scholarly journals TRAMPOline: a Temporal Relative Abundance-focused multi-sPecies Occupancy model, illustrated using fossils

2021 ◽  
Author(s):  
Trond Reitan ◽  
Torbjørn Ergon ◽  
Lee Hsiang Liow
Keyword(s):  
Relative Abundance ◽  
Biased Sampling ◽  
Geological Time ◽  
Modeling Framework ◽  
Time Intervals ◽  
Occupancy Model ◽  
Focal Species ◽  
Additional Information ◽  
Wide Range ◽  
Species Occupancy

The occupancy and relative abundance of species are temporally varying. Estimating these, given incomplete and biased sampling is challenging, not least for fossilized organisms, where preservation is an additional issue. Here, we describe a relative abundance-focused multi-species occupancy model (TRAMPOline) in a hierarchical Bayesian framework. We designed our model on the basis of the need to understand the dynamics of several focal species over 2.3 million years, by drawing on additional information provided by non-focal species observed in the same fossilized community. We expanded our model by adding random effects of species and time intervals (geological formations) and explored potential explanatory factors (paleoenvironmental proxies) and temporal autocorrelation that could provide extra information on unsampled geological time intervals. Our new model, set in an occupancy modeling framework widely used in ecology but little applied in paleoecology, is applicable across a wide range of questions on species-level dynamics in contemporary and palaeoecological community settings.

scholarly journals Relative species abundance and population densities of the past; developing multi-species occupancy models for fossil data

2021 ◽  
Author(s):  
Trond Reitan ◽  
Torbjørn Ergon ◽  
Lee Hsiang Liow
Keyword(s):  
Species Abundance ◽  
Biased Sampling ◽  
Occupancy Models ◽  
Geological Time ◽  
Population Densities ◽  
Time Intervals ◽  
Relative Population ◽  
Modelling Framework ◽  
Wide Range ◽  
Species Occupancy

The number of individuals of species within communities varies, but estimating abundance, given incomplete and biased sampling, is challenging. Here, we describe a new occupancy model in a hierarchical Bayesian framework with random effects, where multi-species occupancy and detection are modeled as a means to estimate relative species abundance and relative population densities. The modelling framework is suited for occupancy data for temporal samples of fossil communities with repeated sampling including multiple species with similar preservation potential. We demonstrate our modelling framework using a fossil community of benthic organisms to estimate changing relative species abundance dynamics and relative population densities of focal species in 9 (geological) time-intervals over 2.3 million years. We also explored potential explanatory factors (paleoenvironmental proxies) and temporal autocorrelation that could provide extra information on unsampled time-intervals. The modelling framework is applicable across a wide range of questions on species-level dynamics in (palaeo)ecological community settings.

scholarly journals EXPRESS: Overcoming the Cold Start Problem of CRM using a Probabilistic Machine Learning Approach

2021 ◽  
pp. 002224372110329
Author(s):  
Nicolas Padilla ◽  
Eva Ascarza
Keyword(s):  
Machine Learning ◽  
Cold Start ◽  
Customer Relationship ◽  
Exponential Families ◽  
Modeling Framework ◽  
Wide Range ◽  
The Moment ◽  
Probabilistic Machine Learning ◽  
Marketing Actions ◽  
Cold Start Problem

The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to identify and leverage differences across customers — a very diffcult task when firms attempt to manage new customers, for whom only the first purchase has been observed. For those customers, the lack of repeated observations poses a structural challenge to inferring unobserved differences across them. This is what we call the “cold start” problem of CRM, whereby companies have difficulties leveraging existing data when they attempt to make inferences about customers at the beginning of their relationship. We propose a solution to the cold start problem by developing a probabilistic machine learning modeling framework that leverages the information collected at the moment of acquisition. The main aspect of the model is that it exibly captures latent dimensions that govern the behaviors observed at acquisition as well as future propensities to buy and to respond to marketing actions using deep exponential families. The model can be integrated with a variety of demand specifications and is exible enough to capture a wide range of heterogeneity structures. We validate our approach in a retail context and empirically demonstrate the model's ability at identifying high-value customers as well as those most sensitive to marketing actions, right after their first purchase.

Patterns of Evolution of the Ediacaran Soft-Bodied Biota

2014 ◽  
Vol 88 (2) ◽  
pp. 269-283 ◽  
Author(s):  
Dmitriy Grazhdankin
Keyword(s):  
High Energy ◽  
Ecosystem Engineering ◽  
Low Energy ◽  
Geological Time ◽  
Time Intervals ◽  
Inner Shelf ◽  
Sedimentary Environments ◽  
Burrowing Activity ◽  
Ecological Associations ◽  
Channel Systems

When each of the Avalon-, Ediacara-, and Nama-type fossil assemblages are tracked through geological time, there appear to be changes in species composition and diversity, almost synchronized between different sedimentary environments, allowing a subdivision of the late Ediacaran into the Redkinian, Belomorian and Kotlinian geological time intervals. The Redkinian (580–559 Ma) is characterized by first appearance of both eumetazoan traces and macroscopic organisms (frondomorphs and vendobionts) in a form of Avalon-type communities in the inner shelf environment, whereas coeval Ediacara-type communities remained depauperate. The Belomorian (559–550 Ma) is marked by the advent of eumetazoan burrowing activity in the inner shelf, diversification of frondomorphs, migration of vendobionts from the inner shelf into higher energy environments, and appearance of tribrachiomorphs and bilateralomorphs. Ediacaran organisms formed distinctive ecological associations that coexisted in the low-energy inner shelf (Avalon-type communities), in the wave- and current-agitated shoreface (Ediacara-type communities), and in the high-energy distributary systems (Nama-type communities). The Kotlinian (550–540 Ma) witnessed an expansion of the burrowing activity into wave- and current-agitated shoreface, disappearance of vendobionts, tribrachiomorphs and bilateralomorphs in wave- and current-agitated shoreface, together with a drop in frondomorph diversity. High-energy distributary channel systems of prodeltas served as refugia for Nama-type communities that survived until the end of the Ediacaran and disappeared when the burrowing activity reached high-energy environments. This pattern is interpreted as an expression of ecosystem engineering by eumetazoans, with the Ediacaran organisms being progressively outcompeted by bilaterians.

Modeling framework for IoT integration of building automation systems

2017 ◽  
Vol 65 (9) ◽  
Author(s):  
Daniel Schachinger ◽  
Andreas Fernbach ◽  
Wolfgang Kastner
Keyword(s):  
Web Services ◽  
Web Service ◽  
Building Automation ◽  
Modeling Framework ◽  
Seamless Integration ◽  
Automation Systems ◽  
Wide Range ◽  
Machine To Machine Communication ◽  
Machine Communication ◽  
The Internet Of Things

AbstractAdvancements within the Internet of Things are leading to a pervasive integration of different domains including also building automation systems. As a result, device functionality becomes available to a wide range of applications and users outside of the building automation domain. In this context, Web services are identified as suitable solution for machine-to-machine communication. However, a major requirement to provide necessary interoperability is the consideration of underlying semantics. Thus, this work presents a universal framework for tag-based semantic modeling and seamless integration of building automation systems via Web service-based technologies. Using the example of the KNX Web services specification, the applicability of this approach is pointed out.

scholarly journals A two-species occupancy model accommodating simultaneous spatial and interspecific dependence

Ecology ◽  
2016 ◽  
Vol 97 (1) ◽  
pp. 48-53 ◽  
Author(s):  
Christopher T. Rota ◽  
Christopher K. Wikle ◽  
Roland W. Kays ◽  
Tavis D. Forrester ◽  
William J. McShea ◽  
...  
Keyword(s):  
Occupancy Model ◽  
Species Occupancy

scholarly journals A comparative survey of the impacts of extreme rainfall in two international case studies

2017 ◽  
Author(s):  
Matthieu Spekkers ◽  
Viktor Rözer ◽  
Annegret Thieken ◽  
Marie-Claire ten Veldhuis ◽  
Heidi Kreibich
Keyword(s):  
Case Studies ◽  
Online Survey ◽  
Residential Buildings ◽  
Age Groups ◽  
Extreme Rainfall ◽  
Water Levels ◽  
Economic Losses ◽  
Biased Sampling ◽  
Wide Range ◽  
Damage Data

Abstract. Flooding is assessed as the most important natural hazard in Europe, causing thousands of deaths, affecting millions of people and accounting for large economic losses in the past decade. Little is known about the damage processes associated with extreme rainfall in cities, due to a lack of accurate, comparable and consistent damage data. The objective of this study is to investigate the impacts of extreme rainfall on residential buildings and how affected households coped with these impacts in terms of precautionary and emergency actions. Analyses are based on a unique dataset of damage characteristics and a wide range of potential damage explaining variables at the household level, collected through computer-aided telephone interviews (CATI) and an online survey. Exploratory data analyses based on a total of 859 completed questionnaires in the cities of Münster (Germany) and Amsterdam (the Netherlands) revealed that the uptake of emergency measures is related to characteristics of the hazardous event. In case of high water levels, more efforts are made to reduce damage, while emergency response that aims to prevent damage is less likely to be effective. The difference in magnitude of the events in Münster and Amsterdam in terms of rainfall intensity and water depth, is probably also the most important cause for the differences between the cities in terms of the suffered financial losses. Factors that significantly contributed to damage in at least one of the case studies are water contamination, the presence of a basement in the building and people's awareness of the upcoming event. Moreover, this study confirms conclusions by previous studies that people's experience with damaging events positively correlates with precautionary behaviour. For improving future damage data acquisition, we recommend to include cell-phones in a CATI survey to avoid biased sampling towards certain age groups.

scholarly journals Channel-independent recreation of artefactual signals in chronically recorded local field potentials using machine learning

2022 ◽  
Vol 9 (1) ◽  
Author(s):  
Marcos Fabietti ◽  
Mufti Mahmud ◽  
Ahmad Lotfi
Keyword(s):  
Machine Learning ◽  
Open Access ◽  
Short Term Memory ◽  
The Body ◽  
Data Sets ◽  
Additional Information ◽  
Machine Learning Model ◽  
Signal Characteristics ◽  
Wide Range ◽  
Memory Network

AbstractAcquisition of neuronal signals involves a wide range of devices with specific electrical properties. Combined with other physiological sources within the body, the signals sensed by the devices are often distorted. Sometimes these distortions are visually identifiable, other times, they overlay with the signal characteristics making them very difficult to detect. To remove these distortions, the recordings are visually inspected and manually processed. However, this manual annotation process is time-consuming and automatic computational methods are needed to identify and remove these artefacts. Most of the existing artefact removal approaches rely on additional information from other recorded channels and fail when global artefacts are present or the affected channels constitute the majority of the recording system. Addressing this issue, this paper reports a novel channel-independent machine learning model to accurately identify and replace the artefactual segments present in the signals. Discarding these artifactual segments by the existing approaches causes discontinuities in the reproduced signals which may introduce errors in subsequent analyses. To avoid this, the proposed method predicts multiple values of the artefactual region using long–short term memory network to recreate the temporal and spectral properties of the recorded signal. The method has been tested on two open-access data sets and incorporated into the open-access SANTIA (SigMate Advanced: a Novel Tool for Identification of Artefacts in Neuronal Signals) toolbox for community use.

scholarly journals Impact of time zones on forecasting of exchange market based on distribution of expected values

2016 ◽  
Author(s):  
Nijolė Maknickienė ◽  
Algirdas Maknickas
Keyword(s):  
New York ◽  
Exchange Rates ◽  
Historical Data ◽  
Trading Strategies ◽  
Exchange Market ◽  
Time Intervals ◽  
Additional Information ◽  
Forecasting Method ◽  
Time Zones ◽  
Expected Values

Forecasting of chaotic changes of exchange rates usually is based on historical data and depends on the choice of time intervals. This study seeks to develop new forecasting method based on data of different time zones. This paper demonstrates how the using of London and New York divisions of the trading day allows getting additional information from predicting exchange rates. This was modelled with the help of ensemble of EVOLINO for obtaining of predictions of the distribution of expected values. The obtained results show that double forecasts evaluation reveals a possible trend in the exchange market and enriches the choice of real-time trading strategies.

scholarly journals Recommendations for the Protocol of functional examination of the anorectal zone and disorders classification: the International Anorectal Physiology Working Group consensus and Russian real-world practice

2020 ◽  
Vol 92 (12) ◽  
pp. 105-119
Author(s):  
O. Yu. Fomenko ◽  
S. V. Morozov ◽  
S. Mark Scott ◽  
H. Charles Knowles ◽  
D. A. Morozov ◽  
...  
Keyword(s):  
Real World ◽  
Working Group ◽  
Anorectal Function ◽  
Anorectal Physiology ◽  
Rectal Sensation ◽  
High Resolution Manometry ◽  
Additional Information ◽  
Wide Range ◽  
Balloon Expulsion ◽  
Function Testing

This manuscript summarizes consensus reached by the International Anorectal Physiology Working Group (IAPWG) for the performance, terminology used, and interpretation of anorectal function testing including anorectal manometry (focused on high-resolution manometry), the rectal sensory test, and the balloon expulsion test. Based on these measurements, a classification system for disorders of anorectal function is proposed. Aim to provide information about methods of diagnosis and new classification of functional anorectal disorders to a wide range of specialists general practitioners, therapists, gastroenterologists, coloproctologists all who face the manifestations of these diseases in everyday practice and determine the diagnostic and therapeutic algorithm. Current paper provides agreed statements of IAPWG Consensus and comments (in italics) of Russian experts on real-world practice, mainly on methodology of examination. These comments in no way intended to detract from the provisions agreed by the international group of experts. We hope that these comments will help to improve the quality of examination based on the systematization of local experience with the use of the methods discussed and the results obtained. Key recommendations: the International Anorectal Physiology Working Group protocol for the performance of anorectal function testing recommends a standardized sequence of maneuvers to test rectoanal reflexes, anal tone and contractility, rectoanal coordination, and rectal sensation. Major findings not seen in healthy controls defined by the classification are as follows: rectoanal areflexia, anal hypotension and hypocontractility, rectal hyposensitivity, and hypersensitivity. Minor and inconclusive findings that can be present in health and require additional information prior to diagnosis include anal hypertension and dyssynergia.

Causes for Large-Scale Hydrographic Changes at the Hawaii Ocean Time Series Station

2008 ◽  
Vol 38 (9) ◽  
pp. 1931-1948 ◽  
Author(s):  
D. Stammer ◽  
S. Park ◽  
A. Köhl ◽  
R. Lukas ◽  
F. Santiago-Mandujano
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Global Ocean ◽  
Modeling Framework ◽  
Decadal Time Scale ◽  
Quasi Biennial Oscillation ◽  
Salinity Field ◽  
Additional Information ◽  
Independent Observations ◽  
Station Aloha

Abstract Results from Estimating the Circulation and Climate of the Ocean (ECCO)–Scripps Institution of Oceanography (SIO) global ocean state estimate, available over the 11-yr period 1992 through 2002, are compared with independent observations available at the Hawaii Ocean time series station ALOHA. The comparison shows that at this position, the estimated temporal variability has some skill in simulating observed ocean variability and that the quality of future syntheses could benefit from additional information available from the Argo network and from the time series observations themselves. On a decadal time scale, the influence radius of the station ALOHA T–S time series covers large parts of the tropical and subtropical Pacific Ocean and reaches even into the Indian Ocean through the Indonesian Throughflow. Estimated changes in sea surface height (SSH) result largely from thermosteric changes; however, nonsteric (barotropic) variations on the order of 1–2 cm also contribute to SSH changes at station ALOHA. Moreover, changes of similar magnitude can be caused by changes in the salinity field because of a quasi-biennial oscillation in the horizontal flow structure and heaving of the mean salinity structure on seasonal and interannual time scales. The adjoint modeling framework confirms westward-propagating Rossby waves (due to wind forcing) and subduction of water-mass anomalies (due to surface buoyancy forcing) as the primary mechanisms leading to observed changes of T–S structures at station ALOHA. Specifically, the analysis identifies surface freshwater fluxes along the wintertime outcrop of intermediate waters as a primary cause for salinity changes at station ALOHA and wind stress forcing east of the station position as another forcing mechanism of salinity variations around the Hawaiian Archipelago.

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