Spatio-Temporal Chaos in Time Evolution of BEC with Attractive Two-Body Interactions

Metropolitan age-specific mortality trends at borough and neighbourhood level: The case of Mexico City

10.21203/rs.2.19611/v2 ◽

2020 ◽

Author(s):

Karol Baca-Lopez ◽

Cristobal Fresno ◽

Jesus Espinal-Enriquez ◽

Miriam V. Flores-Merino ◽

Miguel A. Camacho-Lopez ◽

...

Keyword(s):

Public Policy ◽

Time Evolution ◽

Mexico City ◽

Study Groups ◽

Mortality Rates ◽

Mortality Trends ◽

Mixed Effect ◽

Mixed Effect Models ◽

Specific Mortality ◽

Spatio Temporal

Abstract Background Understanding the spatial and temporal patterns of mortality rates in a highly inhomogeneous metropolis, is a matter of public policy interest. In this context, there is no previous study that correlates both spatio-temporal and age-specific mortality rates in Mexico City. Methods Spatio-temporal kriging modelling was used over six age-specific mortality rates (from the years 2000 to 2016 in Mexico City), to gain both spatial (borough and neighbourhood) and temporal (year and trimester) data level description. Resulting data were modelled using time-evolution mixed effect models to unblurred mortality age-specific patterns. Posterior tests were carried out to compare mortality averages between geospatial locations. Results Mortality correlation extends in all study groups for as long as 12 years and as far as 13.27 km. The highest mortality rate takes place in the Cuauhtémoc borough, as it is the commercial, touristic and cultural core downtown Mexico City. On the contrary, Tlalpan borough is the one with the lowest mortality rates in all the study groups. Interestingly, post-productive mortality is the first age-specific cause of death, followed by infant, productive, pre-school and scholar groups. Conclusion The combinations of spatio-temporal Kriging estimation and time-evolution mixed effect models, allowed us to unveil relevant time and location trends that may be useful for public policy planning in Mexico City.

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Metropolitan age-specific mortality trends at borough and neighbourhood level: The case of Mexico City

10.21203/rs.2.19611/v1 ◽

2020 ◽

Author(s):

Karol Baca-Lopez ◽

Cristobal Fresno ◽

Jesus Espinal-Enriquez ◽

Miriam V. Flores-Merino ◽

Miguel A. Camacho-Lopez ◽

...

Keyword(s):

Public Policy ◽

Time Evolution ◽

Mexico City ◽

Study Groups ◽

Mortality Rates ◽

Mortality Trends ◽

Mixed Effect ◽

Mixed Effect Models ◽

Specific Mortality ◽

Spatio Temporal

Abstract Background Understanding the spatial and temporal patterns of mortality rates in a highly inhomogeneous metropolis, is a matter of public policy interest. In this context, there is no previous study that correlates both spatio-temporal and age-specific mortality rates in Mexico City. Methods Spatio-temporal kriging modelling was used over six age-specific mortality rates (from the years 2000 to 2016 in Mexico City), to gain both spatial (borough and neighbourhood) and temporal (year and trimester) data level description. Resulting data were modelled using time-evolution mixed effect models to unblurred mortality age-specific patterns. Posterior tests were carried out to compare mortality averages between geospatial locations. Results Mortality correlation extends in all study groups for as long as 12 years and as far as 13.27 km. The highest mortality rate takes place in the Cuauhtémoc borough, as it is the commercial, touristic and cultural core downtown Mexico City. On the contrary, Tlalpan borough is the one with the lowest mortality rates in all the study groups. Interestingly, post-productive mortality is the first age-specific cause of death, followed by infant, productive, pre-school and scholar groups. Conclusion The combinations of spatio-temporal Kriging estimation and time-evolution mixed effect models, allowed us to unveil relevant time and location trends that may be useful for public policy planning in Mexico City.

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Metropolitan age-specific mortality trends at borough and neighbourhood level: The case of Mexico City

10.21203/rs.2.24094/v1 ◽

2020 ◽

Author(s):

Karol Baca-Lopez ◽

Cristobal Fresno ◽

Jesus Espinal-Enriquez ◽

Miriam V. Flores-Merino ◽

Miguel A. Camacho-Lopez ◽

...

Keyword(s):

Public Policy ◽

Time Evolution ◽

Mexico City ◽

Study Groups ◽

Mortality Rates ◽

Mortality Trends ◽

Mixed Effect ◽

Mixed Effect Models ◽

Specific Mortality ◽

Spatio Temporal

Abstract BackgroundUnderstanding the spatial and temporal patterns of mortality rates in a highly inhomogeneous metropolis, is a matter of public policy interest. In this context, there is no previous study that correlates both spatio-temporal and age-specific mortality rates in Mexico City. Methods Spatio-temporal kriging modelling was used over six age-specific mortality rates (from the years 2000 to 2016 in Mexico City), to gain both spatial (borough and neighbourhood) and temporal (year and trimester) data level description. Resulting data were modelled using time-evolution mixed effect models to unblurred mortality age-specific patterns. Posterior tests were carried out to compare mortality averages between geospatial locations. Results Mortality correlation extends in all study groups for as long as 12 years and as far as 13.27 km. The highest mortality rate takes place in the Cuauhtémoc borough, as it is the commercial, touristic and cultural core downtown Mexico City. On the contrary, Tlalpan borough is the one with the lowest mortality rates in all the study groups. Interestingly, post-productive mortality is the first age-specific cause of death, followed by infant, productive, pre-school and scholar groups. Conclusion The combinations of spatio-temporal Kriging estimation and time-evolution mixed effect models, allowed us to unveil relevant time and location trends that may be useful for public policy planning in Mexico City.

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Spatio-temporal variability of the photospheric magnetic field

Proceedings of the International Astronomical Union ◽

10.1017/s1743921311006946 ◽

2010 ◽

Vol 6 (S274) ◽

pp. 204-206

Author(s):

A. Vecchio ◽

M. Laurenza ◽

D. Meduri ◽

V. Carbone ◽

M. Storini

Keyword(s):

Magnetic Field ◽

Time Evolution ◽

Empirical Mode Decomposition ◽

Temporal Variability ◽

Solar Magnetic Field ◽

Temporal Dynamics ◽

Heliographic Latitude ◽

Preliminary Results ◽

Mode Decomposition ◽

Spatio Temporal

AbstractThe spatio-temporal dynamics of the solar magnetic field has been investigated by using NSO/Kitt Peak synoptic magnetic maps covering ~28 yr. For each heliographic latitude the field has been analyzed through the Empirical Mode Decomposition, in order to investigate the time evolution of the various characteristic oscillating frequencies. Preliminary results are discussed.

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E3 ubiquitin ligases

Essays in Biochemistry ◽

10.1042/bse0410015 ◽

2005 ◽

Vol 41 ◽

pp. 15-30 ◽

Cited By ~ 123

Author(s):

Helen C. Ardley ◽

Philip A. Robinson

Keyword(s):

Protein Complexes ◽

Loss Of Function ◽

Direct Role ◽

Cellular Processes ◽

Substrate Protein ◽

Protein Ubiquitination ◽

C Terminus ◽

Full Complement ◽

Spatio Temporal ◽

Eukaryotic Organisms

The selectivity of the ubiquitin–26 S proteasome system (UPS) for a particular substrate protein relies on the interaction between a ubiquitin-conjugating enzyme (E2, of which a cell contains relatively few) and a ubiquitin–protein ligase (E3, of which there are possibly hundreds). Post-translational modifications of the protein substrate, such as phosphorylation or hydroxylation, are often required prior to its selection. In this way, the precise spatio-temporal targeting and degradation of a given substrate can be achieved. The E3s are a large, diverse group of proteins, characterized by one of several defining motifs. These include a HECT (homologous to E6-associated protein C-terminus), RING (really interesting new gene) or U-box (a modified RING motif without the full complement of Zn2+-binding ligands) domain. Whereas HECT E3s have a direct role in catalysis during ubiquitination, RING and U-box E3s facilitate protein ubiquitination. These latter two E3 types act as adaptor-like molecules. They bring an E2 and a substrate into sufficiently close proximity to promote the substrate's ubiquitination. Although many RING-type E3s, such as MDM2 (murine double minute clone 2 oncoprotein) and c-Cbl, can apparently act alone, others are found as components of much larger multi-protein complexes, such as the anaphase-promoting complex. Taken together, these multifaceted properties and interactions enable E3s to provide a powerful, and specific, mechanism for protein clearance within all cells of eukaryotic organisms. The importance of E3s is highlighted by the number of normal cellular processes they regulate, and the number of diseases associated with their loss of function or inappropriate targeting.

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Elucidating cyclic AMP signaling in subcellular domains with optogenetic tools and fluorescent biosensors

Biochemical Society Transactions ◽

10.1042/bst20190246 ◽

2019 ◽

Vol 47 (6) ◽

pp. 1733-1747 ◽

Cited By ~ 3

Author(s):

Christina Klausen ◽

Fabian Kaiser ◽

Birthe Stüven ◽

Jan N. Hansen ◽

Dagmar Wachten

Keyword(s):

Cyclic Amp ◽

Adenosine Monophosphate ◽

Adenylyl Cyclases ◽

Temporal Precision ◽

Fluorescent Biosensors ◽

Subcellular Domains ◽

Spatio Temporal ◽

Hydrolysis Of ◽

Shed Light ◽

Cyclic Amp Signaling

The second messenger 3′,5′-cyclic nucleoside adenosine monophosphate (cAMP) plays a key role in signal transduction across prokaryotes and eukaryotes. Cyclic AMP signaling is compartmentalized into microdomains to fulfil specific functions. To define the function of cAMP within these microdomains, signaling needs to be analyzed with spatio-temporal precision. To this end, optogenetic approaches and genetically encoded fluorescent biosensors are particularly well suited. Synthesis and hydrolysis of cAMP can be directly manipulated by photoactivated adenylyl cyclases (PACs) and light-regulated phosphodiesterases (PDEs), respectively. In addition, many biosensors have been designed to spatially and temporarily resolve cAMP dynamics in the cell. This review provides an overview about optogenetic tools and biosensors to shed light on the subcellular organization of cAMP signaling.

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