bluuebunny/crossref_metadata_2025 huggingface dataset:
COMPARISON OF PSI AND DINSAR APPROACH FOR THE SUBSIDENCE MONITORING CAUSED BY COAL MINING EXPLOITATION
Authors: Pawluszek-Filipiak K. , Borkowski A.
Published: August 2020

Abstract. Underground coal exploitation has its reflection in ground movements such as subsidence, sinking or shaking. These cause buildings and infrastructure damage, therefore it is important to measure the magnitude of deformation. Last decades, Differential Interferometric Synthetic Aperture Radar (DInSAR) captured considerable attention as a tool for deformation monitoring. The results of conventional DInSAR, which utilizes two SAR images, are degraded due to atmospheric, topographic and orbital errors. To overcome these limitations, various stacking-based methods have been introduced. Therefore, the goal of presented study is to compare Persistent Scatterer Interferometry (PSI) as stacking-based method with classical DInSAR for monitoring of subsidence caused by underground coal exploitation. Deformations in the areas of active mining exploitation are characterised typically by rapid non-linear movement. The comparison has been performed for the area of active exploitation in Rydułtowy mine located in Upper Silesian Coal Basin (USCB) in Poland. Results from two separate PSI and DInSAR processing portray similar deformation pattern over the study area. Unfortunately, due to the temporal decorrelation, PSI clearly demonstrate smaller information coverage in respect to DInSAR results. Additionally, due to the applied linear deformation model, PSI failed in displacement estimation with magnitude higher than 12 cm. In contrast, DInSAR thanks 6-day temporal baseline and no assumption for a deformation model, was able to capture the maximum magnitude of subsidence reaching 86 cm/year. However, these results are affected by atmospheric artefacts which in presented case study can reach even 14 cm/year. To achieve few cm level of accuracy and to estimate high deformation magnitude such as in presented study case (1m/year), integrated use of both InSAR techniques seems to be the reasonable solution.
P-LINKNET: LINKNET WITH SPATIAL PYRAMID POOLING FOR HIGH-RESOLUTION SATELLITE IMAGERY
Authors: Ding Y. , Wu M. , Xu Y. , Duan S.
Published: August 2020

Abstract. Automatic extraction of buildings from high-resolution remote sensing imagery is very useful in many applications such as city management, mapping, urban planning and geographic information updating. Although extensively studied in the past years, due to the general texture of the building and the complexity of the image background, high-precision building segmentation from high-resolution sensing image is still a challenging task. Repeated pooling and striding operations used in CNNs reduce feature resolutions and cause the loss of detail information. In order to solve this problem, we proposed a deep learning model with a spatial pyramid pooling module based on the LinkNet. The proposed model called P-LinkNet that takes advantage of a spatial pyramid pooling module to capture and aggregate multi-scale contextual information. We tested it on Inria Building dataset. Experimental results show that the proposed P-LinkNet is superior to the LinkNet.
IMPROVING CLASSIFICATION OF MULTISPECTRAL IMAGES BASED ON SELECTED RELATIONS
Authors: Cohen L. , Almog O. , Shoshany M.
Published: August 2020

Abstract. A novel classification technique based on definition of unique spectral relations (such as slopes among spectral bands) for all land cover types named (SSF Significant Spectral Features) is presented in the article.A large slopes combination between spectral band pairs is calculated and spectral characterizations that emphasizes the best spectral land cover separation is sought. Increasing in dimensionality of spectral representations is balanced by the simplicity of calculations. The technique has been examined on data acquired by a flown hyperspectral scanner (AISA). The spectral data was narrowed into the equivalent 8 world-view2 channels. The research area was in the city of “Hadera”, Israel, which included 10 land cover types in an urban area, open area and road infrastructure. The comparison between the developed SSF technique and common techniques such as: SVM (Support Vector Machine) and ML (Maximum Likelihood) has shown a clear advantage over ML technique, while produced similar results as SVM. The poorest results of using SSF technique was achieved in an herbaceous area (70%). However, the simplicity of the method, the well-defined parameters it produces for interpreting the results, makes it intuitive over using techniques such as SVM, which is considered as a not explicit classifier.
A REAL-WORLD HYPERSPECTRAL IMAGE PROCESSING WORKFLOW FOR VEGETATION STRESS AND HYDROCARBON INDIRECT DETECTION
Authors: Dubucq D. , Audebert N. , Achard V. , Alakian A. , Fabre S. , Credoz A. , Deliot P. , Le Saux B.
Published: August 2020

Abstract. In this work, we present the complete workflow used to acquire a large hyperspectral dataset on a western Africa historical hydrocarbon production site, and its processing. Our goal is to study how state-of-the-art hyperspectral processing techniques can help detect hydrocarbon bearing soil either of natural origin or accidental by monitoring the health of the vegetation for exploration or environmental monitoring purposes. We present our complete workflow, from acquisition, atmospheric correction, image annotation and classification using modern machine learning techniques, and show how state-of-the-art research can be applied to real-world use cases.
USING MULTITEMPORAL HYPER- AND MULTISPECTRAL UAV IMAGING FOR DETECTING BARK BEETLE INFESTATION ON NORWAY SPRUCE
Authors: Honkavaara E. , Näsi R. , Oliveira R. , Viljanen N. , Suomalainen J. , Khoramshahi E. , Hakala T. , Nevalainen O. , Markelin L. , Vuorinen M. , Kankaanhuhta V. , Lyytikäinen-Saarenmaa P. , Haataja L.
Published: August 2020

Abstract. Various biotic and abiotic stresses are threatening forests. Modern remote sensing technologies provide powerful means for monitoring forest health, and provide a sustainable basis for forest management and protection. The objective of this study was to develop unmanned aerial vehicle (UAV) based spectral remote sensing technologies for tree health assessment, particularly, for detecting the European spruce bark beetle (Ips typographus L.) attacks. Our focus was to study the early detection of bark beetle attack, i.e. the “green attack” phase. This is a difficult remote sensing task as there does not exist distinct symptoms that can be observed by the human eye. A test site in a Norway spruce (Picea abies (L.) Karst.) dominated forest was established in Southern-Finland in summer 2019. It had an emergent bark beetle outbreak and it was also suffering from other stress factors, especially the root and butt rot (Heterobasidion annosum (Fr.) Bref. s. lato). Altogether seven multitemporal hyper- and multispectral UAV remote sensing datasets were captured from the area in August to October 2019. Firstly, we explored deterioration of tree health and development of spectral symptoms using a time series of UAV hyperspectral imagery. Secondly, we trained assessed a machine learning model for classification of spruce health into classes of “bark beetle green attack”, “root-rot”, and “healthy”. Finally, we demonstrated the use of the model in tree health mapping in a test area. Our preliminary results were promising and indicated that the green attack phase could be detected using the accurately calibrated spectral image data.
A SIMPLE ARTIFICIAL NEURAL NETWORK FOR FIRE DETECTION USING LANDSAT-8 DATA
Authors: Liu Z. , Wu K. , Jiang R. , Zhang H.
Published: August 2020

Abstract. Fixed threshold models have been widely used in active fire detection products. However, its accuracy is limited due to the complexity of setting up thresholds. Artificial neural network (ANN) is capable of learning from data and can decide weights automatically. Given enough data, an ANN model is able to optimize itself and quickly find an optimal solution. In this work, a simple ANN model is implemented to classify fire pixels from Landsat-8 data. Experimental results show that our ANN model effectively achieves fire detection and performs better than fixed threshold model in certain circumstances.
EMAP-DCNN: A NOVEL MATHEMATICAL MORPHOLOGY AND DEEP LEARNING COMBINED FRAMEWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Authors: Teffahi H. , Teffahi N.
Published: August 2020

Abstract. The classification of hyperspectral image (HSI) with high spectral and spatial resolution represents an important and challenging task in image processing and remote sensing (RS) domains due to the problem of computational complexity and big dimensionality of the remote sensing images. The spatial and spectral pixel characteristics have crucial significance for hyperspectral image classification and to take into account these two types of characteristics, various classification and feature extraction methods have been developed to improve spectral-spatial classification of remote sensing images for thematic mapping purposes such as agricultural mapping, urban mapping, emergency mapping in case of natural disasters... In recent years, mathematical morphology and deep learning (DL) have been recognized as prominent feature extraction techniques that led to remarkable spectral-spatial classification performances. Among them, Extended Multi-Attribute Profiles (EMAP) and Dense Convolutional Neural Network (DCNN) are considered as robust and powerful approaches such as the work in this paper is based on these two techniques for the feature extraction stage and used in two combined manners and constructing the EMAP-DCNN frame. The experiments were conducted on two popular datasets: “Indian Pines” and “Huston” hyperspectral datasets. Experimental results demonstrate that the two proposed approaches of the EMAP-DCNN frame denoted EMAP-DCNN 1, EMAP-DCNN 2 provide competitive performances compared with some state-of-the-art spectral-spatial classification methods based on deep learning.
AUTOMATED ROAD INFORMATION EXTRACTION FROM HIGH RESOLUTION AERIAL LIDAR DATA FOR SMART ROAD APPLICATIONS
Authors: Previtali M. , Barazzetti L. , Scaioni M.
Published: August 2020

Abstract. Automatic extraction of road features from LiDAR data is a fundamental task for different applications, including asset management. The availability of updated and reliable models is even more important in the context of smart roads. One of the main advantages of LiDAR data compared with other sensing instruments is the possibility to directly get 3D information. However, the task of deriving road networks form LiDAR data acquired with Airborne Laser Scanning (ALS) may be quite complex due to occlusions, low feature separability and shadowing from contextual objects. Indeed, even if roads elements can be identified in the ALS point cloud, the automated identification of the network starting form them can be involved due to large variability in the size of roads, shapes and presence of connected off-road features such as parking lots. This paper presents a workflow aimed at partially solving the automatic creation of a road network from high-resolution ALS data. The presented method consists of three main steps: (i) labelling of road points; (ii) a multi-level voting scheme; and (iii) the regularization of the extracted road segments. The developed method has been tested using the “Vaihingen”, “Toronto” and “Tobermory” data set provided by the ISPRS.
FUSION OF HYPERSPECTRAL AND PANCHROMATIC DATA BY SPECTRAL UNMIXING IN THE REFLECTIVE DOMAIN
Authors: Constans Y. , Fabre S. , Seymour M. , Crombez V. , Briottet X. , Deville Y.
Published: August 2020

Abstract. Earth observation at the local scale implies working on images with both high spatial and spectral resolutions. As the latter cannot be simultaneously provided by current sensors, hyperspectral pansharpening methods combine images jointly acquired by two different sensors, a panchromatic one providing high spatial resolution, and a hyperspectral one providing high spectral resolution, to generate an image with both high spatial and spectral resolutions. The main limitation in the fusion process is in presence of mixed pixels, which particularly affect urban scenes, and where large fusion errors may occur. Recently, the Spatially Organized Spectral Unmixing (SOSU) method was developed to overcome this limitation, delivering good results on agricultural and peri-urban landscapes, which contain a limited number of mixed pixels. This article presents a new version of SOSU, adapted to urban landscapes. It is validated on a Toulouse (France) urban dataset at a 1.6 m spatial resolution acquired by the HySpex instrument from the 2012 UMBRA campaign. A performance assessment is established, following Wald’s protocol and using complementary quality criteria. Visual and numerical (at the global and local scales) analyses of this performance are also proposed. Notably, in the VNIR domain, around 51 % of the mixed pixels are better processed by the presented version of SOSU than by the method used as a reference. This ratio is improved regarding shadowed areas in the reflective (52 %) and VNIR (57 %) domains.
COMPARING THE GENERATION OF DTM IN A FOREST ECOSYSTEM USING TLS, ALS AND UAV-DAP, AND DIFFERENT SOFTWARE TOOLS
Authors: Crespo-Peremarch P. , Torralba J. , Carbonell-Rivera J. P. , Ruiz L. A.
Published: August 2020

Abstract. Remote sensing and photogrammetry techniques have demonstrated to be an important tool for the characterization of forest ecosystems. Nonetheless, the use of these techniques requires an accurate digital terrain model (DTM) for the height normalization procedure, which is a key step prior to any further analyses. In this manuscript, we assess the extraction of the DTM for different techniques (airborne laser scanning: ALS, terrestrial laser scanning: TLS, and digital aerial photogrammetry in unmanned aerial vehicle: UAV-DAP), processing tools with different algorithms (FUSION/LDV© and LAStools©), algorithm parameters, and plot characteristics (canopy and shrub cover, and terrain slope). To do this, we compare the resulting DTMs with one used as reference and extracted from classic surveying measurements. Our results demonstrate, firstly, that ALS and reference DTMs are similar in the different scenarios, except for steep slopes. Secondly, TLS DTMs are slightly less accurate than those extracted for ALS, since items such as trunks and shrubs cause a great occlusion due to the proximity of the instrument, and some of the points filtered as ground correspond to these items as well, therefore a finer setting of algorithm parameters is required. Lastly, DTMs extracted for UAV-DAP in dense canopy scenarios have a low accuracy, however, accuracy may be enhanced by modifying the processing tool and algorithm parameters. An accurate DTM is essential for further forestry applications, therefore, to know how to take advantage of the available data to obtain the most accurate DTM is also fundamental.
ON THE JOINT EXPLOITATION OF OPTICAL AND SAR SATELLITE IMAGERY FOR GRASSLAND MONITORING
Authors: Garioud A. , Valero S. , Giordano S. , Mallet C.
Published: August 2020

Abstract. Time series of optical and Synthetic Aperture RADAR (SAR) images provide complementary knowledge about the cover and use of the Earth surface since they exhibit information of distinct physical nature. They have proved to be particularly relevant for monitoring large areas with high temporal dynamics and related to significant ecosystem services. Grasslands are such crucial surfaces, both in terms of economic and environmental issues and the automatic and frequent monitoring of their agricultural practices is required for many purposes. To address this problem, the deep-based SenDVI framework is presented. SenDVI proposes an object-based methodology to estimate NDVI values from Sentinel-1 SAR observations and contextual knowledge (weather, terrain). Values are regressed every 6 days for compliance with monitoring purposes. Very satisfactory results are obtained with this low-level multimodal fusion strategy (R2 = 0.84 on a Sentinel-2 tile). Finer analysis is however required to fully assess the relevance of each modality (Sentinel-1, Sentinel-2, weather, terrain) and feature sets and to propose the simplest conceivable framework. Results show that not all features are necessary and can be discarded while others have a mandatory contribution to the regression task. Moreover, experiments prove that accuracy can be improved by not saturating the network with non-essential information (among contextual knowledge in particular). This allows to move towards more operational solution.
MAPPING RECURRENT FLOODING ZONE ALONG ESTONIAN INLAND WATERS FROM SENTINEL-1 AND -2
Authors: Sipelgas L. , Aavaste A. , Uiboupin R.
Published: August 2020

Abstract. In the process of spatial planning in Estonia the local municipalities are required to define the recurrent flooding zone along the inland waters that locate at their territory. Estonia is well known for its large floodplains that are annually covered by water. However, information about the spatial flood extent is scarce. A methodology for mapping the flooded area from Sentinel-1 and -2 imagery was developed and applied on data covering high water seasons in 2016–2019. Statistical information about flooded areas along the inland waters were compared with other available data sources related to wetlands i.e. map of wetlands in Estonian Topographic Database. Results showed that additional information about flood extent and duration retrieved from Sentinel-1 and Sentinel-2 the data can contribute to defining the recurrent flooding zone along the inland waters in process on spatial planning.
POLICY DRIVEN APPLICATION OF REMOTE SENSING IN MITIGATING URBAN SPRAWL: A CASE STUDY OF DEVELOPING NATION
Authors: Shah P. B. , Patel C. R.
Published: August 2020

Abstract. Sustainable Development have drawn much attentions to the direct or indirect relationships of land use/land cover changes in past recent years. Being a limited resource, Land is critical issue to manage by the city administration in absence of effective tool. Geospatial Techniques can solve this issues of sprawl modelling and can act as decision supportive tool. This study focuses on Surat and Lucknow Indian Cities, its surrounding area to delineate a metropolitan area with the use of geospatial technology. It encompasses the jurisdictions of various urban development authorities to provide a regional context of development for the year 2035. These cities have unique characteristic of development which is investigated using remote sensing technology. Temporal analysis of study area images has deployed that there is a pressing need to control the Development because of its incessant characteristic. Role of Remote sensing is found to be very vital to understand and measure the sprawl’s magnitude. Analysing the spatial dynamics of cities has escalated the need of policy making for controlled development. Insights of this study can be useful for framing policy at a regional or global level.
A SEQUENCE-TO-SEQUENCE TEMPORAL CONVOLUTIONAL NEURAL NETWORK FOR IONOSPHERE PREDICTION USING GNSS OBSERVATIONS
Authors: Kaselimi M. , Doulamis N. , Doulamis A. , Delikaraoglou D.
Published: August 2020

Abstract. This paper proposes a model suitable for predicting the ionosphere delay at different locations of receiver stations using a temporal 1D convolutional neural network (CNN) model. CNN model can optimally addresses non-linearity and model complex data through the creation of powerful representations at hierarchical levels of abstraction. To be able to predict ionosphere values for each visible satellite at a given station, sequence-to-sequence (seq2seq) models are introduced. These models are commonly used for solving sequential problems. In seq2seq models, a sequential input is entered to the model and the output has also a sequential form. Adopting this structure help us to predict ionosphere values for all satellites in view at every epoch. As experimental data, we used global navigation satellite system (GNSS) observations from selected sites in central Europe, of the global international GNSS network (IGS). The data used are part of the multi GNSS experiment (MGEX) project, that provides observations from multiple navigation satellite systems. After processing with precise point positioning (PPP) technique as implemented with GAMP software, the slant total electron content data (STEC) were obtained. The proposed CNN uses as input the ionosphere pierce points (IPP) points coordinates per visible satellite. Then, based on outcomes of the ionosphere parameters, the temporal CNN is deployed to predict future TEC variations.
CLOUD CLASSIFICATION FOR GROUND-BASED SKY IMAGE USING RANDOM FOREST
Authors: Wan X. , Du J.
Published: August 2020

Abstract. The use of solar power as a renewable energy has grown rapidly over the last few decades. However, the amount of solar radiation reaching the ground vary significantly in the short term. Clouds are the main factor. In this paper, a novel cloud detection method for ground-based sky images is proposed. First, the multiple features from the sky images, including spectral, texture and colour features are combined into a feature set. Then, Random Forest with this feature set is used to classify different types of cloud and clear sky. The experimental results show that cumulus and cirrus clouds can be identified from sky images. Combined with random forest, three types of features and various feature combinations are used for cloud classification, respectively. The classification accuracy with multiple features is higher than that of single-type features and dual-type features.
SPATIOTEMPORAL ANALYSIS OF SNOW DEPTH ON FIRST-YEAR ICE BASED ON FY3B/MWRI IN THE ARCTIC
Authors: Li L. , Chen H. , Guan L.
Published: August 2020

Abstract. As an important factor in the stability of the climate system in the northern hemisphere, the Arctic has recently attracted considerable attention. In the Arctic, most sea ice is covered by snow year-round, except in the snow-melting season. Given its high albedo and low thermal conductivity, snow cover on sea ice is considered a key component of amplified warming in the Arctic. However, in Arctic regions, the only products available are for snow depths on first-year ice. Therefore, this paper studies the temporal and spatial changes of snow depth on first-year ice in the Arctic using the snow depth on sea ice product determined from the Microwave Radiation Imager onboard the Feng Yun-3B satellite. We averaged the daily snow depth on first-year ice data to give monthly and annual values over the period 2011–2018, using flags for multiyear ice and melting points. Taking the 2012 data as an example, the analysis results show that the spatial distribution of snow depth in the monthly and annual data is similar over the whole first-year ice area. The snow depth basically decreases with latitude, and the distribution features exhibit little variation by month and year. The weekly mean snow depth on first-year ice begins to increase from October/November due to snowfall, and reaches a maximum value in late April/early May of the next year. There is no obvious law governing the inter-annual variation of snow depth in the Arctic from 2011–2018.
ZAB RIVER (IRAQ) SINUOSITY AND MEANDERING ANALYSIS BASED ON THE REMOTE SENSING DATA
Authors: Kalantar B. , Ameen M. H. , Jumaah H. J. , Jumaah S. J. , Halin A. A.
Published: August 2020

Abstract. This work studies the meandering and change of paths along the Zab River in Iraq. Landsat-5 TM, Landsat-7 ETM+ and Landsat-8 (2-sets) images were acquired from the years 1989, 1999, 2015 and 2019, respectively, which were used together with Remote sensing and Geographic Information Systems (GIS) techniques to study the changes. To determine the river/stream shape, the Sinuosity Index was calculated to classify Zab River segments into either the straight, sinuous or meandering class. Our findings via image analysis show coarse river migration and that most river segments fall into the two classes of sinuous and meander. In addition, it seems that the east bank of the Zab River region of the basin has extremely shifted where the river passes near the Kirkuk governorate.
The Piuquencillo Fault System: a long-lived, Andean-transverse fault system and its relationship with magmatic and hydrothermal activity
Authors: Piquer Jose , Rivera Orlando , Yañez Gonzalo , Oyarzun Nicolas
Published: August 2020

Abstract. Lithospheric-scale fault systems control the large-scale permeability in the Earth’s crust and lithospheric mantle, and its proper recognition is fundamental to understand the geometry and distribution of mineral deposits, volcanic and plutonic complexes and geothermal systems. However, their manifestations at the current surface can be very subtle, as in many cases they are oriented oblique to the current continental margin and to the axis of the magmatic arc, can be partially obliterated by younger, arc-parallel faults, and can also be covered by volcanic and sedimentary deposits, through which the fault might propagate vertically. The Piuquencillo Fault System (PFS) is a proposed lithospheric-scale fault system, located in the Main Cordillera of Central Chile. Here we present the results of the first detailed field study of the PFS, based on structural data collected at 82 structural stations distributed across all the Western Main Cordillera. The first published U-Pb zircon ages for the La Obra batholith, which is bounded to the south by the PFS but it is also affected by younger reactivations of it, were obtained. They yielded 20.79 ± 0.13 Ma (granodiorite) and 20.69 ± 0.07 (monzogranite). Statistical analysis of fault plane data shows that the presence of the PFS is reflected on a strong preferred NW to WNW strike, with variable dip directions, evident from the analysis of the total fault plane population and also from individual segments of the PFS. In some segments, the presence of major NE to ENE-striking faults which intersect the PFS is also reflected in the preferred orientation of fault planes. Preferred orientations of hydrothermal veins, breccias and dikes show that both the PFS and some ENE-striking faults were capable of channeling hydrothermal fluids and magma. Kinematic and dynamic analysis of fault-plane data reveals that most of the PFS was reactivated with sinistral ± reverse kinematics during the Neogene, under a strike-slip to transpressive regime with E- to ENE-trending shortening direction (σ1). Detailed kinematic and dynamic analyses were completed for various segments of the PFS and also for the different rock units affected by it. This study supports the concept that the PFS is a lithospheric-scale fault system, which strongly controlled deformation and the flow of magmas and hydrothermal fluids during the Neogene. The PFS forms part of a larger, margin-transverse structure, the Maipo Deformation Zone, a continental-scale discontinuity which cut across the entire Chilean continental margin, and which has been active at least since the Jurassic.
Cover Art
Authors: Ruicci Kara
Published: August 2020

‘Mental Health’ encompasses our cognitive, behavioural and emotional wellbeing; disorders of mental health affect mood, thinking and behaviour. To this day, mental health disorders are feared and stigmatized because these conditions are not overtly visible. The way forward in continuing to dissipate the stigma associated with mental health disorders is to recognize, diagnose and treat these conditions—just as we do for any other ailment of the body. Here, a stethoscope representing medical care is shown surrounding the profile of a human face. Inside, a brain is seen; if you look closely, you will see that its shape is comprised by lines forming a fingerprint. The fingerprint signifies the wide range of mental health conditions and their unique manifestations between individuals. Continued advancements in both research and the clinical management of mental health conditions will improve patient care and help continue to dispel stigma.
Boards’ Gender Diversity and Firms’ Financial and Ethical Performance in Pakistan: A Comparative Analysis
Authors: Awais Hafiz Muhammad , Siddiqui Dr. Danish Ahmed
Published: August 2020

Board diversity has lately being a heavily contested topic of research. Women, having a unique pool of resources and human capital, bring unique and diverse skills to the board that could improve board performance which positively impacts firm value. This study aims to investigate board gender diversity and its impact on firms’ performance in Pakistan. More specifically, this study compares different performance characteristic of firms with and without gender diversity in boards. We also analyzed the effect of women on board (WOB) on different performance measures in the presence of control variables. These measures included Return to assets, equity and sales, TOBIN Q, and Ethical and Social Compliance (ESCC). For this, panel data of 4 years from 2015 to 2018 were collected from 100 companies, and ANOVA and regression analysis were performed. The comparative analysis showed that non-women component has a significantly higher ROA than women, whereas ROE is higher for women. Moreover, non-women board companies seem to take a higher financial risk by taking more leverage. Surprisingly, the ESCC factor seems to be significantly higher for non-women board companies showing better social compliance. Evidence from regression found remains inconclusive. In fact, the performance measures like Tobin Q, and ROA seems to be negatively affected by WOB, whereas ROE was positively and significantly affected. ESCC seems to have a strong and positive effect on Tobin Q in companies with WOB, as well as ROA in overall companies. Evidence also suggested that WOB also seems to have a negative effect on ESCC. Hence, in the case of Pakistan, the findings remained inconclusive because women representation on board is not enough to have an influencing role in the board. The size of the female representation on the board needs to be sufficiently large to have an influencing role on corporate boards.
One Dose Versus Two Doses of Intravenous Tranexamic Acid in Total Joint Arthroplasty
Authors: Golz Andrew G. , Yee Heather K. , Davis Benjamin J. , Adams William H. , Brown Nicholas M.
Published: August 2020

Introduction:

Despite its widespread use, a single formulation or dosing regimen of tranexamic acid (TXA) has not been universally agreed on for total joint arthroplasty. The purpose of this study is to compare previously uninvestigated single-dose and two-dose regimens in postoperative hemoglobin level and secondary outcomes within 30 days of surgery.

Methods:

A retrospective search of our institution's database of patients who underwent primary total knee arthroplasty and primary total hip arthroplasty between January 1, 2017, and July 1, 2019, was performed. Patients were divided into two groups: one group received a 1-g bolus of intravenous TXA just before incision and another intravenous 1-g bolus during wound closure, and the second group received a single 1-g intravenous bolus of TXA just before incision. Two doses of TXA were administered in 873 procedures, and a single dose was administered in 647 procedures.

Results:

A single intravenous TXA dose just before incision was comparable with using two doses of intravenous TXA on patients' postoperative hemoglobin value, length of stay, rate of transfusion, and 30-day postoperative complication rate, although those receiving two doses of TXA trended toward being less likely to require a transfusion (odds ratio = 0.561; 95% confidence interval: 0.296 to 1.062; P = 0.08). A sensitivity analysis was unable to identify a preoperative hemoglobin value that would identify whether patients would benefit from two versus one dose of TXA.

Discussion:

The use of a single intravenous TXA dose was as efficacious as two doses, without an increase in postoperative complications. Further studies may identify patient subgroups that would benefit from a second dose.

Level of Evidence:

Level III, retrospective cohort study
Interprofessional Collaborating: A Model That Prepares Undergraduate Teachers and Social Workers for Interprofessional Practice in Schools
Authors: Testa Doris , Renwick Kerry
Published: August 2020

The Health Promoting School (HPS) premises its approach on interprofessional collaboration. Despite this, there are few studies into how Australian, Victorian social workers and teachers prepare for interprofessional collaboration within health promoting schools. There are few studies into how undergraduate social workers and teachers understand the HPS school setting and the role of social workers and teachers in promoting educational achievement and wellbeing within a HS school site. There are even fewer studies in how undergraduate social workers and teachers experience units of study delivered using interprofessional education (IPE) approaches.
Laboratory diagnostics of iron overload
Authors: Dziatkiewicz-Warkocz Paulina , Gil Lidia , Kozłowska-Skrzypczak Maria
Published: August 2020

Iron is a fundamental trace element, essential to maintain homeostasis in living organisms. Iron overload can result from increased
iron absorption in the gastrointestinal system, repeated blood transfusions or liver diseases. The iron turnover is regulated by a group
of specialized proteins, responsible for its absorption, transport, oxidation and preventing tissue damage that can be caused by the
ferrous ions Fe2+. Diagnosis of iron overload states, as well the course of treatment oversight, is based on continuous monitoring of
the iron concentration in the body. The use of numerous laboratory tests is the first stage of diagnostics. This work describes primary
mechanisms responsible for the regulation of iron metabolism and the consequences of iron overload. Furthermore, it presents an
analysis of the currently applied laboratory parameters and other methods used to evaluate iron overload conditions.
Conjugation of vascular endothelial growth factor to poly lactic-co-glycolic acid nanospheres enhances differentiation of embryonic stem cells to lymphatic endothelial cells
Authors: Yoo Hyunjin , Choi Dongyoon , Choi Youngsok
Published: August 2020

Objective: Pluripotent stem cell-derived lymphatic endothelial cells (LECs) show great promise in their therapeutic application in the field of regenerative medicine related to lymphatic vessels. We tested the approach of forced differentiation of mouse embryonal stem cells into LECs using biodegradable poly lactic-co-glycolic acid (PLGA) nanospheres in conjugation with growth factors (vascular endothelial growth factors [VEGF-A and VEGF-C]).Methods: We evaluated the practical use of heparin-conjugated PLGA nanoparticles (molecular weight ~15,000) in conjugation with VEGF-A/C, embryoid body (EB) formation, and LEC differentiation using immunofluorescence staining followed by quantification and quantitative real-time polymerase chain reaction analysis.Results: We showed that formation and differentiation of EB with VEGF-A/C-conjugated PLGA nanospheres, compared to direct supplementation of VEGF-A/C to the EB differentiation media, greatly improved yield of LYVE1(+) LECs. Our analyses revealed that the enhanced potential of LEC differentiation using VEGF-A/C-conjugated PLGA nanospheres was mediated by elevation of expression of the genes that are important for lymphatic vessel formation.Conclusion: Together, we not only established an improved protocol for LEC differentiation using PLGA nanospheres but also provided a platform technology for the mechanistic study of LEC development in mammals.
Generation of single stranded DNA with selective affinity to bovine spermatozoa
Authors: Vinod Sivadasan Pathiyil , Vignesh Rajamani , Priyanka Mani , Tirumurugaan Krishnaswamy Gopalan , Sivaselvam Salem Nagalingam , Dhinakar Raj Gopal
Published: August 2020

Objective: This study was conducted to generate single stranded DNA oligonucleotides with selective affinity to bovine spermatozoa, assess its binding potential and explore its potential utility in trapping spermatozoa from suspensions.Methods: A combinatorial library of 94 mer long oligonucleotide was used for systematic evolution of ligands by exponential enrichment (SELEX) with bovine spermatozoa. The amplicons from sixth and seventh rounds of SELEX were sequenced, and the reads were clustered employing cluster database at high identity with tolerance (CD-HIT) and FASTAptamer. The enriched nucleotides were predicted for secondary structures by Mfold, motifs by Multiple Em for Motif Elicitation and 5’ labelled with biotin/6-FAM to determine the binding potential and binding pattern.Results: We generated 14.1 and 17.7 million reads from sixth and seventh rounds of SELEX respectively to bovine spermatozoa. The CD-HIT clustered 78,098 and 21,196 reads in the top ten clusters and FASTAptamer identified 2,195 and 4,405 unique sequences in the top three clusters from the sixth and seventh rounds, respectively. The identified oligonucleotides formed secondary structures with delta G values between –1.17 to –26.18 kcal/mol indicating varied stability. Confocal imaging with the oligonucleotides from the seventh round revealed different patterns of binding to bovine spermatozoa (fluorescence of the whole head, spot of fluorescence in head and mid- piece and tail). Use of a 5’-biotin tagged oligonucleotide from the sixth round at 100 pmol with 4×106 spermatozoa could trap almost 80% from the suspension.Conclusion: The binding patterns and ability of the identified oligonucleotides confirms successful optimization of the SELEX process and generation of aptamers to bovine spermatozoa. These oligonucleotides provide a quick approach for selective capture of spermatozoa from complex samples. Future SELEX rounds with X- or Y- enriched sperm suspension will be used to generate oligonucleotides that bind to spermatozoa of a specific sex type.
Growth, carcass traits, immunity and oxidative status of broilers exposed to continuous or intermittent lighting programs
Authors: Abo Ghanima Mahmoud  M. , Abd El-Hack Mohamed E. , Abougabal Mohammed Sh. , Taha Ayman E. , Tufarelli Vincenzo , Laudadio Vito , Naiel Mohammed A. E.
Published: August 2020

Objective: An experiment was conducted to investigate the continuous and intermittent lighting program effects on terms of the productive performance, carcass traits, blood biochemical parameters, innate immune and oxidative status in broiler chicks. Methods: A total of 600 Cobb-500 one day old chicks were randomly allocated into six equal groups (100 chicks per treated group with five replicates of 20 chicks each) based on lighting program; 22 continuous lighting (22 C), 11 h lighting+1 darkness twice daily (11 L/1 D), 20 h continuous lighting (20 C), 5 h lighting+1 darkness four times daily (5 L/1 D), 18 h continuous lighting (18 C) and the final group subjected for 3 h lighting+1 h darkness six times daily (3 L/1 D). The experimental period lasted 42 days. Results: Compared with those under the intermittent light program, broiler chicks exposed to continuous lighting for 22 h had significant improvement in live body weight and carcass (dressing and breast percentage) measured traits. Though reducing lighting hours significantly reduced feed intake and feed conversion ratio values. Different lighting programs revealed no significant effect on all blood biochemical parameters. Oxidative stress and innate immunity parameters significantly enhance by reducing lighting hours (3L/1D). Conclusion: The findings suggest that reducing lighting hours up to 3L/1D would be more useful in enhancing feed efficiency, innate immunity, and oxidative status compared with continuous lighting programs on broilers.
Exploring Constituents of Short Food Supply Chains
Authors: Ashtab Sahand , Xing Yang , Zheng Cheng
Published: August 2020

By deploying a systematic review approach, this chapter provides a holistic exploration of AFNs which contributes to further mobilization of locally produced products. This chapter explores the constituents of AFNs by studying food citizenship, sustainability and food democracy, food safety and quality, embeddedness and social capital, the relationship between the level of participation in AFNs and consumers’ demographics, consumers’ motivations to engage in buy-local activities, vendors’ perspective on selling products in farmers’ market, and the development of short food supply chains in the Canadian context. Specifically, the social interaction aspect of buying local, for example, engaging with vendors and other consumers, has been cited as a factor that motivates consumers to buy local food products from the farmers’ market; however, consumers had to deploy online ordering channels with door delivery option during COVID-19 pandemic to access locally produced products safely. To capture one aspect of the potential impacts of COVID-19 pandemic on AFNs, future research can explore whether social interaction is still an influential factor in consumers decision to buy local, or the importance of the social interaction aspect of buying local will be replaced by the convenience of receiving the fresh, locally produced food products at consumers’ doorstep via online ordering process.
History of Science During the Cold War Under the Microscope
Authors: Báthory Dalia ,   Zeta Books
Published: August 2020

The general post-communist perspective of historiography on the Cold War era is that the world was divided into two blocs, so different and isolated from one another that there was no interaction between them whatsoever. As revisionist literature is expanding, the uncovered data indicates a far more complex reality, with a dynamic East-West exchange of goods, money, information, human resources, and technology, be it formal or informal, official or underground, institutional or personal. The current volume History of Communism in Europe: Breaking the Wall: National and Transnational Perspectives on East-European Science tries to confer more detail to this perspec­tive, by bringing together research papers that focus on the history of science during the Cold War. The articles cover a wide range of subjects, from biology to philosophy and from espionage to medical practices, all sharing an ideological context that continuously impacted and molded the professional relations among scholars from both sides of the Iron Curtain.
L’histoire médicale et politique du pavlovisme en Russie et en France
Authors: Dupont Jean-Claude ,   Zeta Books
Published: August 2020

La méthode psychoprophylactique d’accouchement sans douleur (MPP) se développe en URSS dans un contexte stalinien sur les principes de la médecine pavlovienne, définie officiellement lors de la « session pavlovienne » de 1950. En France, c’est la figure de Fernand Lamaze qui est associée à la promotion de l’accouchement sans douleur, après qu’il ait importé la MPP d’Union soviétique l’année suivante. D’abord soutenue par les organisations marxistes et le mouvement d’émancipation des femmes, elle sera ensuite contestée sous l’effet des transformations dans la gestion médicale de l’accouchement et des rivalités politiques de la guerre froide. L’article interroge les origines historiques, épistémologiques et politiques de la médecine pavlovienne. Il compare la réception du pavlovisme à l’Ouest et à l’Est en suivant le fil de l’histoire de l’accouchement sans douleur et les enjeux en France et en URSS d’une controverse dans laquelle médecine et politique s’entremêlent.
Developing Home Economics Education Programs for Sustainable Development: Focusing on Changemaker Education with the Theme of ‘Improving Consumer Life’
Authors: Kim Nam Eun
Published: August 2020

The purpose of this study is to develop home economics educational programs on the theme of ‘improving consumer life’ for sustainable development. It is a program to enhance the changemaker mindset for responsible production and consumption among the 17 goals of the Sustainable Development Goals(SDGs). The program was developed 8 that to make solar cookers, make household goods from recycled materials, change maker-practice green life, eco-friendly journal 1, plastic warnings, design alternatives for disposable products, change makerefforts and eco-friendly journal 2. The developed program was validated 3 times by a group of experts and students. This program has the following features. First, the Home Economics Education(HEE) program under the theme of ‘Improving consumer life’ for sustainable development are carried out at the stage of change-maker education with project-based process. It can improve students’ collaboration skills, self-directed skills, communication skills and problem solving skills. Second, eight programs can increase understanding and interest in sustainable development, and learners are interested in social issues. This program can raise learners who play an active role in solving social problems by increasing their interest and interest in the class, free from the form of passive classes. Third, the HEE programs under the theme of ‘Improving consumer life’ for sustainable development are meaningful in that they are closely related to students’ lives and encourage them to practice in their own lives. Fourth, since the program is well-suited to the present time and includes content elements for sustainable development, it can induce changes in learners’ perceptions, attitudes and behaviors.
The Effects of Fathers’ Parenting Involvement on Young Children’s Self-Control: The Mediating Effect of Mothers’ Parenting Competence
Authors: Mi-Kyung Choi
Published: August 2020

This study investigated the relationship among fathers’ parenting involvement, mothers’ parenting competence, and young children’s self-control. Participants consisted of 325 mothers and young children (169 boys and 153 girls) from the Seoul area who completed questionnaires on fathers’ parenting involvement, mothers’ parenting competence, and young children’s self-control. Data were statistically analyzed using basic descriptive statistics, Pearson’s correlation, and multiple regression analysis. Baron and Kenny’s method was examined. Subsequently, the Sobel test was performed to check the mediating model’s significance and was adapted to SPSS version 21.0 for Windows. The major findings were as follows. First, fathers’ parenting involvement was positively correlated with young children’s self-control and mothers’ parenting competence. Second, mothers’ parenting competence was positively correlated with young children’s self-control. The mothers’ parenting competence indicated a tendency to play a perfectly/partially play a mediating role between fathers’ parenting involvement and young children’s selfcontrol; consequently, a fathers’ parenting involvement had a direct effect as well as an indirect effect through the mothers’ parenting competence on young children’s self-control. The results indicated that a mothers’ parenting competence plays a crucial role in the relationship between a fathers’ parenting involvement and the young children’s self-control.