bluuebunny/crossref_metadata_2025 huggingface dataset:
SURVEY OF ANCIENT TOMB-LIKE TOPOGRAPHY IN THE NORTH CAPE OF ORONO-SHIMA ISLAND －ORIGINS OF THE ANCIENT TOMB SYSTEM IN JAPAN?－
Authors: Yamaguchi T. , Ogawa S. , Moriyama T. , Taniguchi Y. , Shiraishi H. , Koga T.
Published: May 2022

Abstract. Orono-shima Island is a remote Island in the Tsushima Strait, it is 4.3km around. Since ancient times, it has been a landmark when crossing from the Korean Peninsula to Japanese archipelago via Tsushima Island and Iki Island. However, large-scale ruins and burial mounds are not known on Orono-shima Island until now. During my four years on the island, the author walked all over the island for terrain survey. As a result, the author discovered a topography like keyhole tomb which is a characteristic Japanese burial mound, on the northern cape of the island. It could be up to 150m in size, one of the largest around Kyusyu Island. There is no burial mound comparable to this on a remote island in Japan. Therefore, we created a 3D image using a drone Laser surveying of this terrain and we compared the results with another keyhole tomb. In addition, we analyzed the image of infrared radiation of Orono-shima Island took by Landsat8. In conclusion, it was speculated that this topography was the prototype of the oldest type of keyhole cairn tomb in Japan. The topography of the northern part of Orono-shima could be regaining the missing link between the cairn on the Korean Peninsula of the first century and the oldest type of keyhole cairn tomb in Japan of the third century.
ANALYSIS OF THE PRODUCTS OF THE COPERNICUS GROUND MOTION SERVICE
Authors: Crosetto M. , Solari L. , Barra A. , Monserrat O. , Cuevas-González M. , Palamà R. , Wassie Y. , Shahbazi S. , Mirmazloumi S. M. , Crippa B. , Mróz M.
Published: May 2022

Abstract. Radar interferometry has progressed very much in the last two decades. It is now a powerful remote sensing techniques to monitor ground motion. The technique has undergone an important development in terms of processing and data analysis algorithms. This has been accompanied by an important increase of the Synthetic Aperture Radar (SAR) data acquisition capability by spaceborne sensors. A step forward was the launch of the Copernicus Sentinel-1 constellation. This has made the development of A-DInSAR (Advanced Differential Interferometric SAR) ground deformation services technically feasible. The paper is focused on the most important ground motion initiative ever conceived: the European Ground Motion Service (EGMS). This service is part of the Copernicus Land Monitoring Service managed by the European Environment Agency. EGMS involves the ground deformation monitoring at European scale. The service will deliver the first product in May 2022. In this paper we describe some preliminary examples of deformation products coming from the EGMS.
GROUND DEFORMATION ANALYSIS USING BASIC PRODUCTS OF THE COPERNICUS GROUND MOTION SERVICE
Authors: Shahbazi S. , Crosetto M. , Barra A.
Published: May 2022

Abstract. Monitoring ground deformation at national and regional level with millimetre-scale precision, nowadays, is possible by using Advanced Differential Interferometric SAR (A-DInSAR) techniques. This study concerns the results of the European Ground Motion Service (EGMS), part of the Copernicus Land Monitoring Service, which detects and measures land displacement at European scale. This Service provides reliable and consistent information regarding natural ground motion phenomena such as landslides and subsidence. The ground motion is derived from Synthetic Aperture Radar (SAR) time-series analysis of Sentinel-1A/B data. These data, which provide full coverage of Europe from two different observation geometries (ascending and descending) every six days, are processed at full resolution. The paper is focused on the exploitation of the basic product of EGMS for both regional and local purposes. Analysing the slope and aspect of the deformation field is the novelty of this investigation. In particular, the focus is put on the generation of wide-area differential deformation maps. Such maps indicate the gradient of the deformation field. The obtained information is not only beneficial for monitoring anthropogenic phenomena but also vital for urban management and planning. Most of the significant damages to manmade structures and infrastructures are associated with high deformation gradient values. Thus, monitoring the temporal and spatial variations of deformation gradient is essential for dynamic analysis, early-warning, and risk assessment in urban areas. Although EGMS productions are prepared for monitoring at regional level, their resolutions are high enough to investigate at local level. Therefore, this paper considers the local deformations that affect single structures or infrastructures. Local differences in such deformation can indicate damages in the corresponding structures and infrastructures. We illustrate these types of analysis to generate differential deformation maps using datasets available at CTTC.
STUDY ON THE SPATIAL-TEMPORAL EVOLUTION OF SUBSIDENCE IN THE BEIBU GULF REGION BY TIME-SERIES INSAR
Authors: Wang C. , Wei B. , Zhou L. , Qin D. , Zhao Y. , Li J.
Published: May 2022

Abstract. In this paper, based on the 24 scenes Sentinel-1A images covering the Beibu Gulf region from 2018 to 2020, we used the PSInSAR technique to obtain the surface subsidence information in the study area and analyzed the surface subsidence spatial-temporal characteristics. The results showed that (1) The subsidence rate of most subsidence areas in Beibu Gulf is from −10.0 mm/year to −1.1 mm/year. And most of the subsidence areas are located in the coastal areas in the south of the study area. The distribution was obvious, and the maximum subsidence rate can reach −17.2 mm/a. However, the subsidence areas of villages and towns located in Qinzhou in the north and inland of the study area are relatively stable. (2) Subsidence was mainly concentrated in Yinhai District, Haicheng District, Tieshan Port District and Fangcheng District of Fangchenggang in Beihai City. The annual average Subsidence range from −10.0 mm/year to −1.1 mm/year. Among them, the Tieshan Port area and Fangcheng District had obvious subsidence trends, with the maximum cumulative subsidence reaching −35.9 mm. (3) The spatial-temporal characteristics of wide-area surface subsidence and the relationship between surface subsidence and influencing factors in the Beibu Gulf region were determined.
DETERMINATION OF CHLOROPHYLL CONTENT IN SELECTED GRASS COMMUNITIES OF KRKONOŠE MTS. TUNDRA BASED ON LABORATORY SPECTROSCOPY AND AERIAL HYPERSPECTRAL DATA
Authors: Červená L. , Pinlová G. , Lhotáková Z. , Neuwirthová E. , Kupková L. , Potůčková M. , Lysák J. , Campbell P. , Albrechtová J.
Published: May 2022

Abstract. The study focuses on the determination of chlorophyll content in four prevailing grasses in the relict arctic-alpine tundra located in the Krkonoše Mountains National Park, Czech Republic. We compared two methods for determination of leaf chlorophyll content (LCC) – spectrophotometric determination in the laboratory, and the LCC assessed by fluorescence portable chlorophyll meter CCM-300. Relationships were established between the LCCs and vegetation indices calculated from leaf spectra acquired with contact probe coupled with an ASD FieldSpec4 Wide-Res spectroradiometer. Canopy chlorophyll contents (CCC) were computed from the LCCs and green leaf area index (LAI), and modelled based on the field spectra measured by the spectroradiometer and the hyperspectral images acquired by Headwall Nano-Hyperspec® mounted on the DJI Matrice 600 Pro drone. The calculations are performed on datasets acquired in June, July and August 2020 together and separately for species and months. In general, the correlations based on June datasets work the best at both levels: median R2 for all indices was 0.52 for all species together at leaf level and median R2 = 0.47 at the canopy level (vegetation indices computed from field spectra). Canopy chlorophyll content map was created based on the results of stepwise multiple linear regression. The R2 was 0.42 when using four wavelengths from the red and red edge spectral region. We attribute the weak model performance to a combination of several factors: leaf structure may bias LCC from laboratory measurements, effects of LAI variability on CCC, and the sampling design, probably not covering the whole phenology equally for all studied species.
IMPROVING CNN-BASED BUILDING SEMANTIC SEGMENTATION USING OBJECT BOUNDARIES
Authors: Bousias Alexakis E. , Armenakis C.
Published: May 2022

Abstract. Semantic segmentation is an active area of research with a wide range of applications including autonomous driving, digital mapping, urban monitoring, land use analysis and disaster management. For the past few years approaches based on Convolutional Neural Networks, especially end-to-end approaches based on architectures like the Fully Convolutional Networks (FCN) and UNet, have made great progress and are considered the current state-of-the-art. Nevertheless, there is still room for improvement as CNN-based supervised-learning models require a very large amount of labelled data in order to generalize effectively to new data and the segmentation results often lack detail, mostly in areas near the boundaries between objects. In this work we leverage the semantic information provided by the objects’ boundaries to improve the quality and detail of an encoder-decoder model’s semantic segmentation output. We use a UNet-based model with ResNet as an encoder for our backbone architecture in which we incorporate a decoupling module that separates the boundaries from the main body of the objects and thus learns explicit representations for both body and edges of each object. We evaluate our proposed approach on the Inria Aerial Image Labelling dataset and compare the results to a more traditional Unet-based architecture. We show that the proposed approach marginally outperforms the baseline on the mean precision, F1-score and IoU metrics by 1.1 to 1.6%. Finally, we examine certain cases of misclassification in the ground truth data and discuss how the trained models perform in such cases.
FUSING MULTIPLE UNTRAINED NETWORKS FOR HYPERSPECTRAL CHANGE DETECTION
Authors: Saha S. , Gawlikowski J. , Zhu X. X.
Published: May 2022

Abstract. Change detection in hyperspectral images is challenging due to the presence of a large number of spectral bands. Due to the differences in band composition, a deep model trained on one hyperspectral sensor cannot be reused on another hyperspectral sensor. This challenge can be tackled by using untrained models as feature extractor for change detection in hyperspectral images. However, results produced by such a strategy may show variance if the untrained model is slightly perturbed. Different change detection maps are produced from different versions of the untrained model. We propose a decision fusion based strategy that can combine such different results and produce a final change detection map that retains the change information from all change maps. This approach improves the change detection performance and also improves reliability of the result. Experimental results on two publicly available hyperspectral datasets show the effectiveness of the proposed approach.
TOWARDS BETTER COASTAL MAPPING USING FUSION OF HIGH TEMPORAL SENTINEL-2 AND PLANETSCOPE-2 IMAGERIES: 12 BANDS AT 3 M THROUGH NEURAL NETWORK MODELLING
Authors: Collin A. , James D. , Feunteun E.
Published: May 2022

Abstract. Coastal interfaces are subject to an unprecedented rate of risks, gathering waves and rainfalls’ hazards, human assets’ densification, sea-level rise and precipitation intensification. Their sound management requires iterative observation at the highest possible spatial resolution. Sentinel-2 (S-2), provided with 13 spectral bands, datasets leverage high temporal resolution (one week) but spatial resolution (from 60 to 10 m) often remains too coarse to finely classify and monitor the coastal patches. PlanetScope-2 (PS-2) imagery benefits from very high temporal resolution (< one week) and high spatial resolution (3 m) for its blue-green-red-near-infrared dataset.This research paper proposes to, first, downscale 12 S-2 bands (cirrus S10 being evicted) by using neural network (NN) regressions built on the 4 PS-2 bands following two methods, and second, evaluate the NN classification performance of the 12-band datasets at 3 m for mapping 8 common coastal classes on a representative site (Brittany, France). Straightforward and stepwise downscaling procedures, respectively based on 12 and 22 NN regressions, generated very good performances (R2test=0.92 ± 0.02 and 0.95 ± 0.01, respectively). The 3-m NN classifications were considerably improved by the number of spectral bands (overall accuracy, OA, of the 4 bands: 48.12%) but also the precision of the downscaling (OA of the straightforward and stepwise downscaling: 75.25% and 93.57%, respectively). For the best classification, examination of the contribution of the individual bands revealed that S5, S7, S1, S9, S6 and S8A were meaningful (62.42, 55.02, 50.82, 46.4, 45.1, 31.02%, respectively), contrary to S12, S11 and S12 (12.47, 0 and 0%, respectively).
GOOGLE EARTH ENGINE BASED TEMPORAL ANALYSIS OF INDICES USED FOR FOREST FIRE STUDY IN MIZORAM, INDIA
Authors: Gupta P. , Shukla D. P.
Published: May 2022

Abstract. Forest fires would be a global disaster if they were not addressed seriously? From 2015 to 2021, the number of forest fires in India nearly tripled. According to FSI, the North Eastern Himalayas, one of UNESCO's 36 Biodiversity Hotspots, account for 36% of forest fires in India. This state is dominated by tribal population which practices shifting agriculture. It’s 76.01% of total forest cover is highly prone to Forest fires. Despite this, there hasn't been any time-series research on forest fires in this region. The Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Normalized Burnt Ratio (NBR), Aerosol Free Vegetation Index (AFRI 1600), and Land Surface Temperature may all be linked to forest fires (LST). For Mizoram, India, random samples were taken every 16 days using Landsat 8 satellite data across different land cover types, including dense forest, sparse forest, farmland, and bare land etc. The study was conducted on a bimonthly basis from January 2016 to June 2021. The findings of this work show that an automated temporal analysis utilizing GEE may be used successfully over a wide range of land cover types, providing critical data for future monitoring of such threats.
EXPLAINING A DEEP SPATIOTEMPORAL LAND COVER CLASSIFIER WITH ATTENTION AND REDESCRIPTION MINING
Authors: Méger N. , Courteille H. , Benoit A. , Atto A. , Ienco D.
Published: May 2022

Abstract. Deep learning-based land cover classifiers learnt from Satellite Image Time Series (SITS) are known to reach high performances. In order to explain, at least partly, the rationale leading to each one of their decisions, attention-based architectures have been proposed to automatically weight the importance of predefined data components in the classification process. Though generated for each decision separately, the informational content conveyed by such explanations can remain insufficient to end-users because of the complex nature of SITS. Moreover, getting a general perspective about the way a classifier works requires merging all explanations for each class and relating them to its mode of operation, which is not always straightforward. A preliminary and complementary approach for automatically identifying the data features detected by a pixel-wise deep spatiotemporal land cover classifier and explaining its behavior at the class level is therefore proposed in this paper. Classified pixels are first described using interpretable features coming under the form of data mining patterns. A redescription mining technique is then employed to automatically select, for each class, the features matching the different activation level configurations of the layer that is assumed to capture the aforementioned patterns. Experiments based on a Sentinel-2 time series and a deep spatiotemporal neural network implementing a channel-separated processing as well as a channel-based attention mechanism show the interest of such a combined approach.
THE MONITORING OF NON-FARMING AND NON-GRAIN PURPOSES IN ARABLE LAND OF ZHEJIANG, CHINA WITH DOMESTIC SATELLITE IMAGERY
Authors: Wang X. , Feng C. , Fu Y. , Liu X. , Zhan Y. , Xu P. , Deng X. , Li X. , Zhang T. , Zhang Y. , Zhang Z.
Published: May 2022

Abstract. Arable land protection is essential for Zero hunger the Sustainable Development Goals of United Nations, and the arable land protection includes two aspects, non-farming and non-grain. We try to monitor the arable land protection in Zhejiang with domestic satellite imagery. Satellite remote technology has become an essential way to monitor the land cover change (for non-farming) and grain crops (for non-grain). However, current monitoring frequency and scale were unable to satisfy the needs for non-farming monitoring. The low-resolution image cannot satisfy the feature of land fragmentation of Zhejiang for non-grain monitoring. To address the above problem, this paper proposes a land cover change method to monitor non-farming purposes based on deeplabv3+ with monthly coverage 2 meters resolution images. By focusing on rebuilding training data set and improving training strategy with hard example training, the difficulty of the spurious change caused by the adjustment of farming structure is solved. At the same time, this paper builds three training processes (Initial training, Fine training, Retraining for promotion) based on Fully Convolutional Neural Network FCN-8S to monitor the main grain crops in Zhejiang. The phenological features are added into the process of training to further improve the accuracy. At present, land cover change method of this paper has been applied in Zhejiang province and the monitoring of grain crops has been carried out in some regions according to the specific requirements. The result shows that both the two methods exhibit good accuracy and generalization ability at the time and space scale.
EXTRACTION OF ICE FLOW VELOCITY BY COMBINATION OF DINSAR AND OFFSET TRACKING METHODS FOR PINE GLACIER, WEST ANTARCTICA
Authors: Lin K. , Qiao G. , Zhang L. , Popov S.
Published: May 2022

Abstract. West Antarctica is the main contributor to global sea level rise at present and in the coming decades, since it occupies 80% of mass loss in Antarctica. In this paper, a combination of Differential Interferometric Synthetic Aperture Radar (DInSAR) and offset tracking technology is used to extract the ice flow velocity of the Pine Island Glacier (PIG), a typical glacier in West Antarctica. Due to the large deformation gradients in PIG, DInSAR technology is used to extract ice flow velocity in bare rock and mountains, then offset tracking technology is used to extract ice flow velocity in areas where glaciers collapse frequently. Finally, the above two results are mosaiced into a new image of the interannual ice flow velocity of PIG in 2017. Through qualitative and quantitative evaluation, it is found that the ice flow velocity extracted by the combination has high accuracy in both high and low velocity areas. In summary, we concluded that the combination of DInSAR and Offset tracking can obtain reliable ice velocity products in glaciers that change rapidly. This combination is of scientific significance for monitoring the movement and evolution of glaciers in the West Antarctica.
FOREST PLANTATION DETECTION THROUGH DEEP SEMANTIC SEGMENTATION
Authors: Dallaqua F. B. J. R. , Rosa R. A. S. , Schultz B. , Faria L. R. , Rodrigues T. G. , Oliveira C. G. , Kieser M. E. J. , Malhotra V. , Dwyer T. , Wolfe D. S.
Published: May 2022

Abstract. Forest plantations play an important role ecologically, contribute to carbon sequestration and support billions of dollars of economic activity each year through sustainable forest management and forest sector value chains. As the global demand for forest products and services increases, the marketplace is seeking more reliable data on forest plantations. Remote sensing technologies allied with machine learning, and most recently deep learning techniques, provide valuable data for inventorying forest plantations and related valuation products. In this work, deep semantic segmentation with U-net architecture was used to detect forest plantation areas using Sentinel-2 and CBERS-4A images of different areas of Brazil. First, the U-net models were built from an area of the Centre-East of Paraná State, and then the best models were tested in 3 new areas that present different characteristics. The U-net models built with Sentinel-2 images achieved promising results for areas similar to the ones used in the training set, with F1-score ranging from 0.9171 to 0.9499 and with Kappa values between 0.8712 to 0.9272, demonstrating the feasibility of deep semantic segmentation to detect forest plantations.
ESTIMATION OF NDVI FOR CLOUDY PIXELS USING MACHINE LEARNING
Authors: Agrawal R. , Mohite J. D. , Sawant S. A. , Pandit A. , Pappula S.
Published: May 2022

Abstract. The Normalized Difference Vegetation Index (NDVI) is a useful index for vegetation monitoring. However, due to cloud cover the observations of NDVI are discrete and vary in the intensity. Therefore, there is a need to estimate the NDVI during cloud cover using alternative sources of satellite observations. The main objective of this study is to estimate NDVI during cloudy conditions using moderate resolution multi-spectral and synthetic aperture radar (SAR) observations. Two approaches were identified: 1) pixel replacement and 2) machine learning based regression analysis to estimate cloud free NDVI. Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day NDVI composite, Sentinel-1 SAR and cloud masked Sentinel-2 multi-spectral observations were collected for entire cropping season. The satellite observations were selected only for agricultural areas by applying the agriculture, non-agriculture land use land cover mask. Machine learning algorithms such as Linear Regression (LR), Random Forest Regression (RFR), and Support Vector Regression (SVR) were used for NDVI estimation. Regression analysis was performed using Sentinel-2 NDVI as an independent variable and VV, VH, Cross Ratio (i.e., VV/VH), and MODIS NDVI as dependent variables. NDVI of the cloudy pixel was estimated using the trained regression models over the agriculture areas. A regression model was trained and applied to each Sentinel-2 tile that covers an area of 100 km × 100 km. The RFR and SVR showed the highest R2 of 0.73 and a RMSE of 0.12. A visual comparison of time series graphs showed good alignment between actual (Sentinel-2) and predicted NDVI and usual crop growth trend.
IMPROVEMENT OF THE TECHNIQUES FOR THE COMPUTATION OF EVAPOTRANSPIRATION MAPS
Authors: Stucchi L. , Aiello M. , Gargiulo A. , Brovelli M. A.
Published: May 2022

Abstract. The definition of a methodology for estimating suitable areas for new renewable sources needs to identify possible indexes that describe the fields. One interesting index is the Evapotranspiration (ET). This is usually determined from hydrological models, which however do not provide a real-time estimation. So, new different procedures have been tested to compute it, for example, the use of Satellite images. The Sen-ET project allows using the Copernicus data to compute daily evapotranspiration. An improvement in the automatization of methodology is presented within this work. The model is tested in two different Italian regions with different climates and geographical conditions, considering also different months to study the results in different seasons over the same area. Results are then compared with those obtained in the same areas and period with two hydrological models (BIGBANG and GlobWat). The different outputs are analysed according to their spatial resolutions and respect to agricultural land cover classes. The comparison between Sen-ET evapotranspiration maps and hydrological model results has shown, in the analysed areas, relevant differences and suggests interesting future insights for continuous monitoring of land subject to water stress.
Breakdown of the velocity and turbulence in the wake of a wind turbine – Part 1: large eddy simulations study
Authors: Jézéquel Erwan , Blondel Frédéric , Masson Valéry
Published: May 2022

Abstract. A new theoretical framework, based on wake analysis in the moving and fixed frames of reference (MFOR and FFOR), is proposed to break down the velocity and turbulence fields in the wake of a wind turbine. This approach adds theoretical support to models based on the dynamic wake meandering (DWM) and opens the way for a fully analytical and physically-based model of the wake that takes meandering and atmospheric stability into account, which is developed in the companion paper. The mean velocity and turbulence in the FFOR are broken down into different terms, which are functions of the velocity and turbulence in the MFOR. These terms can be regrouped as pure velocity, pure meandering, pure turbulence and cross-terms, the last ones being implicitly neglected in the DWM. The shape and relative importance of the different terms are estimated with the large eddy simulation solver Meso-NH coupled with an actuator line method. A single wind turbine wake is simulated on flat terrain, under three cases of stability: neutral, unstable, and stable. In the velocity breakdown, the cross-term is found to be relatively low. This is not the case for the turbulence breakdown equation where even though they are overall of a lesser magnitude than the pure terms, the cross-terms redistribute the turbulence and induce non-negligible asymmetry. It is also found that as atmospheric stability increases, the pure turbulence contribution becomes relatively larger and pure meandering relatively smaller.
La cooperación transfronteriza como alternativa a las tensiones limítrofes que ha generado la especialización productiva de la soja en el MERCOSUR
Authors: Ávila Duque Victoria
Published: May 2022

La integración regional del MERCOSUR ha tenido un rol crucial en el desarrollo de los países miembros, principalmente, Brasil y Argentina. Sin embargo, su especialización productiva e inmersión en las cadenas de valor global de la soja como resultado de la creciente demanda de China y su protagónica presencia en la región, ha profundizado las asimetrías entre las economías de los países del bloque y la transformación en las dinámicas fronterizas, dado que gran parte de los efectos derivados de estos intercambios comerciales se materializan en las fronteras. Por esto, se presenta la cooperación transfronteriza como una vía de cohesión social desde lo local, pues se refiere a la capacidad de agencia de las entidades subnacionales en los territorios limítrofes, tomando como ejemplo el caso de Santana do Livramento (Brasil) y Rivera (Uruguay).
Asimetrías de frontera. Oportunidades y limitaciones para el avance hacia la frontera-potencialidad en el territorio binacional de Posadas (Misiones, Argentina) y Encarnación (Itapúa, Paraguay)
Authors: Antonella Cossi Carla , Catalina Capasso Anabel
Published: May 2022

El presente artículo, se propone analizar las oportunidades y limitaciones para el desarrollo conjunto de los sectores comerciales del territorio fronterizo que conforman las ciudades de Posadas (perteneciente a la provincia de Misiones, en Argentina) y Encarnación ( perteneciente al departamento de Itapúa, Paraguay); mediante la caracterización de la competencia entre los sectores comerciales de ambas ciudades; la descripción sistemática de las barreras que enfrentan aquellos actores que van a incorporarse en esta competencia; y la evaluación de las acciones y reclamos que contribuyen o limitan el desarrollo competitivo en tan complejo escenario.
Las cooperativas agropecuarias en Cuba. La negociación y contratación de sus producciones con las empresas estatales
Authors: Arias Salazar Claudio
Published: May 2022

El presente trabajo tiene por objetivo analizar las principales insuficiencias que limitan el proceso de contratación de las cooperativas agropecuarias en la provincia de Granma, Cuba. Dentro de los métodos empíricos se utilizó la observación científica y dos entrevistas grupales con miembros de las juntas directivas de cooperativas agropecuarias en los municipios de Bayamo y Cauto Cristo; además se aplicaron tres encuestas, la primera a 81 presidentes de cooperativas de Granma en el 2005; la segunda a 37 presidentes de cooperativas en el municipio Bayamo en el 2017 y la tercera a 16 presidentes de cooperativas de Cauto Cristo en el 2020. A las principales conclusiones que arrojó esta investigación son que el marco legal de la contratación de la producción de las cooperativas agropecuarias está bien diseñado en los diferentes documentos que norman ese proceso; que los vaivenes de la política de contratación de la producción de las cooperativas agropecuarias en los últimos 20 años ha permitido que se produzcan insuficiencias en el proceso que repercuten negativamente sobre la gestión económica de las cooperativas agropecuarias; y que las principales insuficiencias del proceso de contratación son el reiterado incumplimiento de los contratos tanto para la venta de insumos a las cooperativas como para la compra de las producciones, la imposición de los contratos a las juntas directivas; la baja preparación de las juntas directivas para enfrentar el proceso de negociación y el grado de insatisfacción que tienen con el proceso de contratación.
Diversidade fitoplanctônica e traços funcionais em ecossistemas aquáticos de uma área de preservação do Cerrado brasileiro
Authors: Nascimento Anny Kelly , Bortolini Jascieli Carla
Published: May 2022

As áreas de conservação desempenham um papel importante para conter a perda de habitat e a biodiversidade. No entanto, pouco se sabe sobre a influência dessas áreas nos ecossistemas aquáticos e, principalmente, na comunidade fitoplanctônica. Aqui, exploramos a riqueza, abundância e traços funcionais do fitoplâncton em diferentes ecossistemas aquáticos em uma área protegida em Niquelândia, Goiás (no Cerrado brasileiro). Nós amostramos quatro lagoas, seis riachos e um rio, durante a estação chuvosa e registramos 78 táxons. Nas lagoas predominaram as algas verdes, flagelados mixotróficos e desmídias, enquanto nos riachos e rio predominaram as diatomáceas, as algas verdes e os flagelados mixotróficos. Diferenças entre ambientes lóticos e lênticos foram evidenciadas, para riqueza e densidade, tanto para táxons quanto para traços funcionais. Os traços funcionais mais frequentes nas lagoas foram flagelos e mixotrofia, enquanto que nos riachos e rio, a presença de sílica também foi importante. A maioria das algas registradas foram unicelulares, nanoplanctônicas e com células ovóides e esféricas. Assim, avaliar a diversidade fitoplanctônica é o primeiro passo para o monitoramento de ecossistemas aquáticos em áreas de conservação e para a avaliação de seus efeitos nesses ambientes. Portanto, com esses resultados será possível comparar ecossistemas em áreas protegidas com ecossistemas semelhantes em áreas desprotegidas.
Konsepsi Pembiasaan Sholat Dhuha dan Membaca Al-Qur’an dalam Peningkatan Akhlak
Authors: Mustofa Ali , Ghofur Abdul
Published: May 2022

Pembiasaan-pembiasaan secara islami meliputi membaca Al-qur’an dan sholat dhuha merupakan keberimanan seseorang yang diukur secara akhlaki. Indikasi bahwa akhlak bisa dipelajari dengan metode pembiasaan, pembiasaan secara terus menerus akhirnya mendapakan akhlak yang hasanah. Diberbagai sekolah dasar yang ada disekitar kita, termasuk yang menerapkan progam membiasakan membaca Al-Qur’an sehingga peserta didik sangat antusias sekali dalam mengikuti progam tersebut. Dari pembahasan ini dapat disimpulkan: 1) Pembiasaan Shalat Dhuha dan membaca al qur’an dilaksanakan setiap hari sebelum proses pembelajaran  agar memunculkan aklak islami. 2) Shalat Dhuha dan membaca al qur’an dilaksanakan berjamaah di kelas masing-masing dengan imam yang sudah terjadwal. 3) Kebiasaan melaksanakan shalat dhuha dan membaca al qur’an sebelum kegiatan belajar mengajar merupakan upaya mewujudkan fondasi anak shaleh dan unggul.
ՀՀ պետական պարտատոմսերի շուկայի զարգացման հիմնախնդիրները. Ախտորոշում եվ հիմնական ուղենիշներ/Issues of RA Government Bond Market Development: Diagnostics and the Key Benchmarks
Authors: KARAPETYAN NAREK
Published: May 2022

The RA Government
targets increasing the share of domestic debt in the structure of
public debt, which implies further deepening of the government
bond market. To reveal its possibilities and outline the ways of
improving debt management policy towards this aim, in this
paper RA government bond market development has been
diagnosed. Particularly, quantitative thresholds designed by the
IMF were applied, the factors affecting the development of
primary and secondary markets were estimated with
econometric models, and prerequisites of participation of
foreign investors in the local market were discussed. The
research concludes that the primary market has reached a
significant level of development, whereas the secondary market
is weakly developed, which can be attributed to the low level of
development of the non-bank financial sector and low
participation by foreign investors. As a result of the research,
the author offers to attach much importance to initiatives
towards involving foreign investors into the debt market, which
may result in higher liquidity of the secondary market and
ensure a positive cycle of market development.
Երևան քաղաքի էլեկտրոնային կառավարման համակարգի վերլուծությունը՝ խելացի կառավարման գործարկման համատեքստում/Analysis of the E-governance System of the City of Yerevan in the Context of Smart Governance
Authors: BARSEGHYAN ARAKSYA
Published: May 2022

Smart Governance is one of the components of the Smart City concept
and it is as important as other components of the concept.
Accordingly, the strategy of transforming Yerevan into a smart
city should include a smart governance component. The purpose
of this paper is to study the e-governance system of Yerevan city
in order to find out what are the prerequisites for the operation
of smart governance component in the city. In order to achieve
this goal, the paper presents the stages of e-governance development described by different researchers, the research made by
Rutgers University in the context of the rankings of the city of
Yerevan, it also examined the current e-governance system of
Yerevan, according to the characteristics of e-governance
development stages. As a result of the analysis, relevant
conclusions and recommendations have been made.
Possibilities of constructing a copper smelter in the republic of Armenia
Authors: MELKUMYAN MIKAYEL , ARAKELYAN ARTHUR
Published: May 2022

Nowadays, the export volume of copper concentrate from the Republic of Armenia
equals more than 500 thousand tons per year. This extent fully satisfies the minimum
requirements for constructing a copper smelter in our country.
Calculations show that the copper production capacity of the Republic of Armenia is
estimated more than 120 thousand tons per year. Although it is considered to be a modest
result in the context of copper mining scale worldwide, it is of significant importance for
our country.
The production and export of pure copper will contribute to the flow of currencies
into our country. Meanwhile, it will enable to construct and exploit a cable factory, which,
in turn, will create favorable grounds for new working places and for the rise of overall
economic activation.
The necessity for constructing a copper smelter has also been stated by the
government of the Republic of Armenia.
One of the concerns remains the realization of sulfuric acid extracted in the process
of copper production. A solution could be transporting it to the port by railway through
the area of Georgia. Still, according to some viewpoints, it is possible to recycle sulfuric
acid on the spot and convert to fertilizers, varnish, paint, clay etc.
The paper takes into focus the possibilities of constructing a copper smelter in the
Republic of Armenia demonstrating the efficiency of investments and their buyback
deadlines on current copper price conditions.
Kualitas Produk dan Pelayanan Barista bagi Kepuasan Konsumen kedai Hermess Kopi
Authors: Herda Tri Arnawa I Komang , Oka Saputra I Gde , Manggala RS Aditya
Published: May 2022

The objectives of this study are: (1) To determine whether there is a significant effect of product quality on consumer satisfaction at Hermess Kopi Dalung shop in 2021. (2) To determine whether there is a significant influence on the quality of Barista service on consumer satisfaction at Hermess Kopi Dalung shop in 2021. (3) To find out whether there is a significant effect of product quality and barista service quality on consumer satisfaction at the Hermess Kopi Dalung shop in 2021. The method used in this research is descriptive qualitative. Research informants in this study were consumers of the Hermess Kopi Dalung Store in 2021. Sampling was done by interviewing 5 respondents, including students, students and private employees. This method provides direct answers from informants, so that answers can be found from the questions of interviewees given by the researcher. Researchers can conclude that the quality of products from the Hermess Kopi shop is very popular with customers, not only on the coffee menu that is of interest but many also like it from the non-coffee / frappe menu and from the snacks provided. Apart from the quality of the product, it is also greatly influenced by the barista. which is friendly to the customers of the Hermess Kopi Dalung shop which makes customers not feel awkward to shop at the Hermess Kopi Dalung shop. Thus, customers will feel satisfied with the service received by customers, plus the quality of the menu is not less competitive with well-known Coffee Shops. Therefore, product quality and service quality together greatly affect consumer satisfaction at the Hermess Kopi Dalung shop in 2021.
Pengaruh Motivasi Dan Lingkungan Kerja Terhadap Kinerja Karyawan Hotel Same Boutique Kendari
Authors: Nugraha Muhammad Ilham , Utha Arifin , Sartono Sartono
Published: May 2022

Tujuan yang hendak dicapai dalam penelitian ini adalah Untuk mengetahui pengaruh Motivasi dan Lingkungan Kerja berpengaruh terhadap Kinerja karyawan Hotel Same Boutique Kendari Populasi yang digunakan dalam penelitian ini adalah seluruh karyawan Hotel Same Boutique  Kendari yang berjumlah 50 orang karyawan. Untuk memperoleh data pendukung yang dibutuhkan dari sumber yang dapat dipercaya, maka digunakan teknik dokumentasi. Hasil penelitian ini bahwa pemberian motivasi dan lingkungan kerja karyawan dapat berpengaruh terhadap kinerja karyawan itu sendiri. Hal ini ditunjukan oleh hasil penelitian yang menunjukan bahwa motivasi karyawan dengan berbagai dimensi dan indikatir yang ditetapkan menunjukan hasil persentase sebesar diatas 60 persen, sedangkan lingkungan kerja secara rata-rata berada pada persentase diatas 70 persen. Dari kedua variabel tersebut yang menunjukan persentase yang relatif tinggi, kemudian dengan dasar variabel tersebut dapat mempengaruhi kinerja karyawan, dimana hasil analisis data menunjukan persentase rata-rata diatas 80 persen. Sehingga kesimpulan akhir yang dapat disampaikan bahwa pemberian motivasi dan lingkungan kerja karyawan Hotel Same Boutique  berpengaruh positif terhadap kinerja para karyawan hotel.
ANALISIS PENGEMBANGAN USAHA DALAM MENINGKATKAN PENJUALAN DAN PENDAPATAN PADA RUMAH MAKAN GLATIK
Authors: Humaera Zavira Istigfar , Abdullah Akhyar , Sahrun Sahrun
Published: May 2022

Penelitian ini bertujuan untuk: mengetahui dan menganalisisi pengambangan usaha yang dilakukan oleh rumah makan Glatik. Dalam penelitian ini, informan yang ditentukan adalah tenaga kerja yang bekerja pada rumah makan glatik, yang meliputi satu orang pemimpin rumah makan dan 4 orang karyawan yang bekerja pada Rumah makan glatik. Penelitian ini menggunakan metode penelitian kualitatif sebagai prosedur penelitian yang menghasilkan data deskriptif berupa kata-kata tertulis lisan dari orang-orang dan perilaku yang dapat diamati, serta berdasarkan metode observasi, wawancara dan studi dokumentasi. Hasil penelitian ini menunjukkan bahwa, secara keseluruhan usaha rumah makan Glatik setiap bulannya mengalami keuntungan sebesar, Rp. 18.265.075,- (delapan belas juta dua ratus enampuluh lima ribu tujuh puluh lima rupiah), dengan tingkat rasio R/C sebesar 1,61. Maka dapat disimpulkan bahwa usaha kuliner tersebut tergolong layak untuk dijalankan karena nilai R/C lebih dari 1. Hal ini menunjukan bahwa setiap Rp. 1 biaya produksi yang dikeluarkan oleh pengelola rumah makan mampu memberikan pengembalian berupa penerimaan sebesar, Rp 1,61. Artinya total penerimaan masih lebih besar dari total biaya produksi dan kegiatan usaha kuliner tersebut masih mengalami keuntungan setiap bulannya.
ANALISIS KUALITAS PELAYANAN TERHADAP KEPUASAN PESERTA PADA BPJS KETENAGAKERJAAN CABANG KENDARI
Authors: Putri Ines Pradilla , Amir Muhamad , Nurjannah Nurjannah
Published: May 2022

Tujuan penelitian ini adalah  untuk mengetahui kualitas pelayanan terhadap kepuasan peserta pada BPJS Ketenagakerjaan Cabang Kendari.jenis Penelitian ini merupakan penelitian deskriptif dengan pendekatan kualitatif bertujuan untuk mendeskripsikan peristiwa dan fenomena serta memberikan data tentang fakta atau fenomena dilapangan secara sistematis,mengenai kualitas pelayanan  terhadap kepuasaan perserta BPJS Ketenagakerjaan Cabang Kendari. Informan penelitian ini sebanyak 5 orang Data di kumpulkan melalui  wawancara ,dokumentasi dan  Observasi. Data  yang diperoleh selanjutnya, dianalis dengan  model interaktif  terdiri dari pengumpulan data, reduksi data,penyajian data dan kesimpulan, Berdasarkan hasil penelitian, dapat ditarik kesimpulan bahwa kualitas pelayanan yang diberikan oleh Kantor BPJS Ketenagakerjaan Cabang Kendari dalam meningkatkan kepuasan peserta yang dilihat dari lima dimensi, yakni: a) dimensi bukti fisik (tangibles), b) dimensi keandalan (reliability), c) dimensi daya tanggap (responsiveness), d) dimensi jaminan (assurance), dan e) dimensi empati (empathy) telah dilaksanakan dengan baik. Hal tersebut dilihat dari rata-rata jawaban yang diberikan oleh para informan yang menyatakan bahwa kelima dimensi tersebut sudah baik dalam pelaksanaannya. Kategori tersebut tidak hanya disampaikan baik oleh para karyawan, namun juga oleh para peserta yang juga menyatakan bahwa kualitas pelayanan yang diberikan oleh Kantor BPJS Ketenagakerjaan Cabang Kendari berdasarkan pada lima dimensi tersebut diatas sudah dilaksanakan dengan baik, sehingga berimplikasi dengan baik pada kualitas pelayanan dari Kantor BPJS Ketenagakerjaan Cabang Kendari.
Importancia de las redes de conocimiento en el entorno ingenieril y su aporte en la formación de profesionales
Authors: Hurtado Mesa Ana , Rubiano Acosta Mary , Castillo Araujo Juliana , Gómez Ortiz Yesica
Published: May 2022

La importancia de las redes de conocimiento en el entorno ingenieril son una parte fundamental en el desarrollo profesional. Aplican las multidisciplinarias áreas que transcienden los campos empresariales en los entornos académicos e investigativos y su objetivo en concreto que es construir conocimiento. A su vez algunas redes existentes a nivel nacional e internacional relacionadas con ingeniería evidenciaron la aparición de comunidades que en algunos casos refuerzan los conocimientos en áreas de ciencia, tecnología, ingeniería y matemáticas, también trabajan temas de género. En ese sentido, este artículo realiza la iniciativa de la red de conocimiento Network WE mediante el convenio entre la Corporación Universitaria Iberoamericana y la Universidad de Cundinamarca (sede Ubaté).
An Evidence-Based Approach to Multi-Ligamentous Knee Injuries
Authors: Fortier Luc M , Stylli Jack A , Civilette Matthew , Duran Naim S , Hanukaai Shadi , Wilder Heath , Sherman William F , Kaye Alan D
Published: May 2022

Multi ligament knee injuries (MLKIs) are highly complex injuries with associated complications and often present with difficult management strategies. MLKIs may affect the anterior cruciate ligament (ACL), posterior cruciate ligament (PCL), medial collateral ligament (or posteromedial corner (PMC)), and lateral collateral ligament (or posterolateral corner (PLC)) in addition to other structures including the menisci, common peroneal nerve, and popliteal artery. MLKIs are highly associated with the male sex and are commonly seen in high-velocity motor vehicle accidents and low-velocity sports injuries. Given the multiple planes of movement in the knee and various primary and secondary stabilizers throughout those planes, there is great heterogeneity in an injury pattern and most involve the ACL and PCL. Initial evaluation of this injury includes assessment of lower extremity sensation, distal pulses, and ankle-brachial index (ABI). If vascular compromise is suspected, computed tomography angiography (CTA) or magnetic resonance angiography (MRA) are indicated to evaluate the vasculature. As opposed to CTA, MRA offers visualization of the soft-tissue structures that are commonly damaged in MLKIs. Initial management typically includes closed reduction of the knee with subsequent external fixation. Classification systems guide initial assessments; however, further management is unclear and leads the surgical team to decide the best, individualized management option for each patient. As a result, optimal surgical and postoperative treatment options remain complicated, and clinical outcomes remain difficult to predict. The purpose of this review is to consolidate the most up-to-date practices of the diagnostic workup, management, and treatment of MLKIs.
A modified Mann algorithm for the general split problem of demicontractive operators
Authors: CHAROENSAWAN Phakdi , SUPARATULATORN Raweerote
Published: May 2022

This work proposes a novel method for solving the general split common fixed point problem of demicontractive operators in the framework of real Hilbert spaces. Our proposed technique is principally based on the Mann algorithm. The proof of the weak convergence theorem is additionally established under some particular conditions. We subsequently verify the convergence of our algorithm via numerical examples.
India’s Development of Sea-based Nuclear Capabilities: Implications for Pakistan
Authors: Ghazala Yasmin Jalil
Published: May 2022

India is rapidly building up its navy in order to develop blue-water capabilities and increase its prowess in the Indian Ocean and beyond, which is integral to India’s grand strategy to attain a regional and global power status. This poses a threat to the regional states. It, especially, heightens Pakistan’s threat perception, whose main security threat comes from India. Of all the gravest concerns for Pakistan is India’s development of nuclear triad, which is mainly comprised of its nuclear powered submarine fleet, armed with a range of nuclear-tipped missiles, which gives it a second-strike capability. The paper looks at how India’s development of sea-based nuclear capability would affect nuclear deterrence stability in South Asia. The paper assesses the Indian naval nuclear development and also whether a second strike capability can potentially stabilises deterrence in South Asia. It finds that the development of a nuclear triad, in general, and second strike capability, in particular, would not stabilise deterrence or bring strategic stability to South Asia. In fact, it would increase arms race tendencies. It would eventually brings instability and further uncertainty to the region with complex command and control issues involved, and the risk of accidental or unauthorised launch.