scholarly journals Supplemental Material: Fossilization potential of marine assemblages and environments

2020 ◽  
Author(s):  
Jack Shaw ◽  
et al.
Keyword(s):  
Data Processing ◽  
Predictive Modeling ◽  
Additional Information ◽  
Sampling Biases ◽  
The Impact

Additional information about data processing, taxon- and geography-specific analyses, other sampling biases, determinants of fossilization potential, predictive modeling procedures, and the impact of Lagerstätten on estimating fossilization potential.<br>

scholarly journals Supplemental Material: Fossilization potential of marine assemblages and environments

2020 ◽  
Author(s):  
Jack Shaw ◽  
et al.
Keyword(s):  
Data Processing ◽  
Predictive Modeling ◽  
Additional Information ◽  
Sampling Biases ◽  
The Impact

Additional information about data processing, taxon- and geography-specific analyses, other sampling biases, determinants of fossilization potential, predictive modeling procedures, and the impact of Lagerstätten on estimating fossilization potential.<br>

News and Idiosyncratic Volatility: The Public Information Processing Hypothesis*

2020 ◽  
Author(s):  
Robert F Engle ◽  
Martin Klint Hansen ◽  
Ahmet K Karagozoglu ◽  
Asger Lunde
Keyword(s):  
Information Processing ◽  
Public Information ◽  
Selection Procedure ◽  
Autoregressive Process ◽  
Return Volatility ◽  
Market Outcomes ◽  
The Public ◽  
Additional Information ◽  
Financial News ◽  
The Impact

Abstract Motivated by the recent availability of extensive electronic news databases and advent of new empirical methods, there has been renewed interest in investigating the impact of financial news on market outcomes for individual stocks. We develop the information processing hypothesis of return volatility to investigate the relation between firm-specific news and volatility. We propose a novel dynamic econometric specification and test it using time series regressions employing a machine learning model selection procedure. Our empirical results are based on a comprehensive dataset comprised of more than 3 million news items for a sample of 28 large U.S. companies. Our proposed econometric specification for firm-specific return volatility is a simple mixture model with two components: public information and private processing of public information. The public information processing component is defined by the contemporaneous relation with public information and volatility, while the private processing of public information component is specified as a general autoregressive process corresponding to the sequential price discovery mechanism of investors as additional information, previously not publicly available, is generated and incorporated into prices. Our results show that changes in return volatility are related to public information arrival and that including indicators of public information arrival explains on average 26% (9–65%) of changes in firm-specific return volatility.

scholarly journals Grading Investment Diversification Options in Presence of Non-Historical Financial Information

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 692
Author(s):  
Clara Calvo ◽  
Carlos Ivorra ◽  
Vicente Liern ◽  
Blanca Pérez-Gladish
Keyword(s):  
Risk Measure ◽  
Statistical Information ◽  
Expected Returns ◽  
Financial Assets ◽  
Expected Return ◽  
Additional Information ◽  
Subjective Risk ◽  
The Impact ◽  
Statistical Risk ◽  
Reduction Index

Modern portfolio theory deals with the problem of selecting a portfolio of financial assets such that the expected return is maximized for a given level of risk. The forecast of the expected individual assets’ returns and risk is usually based on their historical returns. In this work, we consider a situation in which the investor has non-historical additional information that is used for the forecast of the expected returns. This implies that there is no obvious statistical risk measure any more, and it poses the problem of selecting an adequate set of diversification constraints to mitigate the risk of the selected portfolio without losing the value of the non-statistical information owned by the investor. To address this problem, we introduce an indicator, the historical reduction index, measuring the expected reduction of the expected return due to a given set of diversification constraints. We show that it can be used to grade the impact of each possible set of diversification constraints. Hence, the investor can choose from this gradation, the set better fitting his subjective risk-aversion level.

Survey Data Quality in Analyzing Harmonized Indicators of Protest Behavior: A Survey Data Recycling Approach

2021 ◽  
pp. 000276422110216
Author(s):  
Kazimierz M. Slomczynski ◽  
Irina Tomescu-Dubrow ◽  
Ilona Wysmulek
Keyword(s):  
Data Processing ◽  
Data Quality ◽  
Survey Data ◽  
A Priori ◽  
Data Sets ◽  
New Approach ◽  
Survey Quality ◽  
Survey Error ◽  
Ex Post ◽  
The Impact

This article proposes a new approach to analyze protest participation measured in surveys of uneven quality. Because single international survey projects cover only a fraction of the world’s nations in specific periods, researchers increasingly turn to ex-post harmonization of different survey data sets not a priori designed as comparable. However, very few scholars systematically examine the impact of the survey data quality on substantive results. We argue that the variation in source data, especially deviations from standards of survey documentation, data processing, and computer files—proposed by methodologists of Total Survey Error, Survey Quality Monitoring, and Fitness for Intended Use—is important for analyzing protest behavior. In particular, we apply the Survey Data Recycling framework to investigate the extent to which indicators of attending demonstrations and signing petitions in 1,184 national survey projects are associated with measures of data quality, controlling for variability in the questionnaire items. We demonstrate that the null hypothesis of no impact of measures of survey quality on indicators of protest participation must be rejected. Measures of survey documentation, data processing, and computer records, taken together, explain over 5% of the intersurvey variance in the proportions of the populations attending demonstrations or signing petitions.

scholarly journals Tools for the Recognition of Sorting Signals and the Prediction of Subcellular Localization of Proteins From Their Amino Acid Sequences

2020 ◽  
Vol 11 ◽  
Author(s):  
Kenichiro Imai ◽  
Kenta Nakai
Keyword(s):  
Amino Acid ◽  
Subcellular Localization ◽  
Amino Acid Sequences ◽  
Additional Information ◽  
Sorting Signals ◽  
Specific Alternative ◽  
Cell Type Specific ◽  
Future Direction ◽  
The Impact ◽  
New Algorithms

At the time of translation, nascent proteins are thought to be sorted into their final subcellular localization sites, based on the part of their amino acid sequences (i.e., sorting or targeting signals). Thus, it is interesting to computationally recognize these signals from the amino acid sequences of any given proteins and to predict their final subcellular localization with such information, supplemented with additional information (e.g., k-mer frequency). This field has a long history and many prediction tools have been released. Even in this era of proteomic atlas at the single-cell level, researchers continue to develop new algorithms, aiming at accessing the impact of disease-causing mutations/cell type-specific alternative splicing, for example. In this article, we overview the entire field and discuss its future direction.

scholarly journals Technical note on measuring run-off dynamics from pavements using a new device: the weighable tipping bucket

2011 ◽  
Vol 15 (5) ◽  
pp. 1379-1386 ◽  
Author(s):  
T. Nehls ◽  
Y. Nam Rim ◽  
G. Wessolek
Keyword(s):  
High Resolution ◽  
Data Processing ◽  
Temporal Resolution ◽  
Hydrological Process ◽  
Flow Measurements ◽  
New Device ◽  
Run Off ◽  
Low Volume ◽  
Rain Events ◽  
The Impact

Abstract. Due to climate change, cities need to adapt to changing rainfall and rainwater run-off dynamics. In order to develop an corresponding process based run-off model for pavements, we had to improve the measurement technique to detect run-off dynamics in an appropriate high resolution. Traditional tipping buckets (TB) have a comparable low volume resolution, capable to quantify the highest intensities in a range of expected flows. This results in varying temporal resolutions for varying flow intensities, especially in low resolutions for small flow events. Therefore, their applicability for run-off measurements and other hydrological process studies is limited, especially when the dynamics of both small and big flow events shall be measured. We improved a TB by coupling it to a balance and called it weighable tipping bucket (WTB). This paper introduces the device set up and the according data processing concept. The improved volume and temporal resolution of the WTB are demonstrated. A systematic uncertainty of TB measurements compared to WTB measurements is calculated. The impact of that increased resolution on our understanding of run-off dynamics from paved urban soils are discussed, exemplary for the run-off and the surface storage of a paved urban soil. The study was conducted on a permeably paved lysimeter situated in Berlin, Germany. Referring to the paved surface, the TB has a resolution of 0.1 mm, while the WTB has a resolution of 0.001 mm. The temporal resolution of the WTB is 3 s, the TB detects individual tippings with 0.4 s between them. Therefore, the data processing concept combines both the benefits of the balance to measure small intensities with that of the TB to measure high flow intensities. During a five months period (July to November 2009) 154 rain events were detected. Accordingly, the TB and WTB detected 47 and 121 run-off events. The total run-off was 79.6 mm measured by the WTB which was 11 % higher than detected by the TB. 95 % of that difference can be appointed to water, which evaporated from the TB. To derive a surface storage estimation, we analyzed the WTB and TB data for rain events without run-off. According to WTB data, the surface storage of the permeable pavement is 1.7 mm, while using TB data leads to an overestimation of 47 % due to low volume resolution of the TB. Combining traditional TB with modern, fast, high resolution digital balances offers the opportunity to upgrade existing TB systems in order to improve their volume detection limit and their temporal resolution, which is of great advantage for the synchronization of water balance component measurements and the investigation of hydrological processes. Furthermore, we are able to quantify the uncertainty of flow measurements gained with traditional tipping buckets.

Toward functional proteomics of alveolar macrophages

2005 ◽  
Vol 288 (4) ◽  
pp. L585-L595 ◽  
Author(s):  
Haifeng M. Wu ◽  
Ming Jin ◽  
Clay B. Marsh
Keyword(s):  
Alveolar Macrophages ◽  
Large Scale ◽  
Cell Types ◽  
Mononuclear Phagocyte ◽  
Detection Sensitivity ◽  
Current Status ◽  
Blood Monocytes ◽  
Protein Patterns ◽  
Additional Information ◽  
The Impact

Alveolar macrophages (AM) belong to a phenotype of macrophages with distinct biological functions and important pathophysiological roles in lung health and disease. The molecular details determining AM differentiation from blood monocytes and AM roles in lung homeostasis are largely unknown. With the use of different technological platforms, advances in the field of proteomics have made it possible to search for differences in protein expression between AM and their precursor monocytes. Proteome features of each cell type provide new clues into understanding mononuclear phagocyte biology. In-depth analyses using subproteomics and subcellular proteomics offer additional information by providing greater protein resolution and detection sensitivity. With the use of proteomic techniques, large-scale mapping of phosphorylation differences between the cell types have become possible. Furthermore, two-dimensional gel proteomics can detect germline protein variants and evaluate the impact of protein polymorphisms on an individual's susceptibility to disease. Finally, surface-enhanced laser desorption and ionization (SELDI) time-of-flight mass spectrometry offers an alternative method to recognizing differences in protein patterns between AM and monocytes or between AM under different pathological conditions. This review details the current status of this field and outlines future directions in functional proteomic analyses of AM and monocytes. Furthermore, this review presents viewpoints of integrating proteomics with translational topics in lung diseases to define the mechanisms of disease and to uncover new diagnostic and therapeutic targets.

Multi-Variable, High Order, Performance Models (2005C)

2005 ◽  
Author(s):  
David Japikse ◽  
Oleg Dubitsky ◽  
Kerry N. Oliphant ◽  
Robert J. Pelton ◽  
Daniel Maynes ◽  
...  
Keyword(s):  
Data Processing ◽  
Large Data ◽  
High Order ◽  
Large Data Sets ◽  
Data Sets ◽  
Performance Models ◽  
Statistical Accuracy ◽  
Evaluation Methodologies ◽  
New Models ◽  
The Impact

In the course of developing advanced data processing and advanced performance models, as presented in companion papers, a number of basic scientific and mathematical questions arose. This paper deals with questions such as uniqueness, convergence, statistical accuracy, training, and evaluation methodologies. The process of bringing together large data sets and utilizing them, with outside data supplementation, is considered in detail. After these questions are focused carefully, emphasis is placed on how the new models, based on highly refined data processing, can best be used in the design world. The impact of this work on designs of the future is discussed. It is expected that this methodology will assist designers to move beyond contemporary design practices.

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