scholarly journals Functional regions in gravity models and accessibility measures

2016 ◽  
Vol 24 (2) ◽  
pp. 60-70 ◽  
Author(s):  
Michael Olsson
Keyword(s):  
Economic Geography ◽  
Gravity Models ◽  
Spatial Constraints ◽  
Data Set ◽  
Functional Region ◽  
Functional Regions ◽  
Friction Parameters ◽  
Potential Customers ◽  
Accessibility Measure ◽  
Economic Studies

Abstract Accessibility measures are useful for studies in Economic Geography. For example, accessibility to potential customers can be used in a study of firm behaviour. In such a study, it would be relevant to consider where potential customers live. This can be accomplished by splitting the accessibility measure into three parts: accessibility within the municipality, in other municipalities within the functional region, and in other regions. Many studies have proved this to be a very useful way to incorporate the spatial structure of the economy into economic studies. This paper deals with the issue of finding the distance-friction parameters needed to calculate such accessibility measures. There is a particular distance-friction parameter for interaction within the municipality, between municipalities within the functional region, and between regions. One way to find the distance-friction parameters is to solve a constrained gravity model, in which the functional regions are used as constraints. Both the models and the optimisation procedures in matrix form, and the Matlab programs used in the research are presented. The spatial constraints are gradually introduced into the models, which empowers the researcher to make such adjustments on their own. The data set used is available for downloading, and the reader can then try the models before creating a data set of their own.

scholarly journals Delineating the Regional Economic Geography of China by the Approach of Community Detection

2019 ◽  
Vol 11 (21) ◽  
pp. 6053 ◽  
Author(s):  
Kang Wu ◽  
Jingxian Tang ◽  
Ying Long
Keyword(s):  
Community Detection ◽  
Economic Geography ◽  
Spatial Distance ◽  
Spatial Proximity ◽  
Data Set ◽  
Regional Economic ◽  
Functional Regions ◽  
Comprehensive Development ◽  
Urbanization In China ◽  
The New Period

With the obvious regionalization trend in the new period of urbanization in China, the scientific delineation of functional regions (FRs) at different scales has become a heated topic recently. Since the 20th century, western academia has formed a basic idea of metropolitan areas’ (MAs) delineation based on population density and commuting rate, for which the subjectivity of threshold setting is difficult to overcome. In this study, community detection algorithms from the field of network science are employed, namely the Louvain algorithm with adjustable resolutions and Combo with high-precision output, respectively. We take the nationwide car-hailing data set as an example to explore a bottom-up method for delineating regional economic geography at different scales based on the interconnection strength between nodes. It was found that most of the prefecture-level cities in China have a dominant commuting region and two or three secondary commuting sub-regions, while regional central cities have extended their commuting hinterlands over jurisdictional boundaries, which is not common due to the larger initial administrative divisions and the comprehensive development niveau of cities. The feasibility and limitation of community detection partitioning algorithms in the application of regional science are verified. It is supposed to be widely used in regional delimitation supported by big data. Both of the two algorithms show a shortage of ignorance of spatial proximity. It is necessary to explore new algorithms that can adjust both accuracy and spatial distance as parameters.

HCVS: Pinpointing Chromatin States Through Hierarchical Clustering and Visualization Scheme

2019 ◽  
Vol 14 (2) ◽  
pp. 148-156
Author(s):  
Nighat Noureen ◽  
Sahar Fazal ◽  
Muhammad Abdul Qadir ◽  
Muhammad Tanvir Afzal
Keyword(s):  
Hierarchical Clustering ◽  
Real Data ◽  
Cell Types ◽  
Computational Scheme ◽  
Data Set ◽  
Chromatin States ◽  
Functional Regions ◽  
Visualization Strategy ◽  
Hidden States ◽  
Next Generation Sequencing Ngs

Background: Specific combinations of Histone Modifications (HMs) contributing towards histone code hypothesis lead to various biological functions. HMs combinations have been utilized by various studies to divide the genome into different regions. These study regions have been classified as chromatin states. Mostly Hidden Markov Model (HMM) based techniques have been utilized for this purpose. In case of chromatin studies, data from Next Generation Sequencing (NGS) platforms is being used. Chromatin states based on histone modification combinatorics are annotated by mapping them to functional regions of the genome. The number of states being predicted so far by the HMM tools have been justified biologically till now. Objective: The present study aimed at providing a computational scheme to identify the underlying hidden states in the data under consideration. </P><P> Methods: We proposed a computational scheme HCVS based on hierarchical clustering and visualization strategy in order to achieve the objective of study. Results: We tested our proposed scheme on a real data set of nine cell types comprising of nine chromatin marks. The approach successfully identified the state numbers for various possibilities. The results have been compared with one of the existing models as well which showed quite good correlation. Conclusion: The HCVS model not only helps in deciding the optimal state numbers for a particular data but it also justifies the results biologically thereby correlating the computational and biological aspects.

Markets and Manpower

2016 ◽  
Vol 43 (3) ◽  
pp. 436-458 ◽  
Author(s):  
Lindsay P. Cohn ◽  
Nathan W. Toronto
Keyword(s):  
Labor Markets ◽  
Economic Variables ◽  
Data Set ◽  
External Threat ◽  
Military Manpower ◽  
Threat Levels ◽  
Over 40 Years ◽  
Economic Studies ◽  
Relevant Factors

Economic studies of military manpower systems emphasize the advantages of voluntarism under all but the most total threats, but this explains neither the persistence of institutionalized conscription in many states nor the timing of shifts from such conscription systems to volunteer militaries. Traditional explanations focus on external threat levels, but this has also proven unsatisfying. We theorize that threat variables establish the state’s baseline need for manpower, but structural economic variables determine whether the necessary manpower can be more efficiently obtained by conscription or voluntarism. Using a new data set of 99 countries over 40 years, we find that states with British origins are less likely and those experiencing greater external threat are more likely to employ conscripts. Most importantly, states with more highly regulated labor markets are more likely to employ conscripts, which suggests that, controlling for a number of relevant factors, labor markets matter in military manpower decisions.

scholarly journals Delineating urban functional regions by considering interaction cohesiveness and function diversity

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Fei-Ying Kuo ◽  
Tzai-Hung Wen
Keyword(s):  
Public Transportation ◽  
Urban System ◽  
Market Area ◽  
Functional Region ◽  
Trip Purpose ◽  
Functional Regions ◽  
Human Movements ◽  
Local Labour ◽  
Almost All ◽  
And Function

<p><strong>Abstract.</strong> A functional region is usually defined as a region characterized by not only interaction cohesiveness but also function diversity. The former indicates that places within a region should share a cohesive interacting pattern of human movements, such as commute or daily travel; the latter means that the places should possess diverse functions like residence, commerce, etc. Due to these two characteristics, people living and moving in one region can acquire almost all their daily needs, and they do not need to frequently move to other regions. In other words, a functional region resembles a life circle. Based on this definition, many previous studies have developed different methods to analyse human flow data so that they can properly profile different types of functional regions like Local labour market area (LLMA) or daily urban system (DUS), which helps people better understand how functional regions compose an area. Existing methods have considered interaction cohesiveness in a functional region, but function diversity is ignored. This is because these studies only used specific-purpose-trip data, such as journey to work or to shop. These kinds of trips describe people moving from their home to their office or to shopping malls, so each trip has an inherent distinction of functions between its origin and destination; thus, a functional region consisting of these trips indirectly owns function diversity. However, this framework has some problems. First, it cannot profile a functional region shaped by composite functions, for only one trip purpose can be taken into account each time. Second, collecting the data of specific-purpose trips needs either some questionnaires or some surveys, so it is often costly and time consuming. Finally, the purpose-unrecorded-trip data provided by rapidly developed smart card systems in several countries can be collected quickly, yet it cannot properly profile functional regions through the aforementioned framework due to the lack of trip purposes. Therefore, we propose a new spatial partitioning algorithm which can simultaneously consider both interaction cohesiveness and function diversity in profiling functional regions. Compared with previous methods, the proposed algorithm can better profile functional regions from many purpose-unrecorded-trip data based on the inclusion of land-use data. Our results provide deeper insights for understanding how various functions of lands and human movements together shape the boundary of a region. It could be significant reference for developing policies for urban planning or public transportation management.</p>

Crustal structure of the offshore Labrador margin into deep water from combined seismic reflection interpretation and gravity modeling

2020 ◽  
Vol 8 (2) ◽  
pp. SH1-SH17 ◽  
Author(s):  
J. Kim Welford ◽  
Deric Cameron ◽  
Erin Gillis ◽  
Victoria Mitchell ◽  
Richard Wright
Keyword(s):  
Late Cretaceous ◽  
Seismic Reflection ◽  
Gravity Data ◽  
Gravity Models ◽  
Gravity Modeling ◽  
Data Set ◽  
Shelf Slope ◽  
Gravity Forward Modeling ◽  
Thickness Variations ◽  
Similar Density

A regional long-offset 2D seismic reflection program undertaken along the Labrador margin of the Labrador Sea, Canada, and complemented by the acquisition of coincident gravity data, has provided an extensive data set with which to image and model the sparsely investigated outer shelf, slope, and deepwater regions. Previous interpretation of the seismic data revealed the extent of Mesozoic and Cenozoic basins and resulted in the remapping of the basin configuration for the entire margin. To map the synrift package and improve understanding of the geometry and extent of these basins, we have undertaken joint seismic interpretation and gravity forward modeling to reduce uncertainty in the identification of the prerift basement, which varies between Paleozoic shelfal deposits and Precambrian crystalline rocks, with similar density characteristics. With this iterative approach, we have obtained new depth to basement constraints and have deduced further constraints on crustal thickness variations along the Labrador margin. At the crustal scale, extreme localized crustal thinning has been revealed along the southern and central portions of the Labrador margin, whereas a broad, margin-parallel zone of thicker crust has been detected outboard of the continental shelf along the northern Labrador margin. Our final gravity models suggest that Late Cretaceous rift packages from further south extend along the entire Labrador margin and open the possibility of a Late Cretaceous source rock fairway extending into the Labrador basins.

scholarly journals The role of networks for migration flows: an update

2016 ◽  
Vol 37 (7) ◽  
pp. 1154-1171 ◽  
Author(s):  
Michel Beine
Keyword(s):  
Specific Role ◽  
Gravity Models ◽  
Immigration Policies ◽  
Recent Experience ◽  
Data Set ◽  
Content Type ◽  
Driving Mechanisms ◽  
Migration Flows ◽  
Over Time

Purpose The purpose of this paper is to cover the literature on the role migrants networks in explaining aggregate migration flows between countries. The author emphasizes the specific role of family immigration policies. To that purpose, the author covers briefly the recent experience of seven receiving countries to highlight the importance of these policies in explaining part of the observed network elasticities. Design/methodology/approach The author first provides a small review of the literature and the issues at stake. The author then provides an update of the estimates of the network elasticities using the data set on migration stocks and flows from Ozden et al. (2011). Using micro-founded gravity models, the author estimates the network elasticities and discusses the key driving mechanisms explaining their size as well the variation in the amplitude across categories of destination and over time. The author accounts for the issue of multilateral resistance to migration. Findings The author obtains estimates that are in line with the ones documented previously in the literature. The author finds that the role of networks in attracting migrants has increased after the 1970s. The author emphasizes the specific role of family immigration policies. To that purpose, the author covers briefly the recent experience of a set of receiving countries to highlight the importance of these policies in explaining part of the observed network elasticities. Originality/value This paper covers the literature on the role migrants networks in explaining aggregate migration flows between countries and obtain new estimates of network elasticities that vary over time and across types of destination countries.

scholarly journals Coding and functional defect region prediction of placental protein in an embryo cell of first trimester using ANN approach

2018 ◽  
Vol 7 (1.9) ◽  
pp. 167
Author(s):  
Bipin Nair B J ◽  
Rahul Reghunath
Keyword(s):  
Dna Sequences ◽  
Energy Levels ◽  
Threshold Energy ◽  
First Trimester ◽  
Embryo Cell ◽  
Cell Protein ◽  
Coding Region ◽  
Protein Coding ◽  
Functional Region ◽  
Functional Regions

The protein coding and functional regions in DNA sequences has become an exciting task in bioinformatics. In particular, the coding region has a 3-base periodicity, which helps for exon identification. Many signal processing tools and techniques have been successfully applied to identify tasks, but still need to be improved in this direction. In our work, we employ ANN classifier to predict coding and functional region of proteinin human embryo cell protein in first trimester, and evaluate their performances according to the comparison energy levels of coding region. The obtained from the threshold energy level, results show that in a box plot finally predict the mutation.

scholarly journals A microanalysis of trade finance: German bank entry and coffee exports in Brazil, 1880–1913

2019 ◽  
Vol 24 (2) ◽  
pp. 356-389
Author(s):  
Wilfried Kisling
Keyword(s):  
Historical Perspective ◽  
Credit Constraints ◽  
Original Data ◽  
Firm Level ◽  
Data Set ◽  
Trade Finance ◽  
German Bank ◽  
Level Data ◽  
Economic Studies ◽  
Bank Entry

Abstract The trade-finance nexus has enjoyed increasing interest in recent economic studies, but empirical evidence is scarce and studies from a historical perspective seem missing. This study analyses the effect of German bank entry on Brazilian coffee exports between 1880 and 1913 using firm-level data. I create an original data set on the yearly quantities of exported coffee and the credit received from the German Brasilianische Bank für Deutschland by export houses in Brazil. Using a difference-in-difference approach, I find that Brasilianische eased previously existing credit constraints, and that companies financed by Brasilianische exported significantly more than those that were not.

The BRAT and GUT Couple: Broadview Radar Altimetry and GOCE User Toolboxes

2020 ◽  
Author(s):  
Américo Ambrózio ◽  
Marco Restano ◽  
Jérôme Benveniste
Keyword(s):  
Gravity Field ◽  
Ad Hoc ◽  
Gravity Anomalies ◽  
Geoid Height ◽  
Gravity Models ◽  
Gravity Gradient ◽  
Data Set ◽  
Radar Altimetry ◽  
Isostatic Gravity ◽  
L1 And L2

&lt;p&gt;The scope of this work is to showcase the BRAT (Broadview Radar Altimetry Toolbox) and GUT (GOCE User Toolbox) toolboxes.&lt;/p&gt;&lt;p&gt;The Broadview Radar Altimetry Toolbox (BRAT) is a collection of tools designed to facilitate the processing of radar altimetry data from all previous and current altimetry missions, including Sentinel-3A L1 and L2 products. A tutorial is included providing plenty of use cases on Geodesy &amp; Geophysics, Oceanography, Coastal Zone, Atmosphere, Wind &amp; Waves, Hydrology, Land, Ice and Climate, which can also be consulted in &amp;#160;http://www.altimetry.info/radar-altimetry-tutorial/.&lt;/p&gt;&lt;p&gt;BRAT's last version (4.2.1) was released in June 2018. Based on the community feedback, the front-end has been further improved and simplified whereas the capability to use BRAT in conjunction with MATLAB/IDL or C/C++/Python/Fortran, allowing users to obtain desired data bypassing the data-formatting hassle, remains unchanged. Several kinds of computations can be done within BRAT involving the combination of data fields, that can be saved for future uses, either by using embedded formulas including those from oceanographic altimetry, or by implementing ad-hoc Python modules created by users to meet their needs. BRAT can also be used to quickly visualise data, or to translate data into other formats, e.g. from NetCDF to raster images.&lt;/p&gt;&lt;p&gt;The GOCE User Toolbox (GUT) is a compilation of tools for the use and the analysis of GOCE gravity field models. It facilitates using, viewing and post-processing GOCE L2 data and allows gravity field data, in conjunction and consistently with any other auxiliary data set, to be pre-processed by beginners in gravity field processing, for oceanographic and hydrologic as well as for solid earth applications at both regional and global scales. Hence, GUT facilitates the extensive use of data acquired during GRACE and GOCE missions.&lt;/p&gt;&lt;p&gt;In the current version (3.2), GUT has been outfitted with a graphical user interface allowing users to visually program data processing workflows. Further enhancements aiming at facilitating the use of gradients, the anisotropic diffusive filtering, and the computation of Bouguer and isostatic gravity anomalies have been introduced. Packaged with GUT is also GUT's Variance/Covariance Matrix (VCM) tool, which enables non-experts to compute and study, with relative ease, the formal errors of quantities &amp;#8211; such as geoid height, gravity anomaly/disturbance, radial gravity gradient, vertical deflections &amp;#8211; that may be derived from the GOCE gravity models.&lt;/p&gt;&lt;p&gt;On our continuous endeavour to provide better and more useful tools, we intend to integrate BRAT into SNAP (Sentinel Application Platform). This will allow our users to easily explore the synergies between both toolboxes. During 2020 we will start going from separate toolboxes to a single one.&lt;/p&gt;&lt;p&gt;BRAT and GUT toolboxes can be freely downloaded, along with ancillary material, at https://earth.esa.int/brat and https://earth.esa.int/gut.&lt;/p&gt;

scholarly journals Identification of the Functional Domain of HPIV3 Matrix Protein Interacting with Nucleocapsid Protein

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Xichuan Deng ◽  
Chaoliang Zhang ◽  
Kehan Zhang ◽  
Nan Lu ◽  
Yonglin He ◽  
...  
Keyword(s):  
Nucleocapsid Protein ◽  
Matrix Protein ◽  
Respiratory Infections ◽  
The Elderly ◽  
Functional Domain ◽  
Functional Region ◽  
Amino Acid Region ◽  
Functional Regions ◽  
C Terminus ◽  
Germination Experiments

Human parainfluenza virus type 3 (HPIV3) is the main pathogen that causes respiratory infections in infants, young children, and the elderly. Currently, there are no vaccines and effective anti-infective drugs. Studying the replication and proliferation mechanism of HPIV3 is helpful for exploring the targets of anti-HPIV3 infection. Matrix protein (M) and nucleocapsid protein (N) are two key structural proteins of HPIV3 that exert important functions in HPIV3 proliferation. Herein, we aim to clarify the functional domains of M and N interaction. HPIV3 M and N expression plasmids of pCAGGS-HA-M and pCAGGS-N-Myc/Flag, M C-terminal truncation mutant plasmids of pCAGGSHA-MΔC120, MΔC170, MΔC190, and MΔC210, and M C-terminal plasmid of pCAGGS-HA-MC190 and C-terminal deletion mutant plasmid of pCAGGS-MΔN143-182 were constructed. By using immunoprecipitation, immunofluorescence, and virus-like particle (VLP) germination experiments, we found that N was encapsulated into M-mediated VLP through N and M interaction. Moreover, the C-terminus of the M played a key role in the interaction between M and N. The C-terminus of the M encapsulated the N into the VLP. We finally determined that the 143-182 amino acids in the M were the functional regions that encapsulated the N into the M-mediated VLP. Our findings confirmed the interaction between M and N and for the first time clarified that the 143-182 amino acid region in M was the functional region that interacted with N, which provides a molecular basis for exploring effective anti-HPIV3 targets.

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