Actual Precipitation Index (API) for Drought Classification

AbstractThe Standard Precipitation Index (SPI) is a widely used statistical technique for the characterization of droughts. It is based on a probabilistic standardization procedure, which converts a Gamma-type probability distribution function (PDF) into a normal (Gaussian) standard series with zero mean and unit standard deviation. Drought classification based on SPI indicates dry and wet spell characteristics, provided that the hydro-meteorological records abide by normal (Gaussian) PDF only, otherwise the results will be biased. Therefore, in this paper, the actual precipitation index (API) method is presented, which provides drought classification and information regardless of the underlying PDFs. The main purpose of this paper is to explain the main differences between SPI and API and to prove that the use of API is the more reliable solution for classification of droughts into five categories described as “Normal dry”, “Slightly dry”, “Medium dry”, “Very dry” and “Extremely dry”. The application of the methodology is presented for two sets of precipitation data; one with exponential PDF monthly precipitation records from Istanbul City, Turkey and one for New Jersey, USA with almost normal (Gaussian) PDF based on annual precipitation records. The comparisons indicate that API is applicable regardless of the underlying PDF of the hydro-meteorology data. It produces real drought classification from the original data without recourse to standard normal PDF conversion.

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Annual Characterization of Regional Hydrological Drought using Auxiliary Information under Global Warming Scenario

10.5194/nhess-2018-373 ◽

2019 ◽

Cited By ~ 3

Author(s):

Zulfiqar Ali ◽

Ijaz Hussain ◽

Muhammad Faisal

Keyword(s):

Global Warming ◽

Standardized Precipitation Index ◽

Auxiliary Information ◽

Hydrological Drought ◽

Precipitation Index ◽

Monthly Precipitation ◽

Warming Scenario ◽

Global Warming Scenario ◽

Precipitation Records

Abstract. Climate change and global warming scenario is likely to increase worsening drought across the World. Drought is a complex natural hazard, which is a composition of many factors such as hydrological, meteorological and agricultural. Accurate characterization of hydrological drought at regional level is challenging. Standardized Drought Indices (SDI) is commonly used method for drought characterization and monitoring. In this study, we proposed a hydrological drought index, which used improved monthly precipitation estimates under global warming scenario. As monthly precipitation records have significant role in regional drought characterization. Therefore, this research suggests auxiliary information as local weights to improve monthly precipitation records in terms of dependence characteristic of temperature with precipitation records under regression estimation settings. Consequently, we proposed a new method of hydrological drought assessment The Locally Weighted Standardized Precipitation Index (LWSDI). We assessed hydrological drought using LWSDI on 10 meteorological stations located in various climatological regions of Pakistan. We compared and evaluated performance of LWSDI with Standardized Precipitation Index (SPI) and Standardized Evapotranspiration Index (SPEI) at 12-month time scale based on Pearson correlation. We found high positive correlation between the LWSDI and existing methods (SPI and SPEI). In summary, improved estimates of precipitation can strengthen drought monitoring system.

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Morphological and Ultrastructural Characterization of Hemocytes in an Insect Model, the Hematophagous Dipetalogaster maxima (Hemiptera: Reduviidae)

Insects ◽

10.3390/insects12070640 ◽

2021 ◽

Vol 12 (7) ◽

pp. 640

Author(s):

Natalia R. Moyetta ◽

Fabián O. Ramos ◽

Jimena Leyria ◽

Lilián E. Canavoso ◽

Leonardo L. Fruttero

Keyword(s):

Cell Biology ◽

Cell Types ◽

Transmission Electron ◽

Ultrastructural Characterization ◽

Current Classification ◽

Contrast Microscopy ◽

First Time ◽

Controversial Aspect

Hemocytes, the cells present in the hemolymph of insects and other invertebrates, perform several physiological functions, including innate immunity. The current classification of hemocyte types is based mostly on morphological features; however, divergences have emerged among specialists in triatomines, the insect vectors of Chagas’ disease (Hemiptera: Reduviidae). Here, we have combined technical approaches in order to characterize the hemocytes from fifth instar nymphs of the triatomine Dipetalogaster maxima. Moreover, in this work we describe, for the first time, the ultrastructural features of D. maxima hemocytes. Using phase contrast microscopy of fresh preparations, five hemocyte populations were identified and further characterized by immunofluorescence, flow cytometry and transmission electron microscopy. The plasmatocytes and the granulocytes were the most abundant cell types, although prohemocytes, adipohemocytes and oenocytes were also found. This work sheds light on a controversial aspect of triatomine cell biology and physiology setting the basis for future in-depth studies directed to address hemocyte classification using non-microscopy-based markers.

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Semi-automated regional classification of the style of activity of slow rock-slope deformations using PS InSAR and SqueeSAR velocity data

Landslides ◽

10.1007/s10346-021-01654-0 ◽

2021 ◽

Author(s):

Chiara Crippa ◽

Elena Valbuzzi ◽

Paolo Frattini ◽

Giovanni B. Crosta ◽

Margherita C. Spreafico ◽

...

Keyword(s):

Rock Slope ◽

Progressive Failure ◽

Principal Component ◽

Cost Effective ◽

Displacement Rate ◽

Machine Learning Classification ◽

Management Perspective ◽

Alpine Environments

AbstractLarge slow rock-slope deformations, including deep-seated gravitational slope deformations and large landslides, are widespread in alpine environments. They develop over thousands of years by progressive failure, resulting in slow movements that impact infrastructures and can eventually evolve into catastrophic rockslides. A robust characterization of their style of activity is thus required in a risk management perspective. We combine an original inventory of slow rock-slope deformations with different PS-InSAR and SqueeSAR datasets to develop a novel, semi-automated approach to characterize and classify 208 slow rock-slope deformations in Lombardia (Italian Central Alps) based on their displacement rate, kinematics, heterogeneity and morphometric expression. Through a peak analysis of displacement rate distributions, we characterize the segmentation of mapped landslides and highlight the occurrence of nested sectors with differential activity and displacement rates. Combining 2D decomposition of InSAR velocity vectors and machine learning classification, we develop an automatic approach to characterize the kinematics of each landslide. Then, we sequentially combine principal component and K-medoids cluster analyses to identify groups of slow rock-slope deformations with consistent styles of activity. Our methodology is readily applicable to different landslide datasets and provides an objective and cost-effective support to land planning and the prioritization of local-scale studies aimed at granting safety and infrastructure integrity.

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Dry and Wet Climate Periods over Eastern South America: Identification and Characterization through the SPEI Index

Atmosphere ◽

10.3390/atmos12020155 ◽

2021 ◽

Vol 12 (2) ◽

pp. 155

Author(s):

Anita Drumond ◽

Milica Stojanovic ◽

Raquel Nieto ◽

Luis Gimeno ◽

Margarida L. R. Liberato ◽

...

Keyword(s):

South America ◽

Potential Evapotranspiration ◽

Monthly Precipitation ◽

Economic Activities ◽

Central Brazil ◽

Moisture Analysis ◽

Dry Conditions ◽

Wet Climate ◽

Climate Events

A large part of the population and the economic activities of South America are located in eastern regions of the continent, where extreme climate events are a recurrent phenomenon. This study identifies and characterizes the dry and wet climate periods at domain-scale occurring over the eastern South America (ESA) during 1980–2018 through the multi-scalar Standardized Precipitation–Evapotranspiration Index (SPEI). For this study, the spatial extent of ESA was defined according to a Lagrangian approach for moisture analysis. It consists of the major continental sink of the moisture transported from the South Atlantic Ocean throughout the year, comprising the Amazonia, central Brazil, and the southeastern continental areas. The SPEI for 1, 3, 6, and 12 months of accumulation was calculated using monthly precipitation and potential evapotranspiration time series averaged on ESA. The analysis of the climate periods followed two different approaches: classification of the monthly SPEI values as mild, moderate, severe, and extreme; the computation of the events and their respective parameters (duration, severity, intensity, and peak). The results indicate that wet periods prevailed in the 1990s and 2000s, while dry conditions predominated in the 2010s, when the longest and more severe dry events have been identified at the four scales.

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The Underlying Order Induced by Orthogonality and the Quantum Speed Limit

Quantum Reports ◽

10.3390/quantum3030024 ◽

2021 ◽

Vol 3 (3) ◽

pp. 376-388

Author(s):

Francisco J. Sevilla ◽

Andrea Valdés-Hernández ◽

Alan J. Barrios

Keyword(s):

Energy Spectrum ◽

Energy Distribution ◽

Finite Time ◽

Complete Characterization ◽

Comprehensive Analysis ◽

Orthogonality Condition ◽

Speed Limit ◽

Physical Quantities

We perform a comprehensive analysis of the set of parameters {ri} that provide the energy distribution of pure qutrits that evolve towards a distinguishable state at a finite time τ, when evolving under an arbitrary and time-independent Hamiltonian. The orthogonality condition is exactly solved, revealing a non-trivial interrelation between τ and the energy spectrum and allowing the classification of {ri} into families organized in a 2-simplex, δ2. Furthermore, the states determined by {ri} are likewise analyzed according to their quantum-speed limit. Namely, we construct a map that distinguishes those ris in δ2 correspondent to states whose orthogonality time is limited by the Mandelstam–Tamm bound from those restricted by the Margolus–Levitin one. Our results offer a complete characterization of the physical quantities that become relevant in both the preparation and study of the dynamics of three-level states evolving towards orthogonality.

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Molecular Classification and Tumor Microenvironment Characterization of Gallbladder Cancer by Comprehensive Genomic and Transcriptomic Analysis

Cancers ◽

10.3390/cancers13040733 ◽

2021 ◽

Vol 13 (4) ◽

pp. 733

Author(s):

Nobutaka Ebata ◽

Masashi Fujita ◽

Shota Sasagawa ◽

Kazuhiro Maejima ◽

Yuki Okawa ◽

...

Keyword(s):

Tumor Microenvironment ◽

Gallbladder Cancer ◽

Epithelial To Mesenchymal Transition ◽

Molecular Classification ◽

Mesenchymal Transition ◽

Elevated Expression ◽

Fresh Frozen ◽

Therapeutic Decision Making

Gallbladder cancer (GBC), a rare but lethal disease, is often diagnosed at advanced stages. So far, molecular characterization of GBC is insufficient, and a comprehensive molecular portrait is warranted to uncover new targets and classify GBC. We performed a transcriptome analysis of both coding and non-coding RNAs from 36 GBC fresh-frozen samples. The results were integrated with those of comprehensive mutation profiling based on whole-genome or exome sequencing. The clustering analysis of RNA-seq data facilitated the classification of GBCs into two subclasses, characterized by high or low expression levels of TME (tumor microenvironment) genes. A correlation was observed between gene expression and pathological immunostaining. TME-rich tumors showed significantly poor prognosis and higher recurrence rate than TME-poor tumors. TME-rich tumors showed overexpression of genes involved in epithelial-to-mesenchymal transition (EMT) and inflammation or immune suppression, which was validated by immunostaining. One non-coding RNA, miR125B1, exhibited elevated expression in stroma-rich tumors, and miR125B1 knockout in GBC cell lines decreased its invasion ability and altered the EMT pathway. Mutation profiles revealed TP53 (47%) as the most commonly mutated gene, followed by ELF3 (13%) and ARID1A (11%). Mutations of ARID1A, ERBB3, and the genes related to the TGF-β signaling pathway were enriched in TME-rich tumors. This comprehensive analysis demonstrated that TME, EMT, and TGF-β pathway alterations are the main drivers of GBC and provides a new classification of GBCs that may be useful for therapeutic decision-making.

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Characterization of alternative splicing events and prognostic signatures in breast cancer

BMC Cancer ◽

10.1186/s12885-021-08305-6 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Pihua Han ◽

Jingjun Zhu ◽

Guang Feng ◽

Zizhang Wang ◽

Yanni Ding

Keyword(s):

Breast Cancer ◽

Alternative Splicing ◽

Proportional Hazards ◽

Pearson Correlation ◽

Original Data ◽

Cox Proportional Hazards ◽

Prognostic Indicators ◽

Splicing Factors ◽

Rna Seq

Abstract Background Breast cancer (BRCA) is one of the most common cancers worldwide. Abnormal alternative splicing (AS) frequently observed in cancers. This study aims to demonstrate AS events and signatures that might serve as prognostic indicators for BRCA. Methods Original data for all seven types of splice events were obtained from TCGA SpliceSeq database. RNA-seq and clinical data of BRCA cohorts were downloaded from TCGA database. Survival-associated AS events in BRCA were analyzed by univariate COX proportional hazards regression model. Prognostic signatures were constructed for prognosis prediction in patients with BRCA based on survival-associated AS events. Pearson correlation analysis was performed to measure the correlation between the expression of splicing factors (SFs) and the percent spliced in (PSI) values of AS events. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted to demonstrate pathways in which survival-associated AS event is enriched. Results A total of 45,421 AS events in 21,232 genes were identified. Among them, 1121 AS events in 931 genes significantly correlated with survival for BRCA. The established AS prognostic signatures of seven types could accurately predict BRCA prognosis. The comprehensive AS signature could serve as independent prognostic factor for BRCA. A SF-AS regulatory network was therefore established based on the correlation between the expression levels of SFs and PSI values of AS events. Conclusions This study revealed survival-associated AS events and signatures that may help predict the survival outcomes of patients with BRCA. Additionally, the constructed SF-AS networks in BRCA can reveal the underlying regulatory mechanisms in BRCA.

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Practical classification of triple-negative breast cancer: intratumoral heterogeneity, mechanisms of drug resistance, and novel therapies

npj Breast Cancer ◽

10.1038/s41523-020-00197-2 ◽

2020 ◽

Vol 6 (1) ◽

Author(s):

Antonio Marra ◽

Dario Trapani ◽

Giulia Viale ◽

Carmen Criscitiello ◽

Giuseppe Curigliano

Keyword(s):

Breast Cancer ◽

Triple Negative Breast Cancer ◽

Triple Negative ◽

Residual Disease ◽

Therapeutic Approaches ◽

Minimal Residual Disease Monitoring ◽

Anticancer Treatment ◽

Immune Contexture

Abstract Triple-negative breast cancer (TNBC) is not a unique disease, encompassing multiple entities with marked histopathological, transcriptomic and genomic heterogeneity. Despite several efforts, transcriptomic and genomic classifications have remained merely theoretic and most of the patients are being treated with chemotherapy. Driver alterations in potentially targetable genes, including PIK3CA and AKT, have been identified across TNBC subtypes, prompting the implementation of biomarker-driven therapeutic approaches. However, biomarker-based treatments as well as immune checkpoint inhibitor-based immunotherapy have provided contrasting and limited results so far. Accordingly, a better characterization of the genomic and immune contexture underpinning TNBC, as well as the translation of the lessons learnt in the metastatic disease to the early setting would improve patients’ outcomes. The application of multi-omics technologies, biocomputational algorithms, assays for minimal residual disease monitoring and novel clinical trial designs are strongly warranted to pave the way toward personalized anticancer treatment for patients with TNBC.

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Kraepelin revisited: a reassessment and statistical analysis of dementia praecox and manic-depressive insanity in 1908

Psychological Medicine ◽

10.1017/s0033291700026337 ◽

1993 ◽

Vol 23 (4) ◽

pp. 843-858 ◽

Cited By ~ 47

Author(s):

A. Jablensky ◽

H. Hugler ◽

M. Von Cranach ◽

K. Kalinov

Keyword(s):

Meta Analysis ◽

Original Data ◽

Dementia Praecox ◽

Schizoaffective Disorders ◽

Homogeneous Groups ◽

Manic Depressive ◽

Original Case ◽

State Examination ◽

Dichotomous Classification

SynopsisA meta-analysis was carried out on 53 cases of dementia praecox (DP) and 134 cases of manic-depressive insanity (MDI) originally diagnosed by Kraepelin or his collaborators in Munich in 1908. The original case material was coded in terms of Present State Examination syndromes and analysed statistically for internal consistency and discrimination between the two diagnostic entities. Kraepelin's DP and MDI were found to define homogeneous groups of disorders which could be clearly distinguished from one another. A CATEGO re-classification of the cases revealed an 80·2% concordance rate between Kraepelin's diagnoses and ICD-9. Cluster analysis of the original data reproduced closely Kraepelin's dichotomous classification of the psychoses but suggested that DP was a narrower concept than schizophrenia today, while MDI was a composite group including both ‘typical’ manic-depressive illnesses and schizoaffective disorders.

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Off-line classification of Polish vowel spectra using artificial neural networks

Journal of the International Phonetic Association ◽

10.1017/s0025100304001537 ◽

2004 ◽

Vol 34 (1) ◽

pp. 37-52

Author(s):

Wiktor Jassem ◽

Waldemar Grygiel

Keyword(s):

Neural Networks ◽

Numerical Data ◽

Word List ◽

Original Data ◽

Data Matrix ◽

Probabilistic Neural Networks ◽

Independent Variable ◽

The Individual ◽

Vowel Phoneme

The mid-frequencies and bandwidths of formants 1–5 were measured at targets, at plus 0.01 s and at minus 0.01 s off the targets of vowels in a 100-word list read by five male and five female speakers, for a total of 3390 10-variable spectrum specifications. Each of the six Polish vowel phonemes was represented approximately the same number of times. The 3390* 10 original-data matrix was processed by probabilistic neural networks to produce a classification of the spectra with respect to (a) vowel phoneme, (b) identity of the speaker, and (c) speaker gender. For (a) and (b), networks with added input information from another independent variable were also used, as well as matrices of the numerical data appropriately normalized. Mean scores for classification with respect to phonemes in a multi-speaker design in the testing sets were around 95%, and mean speaker-dependent scores for the phonemes varied between 86% and 100%, with two speakers scoring 100% correct. The individual voices were identified between 95% and 96% of the time, and classifications of the spectra for speaker gender were practically 100% correct.

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