bluuebunny/crossref_metadata_2025 huggingface dataset:
ANALYSIS AND BIAS IMPROVEMENT OF HEIGHT MODELS BASED ON SATELLITE IMAGES
Authors: Jacobsen K. , Passini R.
Published: June 2021

Abstract. Height models are a fundamental part of the geo-information required for various applications. The determination of height models by aerial photogrammetry, LiDAR or space images is time-consuming and expensive. For height models with large area coverage, UAVs are not economic. The freely available height models ASTER GDEM-3, SRTM, AW3D30 and TDM90 can meet various requirements.With the exception of ASTER-GDEM-3, which cannot compete with the other, the digital surface models SRTM, AW3D30 and TDM90 are analyzed in detail for accuracy and morphology in 4 test sites using LiDAR reference DTMs. The accuracy figures root mean square error, standard deviation, NMAD and LE90 are compared as well as the accuracy dependence on the terrain inclination. The analysis uses a layer for the open areas, excluding forest and settlement areas. Remaining elements that do not belong to a DTM are filtered. Particular attention is paid to systematic errors. The InSAR height models SRTM and TDM90 have some accuracy and morphological restrictions in mountain and settlement areas. Even so, the direct sensor orientation of TDM90 is better than for the other. Optimal results in terms of accuracy and morphology were achieved with AW3D30 corrected by TDM90 for the local absolute height level. This correction reduces the bias and also the tilt of the height models compared to the reference LiDAR DTM.
ON THE CLASSIFIER PERFORMANCE FOR SIMULATION BASED DEBRIS DETECTION IN SAR IMAGERY
Authors: Kuny S. , Hammer H. , Schulz K.
Published: June 2021

Abstract. Urban areas struck by disasters such as earthquakes are in need of a fast damage detection assessment. A post-event SAR image often is the first available image, most likely with no matching pre-event image to perform change detection. In previous work we have introduced a debris detection algorithm for this scenario that is trained exclusively with synthetically generated training data. A classification step is employed to separate debris from similar textures such as vegetation. In order to verify the use of a random forest classifier for this context, we conduct a performance comparison with two alternative popular classifiers, a support vector machine and a convolutional neural network. With the direct comparison revealing the random forest classifier to be best suited, the effective performance on the prospect of debris detection is investigated for the post-earthquake Christchurch scene. Results show a good separation of debris from vegetation and gravel, thus reducing the false alarm rate in the damage detection operation considerably.
SEMANTIC SEGMENTATION OF MOBILE LASER SCANNING POINT CLOUDS WITH LONG SHORT-TERM MEMORY NETWORKS: PRELIMINARY RESULTS
Authors: Balado J. , van Oosterom P. , Díaz-Vilariño L. , Arias P.
Published: June 2021

Abstract. Although point clouds are characterized as a type of unstructured data, timestamp attribute can structure point clouds into scanlines and shape them into a time signal. The present work studies the transformation of the street point cloud into a time signal based on the Z component for the semantic segmentation using Long Short-Term Memory (LSTM) networks. The experiment was conducted on the point cloud of a real case study. Several training sessions were performed changing the Level of Detail of the classification (coarse level with 3 classes and fine level with 11 classes), two levels of network depth and the use of weighting for the improvement of classes with low number of points. The results showed high accuracy, reaching at best 97.3% in the classification with 3 classes (ground, buildings, and objects) and 95.7% with 11 classes. The distribution of the success rates was not the same for all classes. The classes with the highest number of points obtained better results than the others. The application of weighting improved the classes with few points at the expense of the classes with more points. Increasing the number of hidden layers was shown as a preferable alternative to weighting. Given the high success rates and a behaviour of the LSTM consistent with other Neural Networks in point cloud processing, it is concluded that the LSTM is a feasible alternative for the semantic segmentation of point clouds transformed into time signals.
INFORMATION ACQUISITION ON PEDESTRIAN MOVEMENTS IN URBAN TRAFFIC WITH A MOBILE MULTI-SENSOR SYSTEM
Authors: Borgmann B. , Hebel M. , Arens M. , Stilla U.
Published: June 2021

Abstract. This paper presents an approach which combines LiDAR sensors and cameras of a mobile multi-sensor system to obtain information about pedestrians in the vicinity of the sensor platform. Such information can be used, for example, in the context of driver assistance systems. In the first step, our approach starts by using LiDAR sensor data to detect and track pedestrians, benefiting from LiDAR’s capability to directly provide accurate 3D data. After LiDAR-based detection, the approach leverages the typically higher data density provided by 2D cameras to determine the body pose of the detected pedestrians. The approach combines several state-of-the-art machine learning techniques: it uses a neural network and a subsequent voting process to detect pedestrians in LiDAR sensor data. Based on the known geometric constellation of the different sensors and the knowledge of the intrinsic parameters of the cameras, image sections are generated with the respective regions of interest showing only the detected pedestrians. These image sections are then processed with a method for image-based human pose estimation to determine keypoints for different body parts. These keypoints are finally projected from 2D image coordinates to 3D world coordinates using the assignment of the original LiDAR points to a particular pedestrian.
AUTOMATIC MODELLING OF 3D TREES USING AERIAL LIDAR POINT CLOUD DATA AND DEEP LEARNING
Authors: Kippers R. G. , Moth L. , Oude Elberink S. J.
Published: June 2021

Abstract. 3D tree objects can be used in various applications, like estimation of physiological equivalent temperature (PET). During this project, a method is designed to extract 3D tree objects from a country-wide point cloud. To apply this method on large scale, the algorithm needs to be efficient. Extraction of trees is done in two steps: point-wise classification using the PointNet deep learning network, and Watershed segmentation to split points into individual trees. After that, 3D tree models are made. The method is evaluated on 3 areas, a park, city center and housing block in the city of Deventer, the Netherlands. This resulted into an average accuracy of 92% and a F1-score of 0.96.
INCREMENTAL MAP REFINEMENT OF BUILDING INFORMATION USING LIDAR POINT CLOUDS
Authors: Zou Q. , Sester M.
Published: June 2021

Abstract. For autonomous systems, an accurate and precise map of the environment is of importance. Mapping from LiDAR point clouds is one of the promising ways to generate 3D environment models. However, there are many problems caused by inaccurate data, missing areas, low density of points and sensor noise. Also, it is often not possible or accurate enough to generate a map from only one measurement campaign. In this paper, we propose a method to incrementally refine the map by several measurements from different campaigns and represent the map in a hierarchical way with a measure indicating uncertainty and the level of detail for objects. The idea is thus to store all captured information with a tentative semantics and uncertainty – even when it is not yet complete. Hence, occulated areas are presented as well, which can be possibly improved by the supplemental observation from the next measurement campaign. The proposed 3D environment model framework and the incremental update method are evaluated using LiDAR scans obtained from Riegl Mobile Mapping System.
EXPLOITING MULTI-CAMERA CONSTRAINTS WITHIN BUNDLE BLOCK ADJUSTMENT: AN EXPERIMENTAL COMPARISON
Authors: Maset E. , Rupnik E. , Pierrot-Deseilligny M. , Remondino F. , Fusiello A.
Published: June 2021

Abstract. The growing deployment of multi-head camera systems encouraged the emergence of specific processing algorithms, able to face the challenges posed by slanted view geometry. Such multi-camera systems are rigidly tied by their manufacturers hence the exploitation of this internal constraint should be further exploited. Several approaches have been proposed to deal with orientation constraints, with the aim of reducing the number of unknowns, computational time and possibly improve the accuracy. In this paper we compare the results provided by publicly available implementations in order to further investigate the advantages of enforcing relative orientation constraints for aerial and terrestrial triangulation of multi-head camera systems. Data from a Leica CityMapper and a Stereopolis-Ladybug are considered, reporting how constrained solution can improve accuracy with respect to traditional (unconstrained) bundle block adjustment solutions.
MAGO APPROACH FOR SEMANTIC SEGMENTATION: THE CASE STUDY OF UAVID BENCHMARK DATASET
Authors: Gagliolo S. , Sguerso D.
Published: June 2021

Abstract. The present work is focused on a semantic segmentation strategy implemented in the workflow of the tool MAGO (standing for “Adaptive Mesh for Orthophoto Generation”), considering the contribution of the 3D geometry and the colour information, both deriving from the point cloud of the scene. Moreover, the 2D source imagery, previously used to obtain the photogrammetric point cloud, is employed even to enhance the procedure with the recognition of moving objects, comparing the evolution of epochs.The analysed context is an urban scene, deriving from the UAVid dataset proposed for the ISPRS benchmark. In particular, the so-called “seq18”, a set of high-resolution oblique images taken by UAV (Unmanned Aerial Vehicle), has been used to test the semantic segmentation. The workflow includes the production of two Digital Surface Models (DSMs), containing the geometric and radiometric information, respectively, and their processing by means of the Harris corner detector, allowing the understanding of the image variability. Then, starting from the source geometry and colour information and combining them with their variability mapping, a preliminary classification is performed. Further criteria allow the segmentation of the humans and cars present in the scene. In particular, static objects are identified according to the content of the neighbour pixels in a certain kernel, while the evolution in time of moving elements is recognized by means of the comparison of the projected images belonging to the different epochs. The presented preliminary achievements show some criticalities that require further attention and improvement. In particular, the strategy could be enriched getting more information from the source 2D images, which at the moment are directly used only for the comparison of consecutive epochs.
EVALUATING TIE POINTS DISTRIBUTION, MULTIPLICITY AND NUMBER ON THE ACCURACY OF UAV PHOTOGRAMMETRY BLOCKS
Authors: Mousavi V. , Varshosaz M. , Remondino F.
Published: June 2021

Abstract. Image orientation is a fundamental task in photogrammetric applications and it is performed by extracting keypoints with hand-crafted or learning-based methods, generating tie points among the images and running a bundle adjustment procedure. Nowadays, due to large number of extracted keypoints, tie point filtering approaches attempt to eliminate redundant tie points in order to increase accuracy and reduce processing time. This paper presents the results of an investigation concerning tie points impact on bundle adjustment results. Simulations and real data are processed in Australis and DBAT to evaluate different affecting factors, including tie point numbers, location accuracy, distribution and multiplicity. Achieved results show that increasing the amount of tie points improve the quality of bundle adjustment results, provided that the tie points are well-distributed on the image. Furthermore, bundle adjustment quality is improved as the multiplicity of tie points increases and their location uncertainty decrease. Based on simulation results, some suggestions for accurate tie points filtering in typical UAV photogrammetry blocks cases are derived.
A NEW STEREO DENSE MATCHING BENCHMARK DATASET FOR DEEP LEARNING
Authors: Wu T. , Vallet B. , Pierrot-Deseilligny M. , Rupnik E.
Published: June 2021

Abstract. Stereo dense matching is a fundamental task for 3D scene reconstruction. Recently, deep learning based methods have proven effective on some benchmark datasets, for example Middlebury and KITTI stereo. However, it is not easy to find a training dataset for aerial photogrammetry. Generating ground truth data for real scenes is a challenging task. In the photogrammetry community, many evaluation methods use digital surface models (DSM) to generate the ground truth disparity for the stereo pairs, but in this case interpolation may bring errors in the estimated disparity. In this paper, we publish a stereo dense matching dataset based on ISPRS Vaihingen dataset, and use it to evaluate some traditional and deep learning based methods. The evaluation shows that learning-based methods outperform traditional methods significantly when the fine tuning is done on a similar landscape. The benchmark also investigates the impact of the base to height ratio on the performance of the evaluated methods. The dataset can be found in https://github.com/whuwuteng/benchmark_ISPRS2021.
IDENTIFICATION OF MISCLASSIFIED PIXELS IN SEMANTIC SEGMENTATION WITH UNCERTAINTY EVALUATION
Authors: Budde L. E. , Bulatov D. , Iwaszczuk D.
Published: June 2021

Abstract. Classification, and in particular semantic segmentation, plays a major role in remote sensing. In remote sensing, the classes usually correspond to landcover or landuse types while the data elements are image pixels. The results are so-called semantically segmented pixels describing the content of the data for each pixel. The identification of misclassified pixels is essential to perceive the overall performance of the classification algorithm. In the case of semantic segmentation, it is typically done with ground truth labels. However, such ground truth labels are rare and mostly reserved for training only. Especially deep learning approaches are data-hungry algorithms requesting a lot of labeled examples. In this work, we explore the possibility of using Monte-Carlo dropout for the identification of model-induced misclassifications. In particular, we obtain uncertainty measures from several inferences induced by the Monte-Carlo dropout. Furthermore, we examine how Markov Random Field optimization can reduce the number of misclassifications and facilitate their identification. The extent to which uncertainties provide information about misclassifications is assessed. Our results allow detecting 51 % of the misclassifications using uncertainties. Application of Markov Random Field optimization leads to a reduction of the percentage of misclassifications while detecting 0.4 % more misclassifications as without.
LARGE SCALE SEMANTIC SEGMENTATION OF VIRTUAL ENVIRONMENTS TO FACILITATE CORROSION MANAGEMENT
Authors: Garcia R. L. , Happ P. N. , Feitosa R. Q.
Published: June 2021

Abstract. This paper reports the results of a study that aims to develop semi-automatic methods for assessing the degree of corrosion in industrial plant. We evaluated two fully convolutional networks (U-Net and DeepLab v3 +) to segment corroded areas in panoramic images of offshore platforms. The experimental analysis was based on two datasets built for this study. The datasets comprise 9,112 2D images and 3,732 panoramic images. Both FCNs trained on 2D images were tested on 2D images and cubic projections of panoramic images. In addition to pointing out encouraging results, the experiments indicated that most prediction errors concentrated in corrosion defects with a small pixel area.
LARGER RECEPTIVE FIELD BASED RGB VISUAL RELOCALIZATION METHOD USING CONVOLUTIONAL NETWORK
Authors: Qin J. , Li M. , Li D. , Liao X. , Zhong J. , Zhang H.
Published: June 2021

Abstract. Visual Relocalization is a key technology in many computer vision applications. Traditional visual relocalization is mainly achieved through geometric methods, while PoseNet introduces convolutional neural network in visual relocalization for the first time to realize real-time camera pose estimation based on a single image. Aiming at the problem of accuracy and robustness of the current PoseNet algorithm in complex environment, this paper proposes and implements a new high-precision robust camera pose calculation method (LRF-PoseNet). This method directly adjusts the size of the input image without cropping, so as to increase the receptive field of the training image. Then, the image and the corresponding pose tags are input into the improved LSTM-based PoseNet network for training, and the Adam optimizer is used to optimize the network. Finally, the trained network is used to estimate the camera pose. Experimental results on open RGB dataset show that the proposed method in this paper can obtain more accurate camera pose compared with the existing CNN-based methods.
CITYWIDE ESTIMATION OF PARKING SPACE USING AERIAL IMAGERY AND OSM DATA FUSION WITH DEEP LEARNING AND FINE-GRAINED ANNOTATION
Authors: Henry C. , Hellekes J. , Merkle N. , Azimi S. M. , Kurz F.
Published: June 2021

Abstract. Emerging traffic management technologies, smart parking applications, together with transport researchers and urban planners are interested in fine-grained data on parking space in cities. However, there are no standardized, complete and up-to-date databases for many urban areas. Moreover, manual data collection is expensive and time-consuming. Aerial imagery of entire cities can be used to inventory not only publicly accessible and dedicated parking lots, but also roadside parking areas and those on private property. For a realistic estimation of the total parking space, the observed use of multi-functional traffic areas is taken into account by segmenting not only parking areas but also roads according to their purpose. In this paper, different U-Net based architectures are tested for detecting all these types of visible traffic areas. A new large-scale, high-quality dataset of manual annotations is used in combination with selected contextual information from OpenStreetMap (OSM) to depict the actual use as parking space. Our models achieve a good performance on parking area segmentation, and we show the significant impact of OSM data fusion in deep neural networks on the simultaneous extraction of multiple traffic areas compared to using aerial imagery alone.
BUILDING OUTLINE EXTRACTION FROM AERIAL IMAGERY AND DIGITAL SURFACE MODEL WITH A FRAME FIELD LEARNING FRAMEWORK
Authors: Sun X. , Zhao W. , Maretto R. V. , Persello C.
Published: June 2021

Abstract. Deep learning-based semantic segmentation models for building delineation face the challenge of producing precise and regular building outlines. Recently, a building delineation method based on frame field learning was proposed by Girard et al. (2020) to extract regular building footprints as vector polygons directly from aerial RGB images. A fully convolution network (FCN) is trained to learn simultaneously the building mask, contours, and frame field followed by a polygonization method. With the direction information of the building contours stored in the frame field, the polygonization algorithm produces regular outlines accurately detecting edges and corners. This paper investigated the contribution of elevation data from the normalized digital surface model (nDSM) to extract accurate and regular building polygons. The 3D information provided by the nDSM overcomes the aerial images’ limitations and contributes to distinguishing the buildings from the background more accurately. Experiments conducted in Enschede, the Netherlands, demonstrate that the nDSM improves building outlines’ accuracy, resulting in better-aligned building polygons and prevents false positives. The investigated deep learning approach (fusing RGB + nDSM) results in a mean intersection over union (IOU) of 0.70 in the urban area. The baseline method (using RGB only) results in an IOU of 0.58 in the same area. A qualitative analysis of the results shows that the investigated model predicts more precise and regular polygons for large and complex structures.
IMPROVING UAV TELEMETRY POSITIONING FOR DIRECT PHOTOGRAMMETRY
Authors: Rossi L. , Ioli F. , Capizzi E. , Pinto L. , Reguzzoni M.
Published: June 2021

Abstract. A fundamental step of UAV photogrammetric processes is to collect Ground Control Points (GCPs) by means of geodetic-quality GNSS receivers or total stations, thus obtaining an absolutely oriented model with a centimetric accuracy. This procedure is usually time-consuming, expensive and potentially dangerous for operators who sometimes need to reach inaccessible areas. UAVs equipped with low-cost GNSS/IMU sensors can provide information about position and attitude of the images. This telemetry information is not enough for a photogrammetric restitution with a centimetric accuracy, but it can be usefully exploited when a lower accuracy is required. The algorithm proposed in this paper aims at improving the quality of this information, in order to introduce it into a direct-photogrammetric process, without collecting GCPs. In particular, the estimation of an optimal trajectory is obtained by combining the camera positions derived from UAV telemetry and from the relative orientation of the acquired images, by means of a least squares adjustment. Then, the resulting trajectory is used as a direct observation of the camera positions into a commercial software, thus replacing the information of GCPs. The algorithm has been tested on different datasets, comparing the classical photogrammetric solution (with GCPs) with the proposed one. These case-studies showed that using the improved trajectory as input to the commercial software (without GCPs) the reconstruction of the three-dimensional model can be improved with respect to the solution computed by using the UAV raw telemetry only.
Environmental Factors Affecting Wildfire Burned Area In South-Eastern France, 1970–2019
Authors: Bountzouklis Christos , Fox Dennis Michael , Di Bernardino Elena
Published: June 2021

Abstract. Forest fires burn an average of about 440,000 ha each year in southern Europe. These fires cause numerous casualties and deaths and destroy houses and other infrastructures. In order to elaborate suitable fire-fighting strategies, complex interactions between human and environmental factors must be taken into account. In this study, we investigated the spatio-temporal evolution in burned area over a 50-year period (1970–2019) and its interactions between topography (slope inclination and aspect) and vegetation type in south-eastern France by exploiting Geographic Information System databases. Burned area decreased sharply after 1994, with the advent of the new fire suppression policy which focused on rapid extinction of fires in their early phase. The geographic distribution of burned area has also changed in the last 25 years, mainly in regions where large fires occurred (Var department). In other parts, even though forest fires are still frequent and occur in the same geographic locations, the total extent of the burned area is significantly reduced. Slope orientation presents an increasingly important role every decade, S-facing slopes have the greatest burned areas and increase their proportion each decade, while the opposite is observed for N-facing and W-facing ones. Fire increasingly favors low and intermediate slopes after the sharp decrease of burned area in 1990. The largest part of the BA is strongly associated with the location of sclerophyllous vegetation clusters, which exhibit high fire proneness while simultaneously expanding the region. On the contrary, natural grassland numbers decline through time as the proportion of area burned increases.
The flexural strength of bonded ice
Authors: Murdza Andrii , Polojärvi Arttu , Schulson Erland M. , Renshaw Carl E.
Published: June 2021

Abstract. The flexural strength of ice surfaces bonded by freezing, termed
freeze bond, was studied by performing four-point bending tests of bonded
freshwater S2 columnar-grained ice samples in the laboratory. The samples
were prepared by milling the surfaces of two ice pieces, wetting two of the
surfaces with water of varying salinity, bringing these surfaces together,
and then letting them freeze under a compressive stress of about 4 kPa. The
salinity of the water used for wetting the surfaces to generate the bond
varied from 0 to 35 ppt (parts per thousand). Freezing occurred in air under temperatures varying
from −25 to −3 ∘C over periods that varied from 0.5 to
∼ 100 h. Results show that an increase in bond salinity or
temperature leads to a decrease in bond strength. The trend for the bond
strength as a function of salinity is similar to that presented in Timco and
O'Brien (1994) for saline ice. No freezing occurs at −3 ∘C once
the salinity of the water used to generate the bond exceeds ∼ 25 ppt. The strength of the saline ice bonds levels off (i.e., saturates)
within 6–12 h of freezing; bonds formed from freshwater reach strengths
that are comparable or higher than that of the parent material in less than
0.5 h.
COVID-19 SÜRECİNDE TAM KAPANMA KARARININ TÜKETİCİ DAVRANIŞLARINA ETKİSİ: E- TİCARET ÖZELİNDE İNCELENMESİ
Authors: TORAMAN Yavuz
Published: June 2021

Çalışmanın temel problemi COVID-19 pandemisi ile birlikte insanlığın karşılaştığı ‘TAM KAPANMA’ sürecinin tüketicilerin davranışlarına olası etkilerinin incelenmesidir. Tüketicilerin tam kapanma sürecindeki tutum ve davranışları COVID-19 pandemisinin başlangıcından bugüne gelinene kadar elde edilen resmi veriler ile birlikte analiz edilmiştir. Google Docs aracılığıyla hazırlanan ankete 275 kişi katılım göstermiştir. Araştırmada nitel veri analiz yöntemlerinden birisi olan yarı yapılandırılmış derinlemesine görüşme tekniğiyle analizler gerçekleştirilmiştir. Araştırmada tüketicilerin sorulara vermiş oldukları yanıtlar ile birlikte ikincil kaynaklardan elde edilen resmi veriler birlikte analiz edilmiştir. Bu bağlamda COVID-19 pandemisi sürecinde uygulanan ‘TAM KAPANMA’nın’ tüketicilerin alışveriş davranışlarına etki ettiği görülmüştür. Tüketicilerin %60’ı ihtiyaç duydukları ürünleri tam kapanmadan önce satın almayı tercih etmiştir. Diğer taraftan ihtiyaçlarının teminini öteleyen tüketiciler dahil olmak üzere %80’lik bir kesim tam kapanmada yasaklara dahil olmayan e-ticaret uygulamalarından satın alma faaliyetlerine devam edeceklerini belirtmiştir. Tüketici davranışları tam kapanma uygulamasından etkilenmiştir. COVID-19 sürecinde uygulanan tam ve kısmi kapanma uygulamalarının devam etmesi durumunda ilerleyen süreçte e-ticaretin hacminin ve kullanıcı sayısının artacağı varsayılmaktadır.
Chemical Composition and Gas Production Substrates of Maize Cobs Treated with Combinations of Urea and Wood Ash
Authors: ABDULAZEEZ Abdulrazaq , TSOPİTO Christopher Mareledi , MADİBELA Othusitse Ricky
Published: June 2021

Effect of treating maize cobs with a combination of urea and wood ash (WA) on chemical composition and in vitro gas production truly degraded substrate (TDS) were examined. The treatments were:1) 100U = (100% urea and 0% wood ash), 2) 75U25WA = (75% urea and 25% wood ash), 3) 50U50WA = (50% urea and 50% wood ash), 4) 25U75WA = (25 % urea and 75% wood ash) and 5) 0U0WA = (Untreated maize cobs). The concentrations were reconstituted as follows: 100U = 5 kg urea dissolved in 100 liters of water /200 kg maize cobs; 75U25WA = 3.75 kg urea mixed with 7.5 kg WA in 100 liters of water/200 kg maize cobs; 50U50WA = 2.5 kg urea mixed with 15 kg WA in 100 liters of water/200 kg maize cobs; 25U75WA = 1.25kg urea mixed with 22.5 kg WA in 100 liters of water/200 kg maize cobs; Untreated = 200 kg maize cobs mixed with 100 kg water. Chemical composition of samples were analyzed to determine dry matter (DM), organic matter (OM), ash, crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF) and acid detergent lignin (ADL). The samples were then incubated in vitro for 6, 12, 24, 48 and 72 hrs and their DM degradation kinetics determined. It was observed that crude protein contents declined as urea is substituted with WA while the ash contents increased. Treatment 25U75WA had the highest reduction in both NDF and ADF (660 and 360 g/kg) compared to those of 100U (700 and 380g/kg) and 0U0WA (840 and 430 g/kg). In contrast treatment 25U75 had the highest neutral detergent soluble (340 g/kg) while 0U0WA had the least (160 g/kg).Treatment 25U75WA had the highest gas production (73.5ml per 0.5mg sample; P=0.0001) and TDS (70.53%) while 0U0WA had the least. Treatment 25U75WA also resulted in the highest microbial mass protein (MMP) (53.55 mg) while 0U0WA had the least (25.20 mg). Treatment 25U75WA had the highest efficiency of microbial mass protein (EMMP) and partitioning factor (PF) (23.68 and 2.883) while 0U0WA had the least (12.00 and 2.500). It was concluded that combinations of 25% urea and 75% WA in the treatment of maize cobs had beneficial synergic effect and improved its nutritive value compared to treating it with urea alone.
Los Cardenales protectores de la monarquía española (siglos XVI-XVII)
Authors: Bénichou Léa
Published: June 2021

Este estudio se centra en el funcionamiento y significado político de las protecciones de los reinos hispánicos en Roma a los largo de los reinados de Felipe II y Felipe III, a partir del estudio de la documentación de la embajada de la monarquía española ante la Santa Sede conservada en el Archivo General de Simancas y en el Archivo Histórico Nacional. Además de identificar a los distintos cardenales detentores de dichas protecciones, ponemos de relieve los mecanismos que sustentaban el nombramiento de los protectores, protectores interinos y viceprotectores o "comproptectores" así como el papel político y diplomático que desempeñaba el protector más allá de la tarea oficial que le incumbía, o sea la preconización y presentación en consistorio de los candidatos que el monarca proponía a los beneficios eclesiásticos vacantes dependientes de su patronazgo real.
Rechazando una religiosidad ilustrada. El desmantelamiento de las medidas impulsadas por Pablo de Olavide en las Nuevas Poblaciones de Sierra Morena y Andalucía
Authors: Pérez Fernández Francisco José , Hamer Flores Adolfo
Published: June 2021

El propósito de este artículo es analizar cómo tras el encarcelamiento y sentencia inquisitorial condenatoria de Pablo de Olavide, el modelo de religiosidad que había intentado establecer en las Nuevas Poblaciones de Sierra Morena y Andalucía experimentó una rápida transformación que lo llevó a asemejarse a cualquier otra localidad del entorno en pocos años. Este proceso tuvo no solo el impulso de las autoridades civiles y, sobre todo, eclesiásticas sino también la buena disposición y colaboración de los vecinos de estas nuevas colonias que, en muchos casos, no compartieron ni entendieron la religiosidad que Olavide trató de impulsar entre ellos.
La biblioteca del AHN
Authors: Marías Martínez Laura
Published: June 2021

La Biblioteca del Archivo Histórico Nacional pertenece a la RBAE (Red de Bibliotecas de Archivos Estatales) y es una biblioteca especializada, tanto por su cantidad como por su calidad, ya que custodia más de 30000 volúmenes de Historia, Archivística y otras ciencias afines, que resultan sumamente útiles tanto para los archiveros como para los investigadores. Además, tiene unos 300 títulos de publicaciones periódicas y una importante colección de folletos. Pero, sobre todo, destaca por su extraordinario fondo antiguo, procedente en su mayor parte del convento de Uclés. Es decir, el fondo moderno de la Biblioteca constituye al mismo tiempo un instrumento de trabajo para el quehacer archivístico y una herramienta de apoyo a la investigación, y el fondo antiguo, aparte de formar parte del patrimonio bibliográfico español, es de gran interés para los historiadores del libro y la lectura. En este trabajo se pretende esbozar una breve historia de la Biblioteca
Dosimetría por fibra óptica basada en YVO4 : Eu3+
Authors: Martínez Clemente Nahuel Facundo
Published: June 2021

Los avances en las técnicas de radioterapia implementados durante las últimas décadas demandan de manera permanente el desarrollo de sistemas dosimétricos para la medición in vivo y en tiempo real de la tasa de dosis aplicada en cada tratamiento. La Dosimetría por Fibra Óptica (DFO) es una técnica que se encuentra en desarrollo y ha logrado posicionarse en el mercado con algunas ventajas frente a otras técnicas dosimétricas. Esta técnica se basa en el empleo de un material luminiscente que permite estimar la tasa de dosis en un lugar de interés, ya sea dentro o fuera del paciente. Al ser irradiado, el material centellador emite luz con longitud de onda caracteríıstica. Este efecto se conoce como radioluminiscencia o centelleo. Para colectar la señal luminiscente del centellador se emplea una fibra óptica, la cual permite guiar la luz de centelleo fuera del recinto de irradiación hasta un sensor que permite la medición de su intensidad. Dado que en general la intensidad de centelleo es proporcional a la tasa de dosis absorbida por el centellador, la DFO puede utilizarse con fines dosimétricos luego de un adecuado procedimiento de calibración, que dependerá de las propiedades dosimétricas del material luminiscente. El pequeño volumen activo del centellador, la ausencia de conexiones eléctricas próximas al paciente, la robustez mecánica del sistema y su potencial bajo costo son algunas de las características que hacen atractiva a esta técnica. El principal inconveniente de la DFO es la presencia de luminiscencia espuria, producida en la fibra óptica por la radiación incidente. Esta señal espúrea se suma a la emisión del centellador, pudiendo dar lugar a un sesgo en la determinación de la tasa de dosis. Por este motivo, debe suprimirse o minimizarse por debajo de límites aceptables para asegurar la aplicabilidad de la esta técnica dosimétrica en condiciones clíınicas. Estudios preliminares han demostrado que el compuesto luminiscente YVO4:Eu3+ posee propiedades atractivas para ser utilizado como centellador para DFO en tratamientos en aceleradores lineales o LINAC. Además de su alta eficiencia, las características de la luminiscencia de este compuesto permiten implementar técnicas efectivas para reducir la contribución de la luminiscencia espúrea. En este trabajo se estudiaron las características dosimétricas del YVO4:Eu3+como centellador para DFO. Se realizaron mediciones tanto en el laboratorio como in situ (LINAC). Se construyeron y caracterizaron puntas dosimétricas para DFO basadas en este compuesto. Empleando simulaciones computacionales se investigó la respuesta del material a la radiación cuando se emplean distintas configuraciones geométricas, en particular, se realizó un estudio exhaustivo de la respuesta de las puntas dosimétricas ante distintos ángulos de incidencia del haz de radiación.
Leadership participatif et identification organisationnelle : rôle médiateur de la responsabilité sociale des entreprises perçue par les employés et la fierté d’être membre dans les petites et moyennes entreprises béninoises
Authors: NAKOU Zinsou Daniel , SIMEN NANA Serge Francis
Published: June 2021

Cet article étudie l’influence du Leadership Participatif (LP) sur l’Identité Organisationnelle (IO) au moyen de la Responsabilité Sociale des Entreprises (RSE) perçue par les employés et de la Fierté d’Etre Membre (FEM) sous l’angle de la théorie du traitement de l'information sociale dans les PME béninoises. Pour atteindre cet objectif, nous avions utilisé une méthode quantitative basée sur un questionnaire soumis à 740 employés de 17 Petites et Moyennes Entreprises (PME) réparties dans trois (03) villes au Bénin (5 à Cotonou, 7 à Porto-Novo et 5 à Parakou) et dont les données ont été présentées et traitées avec le logiciel SPSS 21.0.  Nos résultats montrent que le LP conduit à des perceptions internes positives des employés en matière de RSE, ce qui fait appel à la gestion de l'information personnelle qui, à son tour, debouche sur une IO. En outre, les perceptions internes de la RSE ont servi de médiaton à la relation entre le LP et la FEM ; puis la FEM, de médiation entre les perceptions internes de la RSE et l’IO dans les PME sélectionnées. Les implications de ces résultats sont également discutées.
«Ferrum complex» for iron deficiency elimination in athletes
Authors: Штерман Сергей Валерьевич , Сидоренко Михаил Юрьевич , Сидоренко Юрий Ильич , Штерман Валерий Соломонович , Чеботарева Наталья Ивановна , Тихонов Дмитрий Анатольевич
Published: June 2021

Установлено, что физические нагрузки могут приводить к серьезным сдвигам в процессах метаболизма в организме. Они связаны, среди прочего, с усилением потерь целого ряда минеральных микроэлементов. Содержание железа в организме спортсменов относится к числу важнейших факторов состояния их здоровья. В частности, оно определяет их способность адаптироваться к длительным аэробным нагрузкам. Потребление специально разработанных продуктов спортивного питания может выступать в качестве эффективного инструмента для улучшения баланса железа в организме атлетов. Целью проведенного исследования была разработка продукта спортивного питания «Феррум комплекс», предназначенного для обеспечения оптимального содержания железа в организме спортсменов в период проведения ими интенсивных тренировок и соревнований. В качестве источника железа в продукте был использован фумарат железа. Он характеризуется высокой биодоступностью, так как двухвалентное железо легко всасывается в кишечнике, а анион фумаровой кислоты способствует этому процессу. Железо гораздо хуже используется для решения стоящих перед ним биохимических задач в условиях дефицита меди в организме. Было обнаружено, что железо и медь обладают способностью оказывать друг на друга синергетическое воздействие и они взаимно усиливают усвоение друг друга. Медь в составе «Феррум комплекс» используется в виде своей биологически усвояемой соли - глюконата меди. Было также установлено, что концентрация марганца в крови спортсменов, занимающихся видами спорта, требующими высокой выносливости, является более высокой, чем в организме людей, ведущих преимущественно малоподвижный образ жизни. В «Феррум комплексе» марганец, как и медь, включен в виде ее глюконата. В разработанном продукте содержится также ряд витаминов - витамины C, B и фолиевая кислота. Эти биологически активные вещества стимулируют процесс кроветворения и принимают активное участие в синтезе железосодержащего белка - гемоглобина, который является переносчиком кислорода. В целом наличие в составе продукта «Феррум комплекс» ряда жизненно важных компонентов способствует созданию оптимальной концентрации железа в организме спортсменов, что позволяет значительно повысить интенсивность их тренировок, увеличить спортивную работоспособность, а также ускорить восстановление атлетов после больших и продолжительных физических нагрузок.
Investigation of the toxic potential of canned cauliflower puree extract in a model plant test system
Authors: Самойлов Артём Владимирович , Сураева Наталья Михайловна , Зайцева Мария Вячеславовна , Кесян Арпик Завеновна , Курбанова Мадинат Насрудиновна , Королев Алексей Александрович
Published: June 2021

Для здорового питания необходимы продукты растительного происхождения, которые обладают питательной и биологической ценностью. Однако в составе растительного сырья представлена большая группа биологически активных соединений, благодаря которым возникает необходимость комплексного контроля качества и безопасности готовой продукции. Целью исследования являлась оценка потенциальной токсичности экстракта консервированного пюре из цветной капусты и его смеси с сорбиновой кислотой при помощи биотестирования. Работа выполнена на корнях репчатого лука Allium cepa . Исследование включало измерение в тканях корней уровня прироста биомассы и концентрации малонового диальдегида (МДА) в качестве биомаркера перекисного окисления липидов, а также анализ природы и частоты пролиферативных и цитогенетических нарушений в клетках меристемы после обработки водным экстрактом пюре (0,1, 0,02 и 0,01 %) и его смесью с сорбиновой кислотой (100 мг/л). Инкубация корней в 0,1%-ном экстракте сопровождалась токсическим эффектом в отношении прироста массы корней (задержка на 62 %). Было показано, что при разбавлении экстракта этот токсичный эффект нивелировался. Однако в случае добавления к экстракту сорбиновой кислоты даже при его десятикратном разбавлении торможение прироста оказалось необратимым. Была также зафиксирована дозозависимая цитотоксичность экстракта, при этом скорость снижения митотического индекса была выше аналогичного показателя массы прироста корней. В смеси всех вариантов концентраций экстракта и консерванта делящиеся клетки практически отсутствовали. Экстракт, в отличие от сорбиновой кислоты, не повышал уровень перекисного окисления липидов, а наоборот, дозозависимо снижал концентрацию МДА после обработки корней в комбинации с этим консервантом благодаря возможному наличию в своем составе антиоксидантных соединений. Полученные результаты могут быть использованы при разработке растительных пищевых добавок и новых продуктов питания для снижения риска возникновения токсичных эффектов.
Study of chromatographic separation of carbohydrates of inulin and oligofruc-tose
Authors: Пучкова Татьяна Сергеевна , Бызов Василий Аркадьевич , Пихало Дания Мустафиевна , Карасева Оксана Михайловна
Published: June 2021

Во ВНИИ крахмалопродуктов разрабатывается универсальная технология инулина и олигофруктозы из цикория и топинамбура. Исследования по хроматографическому разделению углеводов инулина и олигофруктозы с использованием катионообменной смолы марки PCR641Ca компании «Пьюролайт» (США) проводили в колонке размерами 1,7х75 см, при следующих условиях: количество загруженной смолы - 150 см; объем загрузки исходного продукта - 10 % (15 см); температура -20…25 °С и 45…50 °С; скорость элюирования - 0,9-1,1 см/мин. Процесс хроматографического разделения контролировали по сухому веществу, углеводному составу и удельному вращению в элюатах. Для хроматографического разделения использовали инулин марки «Рафтилин», а также олигофруктозный сироп. Образец олигофруктозного сиропа получали из инулинсодержащего сиропа цикория, дополнительно очищенного активным углем, а также на ионообменных смолах. Гидролиз проводили с использованием ферментного препарата инулиназы марки «Новозим 960» компании «Новозаймс» (Дания). При хроматографическом разделении углеводов инулина, содержащего 89,17 % инулина, 10,83 % ди- и моносахаридов, получена фракция элюата, содержащая 95 % инулина и 5 % олиго- и дисахаридов, что соответствует показателям качества импортного инулина. При хроматографическом разделении фруктоолигосахаридного сиропа, содержащего 87,31 % ФОС и 12,69 % ди- и моносахаридов, получена фракция элюата с содержанием не менее 98 % ФОС, что соответствует показателям сертификата качества импортной олигофруктозы. Хроматографическое разделение углеводов инулинсодержащего и фруктоолигосахаридного сиропов позволяет выделить инулин с содержанием не менее 95 % и олигофруктозу с содержанием не менее 98 % ФОС для создания новых безопасных пищевых продуктов лечебно-профилактического и оздоровительного питания населения.
Relationship of indicators of rheological properties of the dough with the quality of the cracker
Authors: Мелешкина Елена Павловна , Коломиец Светлана Николаевна , Коваль Анна Ивановна , Ческидова Анастасия Сергеевна , Жильцова Наталья Сергеевна
Published: June 2021

Представлены результаты исследований, проведенных во Всероссийском научно-исследовательском институте зерна и продуктов его переработки, влияния основных показателей реологических свойств теста, позволяющих максимально дифференцировать свойства пшеничной муки, на качество готового изделия - крекера. Были определены диапазоны пре-дельных значений для показателей реологических свойств теста, влияющих на качество крекера. На основании результатов экспериментальных данных для изготовления крекера рекомендовано использовать муку пшеничную со следующими значениями показателей реологических свойств теста по альвеографу: отношением упругости к растяжимости (P/L), близкое к единице (0,8-1,5). При P/L>2,5 и <0,5 форма и состояние поверхности крекера имели неудовлетворительную оценку; показателем формы кривой 0,5-1,5; энергией деформации теста 100-180х10 Дж, по валориграфу: водопоглощением 59,0-62,0 %, временем замеса теста 3,0-6,5 мин, степенью разжижения 65-85 ЕВ (единиц валориграфа), валориметрической оценкой - не более 70 ЕВ. Высокие значения валориметрической оценки приводили к резкому увеличению толщины крекера. Использование зерна и муки из пшеницы в соответствии с их свойствами позволит существенно сократить применение улучшителей, которые, к сожалению, продолжают использоваться для коррекции качества муки.
FAKTOR-FAKTOR YANG MEMPENGARUHI STATUS GIZI PASIEN HEMODIALISA DI RUMAH SAKIT STELLA MARIS MAKASSAR
Authors: Satti Yunita Carolina , Mistika Sry Reski , Imelda Laorensi
Published: June 2021

Dalam menjalani terapi hemodialisis malnutrisi masih merupakan masalah utama pada pasien sehingga dapat mengakibatkan status gizi buruk pada pasien Penyakit Ginjal Kronik (PGK). Dimana perubahan status gizi merupakan prediktor yang menyebabkan terjadinya kematian pada pasien. Akibat sering mengalami ketidakseimbangan zat gizi pada pasien PGK maka di perlukan suatu pengetahuan mengenai hal-hal yang dapat mempengaruhi status gizi pasien HD. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi status gizi pasien yang menjalani terapi hemodialisa. Penelitian ini merupakan penelitian analitik observasional dengan pendekatan cross sectional. Populasi dari penelitian ini adalah pasien PGK yang menjalani terapi hemodialisis di Ruang Hemodialisa Rumah Sakit Stella Maris Makassar. Sebanyak 66 subjek diambil dengan cara menggunakan teknik non probability sampling dengan pendekatan consecutive sampling. Dilakukan pengumpulan data mengenai nafsu makan menggunakan kuesioner Simplified Nutrirional Appetite Questionnaire (SNAQ), lama hemodialisis menggunakan lembar pengumpulan data karakteristik dan status gizi menggunakan indeks massa tubuh (IMT). Uji statistik yang digunakan adalah Uji Chi Square dan Uji Kolmogorov Smirnov untuk mengetahui hubungan antar variabel. Hasil analisis uji statistik menunjukkan bahwa ada hubungan antara nafsu makan dengan status gizi (p value=0.000) dan tidak ada hubungan antara lama hemodialisis dengan statu gizi (p value=1,000). Hasil penelitian ini didapatkan bahwa tidak ada hubungan antara lama hemodialisis dengan status gizi pasien hemodialisa di Rumah Sakit Stella Maris Makassar dan ada hubungan antara nafsu makan dengan status gizi pasien hemodialisa di Rumah Sakit Stella Maris Makassar. Agar perlu adanya pemantauan secara berkala oleh petugas kesehatan mengenai nafsu makan pada pasien HD untuk mencegah terjadinya malnutrisi pada pasien.