bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Evaluation of Heavy Metals Levels in Feeds, Milk and Urine of Camels at Giade Local Government Area, Bauchi State, Nigeria
Authors: Saleh Aisha , U.F Hassan, , H.M Adamu, , Musa Zakiyya Rilwan , Ibrahim Warji Muhammad , Daniel Solomon
Published: June 2024

The aim of this study was carried out comparative evaluation of the levels of heavy metals in feed, milk and urine of camels at Giade Local government area of Bauchi State, Nigeria. A total of 15 samples were collected during hand milking process of lactating female camel in a corral with bulk of camel feed from five different farms: Faguji farm, Goburawa farm, Isawa farm, Jahuri farm amd Uzum farm .The consumption of camel milk and urine is increasing due to its dietry and medicinal benefits.Concentration of nine heavy metals (As, Cd, Cu, Fe, Hg, Mn, Ni, Pb and Zn) were determined using Atomic Absorption Spectrophotometer. The measured concentration of heavy metals were used to compute human health risk. The mean concentration of heavy metals in camel milk between the two extreme values spread (mg/dm3) from: As 0.004 (Faguji) to 0.092 (Goburawa), Cd 0.022 (Isawa) to 0.045 (Uzum), Cu 0.019 (Uzum) to 0.117 (Jahuri), Fe 0.0278 (Isawa) to 0.0533 (Jahuri), Hg 0.002 (Uzum) to 0.140 (Jahuri) Mn 0.004 (Isawa), to 0.027(Uzum), Ni 0.004 (Jahuri), to 0.020 (Goburawa), Pb 0.007 (Goburawa) to 0.023 (Isawa) and Zn 0.015 (Isawa) to 0.108 (Goburawa). The result of the analysis revealed that from all the farms. As, Cu, Fe, Hg, Mn,Ni, Pb and Zn were within the desirable limit recommended by WHO (2007, 2012, 2017 and 2018) Whilst Hg ( Jahuri farm) are above the desirable limit recommended by WHO (2012 and 2018). For camel urine spread (mg/dm3) from: As 0.003 (Goburawa) to 0.055 (Uzum), Cd 0.002 (Jahuri,) to 0.008 (Faguji), Cu 0.002 (Jahuri) to 0.004 (Isawa), Fe 0.006 (Jahuri) to 0014 (Goburawa), Hg 0.002 (Isawa) to 0.008 (Uzum), Mn 0.003 (Isawa) to 0.040 (Uzum), Ni 0.001 (Faguji) to 0.005 (Jahuri), Pb 0.002 (Uzum) to 0.004 (Jahuri) and Zn 0.008 (Uzum) to 0.076 (Isawa). The result of the analysis revealed that all the element evaluated from urine in all farm were within desirable limit recommended by WHO (2014 and 2018). For camel feed Spread (mg/kg) from: As 0.019 (Uzum) to 0.220 ( Isawa), Cd, 0.054 (Jahuri) to 0.0200 (Uzum), Cu 0.515 (Jahuri) to 1.500 (Uzum), Fe 1.011 (Uzum) to 1.190 (Isawa), Hg 0.040 (Goburawa) to 0.081 (Isawa), Mn, 0.170 (Jahuri) to 1.030 (Isawa), Ni, 0.020 (Jahuri) to 0.060 (Goburawa), Pb, 0.023 (Faguji) to 0.080 (Isawa) and Zn 0.170 (Jahuri) to 3.66 (Isawa). The result of the analysis revealed that feed from all Farm, As, Cu, Fe, Hg, Mn, Pb Ni and Zn were within the desirable limit recommended by WHO (2007and 2012) except Cd in all farm were above the permissible limit recommended by WHO (1999, 2010 and 2012).The experimental values were subjected to one way analysis of variance and the result showed that there was no statistical significant difference at 95 % confidence level therefore it is recommended that camel milk, urine and feed sources should be closely monitored to reduced heavy metals concentrations levels.
Modern Hastaneler: İnovatif Malzemelerle Sağlık ve Sürdürülebilirlik
Authors: Çimen Arzu , Çimen Selçuk
Published: June 2024

Bu çalışma ile, sağlık kurumlarından olan hastanelerde kullanılan inovatif yapı malzemelerinin önemini, sağladığı faydaları ve uygulama alanları detaylı bir şekilde incelenmektedir. Gelişen teknolojiler ile birlikte, yapı alanında kullanılan malzemelerde de yeniliklere gidilmiş, bu yenilikler hastanelerin daha sürdürülebilir, enerji verimli ve içerisinde ki bireylere sağlıklı ortam sunması ile dikkat çekilmektedir. Geri dönüştürülmüş malzemeler, fotovoltaik paneller, antimikrobiyal zemin kaplamalar ile düşük VOC içeren boyalar gibi yenilikçi malzemeler, yapının enerji verimliliğini artırmakta ve içerisinde oluşan enfeksiyon oranının azaltmasında etkindir. Türkiye’de son yıllarda yaygınlaşan şehir hastaneleri projeleri ve çeşitli özel hastaneler ile ABD, İsveç, Avusturalya, Singapur ve Bileşik Arap Emirlikleri’ndeki hastanelerindeki uygulama örnekleri, kullanılan yapı malzemelerinin sağlık ve çevre üzerindeki olumlu etkilerini sergilemektedir. Gerçekleştirilen çalışma ile, hastanelerin daha sürdürülebilir ve sağlıklı bir çevre oluşturması için bilgiler sunulmaktadır.
AVALIAÇÃO DOS SINTOMAS NO PRÉ E PÓS-OPERATÓRIO NA ARTROPLASTIA TOTAL DE QUADRIL
Authors: Oliveira Henrique Cassol de , Kavalco Caroline , Colombo Gustavo Alves , Nandi Lucas Daniel , Bradacz Gustavo Massochin , Duarte Marco Antonio Castellani
Published: June 2024

A artroplastia de quadril (AQ) ou também chamada de prótese de quadril (PQ) é uma técnica cirúrgica relativamente recente na medicina com aplicabilidade em situações em que há algum comprometimento permanente da articulação do quadril com prejuízos à qualidade de vida do paciente. A dor crônica de forte intensidade é o principal sintoma, além da perda da mobilidade, fraqueza da musculatura do quadril e da coxa e dificuldade na execução de atividades da vida diárias. Pode ser causado por desordens do quadril como osteoartrose (OA), impacto femoroacetabular (IFA) e osteonecrose da cabeça femoral (ONCF). A execução do procedimento ocorre pela troca parcial ou total da articulação afetada por um implante sintético (prótese).
PRÁTICA ESPORTIVA COMO FERRAMENTA DE PROMOÇÃO DE QUALIDADE DE VIDA PARA MILITARES COM DEFICIÊNCIA: UMA REVISÃO NARRATIVA DA LITERATURA
Authors: Ferreira Samuel Nunes , Oliveira Rafael Miranda , Mendes Clayton de Oliveira , Cavalli Luis Fernando Sper , Gutierres Filho Paulo José Barbosa
Published: June 2024

O termo qualidade de vida (QV) tem sido utilizado como definição para o completo bem-estar de uma pessoa. Estudos demonstram que a QV pode ser comprometida pela aquisição de uma deficiência, mas que a prática esportiva pode reduzir os impactos negativos, oferecendo uma ampla gama de benefícios. Objetivo: Revisar a literatura científica sobre prática esportiva e QV sob a perspectiva da obtenção de seus benefícios junto a militares com deficiências. Método: Estudo de revisão narrativa da literatura. Resultados: Evidenciou-se que a prática esportiva promove uma série de benefícios de origem física, emocional e social nas pessoas com deficiências. Conclusão: A prática esportiva demonstra ser um método eficaz para a promoção da QV em militares com deficiências, apresentando-se o programa militar paralímpico como uma das formas de intervenção para a obtenção destes benefícios.
SÍNDROME DE GUILLAIN-BARRÉ E INFECÇÃO POR HEPATITE E: UMA REVISÃO DA LITERATURA
Authors: Almeida Artur Barros , Lima Gabriel Antonio Azevedo , Godoy Letícia Valentino de , Siqueira Marcella Aires , Souza Rennan Santos de
Published: June 2024

A síndrome de Guillain-Barré é uma doença periférica pós-infecciosa e autoimune induzida, caracterizada por uma fraqueza simétrica e bilateral rapidamente progressiva dos membros em sua forma clássica, uma polirradiculoneuropatia desmielinativa inflamatória aguda. Embora a forma clássica dessa síndrome esteja mais comumente relacionada ao vírus da hepatite E, quaisquer outros tipos da síndrome podem seguir-se à infecção por HEV. Cerca de dois terços dos pacientes têm uma infecção prévia pelo vírus da hepatite E 3 semanas antes do início da fraquez. Alguns agentes infecciosos comuns que causam Guillain-Barré são os seguintes: Campylobacter jejuni, citomegalovírus (CMV), vírus Epstein-Barr (EBV), Mycoplasma pneumoniae, Haemophilus influenzae e vírus da hepatite B.
Global scenarios of anthropogenic mercury emissions
Authors: Brocza Flora Maria , Rafaj Peter , Sander Robert , Wagner Fabian , Jones Jenny Marie
Published: June 2024

Abstract. Anthropogenic mercury (Hg) emissions to the atmosphere are a long-lived hazard to human and environmental health. The UN Minamata Convention on Mercury is seeking to lower anthropogenic mercury emissions through a mix of policies from banning certain Hg uses to reducing unintentional Hg release from different activities. In addition to independent Hg policy, strategies to mitigate greenhouse gases, particulate matter (PM) and SO2 may also lower Hg emissions as a co-benefit. This study uses the Greenhouse Gas–Air Pollution Interactions and Synergies (GAINS) model to examine the effect of different clean air and climate policies on future global Hg emissions. The baseline scenario assumes current trends for energy use and Hg emissions as well as current legislation for clean air, mercury and climate policy. In addition, we explore the impact of the Minamata Convention, the co-benefits of climate and stringent air pollution policies, and maximum feasible reduction measures for Hg. Hg emission projections until 2050 show noticeable reductions in combustion sectors for all scenarios due to a decrease in global fossil fuel and traditional biomass use, leading to emission reductions of 33 % at baseline and up to 90 % when combining stringent climate controls and the most efficient Hg controls. Cement and non-ferrous metal emissions increase in all scenarios with current air pollution policy but could be reduced by up to 72 % and 46 %, respectively, in 2050 with stringent Hg-specific measures. Other emissions (including waste) are a significant source of uncertainty in this study, and their projections range between a 22 % increase and a 54 % decrease in 2050, depending on both climate and clean air policy. The largest absolute reduction potential for Hg abatement but also the largest uncertainties regarding absolute emissions lie in small-scale and artisanal gold production, where abatement measures could eliminate annual Hg emissions in the range of 601–1371 t (95 % confidence interval), although the uncertainties in the estimate are so high that they might eclipse reduction efforts in all other sectors. In total, 90 % of Hg emissions are covered by provisions of the Minamata Convention. Overall, the findings emphasize the necessity to implement targeted Hg control policies in addition to stringent climate, PM and SO2 policies to achieve significant reductions in Hg emissions.
A series of climate oscillations around 8.2 ka revealed through multi-proxy speleothem records from North China
Authors: Duan Pengzhen , Li Hanying , Ma Zhibang , Zhao Jingyao , Dong Xiyu , Sinha Ashish , Hu Peng , Zhang Haiwei , Ning Youfeng , Zhu Guangyou , Cheng Hai
Published: June 2024

Abstract. The 8.2 ka event has been extensively investigated as a remarkable single event but rarely considered as a part of multi-centennial climatic evolution. Here, we present absolutely dated speleothem multi-proxy records spanning 9.0–7.9 ka from Beijing in North China, near the northern limit of the East Asian summer monsoon (EASM) and thus sensitive to climate change, to provide evidence of the intensified multi-decadal climatic oscillations since 8.52 ka. Three extreme excursions characterized by inter-decadal consecutive δ18O excursions exceeding ±1σ are identified from 8.52 ka in our speleothem record. The earlier two are characterized by enriched 18O at ∼8.50 and 8.20 ka, respectively, suggesting a prolonged arid event, which is supported by the positive trend in δ13C values, increased trace element ratios, and lower growth rate. Following the 8.2 ka event, an excessive rebound immediately emerges in our δ18O and trace element records but moderate in the δ13C, probably suggesting pluvial conditions and nonlinear response of the local ecosystem. Following two similar severe droughts at 8.50 and 8.20 ka, the different behavior of δ13C suggests the recovering degree of resilient ecosystem responding to different rebounded rainfall intensity. A comparison with other high-resolution records suggests that the two droughts–one pluvial pattern between 8.52 and 8.0 ka is of global significance instead of being a regional phenomenon, and is causally linked to the slowdown and acceleration of the Atlantic Meridional Overturning Circulation that was further dominated by the freshwater injections in the North Atlantic.
FLEXPART version 11: Improved accuracy, efficiency, and flexibility
Authors: Bakels Lucie , Tatsii Daria , Tipka Anne , Thompson Rona , Dütsch Marina , Blaschek Michael , Seibert Petra , Baier Katharina , Bucci Silvia , Cassiani Massimo , Eckhardt Sabine , Groot Zwaaftink Christine , Henne Stephan , Kaufmann Pirmin , Lechner Vincent , Maurer Christian , Mulder Marie D. , Pisso Ignacio , Plach Andreas , Subramanian Rakesh , Vojta Martin , Stohl Andreas
Published: June 2024

Abstract. Numerical methods and simulation codes are essential for the advancement of our understanding of complex atmospheric processes. As technology and computer hardware continue to evolve, the development of sophisticated code is vital for accurate and efficient simulations. In this paper, we present the recent advancements made in FLEXPART, a Lagrangian particle dispersion model, which has been used in a wide range of atmospheric transport studies over the past three decades, extending from tracing radionuclides from the Fukushima nuclear disaster, to inverse modelling of greenhouse gases, and to the study of atmospheric moisture cycles. This version of FLEXPART includes notable improvements in accuracy and computational efficiency. 1) By leveraging the native vertical coordinates of European Centre for Medium Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) instead of interpolating to terrain-following coordinates, we achieved an improvement in trajectory accuracy, leading to a ∼ 8−10 % reduction in conservation errors for semi-conserved quantities like potential vorticity. 2) The shape of aerosol particles is now accounted for in the gravitational settling and dry deposition calculation, increasing the simulation accuracy for non-spherical aerosol particles such as microplastic fibers. 3) Wet deposition has been improved by the introduction of a new below-cloud scheme, a new cloud identification scheme, and by improving the interpolation of precipitation. 4) Functionality from a separate version of FLEXPART, the FLEXPART-CTM model, is implemented, which includes linear chemical reactions. Additionally, the incorporation of Open Multi-Processing parallelisation makes the model better suited for handling large input data. Furthermore, we introduced novel methods for the input and output of particle properties and distributions. Users now have the option to run FLEXPART with more flexible particle input data, providing greater adaptability for specific research scenarios (e. g., effective backward simulations corresponding to satellite retrievals). Finally, a new user manual and restructuring of the source code into modules will serve as a basis for further development.
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
Authors: Arnold Nathan P.
Published: June 2024

Abstract. Earth system models (ESMs) typically represent surface heterogeneity on scales smaller than the atmospheric grid, while land–atmosphere coupling is based on grid mean values. Here we present a general approach allowing subgrid surface heterogeneity to influence the updraft thermodynamic properties in a multi-plume mass flux parameterization. The approach is demonstrated in single column experiments with an eddy diffusivity–mass flux (EDMF) boundary layer scheme. Instead of triggering based on grid mean surface values, updrafts are explicitly assigned to individual surface tiles with positive buoyancy flux. Joint distributions of near-surface vertical velocities and thermodynamic variables are defined over individual surface tiles, and updraft properties are drawn from the positive tails of the distributions. The approach allows updraft properties to covary with surface heterogeneity, and updrafts from different tiles maintain distinct properties to heights of several hundred meters. Mass flux contributions to subgrid variances are increased near the surface, but impacts on mean state variables are relatively small. We suggest that larger impacts might be obtained by adding a specialized plume to represent the effects of secondary circulations.
Deep Learning Based Semantic Segmentation for BIM Model Generation from RGB-D Sensors
Authors: Rached Ishraq , Hajji Rafika , Landes Tania , Haffadi Rashid
Published: June 2024

Abstract. RGB-D sensors offer a low-cost and promising solution to streamline the generation of BIM models. This paper introduces a framework designed to automate the creation of detailed and semantically rich BIM models from RGB-D data in indoor environments. The framework leverages advanced computer vision and deep learning techniques to overcome the challenges associated with traditional, labour-intensive BIM modeling methods. The results show that the proposed method is robust and accurate, compared to the high-quality statistic laser scanning TLS. Indeed, 58% of the distances measured between the calculated and the reference point cloud produced by TLS were under 5 cm, and 82% of distances were smaller than 7 cm. Furthermore, the framework achieves 100% accuracy in element extraction. Beyond its accuracy, the proposed framework significantly enhances efficiency in both data acquisition and processing. In contrast to the time-consuming process associated with TLS, our approach remarkably reduces the data collection and processing time by factor of height. This highlights the framework’s substantial improvements in accuracy and efficiency throughout the BIM generation workflows, making it a streamlined and time-effective solution.
Tree Instance Segmentation in Urban 3D Point Clouds Using a Coarse-to-Fine Algorithm Based on Semantic Segmentation
Authors: Burmeister Josafat-Mattias , Richter Rico , Reder Stefan , Mund Jan-Peter , Döllner Jürgen
Published: June 2024

Abstract. 3D point clouds acquired with terrestrial or mobile LiDAR sensors are increasingly used to map urban forests. The segmentation of separate tree instances, i.e., subsets of points representing individual trees, is a relevant step in automatically extracting tree inventory data from 3D point clouds. Various algorithms have been proposed for tree instance segmentation, offering different trade-offs between accuracy, runtime, and robustness against data incompleteness and noise. In this work, we propose a coarse-to-fine algorithm for segmenting tree instances in urban 3D point clouds from terrestrial or mobile LiDAR scanning that combines two existing techniques: (1) the computationally efficient marker-controlled Watershed algorithm and (2) a more accurate 3D region growing algorithm. Initially, the marker-controlled Watershed algorithm generates a coarse segmentation, which is further improved by a Voronoi segmentation-based error removal. Subsequently, the coarse segmentation is refined by the 3D region growing algorithm in areas with overlapping tree crowns and sufficient data quality. In both steps, our algorithm uses the results of a prior semantic segmentation to select suitable markers and seed points. We evaluated our coarse-to-fine algorithm in an ablation study using two mobile LiDAR datasets and one terrestrial LiDAR dataset from three German cities. Our results show that our algorithm outperforms the standard marker-controlled Watershed algorithm in terms of panoptic quality by 3.7, 25.5, and 29.6 percentage points, respectively, while being computationally more efficient than an approach purely based on 3D region growing.
Regional seismic risk assessment based on ground conditions in Uzbekistan
Authors: Ismailov Vakhitkhan Alikhanovich , Yodgorov Sharofiddin Ismatullayevich , Khusomiddinov Akhror Sabriddinovich , Yadigarov Eldor Makhmadiyorovich , Aktamov Bekzod Uktamovich , Avazov Shuhrat Bakhtiyorovich
Published: June 2024

Abstract. The assessment of losses from strong earthquakes and the reduction in earthquake consequences are of great importance in maintaining seismic safety. Special attention is given to evaluating the magnitude of economic losses caused by earthquakes, particularly the assessment of different levels of seismic risk, in order to protect the population and territories located in seismically active areas. To ensure sustainable development of countries, it is essential to estimate the economic losses that will occur in regions due to strong earthquakes and forecast them within the specified return periods at given probabilities. Measures can then be implemented to mitigate the consequences of earthquakes. For the basis of seismic risk assessment, maps of seismic intensity increment and an improved map of seismic hazard have been developed, taking into account the engineering-geological conditions of the territory of Uzbekistan and the seismic characteristics of soils. For seismic risk map development, databases were created based on GIS platforms, allowing us to systematize and evaluate the regional distribution of information on seismic hazards, the number of buildings and construction types, the coefficient of the seismic vulnerability of buildings, the cadastral value of buildings, etc.
A downward-counterfactual analysis of flash floods in Germany
Authors: Voit Paul , Heistermann Maik
Published: June 2024

Abstract. Counterfactuals are scenarios that describe alternative ways of how an event, in this case an extreme rainfall event, could have unfolded. In this study, we present the results of a counterfactual search for flash flood events in Germany. We used a radar-based precipitation dataset from Germany's national meteorological service (Deutscher Wetterdienst) to identify the 10 most extreme precipitation events in Germany from 2001 to 2022 and then assumed that any of these top 10 events could have happened anywhere in Germany. In other words, the events were shifted around all over Germany. For all resulting positions of the precipitation fields, we simulated the corresponding peak discharge for any affected catchment smaller than 750 km2. From all the realizations of this simulation experiment, the maximum peak discharge was identified for each catchment. In a case study, we first focused on the devastating flood event in July 2021 in western Germany. We found that a moderate shifting of the event in space could change the event peak flow at the Altenahr gauge by a factor of 2. Compared to the peak flow of 1004 m3 s−1 caused by the event in its original position, the worst-case counterfactual of that event led to a peak flow of 1311 m3 s−1. Shifting another event that had occurred just 1 month earlier in eastern Germany over the Ahr River valley even effectuated a simulated peak flow of 1651 m3 s−1. For all analysed subbasins in Germany, we found that, on average, the highest counterfactual peak exceeded the maximum original peak (between 2001 and 2022) by a factor of 5.3. For 98 % of the basins, the factor was higher than 2. We discuss various limitations of our analysis, which are important to be aware of, namely, the quantification and selection of candidate rainfall events, the hydrological model, and the design of the counterfactual search experiment. Still, we think that these results might help to expand the view of what could happen in the case that certain extreme events occurred elsewhere and thereby reduce the element of surprise in disaster risk management.
Machine-learning-based estimate of the wind speed over complex terrain using the long short-term memory (LSTM) recurrent neural network
Authors: Leme Beu Cássia Maria , Landulfo Eduardo
Published: June 2024

Abstract. Accurate estimation of the wind speed profile is crucial for a range of activities such as wind energy and aviation. The power law and the logarithmic-based profiles have been widely used as universal formulas to extrapolate the wind speed profile. However, these traditional methods have limitations in capturing the complexity of the wind flow, mainly over complex terrain. In recent years, the machine-learning techniques have emerged as a promising tool for estimating the wind speed profiles. In this study, we used the long short-term memory (LSTM) recurrent neural network and observational lidar datasets from three different sites over complex terrain to estimate the wind profile up to 230 m. Our results showed that the LSTM outperformed the power law as the distance from the surface increased. The coefficient of determination (R2) was greater than 90 % up to 100 m for input variables up to a 40 m height only. However, the performance of the model improved when the 60 m wind speed was added to the input dataset. Furthermore, we found that the LSTM model trained on one site with 40 and 60 m observational data and when applied to other sites also outperformed the power law. Our results show that the machine-learning techniques, particularly LSTM, are a promising tool for accurately estimating the wind speed profiles over complex terrain, even for short observational campaigns.
ENVIRONMENTALLY INDUCED DISEASES CAUSED BY CHANGES IN METEOROLOGICAL FACTORS: DIAGNOSIS AND WAYS TO COUNTERACT
Authors:   National Medical Research Center for Rehabilitation and Balneology, Ministry of Health of the Russian Federation, YAKOVLEV M.YU. ,   Sechenov First Moscow State Medical University (Sechenov University), Ministry of Health of the Russian Federation, RAKHMANIN YU.A. ,   Center for Strategic Planning and Management of Biomedical Health Risks, Federal Biomedical Agency, BOBROVNITSKII I.P. ,   Sechenov First Moscow State Medical University (Sechenov University), Ministry of Health of the Russian Federation,   National Medical Research Center for High Medical Technologies-Vishnevsky Central Military Clinical Hospital, Ministry of Defense of the Russian Federation,   Research Institute of General Pathology and Pathophysiology
Published: June 2024

Climatic and geographic factors characterizing local conditions, as well as the ecological state of the external environment, have a direct effect on human health, morbidity, and life expectancy. The paper considers the basic concepts of medical ecology, a pathogenetic role of environmental atmospheric pollution in the development of environmentally induced and environmentally dependent diseases associated with exposure to meteorological factors. In addition to the major hygienic risk factors affecting the public health (a level of air, water, and soil pollution), the levels of acoustic and electromagnetic background, the type of human nutrition, architectural and planning conditions of human life are of significant importance. Global climate warming causes numerous environmental changes, primarily an increase in surface air temperature, which in turn entails global changes in weather conditions that lead to various weather anomalies. Human health is directly dependent on environmental conditions and a degree of adaptation to them. The paper highlights the issues of diagnosing environmentally induced diseases and measures to counteract their spread. Based on the system diagnosis using physiological indicators of human health and the integration of the adaptation and nosological approaches, a hardware-software complex has been developed and introduced into medical practice. Corrective technologies of regenerative medicine that are used for ecologically dependent pathologies are described. Their application in the process of the complex sanatorium and resort treatment is most effective.
PARAMETERIZING HEAT AND MOISTURE EXCHANGE IN A REGIONAL THERMODYNAMIC MODEL OF SEA ICE
Authors:   Marine Hydrophysical Institute, Russian Academy of Sciences, ZAV'YALOV D.D. , SOLOMAKHA T.A. ,   Marine Hydrophysical Institute, Russian Academy of Sciences
Published: June 2024

The prevailing types of the atmospheric stratification over the snow-ice cover at the top of Taganrog Bay for eleven winter seasons of 2007/2008-2017/2018 have been determined using the numerical experiments on reproducing the seasonal variations in the sea ice thickness. Series of calculations both with the constant transfer coefficients and with the coefficients obtained taking into account the surface stratification of the atmosphere have been carried out. The model results of both series have been compared with each other and with in situ measurements.
ASSESSMENT OF ATMOSPHERIC OZONE FROM REANALYSIS AND GROUND-BASED MEASUREMENTS IN THE BAIKAL REGION
Authors:   Institute of Geography, Russian Academy of Sciences, SMETANINA A. M. ,   Izrael Institute of Global Climate and Ecology, GROMOV S. A. ,   Institute of Geography, Russian Academy of Sciences,   Izrael Institute of Global Climate and Ecology, OBOLKIN V. A. ,   Limnological Institute, Siberian Branch, Russian Academy of Sciences, KHODZHER T. V. ,   Limnological Institute, Siberian Branch, Russian Academy of Sciences, KHURIGANOVA O. I. ,   Limnological Institute, Siberian Branch, Russian Academy of Sciences
Published: June 2024

The machine learning model used to predict ozone concentrations at the Listvyanka monitoring station in the Baikal region is described. The model was trained and verified using automatic ground-based gas analyzer ozone measurements. Random forest and boosting machine learning models were used. According to the ERA5 reanalysis, the mean absolute error of ozone values exceeds 16 ppb, and the mean percentage error is 80%. The respective errors in the ozone values calculated using machine learning models are 6.7 ppb and 29%. The results of forecasting are the most sensitive to the season, air temperature, and vegetation. The ozone values for 2017-2022 were simulated and analyzed using the trained model and reanalysis data.
PRELIMINARY DATA PROCESSING OF THE MSU-GS/VE DEVICE ABOARD THE ARKTIKA-M NO. 1 HIGHLY ELLIPTICAL SATELLITE USING ARTIFICIAL INTELLIGENCE METHODS
Authors:   Planeta State Research Center on Space Hydrometeorology, ASMUS V. V. , BLOSHCHINSKIY V. D. ,   Far East Center, Planeta State Research Center on Space Hydrometeorology, KRAMAREVA L. S. ,   Far East Center, Planeta State Research Center on Space Hydrometeorology, KUCHMA M. O. ,   Far East Center, Planeta State Research Center on Space Hydrometeorology, FILEI A. A. ,   Far East Center, Planeta State Research Center on Space Hydrometeorology
Published: June 2024

The paper presents the research work aimed at improving the quality characteristics of information products based on the MSU-GS/VE radiometer aboard the Arktika-M No. 1 satellite, as well as at obtaining data preprocessing products. All described methods are based on using machine learning algorithms, namely, neural networks of various architectures. The results of developing a technology for minimizing the interference that occurs in the channels of the satellite device are provided. The work on detecting cloud formations based on processing the channel data in the visible and infrared ranges is presented. It is shown that the use of neural networks makes it possible to implement automatic algorithms for obtaining thematic products that take into account various factors and have an accuracy that is commensurate with statistical and physical approaches and reduces the time of satellite data processing.
ARTIFICIAL INTELLIGENCE AND ITS APPLICATION IN NUMERICAL WEATHER PREDICTION
Authors:   Arctic and Antarctic Research Institute, SOLDATENKO S. A. ,   Main Center for Information Technologies and Meteorological Services for Aviation
Published: June 2024

Artificial intelligence is one of the most popular, frequently discussed, and, meanwhile, ambiguous and controversial metaphorical concepts, which defines a scientific direction in computer science that studies the techniques for gaining knowledge, their computer representation, transformation, and application. Presently, it is intensively penetrating into many areas of human activities, including hydrometeorological ones. The concept of artificial intelligence, the history of its origin, and its methods and technologies are considered. The author analyzes the studies related to the use of artificial intelligence in short- and medium-range weather forecasting, including the collection and quality control of meteorological information, assimilation of data in order to generate initial conditions for numerical weather prediction models, development of forecast models and parameterization schemes for physical processes, postprocessing and physical-statistical interpretation of the output data of numerical weather prediction models.
APPLICATION OF DEEP NEURAL NETWORKS FOR DETECTING PROBABLE AREAS OF PRECIPITATION AND THUNDERSTORMS
Authors:   Siberian Center, Planeta State Research Center on Space Hydrometeorology, CHURSIN V. V. , KOSTORNAYA A. A. ,   Siberian Center, Planeta State Research Center on Space Hydrometeorology
Published: June 2024

A method for the probabilistic identification of the precipitation and thunderstorm zones using artificial neural networks (ANNs), in particular, deep neural networks is described. The vertical profiles of temperature and humidity retrieved from satellite data are used as initial data. The ANN calculations have been validated using the ground-based observations in the Siberian region.
A METHOD FOR OBJECT-ORIENTED DETECTION OF DEEP CONVECTION FROM GEOSTATIONARY SATELLITE IMAGERY USING MACHINE LEARNING
Authors:   Hydrometeorological Research Center of the Russian Federation, SHISHOV A. E.
Published: June 2024

Due to high spatial and temporal resolution, geostationary meteorological satellite imagery is a valuable source of information on the development of deep convective clouds and related severe weather events. Some methods for automatic deep convection detection from satellite data provide a satisfactory probability of detection for independent datasets, but are characterized by a high false alarm rate. The paper gives a description of an algorithm for automatic detection of deep convective clouds with satellite imagery using gradient boosting, logistic regression, and artificial neural network models. The results of validation of the proposed method using dependent and independent data of ground-based observations for the period 2013-2020 are presented. A low false alarm rate and high probability of detection suggest that the algorithm can be used in the operational mode.
A Revisit to Estimating Phillips Curve and NAIRU in Pakistan
Authors: Tauseef Tahira , Chaudhary Amtul R. , Tauheed Tahira
Published: June 2024

This paper investigates the conventional Philips curve within the unique economic context of Pakistan, traditionally employed to analyze the intricate interplay between inflation and unemployment. Utilizing the Autoregressive Distributed Lag (ARDL) methodology, the research integrates annual data spanning from 1991 to 2022 on core inflation, unemployment, and supply shocks to estimate the Philips curve. Two distinct specifications of the Philips curve—the new Keynesian and the Triangle model—are employed to capture nuanced relationships. Moreover, the study establishes a constant Non-Accelerating Inflation Rate of Unemployment (NAIRU) derived from the estimated Philips curve, with precision assessed using Delta and Fieller methods. The empirical results robustly affirm the presence of a long-term trade-off between inflation and unemployment, offering fresh insights into Pakistan's economic dynamics. The ARDL error correction model reveals that short-term inflation dynamics are primarily influenced by inertia. At the same time, long-term trends are dictated by unemployment and the import price index, with the industrial productivity index deemed insignificant. The calculated sacrifice ratios of 0.57 and 0.51, alongside NAIRU estimates of 5.7 and 5.0 for the New Keynesian and Triangular models, respectively, signal a need for caution in implementing anti-inflationary policies. Addressing the significant impact of demand gaps and supply shocks on inflation calls for policies to reduce supply-demand disparities. Maintaining an optimal equilibrium of inflation and unemployment (NAIRU) necessitates a combination of stabilization and adverse supply shock control policies. These findings underscore the stabilizing role of commercial policy and advocate for reforms to bolster Pakistan's industrial sector.
The Impact of Remittances and Official Development Assistance on Human Capital: An Evidence from Pakistan
Authors: Khan Muhammad Wajid , Khan Afaq Ali , Afreen Khawar
Published: June 2024

Emerging nations have taken benefits from foreign capital inflows for increasing the amount of human capital, ultimately contributing to both economic development and growth. This research work evaluates the influence of foreign inflow of money and assistance from foreign countries on the lives of people in Pakistan. The study utilizes the post-facto design has and analyzed a sample of 32 years of secondary data ranging from 1990 to 2021, extracted from different data banks. The human capital is taken as a response variable. On the other hand, explanatory variables include official development assistance and remittance. Urban population and financial development are taken as control variables. The outcomes provide evidence that remittances, financial development and urban population provides a favorable and significant influence on the enhancement of human capital, while official development assistance provides no effect for the development of human capital in Pakistan. These findings establish a broader picture of this relationship and are in line with the related theories of economics. Furthermore, efforts should be made to provide policymakers with an understanding of critical factors which link foreign financial support, money transfers, growth in the economy, and improved human development.
CENSUS OF POPULACION – THE IMPORTANT TOOLS OF SUSTAINABLE DEVELOPMENT MONITORING
Authors:   Akaki Tsereteli State University, Virsaladze Naira , Kipiani Mavlina
Published: June 2024

Among the global problems in the world, one of the important topics is the demographic situation. Basic and accurate parameters of the demographic situation are collected during the census, that is why the general population census is an event of national importance. Like the rest of the world, population censuses in Georgia have a centuries-old history. The frequency and main characteristics of the censuses were conducted at different times with different purposes and interests. It is based on the methodology developed by the United Nations and is conducted in accordance with unified, standard and normative indicators. The introduction of a whole series of innovations is designed for sustainable development in accordance with the task of the 2030 agenda. The use of census data shows us that the role and importance of censuses in the modern global world has grown even more. The "Recommendations of the Conference of European Statisticians for the 2020 Round of the Population and Housing Census", which was prepared by the United Nations Economic Commission for Europe (UNECE) for the 2015 round, is particularly noteworthy. The recommendations addressed such important aspects of the population census as data privacy and security, legislation, definitions of terms, phases of the census, publication and dissemination of results, quality assurance and quality management, and technologies used in the census process. Along with the given recommendations, the document focuses on the list of data that countries should receive in the 2020 round of population and housing census, namely: population, its geographical, demographic and economic characteristics; Agriculture, education, migration, ethno-cultural characteristics, disabilities, household and family characteristics and housing characteristics. The census of 2024 will provide us with important and versatile information, which is necessary to assess the demographic situation in the country, to clearly see the existing problems and challenges. The new population census methodology developed by the United Nations and, accordingly, the United Nations Population Fund (UNFDA) includes a number of innovations in the census questionnaire, which deals with immigration status, disabilities, type of marriage and marriage registration. The introduction of innovations is designed for sustainable development in accordance with the task of the 2030 agenda.
RESEARCH AND DEVELOPMENT OF TECHNOLOGY FOR THE PRODUCTION OF FUSED ZIRCONIUM DIOXIDE
Authors: Соколов В.А. , Киров С.С. , Гаспарян М.Д.
Published: June 2024

Проведен анализ современного состояния производства плавленого диоксида циркония различных типов (моноклинного и стабилизированного). Определена практическая возможность получения стабилизированного диоксида циркония из бадделеитового концентрата в опытной электродуговой печи ЭДП-600. Полученные данные технологических и электрических параметров плавки рекомендованы для использования при производстве плавленого диоксида циркония из синтетического диоксида циркония и бадделеитового концентрата на промышленных электродуговых печах ДСП-1,5 и ОКБ-2126 и др. При карботермическом восстановлении цирконового концентрата в электродуговой печи ЭДП-450 достигнуто снижение кремнезема в 3 раза до содержания 10,9% SiO2 в плавленом продукте. Для реализации завершающего этапа по карботермической технологии получения плавленого диоксида циркония с содержанием не менее 95% ZrO2 рекомендовано создать пилотную электродуговую установку на базе электродуговой печи ДС-05.

Analysis of the current state of fused zirconia production of various types (monoclinic and stabilized). Practical defined possibility of obtaining stabilized zirconia from baddeleite concentrate in experimental electric arc furnace EDP-600. Data obtained process and electrical parameters of smelting are recommended for use in the production of fused zirconia production from synthetic zirconia and baddeleite concentrate on industrial electric arc furnaces DSP-1,5, OKB-2126, etc. At carbothermic reduction of zirconium concentrate in electric arc furnace EDP-450 reduction of silica by 3 times to a content of 10,9% SiO2 in melted product. To implement the final stage for carbothermic technology for obtaining fused zirconia production with a content of at least 95% ZrO2 it is recommended to create a pilot electric arc installation based on the DS-05 electric arc furnace.
On the development of Russian tax treaty case law
Authors: Kilinkarova E. V.
Published: June 2024

The research subject. This study focuses on recent developments (2021-2023) in Russian tax treaty case law.

The purpose of the research. The objective of this research is to analyze the key trends and developments in tax treaty case law in Russia for the last three years.

Methodology. The research is based on the analysis of cases where the commercial courts

of circuits and the Supreme court of Russian Federation in 2021-2023 applied Russian double tax treaties (total number – 38 cases).

Main results of the research. The analysis of the tax treaty case law allowed to make a general overview of the relevant judicial practice and identify three strategic areas of law enforcement – development of the beneficial owner concept, issues if qualification of income for the purposes of the application of tax treaties and disputes between withholding agents and taxpayers.

Conclusion. An analysis of judicial practice allows us to conclude that Russia is quite successful in implementing the task of deoffshorization of the Russian economy – this is noticeable both in the geography of the applied agreements and in the content of the issues under consideration. The tax treaty case law is heterogeneous – it includes both simple issues (for example, with obvious mistakes of a withholding agent) and issues on which judicial practice as a whole has already been established (for example, in relation to the beneficial owner concept), as well as quite extraordinary and sometimes difficult questions. It should be admitted that fundamentally new issues of application of double taxation agreements are sometimes not easy for the courts. An analysis of tax treaty case law puts forward the question of the role and risks of a withholding agent – currently the practice does not seem sufficiently balanced in terms of ensuring a balance of private and public interests. For application of double tax treaties procedural issues remain of great importance. Analysis of judicial practice shows that they are crucial both for the withholding agent and the taxpayer.
Digital death: the inheritance of digital information
Authors: Kanakova A. E.
Published: June 2024

The subject of the research is the right to inherit digital information.

The purpose of the research is to substantiate the need to conduct legal regulation of the consequences of the death of a person in the context of inheritance of digital data.

The research is based on the analysis of sources of Russian and foreign law, as well as practical materials of Russian and foreign law in the sphere of rights and freedoms. The methodological basis of the research was formed by general scientific methods of cognition (analysis, synthesis, modelling) and private-scientific methods of cognition (comparativelegal, formal-logical).

Main results. There are some approaches to the correlation of rights and freedoms realized in real and virtual space. The first approach considers digital or virtual rights and freedoms as a new legal phenomenon that requires separate legal regulation. The second approach assesses digital or virtual rights and freedoms as a manifestation of the features of those rights and freedoms that already exist outside the digital world. Although the first approach is more popular, the second approach is more correct because digital rights and freedoms either add a new territory of rights and freedoms or affect the mechanism of realization, but do not create a fundamentally new legal phenomenon.

Because the death of a person does not automatically have consequences for the digital space, it is necessary to create a legal mechanism for recognising digital death, which will allow an individual who died in reality to become so for the virtual space. For the realisation of these powers it is not necessary to create completely new legal categories, it is enough to take into account the peculiarities of the realisation of offline rights and freedoms in virtual space.

Conclusions. It seems more correct to move away from the concept of separating offline and online rights and to focus on the point-by-point introduction of digital rights and freedoms into existing legislation. Such an approach will not only ensure faster regulation of digital rights and freedoms, but will also make it possible to base legal regulation on provisions that have already had experience of implementation, and therefore identify possible gaps, problems, etc.
ОБ ОДНОМ ТИПЕ КОМПАКТНОСТИ РАВНОМЕРНЫХ ПРОСТРАНСТВ
Authors: Канетов Бекболот , Сактанов Улукбек
Published: June 2024

В последнее время интенсивно развивается теория компактных типов равномерных пространств. К типам компактности равномерных пространств относятся предкомпактные, -предкомпактные, - ограниченные, равномерно Менгера, равномерно Гуревича, компактные пространства. В настоящей статье исследуются некоторые свойства равномерно Гуревича пространства (или равномерно - пространства).
ОТРИЦАТЕЛЬНОЕ ВЛИЯНИЕ КОФЕ НА ОРГАНИЗМ СТУДЕНТОВ МИРА
Authors: Тажибаева Феруза , Кулмаматова Урумкан , Вахобов Хусанбой
Published: June 2024

Употребление кофе является не только актуальным в настоящее время, но и с давних времён, среди групп населения включая студентов. Многие студенты начинают утро с чашечки крепкого, ароматного кофе, чтобы повысить умственную и физическую работоспособность в целях успеваемости на учёбе, подготовке самостоятельных работ и для активного проведения свободной времени. Ощутимый эффект от чашечки кофе в среднем длится 5-6 часов, тем временем привыкание и злоупотребление кофеина вызывает повторные его употребление, которое может привести уже к негативным состояниям