scholarly journals Scotland: The Roman Presence

2012 ◽  
Author(s):  
Fraser Hunter ◽  
Martin Carruthers
Keyword(s):  
Aerial Survey ◽  
Data Set ◽  
Development Control ◽  
The Core ◽  
Roman World ◽  
Theoretical Perspectives ◽  
Integrated Approaches ◽  
The Rich ◽  
Rich Data ◽  
The Impact

The main recommendations of the panel report can be summarised under five key headings:  Scotland in the Roman world: Research into Roman Scotland requires an appreciation of the wider frontier and Empire-wide perspectives, and Scottish projects must be integrated into these wider, international debates. The rich data set and chronological control that Scotland has to offer can be used to inform broader understandings of the impact of Rome.  Changing worlds: Roman Scotland’s rich data set should be employed to contribute to wider theoretical perspectives on topics such as identity and ethnicity, and how these changed over time. What was the experience of daily life for the various peoples in Roman Scotland and how did interactions between incomers and local communities develop and change over the period in question, and, indeed, at and after its end?  Frontier Life: Questions still remain regarding the disposition and chronology of forts and forces, as well as the logistics of sustaining and supplying an army of conquest and occupation. Sites must be viewed as part of a wider, interlocking set of landscapes, and the study of movement over land and by sea incorporated within this. The Antonine Wall provides a continuing focus of research which would benefit from more comparison with frontier structures and regimes in other areas.  Multiple landscapes: Roman sites need to be seen in a broader landscape context, ‘looking beyond the fort’ and explored as nested and interlocking landscapes. This will allow exploration of frontier life and the changing worlds of the Roman period. To do justice to this resource requires two elements: o Development-control archaeology should look as standard at the hinterland of forts (up to c.1 km from the ‘core’), as sensitive areas and worthy of evaluation; examples such as Inveresk show the density of activity around such nodes. The interiors of camps should be extensively excavated as standard. o Integrated approaches to military landscapes are required, bringing in where appropriate topographical and aerial survey, LIDAR, geophysics, the use of stray and metal-detected finds, as well as fieldwalking and ultimately, excavation.  The Legacy of Rome: How did the longer term influence of the Romans, and their legacy, influence the formation, nature and organisation of the Pictish and other emergent kingdoms?

Tropospheric layering of ozone in regions of urbanized complex and/or coastal terrain: a review

2000 ◽  
Vol 24 (3) ◽  
pp. 329-354 ◽  
Author(s):  
I. G. McKendry ◽  
J. Lundgren
Keyword(s):  
Boundary Layer ◽  
Global Climate ◽  
Research Priorities ◽  
Lower Troposphere ◽  
Ground Level ◽  
Tropospheric Chemistry ◽  
Future Research ◽  
Data Set ◽  
Rich Data ◽  
The Impact

Exchange of pollutants between the atmospheric boundary layer and free troposphere is an important (yet often neglected) process that tends to produce distinct layers of pollution in the lower troposphere. These layers represent a potential sink for pollutants from the boundary layer, have the potential to be mixed to ground and likely influence tropospheric chemistry and the global climate system. Factors influencing the vertical distribution of ozone in the troposphere are outlined as a prelude to a more specific discussion of elevated layers and myriad meteorological processes responsible for their development. Evidence from a range of geographical settings suggests that these phenomena are ubiquitous. A rich data set from the Lower Fraser Valley, British Columbia, is used to provide an inventory of layer structures and to highlight their diverse origins and histories. Approaches used to assess the impact of down-mixing of pollutants from elevated layers on ground-level concentrations of ozone are outlined and future research priorities recommended.

scholarly journals The regional significance of university locations in Lower Saxony

2020 ◽  
Vol 78 (4) ◽  
pp. 337-359
Author(s):  
Britta Stöver
Keyword(s):  
Spatial Econometrics ◽  
Supply Side ◽  
Lower Saxony ◽  
Data Set ◽  
Capital Theory ◽  
Demand And Supply ◽  
Panel Regressions ◽  
Spillover Theory ◽  
Rich Data ◽  
The Impact

AbstractUniversities are important economic actors and make a considerable impact on the demand and supply side of their local economies. The aim of this paper is to quantify, compare and classify the different economic demand-and supply-side contributions of the university locations within Lower Saxony (Germany) using a combination of multiplier analysis and spatial econometrics on a NUTS 3 level. In comparison to numerous other studies, this paper does not focus on the economic impact of individual cases or a selected university location but gives a complete picture of the importance and significance of all university locations within Lower Saxony. The income-induced direct and indirect demand effects are estimated using a rich data set of higher education statistics in combination with an income and employment multiplier derived from a regional input-output table. The supply-side effects, i.e. the impact of the education and research outcomes, are estimated with the help of spatial panel regressions, a model derived from human capital theory and knowledge spillover theory. The estimation results give a complete and reproducible impression of the importance and significance of the different university locations, offering the opportunity for comparisons and classifications.

scholarly journals NeuRiPP: Neural network identification of RiPP precursor peptides

2019 ◽  
Author(s):  
Emmanuel L.C. de los Santos
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Network Models ◽  
Gene Clusters ◽  
Learning Tools ◽  
Neural Network Models ◽  
Data Set ◽  
The Rich ◽  
Tailoring Enzymes ◽  
Rich Data

ABSTRACTSignificant progress has been made in the past few years on the computational identification biosynthetic gene clusters (BGCs) that encode ribosomally synthesized and post-translationally modified peptides (RiPPs). This is done by identifying both RiPP tailoring enzymes (RTEs) and RiPP precursor peptides (PPs). However, identification of PPs, particularly for novel RiPP classes remains challenging. To address this, machine learning has been used to accurately identify PP sequences. However, current machine learning tools have limitations, since they are specific to the RiPP-class they are trained for, and are context-dependent, requiring information about the surrounding genetic environment of the putative PP sequences. NeuRiPP overcomes these limitations. It does this by leveraging the rich data set of high-confidence putative PP sequences from existing programs, along with experimentally verified PPs from RiPP databases. NeuRiPP uses neural network models that are suitable for peptide classification with weights trained on PP datasets. It is able to identify known PP sequences, and sequences that are likely PPs. When tested on existing RiPP BGC datasets, NeuRiPP is able to identify PP sequences in significantly more putative RiPP clusters than current tools, while maintaining the same HMM hit accuracy. Finally, NeuRiPP was able to successfully identify PP sequences from novel RiPP classes that are recently characterized experimentally, highlighting its utility in complementing existing bioinformatics tools.

scholarly journals NeuRiPP: Neural network identification of RiPP precursor peptides

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Emmanuel L. C. de los Santos
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Gene Clusters ◽  
Learning Tools ◽  
Data Set ◽  
Modified Peptides ◽  
The Rich ◽  
Tailoring Enzymes ◽  
Rich Data ◽  
Peptide Classification

Abstract Significant progress has been made in the past few years on the computational identification of biosynthetic gene clusters (BGCs) that encode ribosomally synthesized and post-translationally modified peptides (RiPPs). This is done by identifying both RiPP tailoring enzymes (RTEs) and RiPP precursor peptides (PPs). However, identification of PPs, particularly for novel RiPP classes remains challenging. To address this, machine learning has been used to accurately identify PP sequences. Current machine learning tools have limitations, since they are specific to the RiPPclass they are trained for and are context-dependent, requiring information about the surrounding genetic environment of the putative PP sequences. NeuRiPP overcomes these limitations. It does this by leveraging the rich data set of high-confidence putative PP sequences from existing programs, along with experimentally verified PPs from RiPP databases. NeuRiPP uses neural network archictectures that are suitable for peptide classification with weights trained on PP datasets. It is able to identify known PP sequences, and sequences that are likely PPs. When tested on existing RiPP BGC datasets, NeuRiPP was able to identify PP sequences in significantly more putative RiPP clusters than current tools while maintaining the same HMM hit accuracy. Finally, NeuRiPP was able to successfully identify PP sequences from novel RiPP classes that were recently characterized experimentally, highlighting its utility in complementing existing bioinformatics tools.

scholarly journals Making sense of consumers’ tweets

2019 ◽  
Vol 47 (9) ◽  
pp. 915-927 ◽  
Author(s):  
Eleonora Pantano ◽  
Simona Giglio ◽  
Charles Dennis
Keyword(s):  
Data Set ◽  
Fast Fashion ◽  
Content Type ◽  
Making Sense ◽  
Negative Comments ◽  
Marketing Intelligence ◽  
Massive Number ◽  
The Rich ◽  
Rich Data ◽  
The Uk

Purpose Consumers online interactions, posts, rating and ranking, reviews of products/attractions/restaurants and so on lead to a massive amount of data that marketers might access to improve the decision-making process, by impacting the competitive and marketing intelligence. The purpose of this paper is to develop understanding of consumers online-generated contents in terms of positive or negative comments to increase marketing intelligence. Design/methodology/approach The research focuses on the collection of 9,652 tweets referring to three fast fashion retailers of different sizes operating in the UK market, which have been shared among consumers and between consumer and firm, and subsequently evaluated through a sentiment analysis based on machine learning. Findings Findings provide the comparison and contrast of consumers’ response toward the different retailers, while providing useful guidelines to systematically making sense of consumers’ tweets and enhancing marketing intelligence. Practical implications The research provides an effective and systemic approach to accessing the rich data set on consumers’ experiences based the massive number of contents that consumers generate and share online and investigating this massive amount of data to achieve insights able to impact on retailers’ marketing intelligence. Originality/value To best of the authors’ knowledge, while other authors tried to identify the effect of positive or negative online comments/posts/reviews, the present study is the first one to show how to systematically detect the positive or negative sentiments of shared tweets for improving the marketing intelligence of fast fashion retailers.

scholarly journals Birthplace diversity and economic growth: evidence from the US states in the Post-World War II period

2019 ◽  
Author(s):  
Frédéric Docquier ◽  
Riccardo Turati ◽  
Jérôme Valette ◽  
Chrysovalantis Vasilakis
Keyword(s):  
Economic Growth ◽  
World War Ii ◽  
College Education ◽  
Large Set ◽  
Market Outcomes ◽  
Data Set ◽  
Us States ◽  
The Usa ◽  
Rich Data ◽  
The Impact

Abstract This paper empirically investigates the impact of birthplace diversity on economic growth. We use panel data on US states over the 1960–2010 period. This rich data set allows us to better deal with endogeneity issues and to conduct a large set of robustness checks. Our results suggest that diversity among college-educated immigrants positively affects economic growth. We provide converging evidence pointing at the existence of skill complementarities between workers trained in different countries. These synergies result in better labor market outcomes for native workers and in higher productivity in the R&D sector. The gains from diversity are maximized when immigrants originate from economically or culturally distant countries (but not both), and when they acquired part of their secondary education abroad and their college education in the USA. Overall, a 10% increase in high-skilled diversity raises GDP per capita by about 6%. On the contrary, low-skilled diversity has insignificant effects.

Distance and Local Competition in Mobile Geofencing

2020 ◽  
Vol 31 (4) ◽  
pp. 1421-1442
Author(s):  
Yi-Jen (Ian) Ho ◽  
Sanjeev Dewan ◽  
Yi-Chun (Chad) Ho
Keyword(s):  
Mobile Apps ◽  
Consumer Welfare ◽  
Location Based Services ◽  
Data Set ◽  
New Era ◽  
Local Competition ◽  
Two Factors ◽  
Surrounding Areas ◽  
Rich Data ◽  
The Impact

The growing ubiquity of GPS-enabled smartphones has ushered in a new era of location-based services and online-to-offline commerce. Geofencing is one instance of this broader phenomenon, and it is being widely adopted in the context of retail, restaurant, entertainment, and other local services. By targeting users on mobile apps while they are in the vicinity of physical establishments, there is potential for higher levels of engagement and consumption of the products or services on offer. However, the level of consumer interest is likely to depend on distance from the establishment and local competition in the surrounding areas. This study examines the impact of these two factors on consumer response to geofence advertising at different points in the purchase funnel, namely the click stage and conversion phase. Analyzing a rich data set from one of the leading location-based marketing agencies and using a sophisticated Bayesian empirical methodology, we find that having one more competitor in the consumer’s vicinity reduces click-through rate by about 1%, and a 1-mile increase in distance is associated with a 17.6% reduction in conversion rate. These and other results suggest that accounting for distance and local competition in data-analytic mobile targeting would increase both the return on advertising spend and consumer welfare.

scholarly journals U.S. Children and Youth’s Physical Activities Inside and Outside of School PE: 1985 vs. 2012

2021 ◽  
Vol 18 (2) ◽  
pp. 398
Author(s):  
Xiaochen Zhao ◽  
Weimo Zhu ◽  
Zezhao Chen ◽  
Sicong Ren ◽  
Xiong Qin
Keyword(s):  
Physical Activity ◽  
Physical Education ◽  
Weight Status ◽  
Youth Sport ◽  
Physical Activities ◽  
Children And Youth ◽  
The Rich ◽  
Rich Data ◽  
The Impact ◽  
Future School

The purpose of this study was, by taking advantage of the rich data from two U.S. national fitness surveys, to examine the physical activity (PA) students engaged in, both inside and outside school physical education (PE), determine if there are differences by grade, sex, and weight status, and if there was a change between 1985 and 2012. The data from the 1985 National Children and Youth Fitness Study (NCYFS) and the 2012 NHANES National Youth Fitness Survey (NNYFS) were matched, merged (N = 6178, 3107 boys and 3071 girls), and analyzed. It was found that basketball remained the most popular PA inside school PE across both surveys. Swimming was the most popular PA outside of school PE in 1985, but was replaced by running in 2012. Although PA taught and promoted inside of school PE and that such PA practiced outside were moderately correlated across the surveys, some disconnections were noticed. The impact of grade, sex, and weight status on PA preference and participation was also confirmed. What is needed is to the design and integration of more lifelong and individual PAs in future school PE curricula and school and community children and youth sport and PA programs.

scholarly journals State Health Insurance Regulations and the Price of High-Deductible Policies

2008 ◽  
Vol 11 (2) ◽  
Author(s):  
Amanda E. Kowalski ◽  
William J. Congdon ◽  
Mark H. Showalter
Keyword(s):  
Health Insurance ◽  
Family Policy ◽  
State Level ◽  
Demographic Characteristics ◽  
State Health ◽  
Data Set ◽  
Insurance Policies ◽  
State Health Insurance ◽  
Rich Data ◽  
The Impact

This study examines the impact of state health insurance regulations on the price of high-deductible family and individual polices in the nongroup market. We use a unique and rich data set on actual insurance policies sold through a large Internet health insurance distributor to examine the impact of various regulations on policy prices, controlling for policy characteristics, demographic characteristics of the purchasers, and state-level demographics. We also use data from a single major insurance firm that provided offer prices for a family policy from a set of randomly selected zip codes. Both datasets suggest a strong statistical relationship between regulation and insurance prices.

scholarly journals The impact of the COVID-19 pandemic on the poor: Insights from the Hrishipara diaries

2021 ◽  
Author(s):  
Risto Rönkkö ◽  
Stuart Rutherford ◽  
Kunal Sen
Keyword(s):  
Rural Setting ◽  
Negative Effects ◽  
Data Set ◽  
Household Expenditures ◽  
Daily Diaries ◽  
The Poor ◽  
Food Expenditures ◽  
Time Basis ◽  
Rich Data ◽  
The Impact

In this paper, we examine the economic impact of the COVID-19 pandemic on the livelihoods of the poor. We use an unusually rich data set from a ‘financial diaries’ study known as the Hrishipara Daily Diaries Project. The data set tracks the economic and financial transactions of 60 individuals and their families in a semi-rural setting in Bangladesh on a real-time basis from October 2019 to September 2020. We document individual diarists’ behavioural responses to COVID-19, which reveal the varied experiences of the poor during the pandemic. We find that the pandemic and associated government lockdowns had significant negative effects on the livelihoods of the poor in our study, with financial inflows and outflows, incomes, and household expenditures below pre-pandemic levels during the pandemic period. To cope with the pandemic, households drew down on their cash reserves at home, as well as cutting down on non-food expenditures to protect their spending on food.

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