bluuebunny/crossref_metadata_2025 huggingface dataset:
Short-Term Photovoltaic Power Forecasting Based on a Feature Rise-Dimensional Two-Layer Ensemble Learning Model
Authors: Wang Hui , Yan Su , Ju Danyang , Ma Nan , Fang Jun , Wang Song , Li Haijun , Zhang Tianyu , Xie Yipeng , Wang Jun
Published: November 2023

Photovoltaic (PV) power generation has brought about enormous economic and environmental benefits, promoting sustainable development. However, due to the intermittency and volatility of PV power, the high penetration rate of PV power generation may pose challenges to the planning and operation of power systems. Accurate PV power forecasting is crucial for the safe and stable operation of the power grid. This paper proposes a short-term PV power forecasting method using K-means clustering, ensemble learning (EL), a feature rise-dimensional (FRD) approach, and quantile regression (QR) to improve the accuracy of deterministic and probabilistic forecasting of PV power. The K-means clustering algorithm was used to construct weather categories. The EL method was used to construct a two-layer ensemble learning (TLEL) model based on the eXtreme gradient boosting (XGBoost), random forest (RF), CatBoost, and long short-term memory (LSTM) models. The FRD approach was used to optimize the TLEL model, construct the FRD-XGBoost-LSTM (R-XGBL), FRD-RF-LSTM (R-RFL), and FRD-CatBoost-LSTM (R-CatBL) models, and combine them with the results of the TLEL model using the reciprocal error method, in order to obtain the deterministic forecasting results of the FRD-TLEL model. The QR was used to obtain probability forecasting results with different confidence intervals. The experiments were conducted with data at a time level of 15 min from the Desert Knowledge Australia Solar Center (DKASC) to forecast the PV power of a certain day. Compared to other models, the proposed FRD-TLEL model has the lowest root mean square error (RMSE) and mean absolute percentage error (MAPE) in different seasons and weather types. In probability interval forecasting, the 95%, 75%, and 50% confidence intervals all have good forecasting intervals. The results indicate that the proposed PV power forecasting method exhibits a superior performance in forecasting accuracy compared to other methods.
Multi-Objective Optimization for High-Performance Building Facade Design: A Systematic Literature Review
Authors: Shan Rudai , Junghans Lars
Published: November 2023

Building facade design plays an essential role in enhancing energy efficiency and reducing environmental impact in high-performance building design. Balancing the conflicts among various building facade design variables to satisfy different optimization objectives constitutes a highly complex optimization problem. The rapidly increasing number of studies demonstrates a significant interest in implementing multi-objective optimization methods to tackle building facade optimization problems. This study conducts a systematic review of optimization methods for building facade optimization (BFO). The optimization objectives and design variables are categorized based on their characteristics. The efficiency and effectiveness of optimization algorithms in addressing BFO problems are compared. Building optimization techniques and tools are showcased, along with their functions and limitations. Key findings highlight the robust feasibility and effectiveness of optimization algorithms, methods, and techniques in resolving a diverse range of BFO challenges. The limitations, challenges, and future potential of these methods are summarized and proposed.
Rapid Photocatalytic Activity of Crystalline CeO2-CuO-Cu(OH)2 Ternary Nanocomposite
Authors: Murugadoss Govindhasamy , Kannappan Thiruppathi , Rajabathar Jothi Ramalingam , Manavalan Rajesh Kumar , Salammal Shyju Thankaraj , Venkatesh Nachimuthu
Published: November 2023

The development of a heterojunction nanocomposite leads to improved optoelectronic properties. Herein, ceria (CeO2), copper oxide (CuO), and ceria–copper–copper hydroxide (CeO2-CuO-Cu(OH)2) nanocomposites were prepared via a facile chemical method and their structural, morphological, and optical properties were studied using various characteristic techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDAX), transmission electron microscopy (TEM), ultra-violet visible light absorption (UV-visible), photoluminescence, and thermogravimetry differential thermal analysis (TG-DTA). In the integration of CeO2 and CuO with Cu(OH)2, the band gap is modified to 2.64 eV; this reduced band gap can improve the photocatalytic efficiency of the nanocomposite. The CeO2 can increase light absorption in the nanocomposite, while CuO acts as an electron trap in the composite and this leads to a good enhancement of the optical properties of the CeO2-CuO-Cu(OH)2 nanocomposite. In addition, the heterojunction combination at the interfaces of the CeO2-CuO-Cu(OH)2 nanocomposite facilitates the photo-generated charge separation in the composite, which increases the charge participation in the catalyzed conversion reactions of the prepared composite. The highest photocatalytic degradation efficiencies of 96.4% and 92.7% were achieved for fast green (FG) and bromophenol blue (BP), respectively, using the CeO2-CuO-Cu(OH)2 nanocomposite.
Leveraging Classical Statistical Methods for Sustainable Maintenance in Automotive Assembly Equipment
Authors: Bucay-Valdiviezo Juan , Escudero-Villa Pedro , Paredes-Fierro Jenny , Ayala-Chauvin Manuel
Published: November 2023

Predictive maintenance management plays a crucial role in ensuring the reliable operation of equipment in industry. While continuous monitoring technology is available today, equipment without sensors limits continuous equipment state data recording. Predictive maintenance has been effectively carried out using artificial intelligence algorithms for datasets with sufficient data. However, replicating these results with limited data is challenging. This work proposes the use of time series models to implement predictive maintenance in the equipment of an automotive assembly company with few records available. For this purpose, three models are explored—Holt–Winters Exponential Smoothing (HWES), Autoregressive Integrated Moving Average (ARIMA), and Seasonal Autoregressive Integrated Moving Average (SARIMA)—to determine the most accurate forecasting of future equipment downtime and advocate the use of SAP PM for effective maintenance process management. The data were obtained from five equipment families from January 2020 to December 2022, representing 36 registers for each piece of equipment. After data fitting and forecasting, the results indicate that the SARIMA model best fits seasonal characteristics, and the forecasting offers valuable information to help in decision-making to avoid equipment downtime, despite having the highest error. The results were less favorable when handling datasets with random components, requiring model recalibration for short-term forecasting.
Provenance Identification of Leaves and Nuts of Bertholletia excelsa Bonpl by Near-Infrared Spectroscopy and Color Parameters for Sustainable Extraction
Authors: Nisgoski Silvana , dos Santos Joielan Xipaia , Vieira Helena Cristina , Naide Tawani Lorena , Stange Rafaela , Silva Washington Duarte Silva da , Souza Deivison Venicio , Gama Natally Celestino , Hamada Márcia Orie de Souza
Published: November 2023

The Brazil nut tree is considered symbolic of the Brazilian Amazon in function of its great importance, being one of the most significant extractivist products and a subsistence practice of the Indigenous people in many municipalities in Pará state. One of the main problems in different communities is related to the marketing process since it is not possible to distinguish the origin of the nuts and this causes inconvenience. The study evaluated the potential of VIS/NIR spectroscopy to identify the origin of leaves and nuts from Brazil nut trees growing in two indigenous villages, in the Xipaya Indigenous Lands, Pará state. Analysis was performed based on CIEL*a*b* parameters and using VIS (360–740 nm) and near-infrared spectra (1000–2500 nm). The samples were differentiated according to means tests, principal component analysis (PCA), and classification analysis based on k-NN. Color parameters and spectra were similar in both communities. Classification models based on k-NN produced adequate results for the distinction of villages in all evaluated situations, with accuracy of 98.54% for leaves, 89% and 90.91% for nuts with and without shell, respectively. Near infrared can be applied in forests as a technique for previous provenance identification and contribute to the subsistence and sustainable practice of extraction.
Different Aspects of Spin in Quantum Mechanics and General Relativity
Authors: Tamm Martin
Published: November 2023

In this paper, different aspects of the concept of spin are studied. The most well-established one is, of course, the quantum mechanical aspect: spin is a broken symmetry in the sense that the solutions of the Dirac equation tend to have directional properties that cannot be seen in the equation itself. It has been clear since the early days of quantum mechanics that this has something to do with the indefinite metric in Lorentz geometry, but the mechanism behind this connection is elusive. Although spin is not the same as rotation in the usual sense, there must certainly be a close relationship between these concepts. And, a possible way to investigate this connection is to instead start from the underlying geometry in general relativity. Is there a reason why rotating motion in Lorentz geometry should be more natural than non-rotating motion? In a certain sense, the answer turns out to be yes. But, it is by no means easy to see what this should correspond to in the usual quantum mechanical picture. On the other hand, it seems very unlikely that the similarities should be just coincidental. The interpretation of the author is that this can be a golden opportunity to investigate the interplay between these two theories.
Calculation of Forces to the High Granularity Calorimeter Stainless Steel Absorber Plates in the CMS Magnetic Field
Authors: Klyukhin Vyacheslav
Published: November 2023

The general-purpose Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC) at CERN incorporates a hadronic calorimeter to register the energies of the charged and neutral hadrons produced in proton–proton collisions at the LHC at a center-of-mass energy of 13.6 TeV. This calorimeter is located inside a superconducting solenoid that is 6 m in diameter and 12.5 m in length, generating a central magnetic flux density of 3.8 T. For operating optimally in the high pileup and high radiation environment of the High-Luminosity LHC, the existing CMS endcap calorimeters will be replaced with a new high granularity calorimeter (HGCal) with an electromagnetic section and a hadronic section in each of the two endcaps. The hadronic section of the HGCal will include 44 stainless-steel absorber plates with a relative permeability value well below 1.05. The volume occupied by 22 plates in each endcap is about 21 m3. The calculation of the axial electromagnetic forces acting on the absorber plates is a crucial element in designing the mechanical construction of the device. With a three-dimensional computer model of the CMS magnet, the axial forces on each absorber plate were calculated, and the dependence of forces on the central magnetic flux density value is presented. The method of calculation and the obtained results are discussed.
An Enhanced Ant Colony System Algorithm Based on Subpaths for Solving the Capacitated Vehicle Routing Problem
Authors: Ahmed Zakir Hussain , Hameed Asaad Shakir , Mutar Modhi Lafta , Haron Habibollah
Published: November 2023

The capacitated vehicle routing problem (CVRP) is regarded as an NP-hard problem. Moreover, the CVRP is described as a model that can be used in many applications such as transport, logistics, and distribution. The exact algorithms can find exact optimal solutions on the small-sized problem instances; however, for large-sized instances it is difficult to find the exact optimal solutions in polynomial time. This reason motivated the researchers to present heuristic/metaheuristic algorithms to solve large-sized problem instances within a reasonable computational time. One of the good algorithms that deal with the CVRP is the ant colony optimization (ACO) algorithm. Several ACO algorithms have been suggested in the literature, such as the ant system (AS) algorithm, ant colony system (ACS) algorithm, and so on. On the other hand, ACO is designed to solve the path problem that finds the best way. However, this algorithm still lacks exploratory mechanisms, which results in premature convergence and stagnation issues. Therefore, we propose to develop an enhanced ACS (EACS) algorithm for solving the CVRP based on subpaths. In our proposed algorithm, we propose to utilize the K-nearest neighbour (KNN) algorithm for finding the best initial solution and then enhance the diversity mechanism of the proposed algorithm by avoiding the generation of the same solution using subpaths. This uses the diversity of the generated solution to find a better solution with a shorter route in a reasonable amount of computational time. Furthermore, we propose to apply the three-opt algorithm to the completed subtour and the k-opt algorithm to the subpath gained from the experience of the subpath. Finally, to verify the effectiveness of the proposed EACS algorithm, the algorithm is tested on some CVRP instances and is compared with one of the state-of-the-art methods, namely, the enhanced simulated annealing algorithm. The comparative study showed a better performance of our EACS compared to the enhanced simulated annealing algorithm.
A Quantitative Multiparametric MRI Analysis Platform for Estimation of Robust Imaging Biomarkers in Clinical Oncology
Authors: LoCastro Eve , Paudyal Ramesh , Konar Amaresha Shridhar , LaViolette Peter S. , Akin Oguz , Hatzoglou Vaios , Goh Alvin C. , Bochner Bernard H. , Rosenberg Jonathan , Wong Richard J. , Lee Nancy Y. , Schwartz Lawrence H. , Shukla-Dave Amita
Published: November 2023

There is a need to develop user-friendly imaging tools estimating robust quantitative biomarkers (QIBs) from multiparametric (mp)MRI for clinical applications in oncology. Quantitative metrics derived from (mp)MRI can monitor and predict early responses to treatment, often prior to anatomical changes. We have developed a vendor-agnostic, flexible, and user-friendly MATLAB-based toolkit, MRI-Quantitative Analysis and Multiparametric Evaluation Routines (“MRI-QAMPER”, current release v3.0), for the estimation of quantitative metrics from dynamic contrast-enhanced (DCE) and multi-b value diffusion-weighted (DW) MR and MR relaxometry. MRI-QAMPER’s functionality includes generating numerical parametric maps from these methods reflecting tumor permeability, cellularity, and tissue morphology. MRI-QAMPER routines were validated using digital reference objects (DROs) for DCE and DW MRI, serving as initial approval stages in the National Cancer Institute Quantitative Imaging Network (NCI/QIN) software benchmark. MRI-QAMPER has participated in DCE and DW MRI Collaborative Challenge Projects (CCPs), which are key technical stages in the NCI/QIN benchmark. In a DCE CCP, QAMPER presented the best repeatability coefficient (RC = 0.56) across test–retest brain metastasis data, out of ten participating DCE software packages. In a DW CCP, QAMPER ranked among the top five (out of fourteen) tools with the highest area under the curve (AUC) for prostate cancer detection. This platform can seamlessly process mpMRI data from brain, head and neck, thyroid, prostate, pancreas, and bladder cancer. MRI-QAMPER prospectively analyzes dose de-escalation trial data for oropharyngeal cancer, which has earned it advanced NCI/QIN approval for expanded usage and applications in wider clinical trials.
Cysteine Attenuates the Impact of Bisphenol A-Induced Oxidative Damage on Growth Performance and Intestinal Function in Piglets
Authors: Qin Pengxiang , Ma Shangyuan , Li Changjin , Di Yanjiao , Liu Zihao , Wang Huiru , Li Yang , Jiang Shuzhen , Yang Weiren , Jiao Ning
Published: November 2023

Bisphenol A (BPA), a kind of environmental toxin, widely impacts daily life. Cysteine (Cys) is a nutritionally important amino acid for piglets. However, it remains unclear whether Cys can alleviate BPA-induced oxidative damage in piglets. The aim of the present study was to explore the protective effects of Cys in BPA-challenged piglets. A total of twenty-four piglets were divided into four groups that were further subdivided based on the type of exposure (with or without 0.1% BPA) in a basal or Cys diet for a 28 d feeding trial. The results showed that BPA exposure decreased the piglets’ average daily weight gain by 14.9%, and decreased dry matter, crude protein and ether extract digestibility by 3.3%, 4.5% and 2.3%, respectively; these decreases were attenuated by Cys supplementation. Additionally, Cys supplementation restored BPA-induced decreases in superoxide dismutase (SOD) and glutathione (GSH), and increases in malondialdehyde (MDA) levels, in the serum and jejunum (p < 0.05). Moreover, BPA decreased the jejunal mRNA expression of antioxidant genes, which were restored by Cys supplementation (p < 0.05). Cys also restored BPA and increased serum D-lactate levels and diamine oxidase (DAO) activity, and BPA decreased jejunal disaccharidase activity (p < 0.05). Further investigations in this study showed that the protective effects of Cys were associated with restoring intestinal barrier integrity by improving the jejunal morphology and enhancing the mRNA expression of tight junction proteins (p < 0.05). Collectively, the results herein demonstrated that Cys supplementation attenuated the impact of BPA-induced oxidative damage on growth performance, nutrient digestibility and intestinal function.
HantaNet: A New MicrobeTrace Application for Hantavirus Classification, Genomic Surveillance, Epidemiology and Outbreak Investigations
Authors: Cintron Roxana , Whitmer Shannon L. M. , Moscoso Evan , Campbell Ellsworth M. , Kelly Reagan , Talundzic Emir , Mobley Melissa , Chiu Kuo Wei , Shedroff Elizabeth , Shankar Anupama , Montgomery Joel M. , Klena John D. , Switzer William M.
Published: November 2023

Hantaviruses zoonotically infect humans worldwide with pathogenic consequences and are mainly spread by rodents that shed aerosolized virus particles in urine and feces. Bioinformatics methods for hantavirus diagnostics, genomic surveillance and epidemiology are currently lacking a comprehensive approach for data sharing, integration, visualization, analytics and reporting. With the possibility of hantavirus cases going undetected and spreading over international borders, a significant reporting delay can miss linked transmission events and impedes timely, targeted public health interventions. To overcome these challenges, we built HantaNet, a standalone visualization engine for hantavirus genomes that facilitates viral surveillance and classification for early outbreak detection and response. HantaNet is powered by MicrobeTrace, a browser-based multitool originally developed at the Centers for Disease Control and Prevention (CDC) to visualize HIV clusters and transmission networks. HantaNet integrates coding gene sequences and standardized metadata from hantavirus reference genomes into three separate gene modules for dashboard visualization of phylogenetic trees, viral strain clusters for classification, epidemiological networks and spatiotemporal analysis. We used 85 hantavirus reference datasets from GenBank to validate HantaNet as a classification and enhanced visualization tool, and as a public repository to download standardized sequence data and metadata for building analytic datasets. HantaNet is a model on how to deploy MicrobeTrace-specific tools to advance pathogen surveillance, epidemiology and public health globally.
Older Age, a High Titre of Neutralising Antibodies and Therapy with Conventional DMARDs Are Associated with Protection from Breakthrough Infection in Rheumatoid Arthritis Patients after the Booster Dose of Anti-SARS-CoV-2 Vaccine
Authors: Picchianti-Diamanti Andrea , Navarra Assunta , Aiello Alessandra , Laganà Bruno , Cuzzi Gilda , Salmi Andrea , Vanini Valentina , Maggi Fabrizio , Meschi Silvia , Matusali Giulia , Notari Stefania , Agrati Chiara , Salemi Simonetta , Di Rosa Roberta , Passarini Damiano , Di Gioia Valeria , Sesti Giorgio , Conti Fabrizio , Spinelli Francesca Romana , Corpolongo Angela , Chimenti Maria Sole , Ferraioli Mario , Sebastiani Gian Domenico , Benucci Maurizio , Li Gobbi Francesca , Santoro Anna Paola , Capri Andrea , Puro Vincenzo , Nicastri Emanuele , Goletti Delia
Published: November 2023

Objectives: We aimed to analyse the incidence and severity of breakthrough infections (BIs) in rheumatoid arthritis (RA) patients after a COronaVIrus Disease 2019 (COVID-19) vaccination booster dose. Methods: We enrolled 194 RA patients and 1002 healthcare workers (HCWs) as controls. Clinical, lifestyle and demographic factors were collected at the time of the third dose, and immunogenicity analyses were carried out in a subgroup of patients at 4–6 weeks after the third dose. Results: BIs were experienced by 42% patients (82/194) with a median time since the last vaccination of 176 days. Older age (>50 years; aHR 0.38, 95% CI: 0.20–0.74), receiving conventional synthetic disease modifying antirheumatic drugs (csDMARDs) (aHR 0.52, 95%CI: 0.30–0.90) and having a titre of neutralising antibodies >20 (aHR 0.36, 95% CI: 0.12–1.07) were identified as protective factors. Conversely, anti-IL6R treatment and anti-CD20 therapy increased BI probability. BIs were mostly pauci-symptomatic, but the hospitalisation incidence was significantly higher than in HCWs (8.5% vs. 0.19%); the main risk factor was anti-CD20 therapy. Conclusions: Being older than 50 years and receiving csDMARDs were shown to be protective factors for BI, whereas anti-IL6R or anti-CD20 therapy increased the risk. Higher neutralising antibody titres were associated with a lower probability of BI. If confirmed in a larger population, the identification of a protective cut-off would allow a personalised risk–benefit therapeutic management of RA patients.
Examining Influenza Vaccination Patterns and Barriers: Insights into Knowledge, Attitudes, and Practices among Diabetic Adults (A Cross-Sectional Survey)
Authors: Al-Qerem Walid , Jarab Anan , AlBawab Abdel Qader , Hammad Alaa , Alazab Badi’ah , Abu Husein Daoud , Eberhardt Judith , Alasmari Fawaz
Published: November 2023

Diabetes mellitus is a prevalent global chronic condition affecting individuals of all ages. People with diabetes face an elevated risk of lower respiratory tract infections such as pulmonary tuberculosis, influenza, and pneumonia. Additionally, the influenza virus increases the likelihood of deep venous thrombosis and pulmonary embolism. This study examined the knowledge, attitudes, and practices of diabetic patients regarding the influenza vaccine. This study involved 418 diabetic patients (53.3% female) at Jordanian outpatient respiratory clinics, with an average age of 49 (±14) years. The results showed that 70.6% had never received the influenza vaccine, and only 23.7% intended to do so in the current year. A positive attitude toward the influenza vaccine significantly reduced hesitancy to get vaccinated (OR = 0.505, 95% CI 0.424–0.601, p < 0.001). The duration of diabetes exhibited a positive association with vaccine hesitancy (OR = 1.053, 95% CI 1.006–1.102, p = 0.028). The primary reason for not getting vaccinated was a lack of awareness of its benefits (42.6%). Future health education programs should emphasize the importance of the influenza vaccine for diabetic patients and address their concerns.
Impact of Urbanization on Pluvial Flooding: Insights from a Fast Growing Megacity, Dhaka
Authors: Sakib Md Shadman , Alam Siam , Shampa  , Murshed Sonia Binte , Kirtunia Ripan , Mondal M. Shahjahan , Chowdhury Ahmed Ishtiaque Amin
Published: November 2023

The 400-year history of Dhaka says that the city once had several well-known natural canals (khals) that drained stormwater and graywater. In addition to city’s combined sewer system, these water bodies offered an essential natural drainage system that allowed to manage the monsoon rainfall effectively. However, over the past three decades, due to rapid urbanization, these khals have significantly depleted to the point where they are no longer capable of draining the city’s monsoon runoff. Using past, present, and future Land Use and Land Cover (LULC) and urban drainage modeling, this study identified the effects of such LULC change on pluvial flooding of the northern part of the city. Analysis shows that the rapid and extensive changes in LULC over the past decades have resulted in significant shrinkage of these khals, consequently leading to escalated rates of urban flooding in this region. The western part of Turag thana, low-lying areas close to the Baunia Khal depression, and the upstream region of Abdullahpur Khal are highly vulnerable to future urban floods. The projected LULC change indicates an increase of 8.47%, 8.11%, and 4.05% in the total inundation area by 2042 for rainfall events with return periods of 50 years, 25 years, and 2.33 years, respectively. The findings also indicate that 11% more area is likely to experience long-duration flooding due to LULC change.
Optimization of Fe(II)/SPC Sludge Conditioning and Dewatering Process Based on Response Surface Methodology: Full-Scale Application
Authors: Zhou Siru , Chen Chuanhan , Li Ruohong
Published: November 2023

Sludge conditioning is a crucial step in sludge dewatering aimed at minimizing excessive sludge production. The Fenton process, which harnesses oxidative radicals to dismantle extracellular polymeric substances (EPS) and microorganisms, has been unequivocally proven to enhance sludge dewaterability. However, the widespread adoption of the Fenton process is hampered by its high costs and logistical challenges in transportation. In contrast, the Fe(II)-activated sodium percarbonate (Fe(II)/SPC) process has emerged as a promising technology for sludge conditioning due to its remarkable performance and safe operation. However, limited information is available regarding the optimization of Fe(II)/SPC for sludge conditioning and dewatering at full scale. This study conducted the sludge conditioning and dewatering process within a full-scale wastewater treatment plant, utilizing the response surface methodology (RSM) to optimize the Fe(II)/SPC process. Furthermore, this study investigated its impact on sludge structure and compared the economic benefits of the Fe(II)/SPC process with other full-scale conditioning processes. The results of bound water and LDH analysis revealed that the Fe(II)/SPC process not only degraded EPS but also disrupted microbial cells, thereby releasing intracellular water. Based on the RSM results, we successfully established a polynomial prediction model to determine the optimal capillary suction time (CST) and moisture content. The optimal parameters determined through RSM were an initial pH of 3.02, Fe(II) dosage of 0.05 g/g TSS, and SPC dosage of 0.07 g/g TSS. The validation test confirmed the accuracy of the prediction results, with the conditioned sludge exhibiting a CST of 31.6 s and a moisture content of 51.47%. Furthermore, when compared to the PFS and Fenton processes, the Fe(II)/SPC process demonstrated higher economic efficiency and safety, while maintaining good dewatering performance. Overall, the Fe(II)/SPC treatment shows promise as a prospective sludge dewatering and conditioning process.
The land planning, use and land protection in the USSR and using this experience in modern Russia
Authors:   Russian Academy of Sciences, Khlystun V.N. ,   State University of Land Use Planning, Moscow
Published: November 2023

The content of the article presents a retrospective analysis of forecasting and planning land use in the USSR. The paper shows the content of General Schemes for the use of land resources in the country and land management schemes for regions (Autonomous Soviet Socialist Republics) and administrative districts developed from 1972 to 1990. The authors discuss the possibility to revive this institution of land management and developing such documents in modern Russia.
GIS technologies in geobotanical survey of pastures (by example of Batken region)
Authors:   Land Management and Cadastre Department, Kyrgyz National Agrarian University named after K. I. Scriabin, Bishke, Batykova A.Z. , Denisov V.V. ,   Land Management and Cadastre Department, Kyrgyz National Agrarian University named after K. I. Scriabin, Bishke, Zhusupova A.K. ,   Land Management and Cadastre Department, Kyrgyz National Agrarian University named after K. I. Scriabin, Bishke, Rasheva A.T. ,   Land Management and Cadastre Department, Kyrgyz National Agrarian University named after K. I. Scriabin, Bishke, Bazarbaeva I.D. ,   Land Management and Cadastre Department, Kyrgyz National Agrarian University named after K. I. Scriabin, Bishke
Published: November 2023

The article deals with the issues of geobotanical survey of the pasture area "Baytak- Ravat-Jakub" using geoinformation technologies to determine the productivity of pastures, the botanical composition of the herbage, the quality of herbaceous vegetation, and the possibility of using pastures for grazing livestock.
The IMF’s Credit Policy — Assistance to the Needy or a Tool of Enslavement?
Authors:   Plekhanov Russian University of Economics (PRUE), Moscow, Vlasova Yu. A. , Markin M. O. ,   Higher School of Finance of the Plekhanov Russian University of Economics, Moscow
Published: November 2023

The paper discusses examples of lending by the International Monetary Fund in three countries with different degrees of economic development. The subject of the paper is not the loan itself, but the fact that in order to receive it, the IMF puts forward a number of conditions designed to ensure the stability of the economy, but in fact repeatedly criticized for the opposite, negative result. The impact of the IMF loan on the economy, therefore, becomes very ambiguous and requires a closer analysis. Macroeconomic analysis allows us to determine the specific effects of the crisis and IMF reforms on the economy, while the world-system analysis based on these data reveals the position of certain countries in the international division of labor. The aim of the work was to identify the impact of loans provided by the International Monetary Fund on the economies of countries. Based on the results of the analysis, it became possible to determine the role of the International Monetary Fund in the international economy and identify diffi culties in achieving its global goals. Thus, the IMF’s activities only allow preserving the existing world order without leading to rapid growth of the economies of the borrowing countries. In this regard, taking into account all current global trends, the authors believe that attention should be paid to the development of other international institutions that will allow in the medium and long term to fulfill the goals laid down in the charter of the International Monetary Fund.
New Migration Trends in the EU Countries: Disagreements, Compromises, Prospects
Authors:   Primakov National Research Institute of World Economy and International Relations of Russian Academy of Sciences (IMEMO RAS), Moscow, Trofimova O. E.
Published: November 2023

The article describes specifics and new migration tendencies in EU countries after the crisis of 2015. The author examines situation with migrants and asymmetric approach of the European states to these problems using methods of comparative and statistical analysis. The study identifi ed the causes of disagreements within the European Union, lack of balance between national and supranational levels of EU migration policy, especially during crisis, weakness of integration in migration sphere. The processes of sub-regionalization are analyzed in the article, they intensifi ed after migration crisis and led to disconnection between European states. The special approach of the EU countries to Ukranian refugees is noted in this study and main reasons are more political than humanitarian. Different forecasts of migration process are considered. The author makes a conclusion that volatility and unpredictability of migration and multiplicity of different factors influence the forecasts and scenarios, especially medium and long-term and requires more complicated methods, criteria and system analysis. The growth of migration flows in EU countries is wave-like and depends on social, political and economic situation in receiving and origin countries. These processes are irreversible and difficult to resolve within European Union.
Optimal by the Order of Accuracy Cubature Formula for the Approximate Calculation of Triple Integrals from Fast Oscillating Functions in General View
Authors: Nechuiviter Olesia , Ivanov Serhii
Published: November 2023

Introduction. The rapid development of digital technologies encourages scientists to create new or improve existing mathematical models of technical processes. It is time to develop mathematical models with different types of data. In the tasks of digital signal and image processing, the approximate calculation of integrals from rapidly oscillating functions using new information operators makes it possible to build cubature formulas using different types of information: the values of functions on planes, lines and points can be used as data.
The purpose is to present and investigate the optimal cubature formula for the approximate calculation of the triple integral from rapidly oscillating functions in the general form on the class of differential functions. Information about functions are traces on systems of mutually perpendicular planes.
Results. The study of the problems of digital signal and image processing continued using the example of numerical integration of triple integrals from rapidly oscillating functions in the general form.
The values of functions on systems of mutually perpendicular planes are using for constructed cubature formula.
The main attention in the research focuses on obtaining the estimations of errors. Proposed cubature formula for the approximate calculation of the triple integral from rapidly oscillating functions in general view is optimal in order of accuracy on the class of differential functions. The conducted numerical experiment confirmed the theoretical results.
Conclusions. The obtained results make it possible to build new and improve existing mathematical models of processes with different types of input information. New information operators are a powerful tool in the development of such models. Cubature formulas for the approximate calculation of integrals from rapidly oscillating functions of many variables have been created. Іn the construction of the formulas traces of the function on planes, lines, and points are used. Formulas in their construction use function traces on planes, lines, and points. In this work, a cubature formula for the approximate calculation of the triple integral from a rapidly oscillating function in the general form, which is optimal in order of accuracy, is constructed and investigated on the class of differentiable functions. A feature of the proposed formula is the use of values of functions on systems of mutually perpendicular planes as data. Keywords: integrals of rapidly oscillating functions of many variables, cubature formulas, new information operators, digital signal and image processing.
Exploring Policy Trends and Implications for Supporting Chinese Teachers’ AI and Digital Competencies
Authors:   Education Research Institute, Lee SuJin , Kim SangCheol , Joo YoungHyeo , Kim HeeKyu
Published: November 2023

This study explored implications for improving our AI and digital competencies by analyzing policies to enhance AI and digital competencies in China and case studies related to AI and digital competencies. First, the background of policy promotion related to China's AI and digital competencies and the conceptual definition of China's AI and digital competencies were examined, and the types of AI and digital competencies in China were specifically explored. Based on this, we looked at the actual support and use of Chinese teachers' AI and digital competencies in the current teaching situation in Chinese schools, and explored Chinese education policies to support teachers' AI and digital competencies. This search was in-depth approach and analysis based on literature published in the original Chinese language, such as announcements from the Ministry of Education of China, Chinese academic journals, Chinese websites, and Chinese media. Through this, the implications of China's AI/digital competency training for Korea and the future direction of Korea's AI/digital competency support policy were suggested as follows. First, it is necessary to establish a teacher training model that combines the capacities of the government and the private sector. Second, AI and digital resources must be fully utilized in the teaching and learning process. Third, it is necessary to strengthen the education of prospective teachers and expand the training of incumbent teachers.
Mediating Effect of Covert Narcissism in the Relationship between Parent-Child Communication perceived by High School Students, Peer Attachmentand and Their Smartphone Addiction
Authors:   Education Research Institute, Jeong MyungSun , Cho GyuPan
Published: November 2023

The purpose of this study is to find out the mediating effect of covert narcissism in the relationship between parent-child communication perceived by high school students, peer attachment and their smartphone addiction. For the purpose of the study, 239 high school students in Busan were tested for parent-child communication, peer attachment, covert narcissism, and smartphone addiction. Correlation analysis and hierarchical regression analysis were on the collected data and the results of this study are as follows. First, there is a significant correlation between parent-child communication perceived by high school students, peer attachment, covert narcissism, and smartphone addiction. Second, in the relationship between parent-child communication perceived by high school students and smartphone addiction, covert narcissism has a complete mediating effect. Third, in the relationship between high school students' peer attachment and smartphone addiction, covert narcissism has a complete mediating effect. These findings suggest the importance of healty management of covert narcissism as well as parent-child communication and peer attachment, which are major environmental factors for teenagers, to prevent high school students from smartphone addiction.
Technology Assistance of Automatic Ginger Grating Machine for the Herbs Industry in Joketro Village, Magetan Regency
Authors: Denny Hardiyanto  , Ihtiari Prastyaningrum  , Dio Muhammad Thaariq Akbar  , Alif Mashuri  , Agil Ridhohan
Published: November 2023

Joketro Village, Parang District is one of the villages in Magetan Regency, East Java, where most of the people make a living as producers and sellers of traditional herbal medicine. From generation to generation, this herb is a legacy from our ancestors which is preserved and beneficial for the health of the human body. Currently, these herbs are only produced on a small scale and are only sold by going door to door. The Universitas PGRI Madiun community service aims to help improve the herbal medicine business. The methods used include: 1) we donated PIR sensor-based automatic grater machines, and 2) provided assistance and training in the use of tools for herbal medicine entrepreneurs with the aim of increasing herbal medicine production. The result of mentoring is that herbal medicine entrepreneurs have the skills to use machine technology to increase the quantity of herbal medicine produced. By increasing herbal medicine production, it will certainly improve the community's economy, especially herbal medicine entrepreneurs in Joketro Village.
Socialization of Waste Management in Klawalu Mangrove Forest Tourist Attraction Area of Sorong City
Authors: Dayera Disabella , Roger R. Tabalessy  , Ahmad Rizal Nurul Kusumawardana  , Ishak Aryanto  , Rosa O. Sapulette  , Christina Bastian
Published: November 2023

Waste can damage the beauty of the environment and is a threat to humans and ecosystems that are directly affected if not appropriately managed. Public understanding of the impact of waste needs to be improved. So, community service is carried out to provide understanding to the community about handling sound waste and its management around the Klawalu mangrove tourism area so that this place becomes a tourist attraction that the community loves. The methods used in this service are lecture and discussion methods. The results of the service activities found that the community only understood the impact caused by waste in depth. However, with this socialization, the community realizes it is necessary to manage the garbage in the area to produce a clean and beautiful area that is free from garbage. Based on the findings of this study, providing the community with training and fostering a sense of environmental stewardship is essential to cultivating a healthy and pristine environment.
Kompetensi Literasi dan Numerasi Berbasis Education for Sustainable Development di Sekolah Dasar
Authors: Umroh Yayu Umul , Hamdu Ghullam , Nugraha Akhmad , Hadiana Deni
Published: November 2023

Penelitian ini bertujuan untuk mengetahui kompetensi literasi dan numerasi berbaisis Education For Sustainable Development (ESD) di Sekolah Dasar. Metode Penelitian ini menggunakan metode kualitatif deskriptif dengan subjek penelitian guru dan siswa kelas 4 di salah satu SD di Kabupaten Tasikmalaya. Pengambilan data melalui wawancara, studi dokumentasi, dan test. Soal tes yang saat ini dibuat dan dikembangkan oleh guru masih belum mengukur kompetensi literasi dan numerasi, tingkat kemampuan berfikirnya masih rendah, dan masih belum berbasis Education For Sustainable Development (ESD). Berdasarkan tes yang dilakukan melalui soal tes literasi dan numerasi berbasis ESD yang kemudian dianalisis melalui pemodelan Rasch melalui person measure berdasarkan perbandingan nilai standar deviasi dan nilai logit menunjukan bahwa abilitas peserta didik dalam kompetensi literasi dan numerasi berbasis ESD masih rendah.
Assessment of the psycho-emotional state of pregnant women and features of anesthesia in an obstetric hospital
Authors: Trukhanova Inna G. , Zinatullina Dilyara S. , Krugova Lidiya V. , Kutyreva Yuliya G.
Published: November 2023

Aim to determine the indicators of anxiety and depression in pregnant women who are going to have an operative delivery and, depending on this, to provide the optimal type of anesthesia and psychological support during the operation.
Material and methods. We examined 215 pregnant women aged 18 to 45 years (M=29,84,79) who were to undergo operative delivery. We also tested 188 women from the KG with the physiological course of pregnancy, with the same age and gestation period, whose delivery was carried out through the natural birth canal.
Results. In MG patients, the optimal type of PCGD was significantly lower than in CG patients (p0.05). Euphoric, hypogestognosic and anxious types of PCGD in pregnant CG were also significantly higher than in MG patients (p0.05). When analyzing the data on personal and situational anxiety, it was found that a high degree of severity according to the Spielberg-Khanin scale was observed in patients with anxious and depressive types of PCGD Endogenous depression in pregnant women of the main and control groups is absent when using the questionnaire for the presence and severity of depressive states I.G. Bespalko.
Conclusion. In pregnant women who were to have an operative delivery, the optimal type of PCGD was significantly lower than in women who were to have a natural birth. Anxious and depressive type of PCGD in patients with planned operative delivery was significantly higher than in patients with planned natural childbirth. Psychocorrective work and additional psychological support by an anesthesiologist-resuscitator during a caesarean section reduced the severity of anxiety and depressive disorders.
Parent's Contribution to Strengthening Moral Awareness of Student Religiosity Behaviour
Authors: Hendra Hendra , Khozin Khozin , Irwan Irwan , Anwar Saiful
Published: November 2023

Strengthening religiosity for students is a variable that is considered very important in enhancing character in madrasas. This research aims to explain the contribution of parents' role in parenting patterns and students' moral awareness towards students' religious behaviour. This research uses quantitative analysis using cause and effect relationships. The population in this study was 246 students. The research sample was 159 students using the Slovin formula. Data collection techniques use interviews, questionnaires and documentation. This research uses several assumption tests, including normality, heteroscedasticity and linearity, multicollinearity, and suitability of the regression model. The research results show an R-value of 0.545, which shows the level of reliability based on the Alpha value in the Medium category in the interval 0.4≤0.70. The role of parents in providing motivation and moral awareness in shaping religious behaviour has a significant contribution, with an increase in the ability of 29.7%. Therefore, parents have an essential role in providing parenting patterns in the form of exemplary habituation to children to provide an awareness value so that children have good religious behaviour.
Evaluation of Fetomaternal Outcome in Expectant and Active Management of Term Prelabour Rupture of Membranes
Authors: Begum Sharifa , Parven Rehana , Sultana Shadia Sharmin , Mondal Mousumee , Khatun Marzina
Published: November 2023

Background: PROM is a complex condition with multifactorial etiology, including factors like multigravida, low socioeconomic status, concomitant infections, late symptom presentation, and a history of preterm PROM. Conventional management strategies include expectant management, waiting for spontaneous labor, and active management, involving induction with oxytocin or prostaglandins. Objectives: This prospective cross- sectional observational study aimed to evaluate fetomaternal outcomes in both expectant and active management of term PROM. Methods: Conducted at the Obstetrics and Gynecology Department of Rangpur Medical College Hospital, the study included 50 pregnant women with a history of PROM, gestational age ≥37 weeks, and spontaneous membrane rupture. Data were collected from March to September 2019 using purposive sampling. Demographic information was recorded, and clinical examinations were performed. Data were processed, analyzed, and compared between active management (Group-A) and expectant management (Group-B). Results: The study population's age ranged from 17 to 35 years, with a majority aged 20-25 years (42.0%). Most patients were from urban areas (52.0%), with 52% belonging to a socioeconomically disadvantaged class. Group-A, which underwent active management, showed a significantly higher rate of delivery within 12 hours (80.0%) compared to Group-B (48%). Both groups had similar induction-to-delivery intervals. Vaginal deliveries were more frequent in Group-A (84% vs. 64%), while Group-B had a higher rate of C-sections due to fetal distress. Group-B experienced more maternal complications, including puerperal sepsis, wound infections, and postpartum hemorrhage. Neonatal outcomes were better in Group-A, with higher Apgar scores at both 1 and 5 minutes. Conclusion: Active management was associated with better outcomes in term PROM cases compared to expectant management. Early antenatal diagnosis and risk factor identification are essential tools.....