume, on a higher level of incivilmento (Vico), what had been obscured by cultural decline: the spirit of freedom and equality, which Ibn Khaldūn had attributed to the Bedouins and their dynamics in history.

scholarly journals A universal graphitic interlayered centroid intercalation theory for intercalation chemistry

2021 ◽  
Author(s):  
Kemeng Ji ◽  
Kailong Hu ◽  
Yuhao Shen ◽  
Yoshikazu Ito ◽  
Cheng Liu ◽  
...  
Keyword(s):  
Metal Ion ◽  
Nitrogen Doping ◽  
Model Case ◽  
Storage Mechanism ◽  
Intercalation Reaction ◽  
Crystal Texture ◽  
Carbon Foams ◽  
History Of ◽  
Electrochemical Storage ◽  
New Research

Abstract Neither of the two widely used staging models in the long history of intercalation chemistry, namely the classical Rüdorff-Hofmann model proposed in 1938 and the pleated-layer domain-modified one in 1969, can explain the intercalation reaction phenomena and mechanism logically. Taking the landmark potassium-intercalation reaction of graphite as a model case and two advanced monolithic graphitic/graphenic carbon foams as model electrodes, here we have revealed that the electrochemical storage of potassium in graphitic/graphenic carbon (as that of lithium) obeys a simple interlayered centroid intercalation (ICIC) rule to achieve the staged potassium intercalation into each graphitic interlayer: C → KC72 → KC24 → KC8. Moreover, judging from the typical potassium-storage behaviors and crystal texture of graphitic electrodes, nitrogen doping and pre-embedded K atoms would enable incoming K+ ions to perform fast pseudocapacitive diffusion in graphitic gallery. This study not only makes clear the basic K-storage mechanism and phenomena in graphitic carbon, but also establishes a more reasonable ICIC model for intercalation chemistry, and thus may help open a new research era for this field as well as graphite-based metal-ion batteries.

scholarly journals Recently expanded clonal lineages of the rice blast fungus display distinct patterns of presence/absence of effector genes

2020 ◽  
Author(s):  
Sergio M. Latorre ◽  
C. Sarai Reyes-Avila ◽  
Angus Malmgren ◽  
Joe Win ◽  
Sophien Kamoun ◽  
...  
Keyword(s):  
Rice Blast ◽  
Plant Pathogens ◽  
Rice Blast Fungus ◽  
Population History ◽  
Blast Disease ◽  
Diverse Group ◽  
Genetic History ◽  
Effector Genes ◽  
Blast Fungus ◽  
History Of

AbstractBackgroundUnderstanding the mechanisms and timescales of plant pathogen outbreaks requires a detailed genome-scale analysis of their population history. The fungus Magnaporthe (Syn. Pyricularia) oryzae —the causal agent of blast disease of cereals— is among the most destructive plant pathogens to world agriculture and a major threat to the production of rice, wheat and other cereals. Although M. oryzae is a multihost pathogen that infects more than 50 species of cereals and grasses, all rice-infecting isolates belong to a single genetically defined lineage. Here, we combined multiple genomics datasets to reconstruct the genetic history of the rice-infecting lineage of M. oryzae based on 131 isolates from 21 countries.ResultsThe global population of the rice blast fungus consists of a diverse set of individuals and three well-defined genetic groups. Multiple population genetic tests revealed that the rice-infecting lineage of the blast fungus probably originated from a recombining diverse group in South East Asia followed by three independent clonal expansions that took place over the last ∼200 years. Patterns of allele sharing identified a subpopulation from the recombining diverse group that introgressed with one of the clonal lineages before its global expansion. Remarkably, the four genetic lineages of the rice blast fungus vary in the number and patterns of presence/absence of candidate effector genes. In particular, clonal lineages carry a reduced repertoire of effector genes compared with the diverse group, and specific combinations of effector presence/absence define each of the pandemic clonal lineages.ConclusionsOur analyses reconstruct the genetic history of the rice-infecting lineage of M. oryzae revealing three clonal lineages associated with rice blast pandemics. Each of these lineages displays a specific pattern of presence/absence of effector genes that may have shaped their adaptation to the rice host and their evolutionary history.

scholarly journals Compound Grey-Logistic Model and Its Application

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xiao-Lan Wu ◽  
Sheng-Yuan Wang ◽  
Guo-Yin Xu
Keyword(s):  
Information Entropy ◽  
Logistic Model ◽  
Original Data ◽  
Percentage Error ◽  
Growth Data ◽  
Simulation Accuracy ◽  
Logistic Method ◽  
Share Data ◽  
Error Index ◽  
Accuracy Of Prediction

Logistic regression model is widely used in ecology and in the analysis of social economic systems, because of its good adaptability. In order to improve the measurement accuracy of logistic model, this paper proposes a new method. A compound grey-logistic model is developed to carry out the grey transformation of the original data. Practice shows that the grey transformation data has better simulation accuracy; at the same time, grey transformation can reduce the observation noise of the original data. Mean absolute percentage error index has been used to evaluate the accuracy of prediction model, and information entropy can be used to evaluate the change of information entropy of forecasting data. In this paper, three cases are used to verify the applicability of grey-logistic model. From the perspective of the type of original data, the three cases represent three different data conditions: sufficient data, insufficient data, and fragmentary data. The cases represent different related fields: market share data, economic growth data, and R&D output data. The results show that the proposed grey-logistic method can effectively carry out the population growth analysis.

Abstract WMP27: PAT Model Accurately Predicts Aneurysm Enlargement in 16 Growing Aneurysm Cases

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Aichi Chien ◽  
Michelle Hildebrandt ◽  
Geoffrey Colby ◽  
Victor Chang ◽  
Gary Duckwiler ◽  
...  
Keyword(s):  
Medical Records ◽  
Intracranial Aneurysms ◽  
Medical Center ◽  
Patient Characteristics ◽  
Percentage Error ◽  
Limited Information ◽  
Unruptured Intracranial Aneurysms ◽  
History Of ◽  
And Behavior

Objective: Imaging technology for unruptured intracranial aneurysms (UIA) has improved detection of such aneurysms. However, there is limited information on UIA change over time, and how to predict the rate of enlargement. The objective of this study was to quantify the accuracy of the Predicted Aneurysm Trajectory (PAT) model recently developed by Chien et al. (J Neurosurgery. 2019; Mar 1:1-11). Methods: Patients diagnosed with UIA were prospectively enrolled at the UCLA Medical Center, and followed through serial imaging. 16 UIA cases exhibiting growth across multiple follow-ups were included in this study. Prior images and medical records were collected. Characteristics relevant to the PAT model (mean ± stdev), including initial UIA size (7.26 ± 6.38), patient age (67.4 ± 9.48 yrs.), sex (4 male), history of smoking (n=5), hypothyroidism (n=4), and follow-up duration (36.5 ± 50.0 mos.) were used to predict UIA size at each follow-up. Predicted and actual UIA sizes at follow-up were compared using symmetric mean absolute percentage error (SMAPE) with percentage error ranging from 0-100%. Results: The 16 UIA cases were split by initial UIA size. For UIA smaller than 7 mm (10 cases, 23 follow-up), SMAPE = 11.13%. For UIA greater than 7 mm (6 cases, 15 follow-up), SMAPE = 8.07%. For all UIA cases (16 cases, 38 follow-up), SMAPE = 9.92%. Conclusions: The PAT model predicts the rate of enlargement for UIA, as opposed to whether or not UIA will grow. With this new sample of data, we found the predicted UIA size at follow-up to be quite accurate, deviating in the range of 10% from the actual, measured size. Patient characteristics such as the demographics and behavior included in the model influence the growth of UIA, which allows prediction of growth to optimize treatment and management in future cases.

scholarly journals Gene Flow between Divergent Cereal- and Grass-Specific Lineages of the Rice Blast Fungus Magnaporthe oryzae

mBio ◽  
2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Pierre Gladieux ◽  
Bradford Condon ◽  
Sebastien Ravel ◽  
Darren Soanes ◽  
Joao Leodato Nunes Maciel ◽  
...  
Keyword(s):  
Gene Flow ◽  
South America ◽  
Magnaporthe Oryzae ◽  
Rice Blast ◽  
Evolutionary History ◽  
Blast Disease ◽  
Whole Genome ◽  
Disease Emergence ◽  
Wheat Blast ◽  
History Of

ABSTRACT Delineating species and epidemic lineages in fungal plant pathogens is critical to our understanding of disease emergence and the structure of fungal biodiversity and also informs international regulatory decisions. Pyricularia oryzae (syn. Magnaporthe oryzae) is a multihost pathogen that infects multiple grasses and cereals, is responsible for the most damaging rice disease (rice blast), and is of growing concern due to the recent introduction of wheat blast to Bangladesh from South America. However, the genetic structure and evolutionary history of M. oryzae, including the possible existence of cryptic phylogenetic species, remain poorly defined. Here, we use whole-genome sequence information for 76 M. oryzae isolates sampled from 12 grass and cereal genera to infer the population structure of M. oryzae and to reassess the species status of wheat-infecting populations of the fungus. Species recognition based on genealogical concordance, using published data or extracting previously used loci from genome assemblies, failed to confirm a prior assignment of wheat blast isolates to a new species (Pyricularia graminis-tritici). Inference of population subdivisions revealed multiple divergent lineages within M. oryzae, each preferentially associated with one host genus, suggesting incipient speciation following host shift or host range expansion. Analyses of gene flow, taking into account the possibility of incomplete lineage sorting, revealed that genetic exchanges have contributed to the makeup of multiple lineages within M. oryzae. These findings provide greater understanding of the ecoevolutionary factors that underlie the diversification of M. oryzae and highlight the practicality of genomic data for epidemiological surveillance in this important multihost pathogen. IMPORTANCE Infection of novel hosts is a major route for disease emergence by pathogenic microorganisms. Understanding the evolutionary history of multihost pathogens is therefore important to better predict the likely spread and emergence of new diseases. Magnaporthe oryzae is a multihost fungus that causes serious cereal diseases, including the devastating rice blast disease and wheat blast, a cause of growing concern due to its recent spread from South America to Asia. Using whole-genome analysis of 76 fungal strains from different hosts, we have documented the divergence of M. oryzae into numerous lineages, each infecting a limited number of host species. Our analyses provide evidence that interlineage gene flow has contributed to the genetic makeup of multiple M. oryzae lineages within the same species. Plant health surveillance is therefore warranted to safeguard against disease emergence in regions where multiple lineages of the fungus are in contact with one another.

Course and outcome of schizophrenia and their prediction

2012 ◽  
pp. 568-578
Author(s):  
Assen Jablensky
Keyword(s):  
Personal Growth ◽  
Significant Proportion ◽  
Complete Recovery ◽  
Psychotic Symptoms ◽  
Term Outcome ◽  
Longitudinal Course ◽  
Duration Of Illness ◽  
History Of ◽  
Episodic Course ◽  
Accuracy Of Prediction

Studies conducted over many decades consistently demonstrate that schizophrenia presents a broad spectrum of possible outcomes and course patterns, ranging from complete or nearly complete recovery after acute episodes of psychosis to continuous, unremitting illness leading to progressive deterioration of cognitive performance and social functioning. Between these extremes, a substantial proportion of patients show an episodic course with relapses of psychotic symptoms and partial remissions during which affective and cognitive impairments become increasingly conspicuous and may progress to gross deficits. Although no less than one-third of all patients with schizophrenia have relatively benign outcomes, in the majority the illness still has a profound, lifelong impact on personal growth and development. The initial symptoms of the disorder are not strongly predictive of the pattern of course but the mode of onset (acute or insidious), the duration of illness prior to diagnosis and treatment, the presence or absence of comorbid substance use, as well as background variables such as premorbid adjustment (especially during adolescence), educational and occupational achievement, marital status, and availability of a supportive social network allow a reasonable accuracy of prediction in the short- to medium-term (2–5 years). One of the most striking aspects of the longitudinal course of schizophrenia is the so-called ‘terminal improvement’. A relatively high proportion of patients tend to improve substantially with ageing. What determines this long-term outcome is far from clear but the stereotype view of schizophrenia as an invariably progressive, deteriorating disorder does not accord well with the evidence. Similarly, a model of schizophrenia as a static neurodevelopmental encephalopathy decompensating post-adolescence under the influence of a variety of stressors fits only part of the spectrum of course patterns. In a significant proportion of cases, the disorder exhibits the unmistakable features of a shift-like process with acute exacerbations and remissions which may progress to severe deterioration or come to a standstill at any stage. Whether a single underlying pathophysiology can explain the variety of clinical outcomes, or several different pathological processes are at work, remains obscure. It has been suggested that the longitudinal course of schizophrenia should be seen as an open-ended, dynamic life process with multiple, interacting biological and psychosocial determinants. Obviously, such issues cannot be resolved by clinical follow-up studies alone, and require a strong involvement of neurobiological research in prospective investigations of representative samples of cases spanning the entire spectrum of course and outcomes. No such studies have been possible until recently, both because of the technical complexity of such an undertaking and because of the tendency to selectively recruit for biological investigations patients from the severe, deteriorating part of the spectrum. Overcoming such limitations will be essential to the uncovering of the mechanisms driving the ‘natural history’ of schizophrenia.

APPLYING TOPSIS AND QSPM METHODS IN FRAMEWORK SWOT MODEL: CASE STUDY OF THE IRAN’S STOCK MARKET

2011 ◽  
Vol 01 (05) ◽  
pp. 93-103
Author(s):  
Mahsa Beidokhty nejad ◽  
Nina Pouyan ◽  
Mohammad reza shojaee
Keyword(s):  
Stock Market ◽  
Capital Market ◽  
Swot Analysis ◽  
Stock Exchange ◽  
Model Case ◽  
Structural Problems ◽  
History Of ◽  
Factor Evaluation ◽  
First Time

The Stock Exchange today, is one of the pillars of the capital market financing in countries. The history of market activity in Iran dates back 43 years ago, Despite this history due to structural problems, people's ignorance and limited activities inside the country still has not got an appropriate place in the country and in economic and financial areas. In This article for the first time, the Iran’s stock market SWOT analysis has been practiced. In this regard weaknesses ,strengths, opportunities and threats points of the Iran’s stock market ,through Delphi and questionnaire were gathered and ultimately through the internal and external factor Evaluation, SWOT matrixes the data has been analyzed and with QSPM and TOPSIS models, strategy has been codified to improve the performance of this market.

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