bluuebunny/crossref_metadata_2025 huggingface dataset:
СИСТЕМА УПРАВЛЕНИЯ БИЗНЕС-ПРОЦЕССАМИ В АГРОПРОМЫШЛЕННОМ КОМПЛЕКСЕ В УСЛОВИЯХ ЦИФРОВОЙ ТРАНСФОРМАЦИИ
Authors: Tuskov Andrey , Efimov Ivan , Elfimov Peter , Grosheva Ekaterina
Published: December 2023

В настоящее время особое внимание уделяется инновационным программным системам, посредством которых можно осуществлять управление бизнесом на любом из предприятий, в том числе в отрасли (агропромышленного комплекса) АПК. Цель исследования состоит в том, чтобы проанализировать возможность применения автоматизированной системы Runa WFE в компаниях агропромышленного комплекса. Методами исследования, применяемыми в статье, являются эксперимент, системный анализ.
Материалами исследования служат ряд статей и научных журналов, рассматривающих инновационную составляющую в управлении бизнесом на предприятиях. Наиболее важными результатами исследования, представленными в данной работе, является отражение основного функционала программного обеспечения, который можно использовать в сфере агропромышленного комплекса, помимо этого рассмотрены ключевые особенности анализа, заложенного в программное обеспечение (ПО), а также исследованы основные факторы и риски при внедрении автоматизированных информационных систем в фирмах.
Теоретическая значимость исследования состоит в том, что полученные результаты можно применить для создания эффективного плана по внедрению инноваций на предприятии, а также для создания эффективной методики оптимизации бизнес-процессов в компании. Практическая значимость исследования заключается в том, что благодаря внедрению систем автоматизации бизнес-процессов на предприятии можно упростить задачи управления и координации между различными уровнями предприятия, сократить затраты на трудовые и материальные ресурсы, улучшить управление поставками и оперативность принятия решений на производстве, тем самым повысить эффективность функционирования организации.
ORGANIC FERTILIZER AN ALTERNATIVE TO CHEMICAL (INORGANIC) FERTILIZER FOR SUSTAINABLE SOIL PRODUCTIVITY IN THE ERA OF ECONOMIC CHALLENGES (A REVIEW)
Authors:   Department of Agriculture, Alex-Ekwueme Federal University Ndufu Alike, Ebonyi State, Orji J
Published: December 2023

The major constraint limiting crop yield in developing countries globally and especially in the tropical Africa is soil infertility. In order to improve the fertility of the soils for maximum food production and supplies, the use of inorganic (chemical) fertilizers was adopted and used extensively. However, the scarcity and high cost of the inorganic fertilizers in recent times due to economic and global challenges like covid 19 pandemic and wars is worrisome. Also, research has shown that the continuous use of inorganic fertilizer and total dependence on it for agricultural production have led to a decline in soil fertility, land degradation and rottening of certain crops especially tubers, hence the need for an alternative. This review work studies the need of producing organic fertilizers from various organic wastes (such as agricultural waste, sewage sludge, animal waste, municipal solid waste, food waste, etc) as alternative soil amendment using the technology advancement for solid organic waste management as obtained in the developed countries. This when adopted will not only enhance and sustain soil productivity but will help to free the environment of pollution and encourage economic growth. The work also provides insight to the production line of the organic fertilizer, sources or raw materials and advantages of substituting chemical (inorganic) fertilizer with organic fertilizer. It is obvious that organic fertilizer when produced will be affordable, available, cheaper and will improve and sustain the physical, chemical and biological conditions of the soils.
The growing role of telemedicine – possibilities and regulations concerning teleradiology in Poland
Authors: Madej Małgorzata , Sąsiadek Marek J.
Published: December 2023

In recent years, imaging studies have become increasingly used at various stages in the management of patients with various conditions and disorders. This process results in a necessity to provide an increasing number of exams, which involves a growing role of radiologists in assessing and reporting those exams. The article discusses tele­radiology as a method that can improve access to radiology services, presenting its potential benefits, as well as the risks involved. It analyses access to radiology healthcare services in Poland in the context of the international and Polish legal provisions concerning the right to healthcare. While funding for imaging studies for patients is widely available and imaging equipment in Poland is improving despite some shortages, the main barrier is identified in the number of specialists capable of assessing the exams. Teleradiology can alleviate this shortage, so the article presents legal provisions and international good practice guidelines in this area, focusing on documents issued by the European Society of Radiology, the American College of Radiology, and the British Royal College of Radiologists. The guidelines concerning such aspects as patients’ rights, teleradiologists’ qualifications, communication and reporting, responsibility, and technical requirements may help make teleradiology a safe and valuable component of the healthcare system in Poland.
Development of Android Based Mathematics Learning Media for Primary School Students
Authors: Triayomi Ria , Pamugkas Simon Panji
Published: December 2023

This research was conducted to develop an android-based mathematics learning media design for second-grade students at Xaverius 2 Primary School Palembang. This research adopted the research procedures outlined by Borg and Gall. The findings of this research are divided into two parts. The first part of the result research pertains to the needs analysis. Based on the need analysis, it is obvious that the development of learning media design to enhance students’ independent learning at home is highly necessary. The second result research relates to the validation of the development of Android-based learning media design. The development of the android-based learning media design falls under the category of validity. Validation testing was conducted through a single assessment, The level of feasibility of Android-based Mathematics Learning Media for Elementary School Students by media experts obtained an overall average of 95.34% in the "Very Feasible" category, by material experts an overall average of 88.6% was obtained in the "Very Feasible" category, and Testing by students obtained an average of 82.47% in the "Very Appropriate" category, so it can be concluded that the Android-based learning media developed is very suitable for use.

Keywords: Learning Media, Android-Based Mathematics Learning
“Pues la fama a tanto te provoca”. Un eco salmantino en las relaciones entre Lope de Vega, Cervantes y Armendáriz
Authors: Carabias Orgaz Miguel
Published: December 2023

RESUMEN:
Se ofrece el estudio de un conjunto de textos poéticos copiados en las guardas de un ejemplar de la edición salmantina de 1582 del Hypotyposeon, de Martínez de Cantalapiedra. Entre ellos, se encuentra el soneto “Hermano Lope, bórrame el soné” –que se ha venido atribuyendo a Cervantes, a Góngora y a Julián de Armendáriz–, un nuevo testimonio muy cercano a la fecha de composición y con algunas variantes. Otro soneto, hasta ahora desconocido, presenta una sátira contra cierto poeta llamado Blasco. Diversos datos permiten defender la atribución de ambas composiciones al escritor salmantino Julián de Armendáriz.
ABSTRACT:
We offer the study of a set of poetic texts copied in the endpapers of a copy of the Hypotyposeon, by Martínez de Cantalapiedra, from 1582. Among them is the sonnet “Hermano Lope, bórrame el soné” (which has been attributed to Cervates, Góngora and Julián de Armendáriz), a new testimony very close to the date of composition and with some variants. Another sonnet, hitherto unknown, presents a satire against a poet named Blasco. Various data allow us to defend the attribution of both compositions to the writer born in Salamanca Julián de Armendáriz.
Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers
Authors: De Pue Jan , Wieneke Sebastian , Bastos Ana , Barrios José Miguel , Liu Liyang , Ciais Philippe , Arboleda Alirio , Hamdi Rafiq , Maleki Maral , Maignan Fabienne , Gellens-Meulenberghs Françoise , Janssens Ivan , Balzarolo Manuela
Published: December 2023

Abstract. The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. It is modulated by hydrometeorological drivers (i.e. short-wave radiation, air temperature, vapour pressure deficit and soil moisture) and the vegetation state (i.e. canopy greenness, leaf area index) at instantaneous to interannual timescales. In this study, we set out to evaluate the ability of GPP models to capture this variability. Eleven models were considered, which rely purely on remote sensing data (RS-driven), meteorological data (meteo-driven, e.g. dynamic global vegetation models; DGVMs) or a combination of both (hybrid, e.g. light-use efficiency, LUE, models). They were evaluated using in situ observations at 61 eddy covariance sites, covering a broad range of herbaceous and forest biomes. The results illustrated how the determinant of temporal variability shifts from meteorological variables at sub-seasonal timescales to biophysical variables at seasonal and interannual timescales. RS-driven models lacked the sensitivity to the dominant drivers at short timescales (i.e. short-wave radiation and vapour pressure deficit) and failed to capture the decoupling of photosynthesis and canopy greenness (e.g. in evergreen forests). Conversely, meteo-driven models accurately captured the variability across timescales, despite the challenges in the prognostic simulation of the vegetation state. The largest errors were found in water-limited sites, where the accuracy of the soil moisture dynamics determines the quality of the GPP estimates. In arid herbaceous sites, canopy greenness and photosynthesis were more tightly coupled, resulting in improved results with RS-driven models. Hybrid models capitalized on the combination of RS observations and meteorological information. LUE models were among the most accurate models to monitor GPP across all biomes, despite their simple architecture. Overall, we conclude that the combination of meteorological drivers and remote sensing observations is required to yield an accurate reproduction of the spatio-temporal variability of GPP. To further advance the performance of DGVMs, improvements in the soil moisture dynamics and vegetation evolution are needed.
Seasonal and diurnal variability of sub-ice platelet layer thickness in McMurdo Sound from electromagnetic induction sounding
Authors: Brett Gemma Marie , Leonard Gregory Howard , Rack Wolfgang , Haas Christian , Langhorne Patricia Jean , Robinson Natalie , Irvin Anne
Published: December 2023

Abstract. Here, we present observations of temporal variability of sub-ice platelet layer over seasonal and diurnal timescales under Ice Shelf Water-influenced fast ice in McMurdo Sound. Electromagnetic induction (EM) sounding time-series measurements of the thicknesses of fast ice and sub-ice platelet layer were made in winter and late spring of 2018. Winter objectives were to measure the seasonal growth of fast ice and sub-ice platelet layer near the McMurdo Ice Shelf in the east, while in late spring we assessed the diurnal variability of sub-ice platelet layer with coincident EM time-series and oceanographic measurements collected in the main outflow path of supercooled Ice Shelf Water in the west. During winter, we observed when the sub-ice platelet layer formed beneath consolidated ice. Episodes of rapid sub-ice platelet layer growth (~0.5–1 m) coincided with strong southerly-wind-events and polynya activity, suggesting wind-enhanced Ice Shelf Water circulation from the McMurdo-Ross Ice Shelf cavity. In late spring, we investigated how the tides and ocean properties influenced the sub-ice platelet layer. Over a two-week neap-spring tidal cycle, changes in sub-ice platelet layer thickness were observed to correlate with the tides, increasing more during neap than spring tide cycles, and on diurnal timescales, more on ebb than flood tides. Neap and ebb tides correspond with stronger northward circulation out of the cavity, indicating that sub-ice platelet layer growth was driven by tidally-enhanced Ice Shelf Water outflow. The observed variability indicated that wind-driven circulation and the tides influence Ice Shelf Water outflow in McMurdo Sound, and consequently, sub-ice platelet layer evolution over a range of timescales.
OpenWQ v.1: A multi-chemistry modelling framework to enable flexible, transparent, interoperable, and reproducible water quality simulations in existing hydro-models
Authors: Costa Diogo , Klenk Kyle , Knoben Wouter , Ireson Andrew , Spiteri Raymond J. , Clark Martyn
Published: December 2023

Abstract. This work advances the cross-model deployment of ecological and biogeochemical simulation capabilities in existing process-based hydro-modeling tools, which we term "Open Water Quality" (OpenWQ). We detail aspects of OpenWQ's architecture that enable its plug-in type incorporation into existing models, along with its innovative aspects that enable biogeochemistry lab-like capabilities. OpenWQ's innovative aspects allow modelers to define the pollution problem(s) of interest, the appropriate complexity of the biogeochemistry routines, test different modeling hypotheses, and deploy them across different hydro-models. A coupling recipe for linking OpenWQ to existing hydro-models is described and demonstrated on two models with different model structures, SUMMA and CRHM. Such model integration helps establish a more formal (and direct) exchange of innovation between hydrological and biogeochemical-water quality modeling communities. Example applications of different pollution studies enabled by OpenWQ are provided with robust numerical verification.
First release of the Pelagic Size Structure database: Global datasets of marine size spectra obtained from plankton imaging devices
Authors: Dugenne Mathilde , Corrales-Ugalde Marco , Luo Jessica , Kiko Rainer , O'Brien Todd , Irisson Jean-Olivier , Lombard Fabien , Stemmann Lars , Stock Charles , Anderson Clarissa R. , Babin Marcel , Bhairy Nagib , Bonnet Sophie , Carlotti Francois , Cornils Astrid , Crockford E. Taylor , Daniel Patrick , Desnos Corinne , Drago Laetitia , Elineau Amanda , Fischer Alexis , Grandrémy Nina , Grondin Pierre-Luc , Guidi Lionel , Guieu Cecile , Hauss Helena , Hayashi Kendra , Huggett Jenny A. , Jalabert Laetitia , Karp-Boss Lee , Kenitz Kasia M. , Kudela Raphael M. , Lescot Magali , Marec Claudie , McDonnell Andrew , Mériguet Zoe , Niehoff Barbara , Noyon Margaux , Panaïotis Thelma , Peacock Emily , Picheral Marc , Riquier Emilie , Roesler Collin , Romagnan Jean-Baptiste , Sosik Heidi M. , Spencer Gretchen , Taucher Jan , Tilliette Chloé , Vilain Marion
Published: December 2023

Abstract. In marine ecosystems, most physiological, ecological, or physical processes are size-dependent. These include metabolic rates, uptake of carbon and other nutrients, swimming and sinking velocities, and trophic interactions, which eventually determine the stocks of commercial species, as well as biogeochemical cycles and carbon sequestration. As such, broad scale observations of plankton size distribution are important indicators of the general functioning and state of pelagic ecosystems under anthropogenic pressures. Here, we present the first global datasets of the Pelagic Size Structure database (PSSdb), generated from plankton imaging devices. This release includes the bulk particle Normalized Biovolume Size Spectrum (NBSS) and bulk Particle Size Distribution (PSD), along with their related parameters (slope, intercept, and R2) measured within the epipelagic layer (0–200 m) by three imaging sensors: the Imaging FlowCytobot (IFCB), the Underwater Vision Profiler (UVP) and benchtop scanners. Collectively, these instruments effectively image organisms and detrital material in the 7–10,000 μm size range. A total of 92,472 IFCB samples, 3,068 UVP profiles, and 2,411 scans passed our quality control and were standardized to produce consistent instrument-specific size spectra averaged in 1x1° latitude/longitude, and by year and month. Our instrument-specific datasets span all major ocean basins, except for the IFCB which was exclusively deployed in northern latitudes, and cover decadal time periods (2013–2022 for IFCB, 2008–2021 for UVP, and 1996–2022 for scanners), allowing for a further assessment of the pelagic size spectrum in space and time. The datasets that constitute PSSdb’s first release are available at https://doi.org/10.5281/zenodo.10150020 (Dugenne et al., 2023).
Estimation of groundwater age distributions from hydrochemistry: comparison of two metamodelling algorithms in the Heretaunga Plains aquifer system, New Zealand
Authors: Tschritter Conny , Daughney Christopher J. , Karalliyadda Sapthala , Hemmings Brioch , Morgenstern Uwe , Moore Catherine
Published: December 2023

Abstract. Groundwater age or residence time is important for identifying flow and contaminant pathways through groundwater systems. Typically, groundwater age and age distributions are inferred via lumped parameter models based on measured age tracer concentrations. However, due to cost and time constraints, age tracers are usually only sampled at a small percentage of the wells in a catchment. This paper describes and compares two methods to increase the number of groundwater age data points and assist with validating age distributions inferred from lumped parameter models. Two machine learning techniques with different strengths were applied to develop two independent metamodels that each aim to establish relationships between the hydrochemical parameters and the modelled groundwater age distributions in one test catchment. Ensemble medians from the best model realisations per age distribution percentile were used for comparison with the results from traditional lumped parameter models based on age tracers. Results show that both metamodelling techniques predict age distributions from hydrochemistry with good correspondence to traditional lumped parameter model (LPM)-derived age distributions. Therefore, these techniques can be used to assist with the interpretation of lumped parameter models where age tracers have been sampled, and they can also be applied to predict groundwater age distributions for wells in a similar hydrogeological regime that have hydrochemistry data available but no age tracer data.
CHALLENGES AND RECOMMENDATIONS FOR 3D PLANT PHENOTYPING IN AGRICULTURE USING TERRESTRIAL LASERS SCANNERS
Authors: Medic T. , Bömer J. , Paulus S.
Published: December 2023

Abstract. Active sensing with LiDAR, and terrestrial laser scanners (TLS) in particular, are increasingly being used in plant phenotyping for assessing structural or 3D geometrical plant traits. Although these technologies provide the unprecedented possibility for remote, non-destructive, automatable, and efficient estimation of plant geometry, their deployment does not come without challenges. In this publication, we present a systematic overview of all challenges impacting TLS-based 3D plant phenotyping. We provide actionable recommendations for the end users of the technology, as well as the research questions and possible directions that can contribute the most to resolving these challenges. We specifically focus on TLSs, as we detected a lack in the existing literature dedicated to this sensing system providing a unique compromise between data quality and resolution vs. measurement efficiency and covered volume. The presented discussions are based on the literature review and our own experience in estimating the structural traits of sugar beet and wheat in plant phenotyping experiments.
FUSION OF DIRECT GEOREFERENCED AERIAL DRONE WITH TERRESTRIAL LASER SCANNER DATA THE CASE OF THE ROMAN BATHS OF AMATHUS, CYPRUS
Authors: Kafataris G. , Skarlatos D. , Vlachos M.
Published: December 2023

Abstract. The fusion of geomatic techniques with different accuracy and resolution has been used in recent years to applications of geometrical documentation for several archaeological sites. In this research article, the case of the Roman Baths of Amathus in Limassol, Cyprus was investigated.Aerial photogrammetry and Terrestrial Laser Scanning (TLS) techniques were used to produce the final product. The photogrammetric data were based on Post-Processed Kinematic (PPK) imagery while the TLS georeference was based on targets.The main research objective of this paper is to examine the reliability of PPK photogrammetric data without the use of Ground Control Points (GCPs) and how well they can be integrated with TLS data. Also, the two acquisition techniques were compared and indicated that 0.005 m Ground Sampling Distance (GSD) resolution aerial images and 0.0061/10 m resolution scans can be qualitatively fused.The research paper will present the entire methodology up to the generation of the final 3D photorealistic product.
SURFACE DEFORMATION MONITORING IN SHIYAN BASED ON MULTI-TEMPORAL INSAR TECHNOLOGY
Authors: Zhu Z. , Chen L. , Zhou L. , Zhou Y. , Zhu Z. , Li J. , Luo J. , Xiao S. , Gao Q.
Published: December 2023

Abstract. In recent years, InSAR technology has continuously developed and become a mainstream technology for monitoring wide-area surface deformation. In this study, Shiyan was selected as the work area, and Multi-temporal Synthetic Aperture Radar Interferometry (MT-InSAR) technology was used to monitor surface deformation over a long time series. The temporal and spatial distribution characteristics of the InSAR monitoring results were analyzed. The surveillance results showed that from January 2021 to March 2023, Shiyan experienced noticeable uneven settlement, with a deformation rate range of [−111.8mm/a, 20.9mm/a]. The maximum cumulative deformation variable reached −212.9mm, and more than 70 deformation zones were identified during the study period. The main causes of deformation were also analyzed. This study provides a reference for large-scale surface deformation monitoring and disaster management in Shiyan.
DEEP LEARNING-BASED MODEL FOR PADDY DISEASES CLASSIFICATION BY THERMAL INFRARED SENSOR: AN APPLICATION FOR PRECISION AGRICULTURE
Authors: Attallah O.
Published: December 2023

Abstract. The rice plant is an extremely valuable food crop worldwide. Paddy diseases not only reduce the cultivation of rice but most significantly, they contribute to environmental damage. The identification of paddy diseases before the onset of any visible signs has gained consideration with the development of deep learning (DL) and thermal infrared sensors. According to previous investigations, certain internal alterations in the paddy occur before signs of the infection become apparent. Such modifications couldn't be seen by exterior visible light sensors. On the other hand, thermal infrared sensors may be able to detect these variations, which will aid in predicting illness at earlier phases. However, there are few research articles regarding this topic. This study suggests a DL-based model for identifying paddy diseases from thermal images. The proposed DL-based model, in contrast to earlier approaches for classifying plant diseases, uses three convolutional neural networks (CNNs) with distinctive configurations. In addition, it makes use of discrete wavelet transform (DWT) to give a time-frequency illustration of the spatial deep features gathered via the three CNNs to develop the classification models instead of relying on solely spatial data like current models. Furthermore, it merges the spatial-time-frequency features of the three CNNs and uses a feature selection method based on Relief-F to choose the most beneficial attributes and reduce the dimensionality of the feature space. The outcomes of the proposed DL-based model show that spatial-time-frequency demonstrations are preferable to spatial data. The results additionally demonstrate that integrating high-level features from various CNNs can improve classification performance reaching an accuracy of 96.5% using a cubic support vector machine (SVM) classifier. Furthermore, the findings attained in this study outperform current DL-based models for plant disease classification.
IMPACT OF UAV AND SENTINEL-2A IMAGERY FUSION ON VEGETATION INDICES PERFORMANCE
Authors: Ayyappa Reddy A. , Shashi M.
Published: December 2023

Abstract. Image fusion techniques can improve the quality of remote sensing images by combining high spatial resolution images with low spectral resolution images. This enhancement of the images may impact the performance of various vegetation indices (VI’s). This study investigates the impact of image fusion on the quality of vegetation indices by fusing UAV (Unmanned Aerial Vehicle) bands with Sentinel-2A images using Principal Component Analysis (PCA) and Brovery Transform (BT) fusion techniques.The fused images were used to calculate the Normalized Difference Vegetation Index, Normalized Difference Red Edge, Green Red Vegetation Index, and Normalized Difference Water Index. To assess the performance of the fused images, several image quality assessment metrics were used, including Root Mean Square Error (RMSE), Entropy, etc...The results showed that image fusion techniques can improve the quality of images which is important to assess crop health. The PCA image fusion technique showed higher quality than the BT technique. The PCA fused images had lower RMSE, ERGAS, and Entropy Difference and higher UIQI, CC, and SSIM values than the original images. Moreover, the fused images produced higher VIs values than the Sentinel-2A images.Finally, scatter plots were created to compare the correlation between the VIs calculated from the original and fused images. The results showed a strong correlation between the VIs calculated from the Sentinel-2A and fused images, indicating that the fused images can accurately estimate vegetation health parameters. Overall, this study demonstrates the potential of image fusion techniques to improve the quality of VI’s for monitoring vegetation health.
WHICH SATELLITE IMAGE SHOULD BE USED FOR MAPPING
Authors: Jacobsen K.
Published: December 2023

Abstract. Today, topographical mapping based on satellite images is a standard method. With the large number of very high-resolution optical satellites, it only a question of the Ground Sampling Distance (GSD) and the map scale to be generated. But the classical large-format satellite images are expensive. With the today’s variety of the classical small satellites (601kg to 1200kg) to Nano-satellites (1.1kg to 10kg) of 3U (10cm × 10cm × 30cm), various options are available that influence the economic solutions. An overview of the accessible optical satellites is given, with some specific information on the mini-satellites that offer new economical solutions for topographic mapping. Significantly more optical satellites are currently in operation, but their images are used only for military purposes or they are restricted for national use due to lack of image storage and limited download possibilities.
COMPARISON AND EVALUATION OF MACHINE-LEARNING-BASED SPATIAL DOWNSCALING APPROACHES ON SATELLITE-DERIVED PRECIPITATION DATA
Authors: Zhu H. , Zhou Q. , Cui A.
Published: December 2023

Abstract. Precipitation estimation with high accuracy and resolution is crucial for hydrological and meteorological applications, particularly in ungauged river basins and regions with scarce water resources. Many machine learning (ML) algorithms have been employed in the downscaling of precipitation, however, it remains unclear which algorithm can outperform others. To address this issue, this study evaluates the performance of four ML based downscaling methods to generate high-resolution precipitation estimates at an annual scale. The satellite-derived precipitation data, environmental variables, such as, latitude, longitude, normalized difference vegetation index (NDVI), digital elevation model (DEM), and land surface temperature (LST), as well as the observations from rainfall gauges were used to constructed the regression models. The performance of the four ML algorithms including the Support Vector Regression (SVR), Random Forest (RF), Spatial Random Forest (SRF), and Extreme Gradient Boosting (XGBoost) algorithms was compared with three conventional methods: Multiple Linear Regression (MLR), geographically weighted regression (GWR) and Kriging interpolation model. Results showed that ML-based method generally outperformed traditional interpolation methods in precipitation downscaling, as they had higher accuracy and were better at reproducing the spatial distribution of rainfall. Out of ML approaches, XGBoost received the best performance, followed by SRF, RF and SVR, indicating its robustness of capturing nonlinear relationships. After the XGBoost, better performance of SRF than RF and SVR was found. This might be because the SRF just introduced the spatial autocorrelation into the RF models, which illustrated the importance of capturing spatial variations in ML algorithms. These findings regarding the comparison and assessment provided a novel downscaling method for generating high-resolution precipitation data, which could benefit regional flood forecasting, drought monitoring, and irrigation planning.
VEHICLE POSE AND SHAPE ESTIMATION IN UAV IMAGERY USING A CNN
Authors: El Amrani Abouelassad S. , Mehltretter M. , Rottensteiner F.
Published: December 2023

Abstract. Vehicle reconstruction from single aerial images is an important but challenging task. In this work, we introduce a new framework based on convolutional neural networks (CNN) that performs monocular detection, pose, shape and type estimation for vehicles in UAV imagery, taking advantage of a strong 3D object model. In the final training phase, all components of the model are trained end-to-end. We present a UAV-based dataset for the evaluation of our model and additionally evaluate it on an augmented version of the Hessingheim benchmark dataset. Our method presents encouraging pose and shape estimation results: Based on images of 3 cm GSD, it achieves median errors of up to 5 cm in position and 3° in orientation, and RMS errors of ±7 cm and ±24 cm in planimetry and height, respectively, for keypoints describing the car shape.
SEGMENTATION OF INDUSTRIAL BURNER FLAMES: A COMPARATIVE STUDY FROM TRADITIONAL IMAGE PROCESSING TO MACHINE AND DEEP LEARNING
Authors: Landgraf S. , Hillemann M. , Aberle M. , Jung V. , Ulrich M.
Published: December 2023

Abstract. In many industrial processes, such as power generation, chemical production, and waste management, accurately monitoring industrial burner flame characteristics is crucial for safe and efficient operation. A key step involves separating the flames from the background through binary segmentation. Decades of machine vision research have produced a wide range of possible solutions, from traditional image processing to traditional machine learning and modern deep learning methods. In this work, we present a comparative study of multiple segmentation approaches, namely Global Thresholding, Region Growing, Support Vector Machines, Random Forest, Multilayer Perceptron, U-Net, and DeepLabV3+, that are evaluated on a public benchmark dataset of industrial burner flames. We provide helpful insights and guidance for researchers and practitioners aiming to select an appropriate approach for the binary segmentation of industrial burner flames and beyond. For the highest accuracy, deep learning is the leading approach, while for fast and simple solutions, traditional image processing techniques remain a viable option.
Hurricane Irma: an unprecedented event over the last 3700 years? Geomorphological changes and sedimentological record in Codrington Lagoon, Barbuda
Authors: Biguenet Maude , Chaumillon Eric , Sabatier Pierre , Bastien Antoine , Geba Emeline , Arnaud Fabien , Coulombier Thibault , Feuillet Nathalie
Published: December 2023

Abstract. Low-lying coasts and small islands, such as in the Lesser Antilles, are particularly vulnerable to hurricane-induced marine floods. In September 2017, category 5 Hurricane Irma, with winds up to 360 km h−1, hit the northern Caribbean islands and caused the destruction of 95 % of the structures on Barbuda Island. We investigated the geomorphological impacts and the sedimentological record related to the storm surge of this hurricane in Barbuda's Codrington Lagoon. Following Hurricane Irma, two wide inlets developed across the Codrington sandy barrier. One of these inlets was enlarged and was still open 4 years later. From available data, it seems that this barrier remained continuous for the last 250 years before Hurricane Irma. At a longer timescale, very high-resolution seismic exploration combined with sediment cores sampled in Codrington Lagoon were used to investigate Irma deposits and environmental changes for the last 3700 years. The evolution from a low-energy small and shallow lagoon to the modern wide and high-energy lagoon recorded by the lagoon sediment fill was related to both long-term sea level rise and subsidence. The top of the lagoon fill consists of a thick and extensive sand sheet recording an abrupt increase in energy. Given its location at the top of the cores and its very recent age, supported by short-lived radionuclide data, together with large inlets opening and barrier erosion after Irma that imply a large sand supply to the lagoon, this sand sheet was attributed to Hurricane Irma. From our cores, it appears that this deposit is unique over more than 3700 years. Both the opening of a new inlet and the thick upper sand sheet support the exceptional character of Irma at the scale of centuries to millennia. Our study reinforces the idea that Hurricane Irma was exceptional in terms of intensity and may be associated with global warming.
A conceptual model for glacial lake bathymetric distribution
Authors: Zhang Taigang , Wang Weicai , An Baosheng
Published: December 2023

Abstract. The formation and expansion of glacial lakes worldwide due to global warming and glacier retreat have been well documented in the past few decades. Thousands of glacial lake outburst floods (GLOFs) originating from moraine-dammed and ice-dammed lakes were reported, causing devastating impacts on downstream lives and properties. Detailed glacial lake bathymetry surveys are essential for accurate GLOF simulation and risk assessment. However, these bathymetry surveys are still scarce as glacial lakes located in remote and high-altitude environments hamper a comprehensive investigation. We developed a conceptual model for glacial lake bathymetric distribution using a semi-automatic simulation procedure. The basic idea is that the statistical glacial lake volume–area curves conform to a power-law relationship indicating that the idealized geometric shape of the glacial lake basin should be hemispheres or cones. First, by reviewing the evolution of various types of glacial lakes, we identified nine standard conceptual models to describe the shapes of lake basins. Second, we defined a general conceptual model to depict the continuum transitions between different standard conceptual models for those specific glacial lakes that lie between two standard conceptual models. Third, we nested the optimal conceptual model in the actual glacial lake basin to construct the water depth contours and interpolate the glacial lake bathymetric distribution. We applied the conceptual model to simulate six typical glacial lakes in the Third Pole with in situ bathymetric surveys to verify the algorithm's applicability. The results show a high consistency in the point-to-point comparisons of the measured and simulated water depths, with a total volume difference of approximately ±10 %. The conceptual model has significant implications for understanding glacial lake evolution and modeling GLOFs in the future.
Measuring the impact of tax revenues on economic growth and investment in Sudan during the period (2006-2021)
Authors:   Assistant Professor, PhD in Economics, College of Business Administration, Albaha University, Saudi Arabia, Ealgzoli Ebtihag
Published: December 2023

This study aimed to identify the nature of the relationship between tax revenues ,economic growth and investment in Sudan during the period (2006-2021).Also building mathematical models through which tax revenues can be predicted. The descriptive analytical approach was used.The study relied on secondary data collected from the reports of the Central Bank of Sudan for different years. The study used the Autoregressive Distrbuted Lag Mode methodology (ARDL) to analyze tax revenue data to find out the nature of the relationship between the study variables for the long and short period of time for the Sudanese economist. The standard approach was also relied upon to estimate the relationship and nature between tax revenues, economic growth and investment in Sudan. The research showed the validity of some of the hypotheses of the study. The existence of a positive relationship between tax revenues and economic growth and the invalidity of the hypothesis for the existence of a positive relationship between tax revenues and investment, the study reached a number of results, the most important of which is that there is a positive relationship between tax revenues and economic growth and the inverse relationship between tax revenues and investment, due to the weak ability of Sudan to compete in Attracting foreign investments, The main reason for this is due to the weak investment climate in the country, and the weakness of attractive regulations, laws and policies, The most important recommendation of the study is the need to work to improve the tax base and reduce tax evasion because taxes have a positive impact on GDP.
Methodological approaches to assessing the effectiveness of government support measures for industry: comparative analysis of foreign experience
Authors:   Peoples' Friendship University  of Russia named after Patrice Lumumba, Ragulina Y.V.
Published: December 2023

This article provides a comparative analysis of methodological approaches to assessing the effectiveness of state support measures for industry. The authors explore various approaches used in the scientific literature and practical experience to measure the effectiveness of government programs and tools aimed at supporting the industrial sector. Special attention is paid to the analysis of the features and level of centralization of state support. The authors analyze both qualitative and quantitative assessment methods covering such aspects as production growth, innovation, competitiveness and resource efficiency. In addition, the authors draw attention to the advantages and limitations of each approach and offer recommendations for improving the process of evaluating the effectiveness of state support.
Problematic issues and current solutions in the field of municipal waste management
Authors:   NRU Moscow State University of Civil Engineering, Kirillova A.N.
Published: December 2023

The article discusses problematic issues of the current stage of development in the field of waste management related to the implementation of the national goal of sorting waste in the amount of 100% and reducing the volume of waste sent to landfills by 2 times. The materials proposed in the article, highlighting foreign experience, note investment approaches to the implementation of projects for MSW processing complexes, and pay attention to the stage of organizing separate waste collection. Based on new environmental initiatives and regional practical experience, it is advisable to adjust the FC «Integrated System for Management of Municipal Solid Waste» and regional waste management programs in the direction of digitalization and development of new design and technological solutions.
Model analysis of the efficacy of pseudorandom code sequences for seismic wave generation in vibroseis systems
Authors:   Moscow Institute of Physics  and Technology, Dolgoprudny, Alekseev D.A. ,   Schmidt Institute of Physics  of the Earth, Kudinov D.S. ,   Siberian Federal University, Krasnoyarsk, Potylitsyn V.S. ,   Siberian Federal University, Krasnoyarsk, Goncharov A.A. ,   Moscow Institute of Physics  and Technology, Dolgoprudny,   Scientific Center for the Study  of the Arctic, Salekhard
Published: December 2023

Using numerical simulation, we analyze noise cancellation capabilities of the vibroseis method employing pseudo-random (PSR) and frequency-modulated (FM) sweep signals, with primary focus on PSR efficiency compared to the conventional FM correlation-based approach. Both synthetic and field seismic records are used as noise to simulate interference with sweep-signal data. The results suggest that PSR sweeps along with deconvolution-based processing provide a significant (10-fold) improvement over the conventional FM sweeps in terms of signal-to-noise ratio.
Institutional aspects of spatial regulation in Russian federation
Authors:   Institute of Economics of the  Russian Academy of Sciences, Buchwald E.M. , Valentik O.N. ,   Institute of Economics of the  Russian Academy of Sciences
Published: December 2023

The article examines the directions of institutional transformations, related to the need to ensure the consistent implementation of key directions and tasks in the sphere of spatial regulation in the economy of Russia. One of such institutional components is the system of federal relations, which constitute the most significant "frame" of the country's economic space. At the same time, federal structures represent not a “frozen”, but a dynamically developing block of economic and legal relations, which are implemented in the form of a periodic appeal to the idea of federal reform.
The features of the Free Port of Vladivostok as a preferential regime-territory
Authors:   Federal State Budgetary Institution  of Science Institute of Economics  of the Russian Academy of Sciences, Vilenskiy A.V.
Published: December 2023

The article presents an analysis of the features of the Free Port of Vladivostok. It belongs to a small number of relatively successful Russian preferential regimes-territories and this alone attracts special attention. It not only makes a due contribution to the urgently needed “turn to the East” under Western sanctions through transport services for cooperation with friendly countries of the Pacific region, but also actually ensures the restoration and further socio-economic development of the Russian Far East, the growth of the level and quality of life of its population.
Fifty years of research in the Scandinavian Journal of Work, Environment & Health
Authors: Burdorf Alex , Rugulies Reiner
Published: December 2023

OBJECTIVE: The Scandinavian Journal of Work, Environment & Health was launched 50 years ago. In this paper we describe how research topics have changed over time.

METHODS: A complete list of all 2899 articles in the past 50 years was compiled. Each article was coded for type of exposure, type of health outcome, research design, first author, and country of correspondence address. Count of citations was based on the Scopus database.

RESULTS: Overall, the attention for chemical exposure in the first 30 years has shifted towards the psychosocial work environment, shift work, and physical work load. These shifts in exposure are mirrored by increased attention over time for mental disorders and musculoskeletal disorders. Cardiovascular disorders and cancer have been studied consistently over the past 50 years. Researchers from Scandinavian countries have been responsible for about 50% of the Journal’s content, while authorship has broadened to about 30 countries in recent years.

CONCLUSION: During the past 50 years, some research topics have consistently remained highly visible in the Journal, whereas other topics have gained or lost interest. In terms of authors’ contribution, the Journal has its roots in research from the Nordic countries, but has evolved over time as a truly international periodical with a well-recognized position in research on occupational health.
Amyotrophic Lateral Sclerosis: From Mechanisms to Current, Emerging, and Alternative Therapeutics
Authors:   University of Florida, College of Medicine, Gainesville, FL 32611, USA, Kioutchoukova Ivelina P
Published: December 2023

Amyotrophic Lateral Sclerosis (ALS) is a severe neurodegenerative disease affecting the motor neurons. Although the etiology remains unknown, mutations in superoxide dismutase 1 have been observed in patients with familial ALS
Long COVID-19
Authors:   Clinical Research Institute, University of Zulia, Postal Box 23, Maracaibo 4001- A, Venezuela., Bonilla Leonor Chacin
Published: December 2023

COVID-19 may lead to a perseverance of symptoms after recovery from the disease, a condition known as long COVID, characterized by continual cognitive, somatic and behavioral symptoms.
Factors Related to the Couple Relationship Satisfaction of Wives in Commuter Marriage: Differences Between Those With and Without Children in School Age
Authors:   Society for the Study of Family Policy, Kim Soyoung
Published: December 2023

This study investigated the factors related to the couple relationship satisfaction of 213 wives in commuter marriages and whether the factors differed for those with or without children in school age. Data were extracted from the 6th wave of the KLoWF. Analytic results revealed that, first, wives with school-aged children shared more time with husbands and were more satisfied with their husbands’ sharing of domestic labor and couple relationships. Second, wives with school-aged children had better couple relationships when they were in commuter marriage due to the husband’s workplace and were more satisfied with the husband’s sharing of domestic labor. Third, wives without school-aged children had higher couple relationship satisfaction when they lived apart due to the husband’s workplace, were more satisfied with the husband’s sharing of domestic labor, had traditional family values, when the husband’s income was higher than the wife, and when couples shared more time. Findings suggest that child education might have acted as a significant factor in the wives’ assessment of couple relationships, and that interventions that aims to improve couple relationships in commuter marriage should consider the family life cycle.
Using Biological Control as a Tool for Sustainability
Authors: Marchiori Carlos Henrique
Published: December 2023

The basic premise of biological control is to control agricultural pests and disease-transmitting insects using their natural enemies, which can be other beneficial insects, predators, parasitoids, and microorganisms such as fungi, viruses, and bacteria. Biological control has been growing exponentially in recent years, and the main reason for some countries is the demand for chemical-free food. Biological control of harmful insects is an environmentally correct technique and should be considered as a tool in Integrated Pest Management or organic farming systems. The objective of this practice is to control and even eliminate agricultural pests without leaving residues or causing damage to plants and the environment. Biological control is also essential when conventional methods do not work properly. This review aims to verify the biological control strategies of pests and diseases in agriculture, given the need for more efficient, sustainable, and profitable methods for their control. To achieve the main objective, we used the qualitative method based on research and analysis of theoretical books, theses banks, university dissertations, national and international scientific articles, scientific journals, documents, and digital platforms.