bluuebunny/crossref_metadata_2025 huggingface dataset:
Features of organization of training at Academy of FPS of Russia in interaction of teacher and cadets using information and communication networks
Authors:   Academy of the FPS of Russia, MASKINA MARIYA S.
Published: August 2021

The article describes specific features of the organization of training at the Academy of the FPS of Russia in the interaction of a teacher and cadets in the context of restrictions on contact work associated with countering the spread of the new corona-virus infection. The aim of the work was to substantiate the effectiveness of using the algorithmic method for the formation of sustainable skills in the implementation of the educational process through the use of distance technologies. The methodological framework of the study was made up of analysis, synthesis, induction, systematization and generalization. The study was carried out throughout a year at refresher courses and classes conducted by employees of the Department of Mathematics and Information Technologies of Management of the Academy of the FPS of Russia. As a result, it was found that to maintain the quality of education at a proper level, it is necessary to develop the computer literacy of teachers, familiarize them with modern innovative pedagogical technologies and features of their application; expand the variety of methods, forms and means of teaching used in the interaction of a teacher and students through information and communication networks. Conclusions are made about the importance of combining organizational, information-technical and methodological measures to improve the professional competence of the teaching staff and ensure the proper quality of education when switching to e-learning. The fact of maintaining the quality of education at the Academy of the FPS of Russia at a proper level was confirmed by the commission of experts, which in 2021 conducted an accreditation examination in relation to the educational programs implemented. The described experience will be useful to the teaching staff of educational organizations of the Federal Penitentiary Service of Russia. Key words: information technology, computer literacy, professional pedagogical competence, distance learning technologies.
Highly oxygenated organic molecules produced by the oxidation of benzene and toluene in a wide range of OH exposure and NOx conditions
Authors: Cheng Xi , Chen Qi , Jie Li Yong , Zheng Yan , Liao Keren , Huang Guancong
Published: August 2021

Abstract. Oxidation of aromatic volatile organic compounds (VOCs) leads to the formation of tropospheric ozone and secondary organic aerosol, for which gaseous oxygenated products are important intermediates. We show,
herein, the experimental results of highly oxygenated organic molecules (HOMs) produced by the oxidation of benzene and toluene in a wide range of OH exposure and NOx conditions. The results suggest that multigeneration OH oxidation plays an important role in the product distribution, which likely proceeds more preferably via H subtraction than OH addition for early generation products from light aromatics. More oxygenated products present in our study than in previous flow tube studies, highlighting the impact of experimental conditions on product distributions. The formation of dimeric products, however, was suppressed and might be unfavorable under conditions of high OH exposure and low NOx in toluene oxidation. Under high-NOx conditions, nitrogen-containing multifunctional products are formed, while the formation of other HOMs is suppressed. Products containing two nitrogen atoms become more important as the NOx level increases, and the concentrations of these compounds depend significantly on NO2.
The highly oxygenated nitrogen-containing products might be peroxyacyl nitrates, implying a prolonged effective lifetime of RO2 that
facilitates regional pollution. Our results call for further investigation
on the roles of high-NO2 conditions in the oxidation of aromatic VOCs.
A global total column ozone climate data record
Authors: Bodeker Greg E. , Nitzbon Jan , Tradowsky Jordis S. , Kremser Stefanie , Schwertheim Alexander , Lewis Jared
Published: August 2021

Abstract. Total column ozone (TCO) data from multiple satellite-based instruments have been combined to create a single near-global daily time series of ozone fields at 1.25∘ longitude by 1∘ latitude spanning the period 31 October 1978 to 31 December 2016. Comparisons against TCO measurements from the ground-based Dobson and Brewer spectrophotometer networks are used to remove offsets and drifts between the ground-based measurements and a subset of the satellite-based measurements. The corrected subset is then used as a basis for homogenizing the remaining data sets. The construction of this database improves on earlier versions of the database maintained first by the National Institute of Water and Atmospheric Research (NIWA) and now by Bodeker Scientific (BS), referred to as the NIWA-BS TCO database. The intention is for the NIWA-BS TCO database to serve as a climate data record for TCO, and to this end, the requirements for constructing climate data records, as detailed by GCOS (the Global Climate Observing System), have been followed as closely as possible. This new version includes a wider range of satellite-based instruments, uses updated sources of satellite data, extends the period covered, uses improved statistical methods to model the difference fields when homogenizing the data sets, and, perhaps most importantly, robustly tracks uncertainties from the source data sets through to the final climate data record which is now accompanied by associated uncertainty fields. Furthermore, a gap-free TCO database (referred to as the BS-filled TCO database) has been created and is documented in this paper. The utility of the NIWA-BS TCO database is demonstrated through an analysis of ozone trends from November 1978 to December 2016. Both databases are freely available for non-commercial purposes: the DOI for the NIWA-BS TCO database is https://doi.org/10.5281/zenodo.1346424 (Bodeker et al., 2018) and is available from https://zenodo.org/record/1346424. The DOI for the BS-filled TCO database is https://doi.org/10.5281/zenodo.3908787 (Bodeker et al., 2020) and is available from https://zenodo.org/record/3908787. In addition, both data sets are available from http://www.bodekerscientific.com/data/total-column-ozone (last access: June 2021).
Evaluating the Atibaia River Hydrology using JULES6.1
Authors: Chou Hsi-Kai , de Avila Ana Maria Heuminski , Bray Michaela
Published: August 2021

Abstract. Land surface models such as the Joint UK Land Environment Simulator (JULES) are increasingly used for hydrological assessments because of their state-of-the-art representation of physical processes and versatility. Unlike statistical models and AI models, the JULES model simulates the physical water flux under given meteorological conditions, allowing us to understand and investigate the cause and effect of environmental processes changes. Here we explore the possibility of this approach using a case study in the Atibaia river basin, which serves as a major water supply for metropolitan regions of Campinas and São Paulo, Brazil. The watershed is suffering increasing hydrological risks, which could be attributed to environmental changes, such as urbanization and agricultural activity. The increasing risks highlight the importance to evaluate the land surface processes of the watershed systematically. We explore the use of local precipitation collection complement with multiple sources of global reanalysis data to simulate the basin hydrology. Our results show that the coarse resolution of rainfall data is the main reason to reduce model performance. Despite this shortcoming, key hydrological fluxes in the basin can be represented by the JULES model simulations.
Geometric remapping of particle distributions in the Discrete Element Model for Sea Ice (DEMSI v0.0)
Authors: Turner Adrian K. , Peterson Kara J. , Bolintineanu Dan
Published: August 2021

Abstract. A new sea ice dynamical core, the Discrete Element Model for Sea Ice (DEMSI), is under development for use in coupled Earth system models. DEMSI is based on the discrete element method, which models collections of ice floes as interacting Lagrangian particles. In basin-scale sea ice simulations the Lagrangian motion results in significant convergence and ridging, which requires periodic remapping of sea ice variables from a deformed particle configuration back to an undeformed initial distribution. At the resolution required for Earth system models we cannot resolve individual sea ice floes, so we adopt the sub-gridscale thickness distribution used in continuum sea ice models. This choice leads to a series of hierarchical tracers depending on ice fractional area or concentration that must be remapped consistently. The circular discrete elements employed in DEMSI help improve the computational efficiency at the cost of increased complexity in the effective element area definitions for sea ice cover that are required for the accurate enforcement of conservation. An additional challenge is the accurate remapping of element values along the ice edge, the location of which varies due to the Lagrangian motion of the particles. In this paper we describe a particle-to-particle remapping approach based on well-established geometric remapping ideas that enforces conservation, bounds-preservation, and compatibility between associated tracer quantities, while also robustly managing remapping at the ice edge. One element of the remapping algorithm is a novel optimization-based flux correction that enforces concentration bounds in the case of non-uniform motion. We demonstrate the accuracy and utility of the algorithm in a series of numerical test cases.
MACHINE LEARNING FOR MOBILE LIDAR DATA CLASSIFICATION OF 3D ROAD ENVIRONMENT
Authors: Mohamed M. , Morsy S. , El-Shazly A.
Published: August 2021

Abstract. 3D road mapping is essential for intelligent transportation system in smart cities. Road features can be utilized for road maintenance, autonomous driving vehicles, and providing regulations to drivers. Currently, 3D road environment receives its data from Mobile Laser Scanning (MLS) systems. MLS systems are capable of rapidly acquiring dense and accurate 3D point clouds, which allow for effective surveying of long road corridors. They produce huge amount of point clouds, which requires automatic features classification algorithms with acceptable processing time. Road features have variant geometric regular or irregular shapes. Therefore, most researches focus on classification of one road feature such as road surface, curbs, building facades, etc. Machine learning (ML) algorithms are widely used for predicting the future or classifying information to help policymakers in making necessary decisions. This prediction comes from a pre-trained model on a given data consisting of inputs and their corresponding outputs of the same characteristics. This research uses ML algorithms for mobile LiDAR data classification. First, cylindrical neighbourhood selection method was used to define point’s surroundings. Second, geometric point features including geometric, moment and height features were derived. Finally, three ML algorithms, Random Forest (RF), Gaussian Naïve Bayes (GNB), and Quadratic Discriminant Analysis (QDA) were applied. The ML algorithms were used to classify a part of Paris-Lille-3D benchmark of about 1.5 km long road in Lille with more than 98 million points into nine classes. The results demonstrated an overall accuracy of 92.39%, 78.5%, and 78.1% for RF, GNB, and QDA, respectively.
SCALING UP SAGEBRUSH CHEMISTRY WITH NEAR-INFRARED SPECTROSCOPY AND UAS-ACQUIRED HYPERSPECTRAL IMAGERY
Authors: Olsoy P. J. , Barrett S. N. , Robb B. C. , Forbey J. S. , Caughlin T. T. , Blocker M. D. , Merriman C. , Nobler J. D. , Rachlow J. L. , Shipley L. A. , Delparte D. M.
Published: August 2021

Abstract. Sagebrush ecosystems (Artemisia spp.) face many threats including large wildfires and conversion to invasive annuals, and thus are the focus of intense restoration efforts across the western United States. Specific attention has been given to restoration of sagebrush systems for threatened herbivores, such as Greater Sage-Grouse (Centrocercus urophasianus) and pygmy rabbits (Brachylagus idahoensis), reliant on sagebrush as forage. Despite this, plant chemistry (e.g., crude protein, monoterpenes and phenolics) is rarely considered during reseeding efforts or when deciding which areas to conserve. Near-infrared spectroscopy (NIRS) has proven effective in predicting plant chemistry under laboratory conditions in a variety of ecosystems, including the sagebrush steppe. Our objectives were to demonstrate the scalability of these models from the laboratory to the field, and in the air with a hyperspectral sensor on an unoccupied aerial system (UAS). Sagebrush leaf samples were collected at a study site in eastern Idaho, USA. Plants were scanned with an ASD FieldSpec 4 spectroradiometer in the field and laboratory, and a subset of the same plants were imaged with a SteadiDrone Hexacopter UAS equipped with a Rikola hyperspectral sensor (HSI). All three sensors generated spectral patterns that were distinct among species and morphotypes of sagebrush at specific wavelengths. Lab-based NIRS was accurate for predicting crude protein and total monoterpenes (R2 = 0.7–0.8), but the same NIRS sensor in the field was unable to predict either crude protein or total monoterpenes (R2 < 0.1). The hyperspectral sensor on the UAS was unable to predict most chemicals (R2 < 0.2), likely due to a combination of too few bands in the Rikola HSI camera (16 bands), the range of wavelengths (500–900 nm), and small sample size of overlapping plants (n = 28–60). These results show both the potential for scaling NIRS from the lab to the field and the challenges in predicting complex plant chemistry with hyperspectral UAS. We conclude with recommendations for next steps in applying UAS to sagebrush ecosystems with a variety of new sensors.
PERFORMANCE ASSESSMENT OF CLASSIFICATION ALGORITHMS FOR LANDUSE / LANDCOVER CHANGE USING SENTINEL 2 DATA – A CASE STUDY OF TIRUPPUR
Authors: Prawin B. , Masilamani P. , Abdul Rahaman S.
Published: August 2021

Abstract. In the history of mankind, one of the vibrant geographical phenomena is urbanization. The urbanization process is characterized by the expansion of the city from the core to peripheral areas which includes economic development, social, political forces and population density. Very rapid urbanization in the highly populated country like India, which changes natural land cover into urban land use, which is unavoidable. However, the study region Tiruppur is known as the knitwear capital of India that induces urban development in the region which results in the modification of the natural land cover. For understating the interaction between the natural landscape and human activities, land use and land cover (LULC) is considered as the important indicator. Research on land-use and land cover changes using remote sensing technology has a long history to evident. The advancement in the Remote Sensing and GIS techniques provide the fine resolution of data sets to proceed. Sentinel-2B imagery was chosen for this study for two main reasons one is that compare to Landsat imagery it has a high spatial resolution of 10 m and its radiometry includes three vegetation red edge bands. These two characteristics make the Sentinel-2B data appealing for LULC mapping. Different types of classification algorithms have been used to perform land use and land cover mapping. The study aims to create land use and land cover classification by making a comparison between different algorithms in Tiruppur by using Sentinel-2B satellite imagery. The commonly known classification algorithms, K-means, IsoData, support vector machines (SVMs), and maximum likelihood (ML) classification are adopted for investigation. This is followed by the selection of training pixels from the remaining classes to perform and compare different supervised learning algorithms for the first- and second-level classification in terms of accuracy rates. Accuracy was assessed through metrics derived from an error matrix, but primarily overall accuracy and kappa coefficient was used in allocating algorithm hierarchy. Finally, after the comparison, the highly accurate algorithm was suggested for the mapping of urban areas. The highest overall accuracy and kappa coefficient was produced by support vector machine (SVM) is due to the algorithm’s relatively small number of complex decision boundaries. The results are helpful to understand the performance of the classification algorithm for the future studies.
IDENTIFYING OIL PADS IN HIGH SPATIAL RESOLUTION AERIAL IMAGES USING FASTER R-CNN
Authors: Sunil A. , Sajithvariyar V. V. , Sowmya V. , Sivanpillai R. , Soman K. P.
Published: August 2021

Abstract. Deep learning (DL) methods are used for identifying objects in aerial and ground-based images. Detecting vehicles, roads, buildings, and crops are examples of object identification applications using DL methods. Identifying complex natural and man-made features continues to be a challenge. Oil pads are an example of complex built features due to their shape, size, and presence of other structures like sheds. This work applies Faster Region-based Convolutional Neural Network (R-CNN), a DL-based object recognition method, for identifying oil pads in high spatial resolution (1m), true-color aerial images. Faster R-CNN is a region-based object identification method, consisting of Regional Proposal Network (RPN) that helps to find the area where the target can be possibly present in the images. If the target is present in the images, the Faster R-CNN algorithm will identify the area in an image as foreground and the rest as background. The algorithm was trained with oil pad locations that were manually annotated from orthorectified imagery acquired in 2017. Eighty percent of the annotated images were used for training and the number of epochs was increased from 100 to 1000 in increments of 100 with a fixed length of 1000. After determining the optimal number of epochs the performance of the algorithm was evaluated with an independent set of validation images consisting of frames with and without oil pads. Results indicate that the Faster R-CNN algorithm can be used for identifying oil pads in aerial images.
INTEGRATION OF REMOTE SENSING & ENVIRONMENTAL SCIENCE IN PLACED-BASED LEARNING
Authors: Ignatius A. R. , Flood M. G.
Published: August 2021

Abstract. Integration of remote sensing techniques and Environmental Science methodologies in placed-based curriculum design creates unique learning opportunities. To promote introductory-level student engagement with STEM, our team designed a set of multidisciplinary teaching materials to intensely examine a single location: the Lake Sidney Lanier watershed of North Georgia, USA. Using a combination of scientific approaches from a variety of disciplines, course exercises encourage students to holistically learn about environmental conditions within the watershed. Remote sensing exercises are embedded throughout the course content and include analysis of historic aerial imagery, Landsat-derived dynamic surface water extent, google timelapse land cover change, Sentinel 2 spectral bands, and evaluation of topography.Fundamental spatial concepts of scale and connectivity are considered using interdisciplinary approaches and local data. Landscape ecology is presented alongside remote sensing concepts of spatial and temporal resolution. This allows students to think about the diverse ways scientists understand scale, pattern, and the definition of “place”. Multiple data sources are also provided for each topic. For example, remote sensing imagery is used to investigate surface water conditions during drought and high-rainfall time periods. In addition, USGS streamgage river discharge data and rainfall estimates are provided for students to examine drought history using multiple parameters. Lastly, sensor deployment and limitations of each data source are described so that students understand both the history of place as well as the process and development of science. Through the use of a place-based curriculum design and interdisciplinary lab exercises, students gain a holistic understanding of a regional watershed.
3D crustal stress state of Germany according to a data-calibrated geomechanical model
Authors: Ahlers Steffen , Henk Andreas , Hergert Tobias , Reiter Karsten , Müller Birgit , Röckel Luisa , Heidbach Oliver , Morawietz Sophia , Scheck-Wenderoth Magdalena , Anikiev Denis
Published: August 2021

Abstract. The contemporary stress state in the upper crust is of
great interest for geotechnical applications and basic research alike.
However, our knowledge of the crustal stress field from the data perspective
is limited. For Germany basically two datasets are available: orientations
of the maximum horizontal stress (SHmax) and the stress regime as part
of the World Stress Map (WSM) database as well as a complementary
compilation of stress magnitude data of Germany and adjacent regions.
However, these datasets only provide pointwise, incomplete and heterogeneous
information of the 3D stress tensor. Here, we present a
geomechanical–numerical model that provides a continuous description of the
contemporary 3D crustal stress state on a regional scale for Germany. The
model covers an area of about 1000×1250 km2 and extends to a depth of
100 km containing seven units, with specific material properties (density
and elastic rock properties) and laterally varying thicknesses: a
sedimentary unit, four different units of the upper crust, the lower crust
and the lithospheric mantle. The model is calibrated by the two datasets to
achieve a best-fit regarding the SHmax orientations and the minimum
horizontal stress magnitudes (Shmin). The modeled orientations of
SHmax are almost entirely within the uncertainties of the WSM data used
and the Shmin magnitudes fit to various datasets well. Only the
SHmax magnitudes show locally significant deviations, primarily
indicating values that are too low in the lower part of the model. The model is open
for further refinements regarding model geometry, e.g., additional layers
with laterally varying material properties, and incorporation of future
stress measurements. In addition, it can provide the initial stress state
for local geomechanical models with a higher resolution.
A portable lightweight in situ analysis (LISA) box for ice and snow analysis
Authors: Kjær Helle Astrid , Lolk Hauge Lisa , Simonsen Marius , Yoldi Zurine , Koldtoft Iben , Hörhold Maria , Freitag Johannes , Kipfstuhl Sepp , Svensson Anders , Vallelonga Paul
Published: August 2021

Abstract. There are enormous costs involved in transporting snow
and ice samples to home laboratories for “simple” analyses in order to
constrain annual layer thicknesses and identify accumulation rates of
specific sites. It is well known that depositional noise, incurred from factors such as wind
drifts, seasonally biased deposition and melt layers can influence
individual snow and firn records and that multiple cores are required to
produce statistically robust time series. Thus, at many sites, core samples
are measured in the field for densification, but the annual accumulation and
the content of chemical impurities are often represented by just one core to
reduce transport costs. We have developed a portable “lightweight in situ
analysis” (LISA) box for ice, firn and snow analysis that is capable of constraining
annual layers through the continuous flow analysis of meltwater
conductivity and hydrogen peroxide under field conditions. The box can run
using a small gasoline generator and weighs less than 50 kg. The LISA box
was tested under field conditions at the East Greenland Ice-core Project (EastGRIP) deep ice core drilling site
in northern Greenland. Analysis of the top 2 m of snow from seven
sites in northern Greenland allowed the reconstruction of regional snow
accumulation patterns for the 2015–2018 period (summer to summer).
Resolving GIA in response to modern and future ice loss at marine grounding lines in West Antarctica
Authors: Wan Jeannette Xiu Wen , Gomez Natalya , Latychev Konstantin , Han Holly Kyeore
Published: August 2021

Abstract. Accurate glacial isostatic adjustment (GIA) modeling in the cryosphere is required for interpreting satellite, geophysical and geological records and to assess the feedbacks of Earth deformation and sea level change on marine ice-sheet grounding lines. Assessing GIA in areas of active ice loss in West Antarctica is particularly challenging because the ice is underlain by laterally varying mantle viscosities that are up to several orders of magnitude lower than the global average, leading to a faster and more localized response of the solid Earth to ongoing and future ice sheet retreat and necessitating GIA models that incorporate 3-D viscoelastic Earth structure. Improvements to GIA models allow for computation of the viscoelastic response of the Earth to surface ice loading at sub-kilometre resolution and ice-sheet models and observational products now provide the inputs to GIA models at comparably unprecedented detail. However, the resolution required to capture GIA in models remains poorly understood, and high-resolution calculations come at heavy computational expense. We adopt a 3-D GIA model with a range of Earth structure models based on recent seismic tomography and geodetic data to perform a comprehensive analysis of the influence of grid resolution on predictions of GIA in the Amundsen Sea Embayment (ASE) in West Antarctica. Through idealized sensitivity testing down to sub-kilometre resolution with spatially isolated ice loading changes, we find that a grid resolution of ~3 times the radius of the load is required to accurately capture the elastic response of the Earth. However, when we consider more realistic, spatially coherent ice loss scenarios based on modern observational records and future ice sheet model projections and adopt a viscoelastic Earth, we find that errors of less than 5 % along the grounding line can be achieved with a 7.5 km grid, and less than 2 % with a 3.75 km grid, even when the input ice model is on a 1 km grid. Furthermore, we show that low mantle viscosities beneath the ASE lead to viscous deformation that contributes to the instrumental record on decadal timescales and equals or dominates over elastic effects by the end of the 21st century. Our findings suggest that for the range of resolutions of 1.9–15 km that we considered, the error due to adopting a coarser grid in this region is negligible compared to the effect of neglecting viscous effects and the uncertainty in the adopted mantle viscosity structure.
Like Mother, Like Daughter. Intergenerational Transmission of Infant Mortality Clustering in Zeeland, the Netherlands, 1833-1912
Authors: Van Dijk Ingrid K. , Mandemakers Kees
Published: August 2021

The burden of infant mortality is not shared equally by all families, but clusters in high risk families. As yet, it remains unclear why some families experience more infant deaths than other families. Earlier research has shown that the risk of early death among infants may at least partially be transmitted from grandmothers to mothers. In this paper, we focus on the intergenerational transmission of mortality clustering in the Netherlands in the province of Zeeland between 1833 and 1912, using LINKS Zeeland, a dataset containing family reconstitutions based on civil certificates of birth, marriage and death. We assess whether intergenerational transmission of mortality clustering occurred in Zeeland, and if so, whether it can be explained on the basis of the demographic characteristics of the families in which the infants were born. In addition, we explore the opportunities for comparative research using the Intermediate Data Structure (IDS). We find that mortality clustering is indeed transmitted from grandmothers to mothers, and that the socioeconomic status of the family, the survival of mothers and fathers, and the demographic characteristics of the family affected infant survival. However, they explain the heterogeneity in infant mortality at the level of the mother only partially.
Later-Life Mortality and Longevity in Late-18th and 19th-Century Cohorts. Where Are We Now, and Where Are We Heading?
Authors: Mourits Rick
Published: August 2021

The limits to human lifespan are a widely discussed topic. Yet, later-life mortality and longevity are generally studied from a genetic perspective, while the social dimension has received less attention. This paper gives a systematic overview of trends in later-life mortality and longevity for cohorts that were born in the late 18th and 19th century, and shows that the average population and the top survivors from cohorts born between 1800 and 1850 were already growing older. These improvements in human survival were similar for both of the sexes among the top survivors, whereas gender equality in the life expectancy at age 50 grew rapidly in cohorts born after 1880. Differences between populations were determined by the disease environment, availability of food, and local diets, while lifestyles and social support from spouses and kin affected later-life expectancy and longevity within these populations. These findings have major implications on how we view the demographic and epidemiological transition, and forces us to reconsider existing explanations for improvements in survival during the 19th century. However, in order to find out the determinants of later-life mortality, external validity of results, blind spots due to missing data, and familial clustering need to be studied more thoroughly.
Partner Choices in Long Established Migrant Communities in Belgium
Authors: Dupont Emilien , Van Pottelberge Amelie , Van de Putte Bart , Lievens John , Caestecker Frank
Published: August 2021

This paper aims to shed light on the partner choices of Moroccan, Turkish, Congolese, and Algerian migrants in Belgium. Three partner choices are distinguished: marrying a partner from the country of origin (partner migration), marrying a local co-ethnic partner, and establishing a mixed marriage. We focused on the role of migration history and transnational links, culture (religion, language), skin colour and structural characteristics of the district migrants live in (mainly community size) to gain further insight into the partner choices of migrants in Belgium. Our data comprise an extraction of the Belgian national register (2001-2008) and focus on first marriages among first, 1.5, and second generation migrants of Moroccan, Turkish, Algerian, and Congolese origin (N=52,142). We apply a multinomial logistic multilevel design to simultaneously incorporate individual and contextual effects at the district level. The main conclusion from this paper is that the partner selection pattern in early 21st century Belgian society still bears the traces of the starting conditions that migrant groups experienced when they first entered the country. While this continuity is important to understand the situation citizens with a migrant origin have to deal with today, it does not make change impossible. In fact, for the Turkish and Moroccan group, research recently showed a quite strong decline in transnational marriages and a modest increase in mixed marriages. These are indications that after 50 years of migration a transition towards full inclusion in Belgian society is not beyond reach. The conditions analysed in this paper, namely the strength of transnational networks, the cultural boundaries and the ethnic community size, may help to understand why this inclusion takes such a long period of time.
Changes in the Order of Family Life Events in 20th-Century Europe: A Cross-Regional Perspective
Authors: Burgin Reto , Schumacher Reto , Ritschard Gilbert
Published: August 2021

This article analyzes the evolution of the sequencing of family life events in Europe during the second half of the 20th century using individual data from the European Social Survey and from the Generation and Gender Program. Considering the four events ‘leaving the parental home‘, ‘first cohabiting union‘, ‘first marriage‘, and ‘first parenthood‘, we hypothesize a transition from a traditional standard event order characterized by a high degree of synchronization between the first three events towards a new standard whose features are a high degree of de-synchronization between first cohabitation and first marriage and a reversal of the traditional order between first marriage and first parenthood. We also hypothesize cross-regional differences in the timing and in the shape of the transition from one standard to another. Applying specifically developed tools to visualize and analyze event sequences, we show important regional variation in the evolution of the sequencing of family life events. Hardly any change can be observed in Southern Europe, where the sequencing behavior of family events has remained highly standardized and rooted in the traditional standard. In Eastern Europe where family event sequences have become less standardized and where a particular sequence characterized by the reversal of the traditional order between leaving home and family formation has been observed, the hypothesized transition is still in its very beginning. In Western Europe the transition is clearly on its way, but no re-standardization towards a new standard can be observed as for now. As expected, the transition is most advanced in Northern Europe, where evidence for a certain re-standardization process in the sequencing of family life events has been found.
Seasonality of livebirths and climatic factors in Italian regions (1863-1933)
Authors: Ruiu Gabriele , Breschi Marco
Published: August 2021

Birth seasonality is a phenomenon that characterizes almost all the populations of the world. In spite of this, the causes underlying these seasonal fluctuations represent an as yet unsolved puzzle. Two main theoretical approaches have been proposed to explain birth seasonality. The first encompasses a social explanation and emphasizes the role of social, economic and cultural factors in determining the optimal moment (from a social perspective) for conception (e.g., according to the cycle of agricultural workload, religious festivity, marriage seasonality, etc.). The second theoretical approach encompasses an environmental explanation and focuses on the role that climatic factors (e.g., temperature, rainfall, light intensity, etc.) play in determining the optimal moment of conception from a biological perspective. Our paper may be collocated in the latter strand of the literature. The aim is to investigate the effects of temperature on conceptions, and subsequently on the seasonality of livebirths, while controlling for a possible social confounding effect, i.e. the seasonal pattern of marriage. To achieve this end, we empirically investigate the role of temperature as well as that of marriage seasonality in Italian regions for the period stretching from the Italian unification to the eve of World War II. We find that extreme temperatures (both cold and hot) negatively affect the number of births. At the same time, marriage seasonality also seems to be an important explicative factor of the seasonal fluctuation of live births.
Intergenerational Transmission of Reproductive Behavior in Sweden, 1850-1889
Authors: Rotering Paul
Published: August 2021

Previous studies have consistently observed intergenerational continuities in childbearing. This study uses individual-level parish records to examine the intergenerational transmission of fertility over the life course of women in Sweden during the fertility transition in the second half of the nineteenth century. Bivariate correlations, event history analysis and Poisson regression models are estimated for a large number of indicators of reproductive behavior. In line with the literature, the findings show evidence of intergenerational fertility correlations. The observed correlations are often small, but show that fertility transmission did occur during the demographic transition. The findings confirm our current understanding of intergenerational transmission and highlight the role of kin members in shaping reproductive outcomes.
A Tale of Two Transcriptions. Machine-Assisted Transcription of Historical Sources
Authors: Thorvaldsen Gunnar , Pujadas-Mora Joana Maria , Andersen Trygve , Eikvil Line , Lladós Josep , Fornés Alícia , Cabré Anna
Published: August 2021

This article explains how two projects implement semi-automated transcription routines: for census sheets in Norway and marriage protocols from Barcelona. The Spanish system was created to transcribe the marriage license books from 1451 to 1905 for the Barcelona area; one of the world’s longest series of preserved vital records. Thus, in the Project “Five Centuries of Marriages” (5CofM) at the Autonomous University of Barcelona’s Center for Demographic Studies, the Barcelona Historical Marriage Database has been built. More than 600,000 records were transcribed by 150 transcribers working online. The Norwegian material is cross-sectional as it is the 1891 census, recorded on one sheet per person. This format and the underlining of keywords for several variables made it more feasible to semi-automate data entry than when many persons are listed on the same page. While Optical Character Recognition (OCR) for printed text is scientifically mature, computer vision research is now focused on more difficult problems such as handwriting recognition. In the marriage project, document analysis methods have been proposed to automatically recognize the marriage licenses. Fully automatic recognition is still a challenge, but some promising results have been obtained. In Spain, Norway and elsewhere the source material is available as scanned pictures on the Internet, opening up the possibility for further international cooperation concerning automating the transcription of historic source materials. Like what is being done in projects to digitize printed materials, the optimal solution is likely to be a combination of manual transcription and machine-assisted recognition also for hand-written sources.
Creating a typology of parishes in England and Wales: Mining 1881 census data
Authors: Schürer Kevin , Penkova Tatiana
Published: August 2021

The paper presents the application of principal component analysis and cluster analysis to historical individual level census data in order to explore social and economic variations and patterns in household structure across mid-Victorian England and Wales. Principal component analysis is used in order to identify and eliminate unimportant attributes within the data and the aggregation of the remaining attributes. By combining Kaiser’s rule and the Broken-stick model, four principal components are selected for subsequent data modelling. Cluster analysis is used in order to identify associations and structure within the data. A hierarchy of cluster structures is constructed with two, three, four and five clusters in 21-dimensional data space. The main differences between clusters are described in this paper.
Social Strata Differentials in Reproductive Behavior among Agricultural Families in the Krummhörn Region (East Frisia, 1720-1874)
Authors: Willführ Kai P. , Störmer Charlotte
Published: August 2021

In this paper, we investigate how the reproductive behavior of families in the historical Krummhörn region was affected by their social status and by short-term fluctuations in their socioeconomic conditions. Poisson and Cox regression models are used to analyze the age at first reproduction, fertility, the sex ratio of the offspring, sex-specific infant/child survival, and the number of children. In addition, we investigate how fluctuations in crop prices affected infant and child mortality and fertility using Cox proportional regression models. We also include information about the seasonal climate that may have had an effect on crop prices, as well as on infant mortality via other pathways. We find that the economic upper class produced more infants and had more children who survived to adulthood than the lower social strata. While the upper class did not have lower infant and child mortality than the lower class, they had more surviving children because of their shorter birth intervals and lower female age at marriage. Crop prices did not affect mortality or fertility before 1820. From 1820 onwards, high crop prices were associated with increased child (but not infant) mortality and with extended inter-birth intervals. We believe this period-sensitive response to changes in the crop price was the result of a social transition that took place during our study period, in which relations between the classes went from being based on communal “table fellowships” (Tischgemeinschaft) to being based on capitalist employer/employee arrangements.
Praktyki społeczne w czasie pandemii covid-19 wśród polskiej i ukraińskiej młodzieży
Authors: Długosz Piotr , Kryvachuk Liudmyla , Shyyan Olena
Published: August 2021

Abstrakt: Raport prezentuje wyniki badań dotyczące polskich i ukraińskich uczniów przebywających w domach podczas lockdownu. Głównym celem badawczym była próba odpowiedzenia na pytanie o to, w jaki sposób sobie radzą uczniowie z zagrożeniem pandemią COVID-19, a także czy pojawiają się różnice między młodzieżą polską i ukraińską w zakresie stosunku do pandemii, dobrostanu psychologicznego, reakcji na zagrożenie, wykorzystywania internetu w kwarantannie, form spędzania czasu wolnego oraz oceny zdalnego nauczania i jego wpływu na szanse życiowe i edukacyjne. Badania w obu krajach zostały przeprowadzone za pomocą ankiety online. W Polsce zrealizowano badania na próbie 1768, a na Ukrainie na próbie 2291 respondentów. Wyniki badań pokazują, że młodzież jest zainteresowana problematyką pandemii, śledzi jej przebieg. Poziom obaw uczniów przed zarażeniem się koronawirusem jest niski. Młodzież cechuje się dobrostanem psychologicznym i preferuje aktywne strategie walki z zagrożeniem. Większość swojego czasu spędza w internecie. Wykorzystuje go głównie do zdalnej edukacji, komunikacji z rówieśnikami oraz rozrywki. W czasie offline uczniowie najczęściej słuchają muzyki, uprawiają aktywność fizyczną i spacerują po okolicy. Niewielka część respondentów angażuje się w pomoc seniorom. Negatywnie oceniają zdalne nauczanie i uważają, że kwarantanna nie wpłynie zbyt silnie na ich szanse życiowe.
Temporal Land Use Change Analysis of Saleran Dam Catchment in Shivalik Foot-hills of Punjab using Geospatial Techniques
Authors: Vishnu Prasad  , Anil Bhardwaj
Published: August 2021

Mapping and monitoring of land use change in Shivalik foot-hills of north-west India is important for development, planning, and management of various catchments situated in this region. The present study was thus undertaken to monitor changes in land use of Saleran dam catchment located in Shivalik foot-hills of Punjab for the periods of 1999- 2009, 2009-2019, and 1999-2019 using remote sensing and GIS. The satellite imageries from Landsat-5 and Landsat-8 were used for change analysis. The supervised classification technique with maximum likelihood algorithm was applied to prepare land use maps of the catchment. Four major land use classes viz. mixed forest, degraded land, streams, and water bodies were identified. The accuracy of classified maps was assessed using high-resolution Google earth images, and ground realities were verified and determined through field observations. The results obtained from the accuracy assessment of classified images indicated the overall accuracy of 93.65%, 92.06%, and 92.86% with corresponding kappa values of 0.85, 0.89, and 0.84 for the classified image of the years 1999, 2009 and 2019, respectively. The results demonstrated significant changes in the catchment land use during the period of past 20 years (1999-2019), indicating significant decrease in mixed forests from 552.07 ha (74.87%) to 483.17 ha (65.53%), whereas an increase in degraded land from 142.39 ha (19.31%) to 221.1 ha (29.99%) was observed. The area under water bodies and mixed forest decreased by 36.49% and 12.48%, respectively, while the area under streams increased by 14.01 per cent. The study highlights the important policy implications for the sustainable land use management in the Saleran dam catchment of Shivalik foot-hills.
Identification of Soil Erosion Prone Areas of Madhya Pradesh using USLE/RUSLE
Authors: Ashwini Suryawanshi  , Anupam Kumar Nema  , Rahul Kumar Jaiswal  , Sukant Jain  , Saswat Kumar Kar
Published: August 2021

Soil erosion is caused due to the dynamic action of erosive agents, mainly water, and is a major threat to the environment. Primary aim of the present study was to study the soil loss dynamics, and identify the environmental hotspots in Madhya Pradesh to aid decision-makers to plan and prioritize appropriate conservation measures. Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE) models were applied for erosion rate estimation by generating thematic maps of R (Rainfall erosivity factor), K (Soil erodibility factor), LS (Topographic factor), C (Cover and management factor), and P (Support practice factor) factors by using several input parameters in QGIS software. Subsequently, the different classes of soil erosion and percentage area under these classes were identified. The average annual soil erosion for the entire state as obtained from the USLE and RUSLE model were 5.80 t.ha-1.yr-1 and 6.64 t.ha-1.yr-1, respectively. The areas under severe risk were 1.09 % and 1.80 %, and very severe risk areas were 1.57 % and 1.83 % as estimated by USLE and RUSLE model, respectively. As compared to RUSLE model, USLE model underestimated rate of soil erosion for most river basins of the state as well as for the entire state.
Potential of Pine Needle Biomass as an Alternative Fuel to Mitigate Forest Fire in Uttarakhand Himalayas - A Review
Authors: Padam Singh  , T. P. Singh  , Rajat Kumar Sharma  , Yogesh Kumar Negi  , Ramesh Pal
Published: August 2021

Pine needle is a typical biomass which is abundantly available in Uttarakhand hills. This shredded biomass contributes significantly in forest fire occurring regularly in Uttarakhand. Different energy harnessing routes as direct combustion, anaerobic digestion, pyrolysis, gasification, and briquetting for pine needle were reviewed. These routes were further compared on the basis of energy consumption and energy efficiency of the processes as per the available literature. The review suggested that briquetting of pine needle and its anaerobic digestion are two most energy efficient methods having energy efficiency of 88% and 41.6%, respectively. The estimated energy required for briquetting of 1 ton pine needle was 1370.5 MJ, whereas for gasification it was 1170 MJ.