bluuebunny/crossref_metadata_2025 huggingface dataset:
MSE-NERSPPNet: A Multi-Channel Framework for Bearing Fault Diagnosis in the Presence of Imbalanced Samples
Authors: Lin Daxuan , Dong Zhilin , Sun Jianfeng , Xu Wanxiu , Chen Xiaohao , Liu Siyu , Jiang Yonghua , Jiao Weidong
Published: January 2025

Bearing monitoring data in industrial applications exhibits pronounced class imbalance, where the disproportionate ratio of healthy to faulty samples imposes significant constraints on the feature extraction and generalization capabilities of intelligent diagnostic models. Multi-channel sensing systems are extensively deployed in engineering practices to facilitate precise fault diagnosis and obtain multidimensional complementary information. However, the intrinsic heterogeneity of such data (e.g., spatiotemporal dependencies across channels) and unavoidable redundancy (e.g., overlapping or correlated information among channels) substantially escalate the complexity of implementing robust feature engineering techniques. To overcome these challenges, a Multi-scale Sample Entropy-driven Nonlinear Residual Spatial Pyramid Pooling Network (MSE-NERSPPNet) is proposed in this study. Initially, multi-scale sample entropy is employed to analyze signals from each channel, extracting complexity-domain entropy features. Subsequently, multi-channel features are pooled and fused across three distinct spatial scales (global, intermediate, and local) via a spatial pyramid pooling layer, enhancing the capability of model to extract features from heterogeneous multi-channel data. Finally, a residual module, augmented with the Kolmogorov–Arnold Network, is introduced to refine feature fusion further. The fused features are then subjected to residual learning and nonlinear mapping mechanisms to optimize the overall feature representation. MSE-NERSPPNet is extensively evaluated using two sets of multi-channels bearing data featuring varying imbalance ratios. Experimental results indicate that MSE-NERSPPNet outperforms several benchmark algorithms, achieving superior recognition rates across various tasks.
Designing Serious Games for Cognitive and Motor Rehabilitation in Post-Stroke Patients
Authors: Alves Thiago , Gonçalves Rogério Sales , Kishi Marcos Seizo
Published: January 2025

Stroke remains the leading cause of disability, often resulting in severe motor and cognitive impairments, including functional deficits and memory loss. Rehabilitation leverages neuroplasticity, enabling undamaged brain regions to compensate for lost functions. Enhancing traditional therapy with robotic bilateral priming and non-invasive brain stimulation, such as serious games, addresses issues like learned non-use and interhemispheric inhibition. These approaches promote cortical excitability rebalancing, fostering a neuroplastic environment conducive to motor and cognitive recovery. Therapeutic tools, like pegboards, aid fine motor coordination recovery, supporting Activities of Daily Living (ADLs), while improving attention, concentration, and visuospatial cognition. Additionally, puzzle games further stimulate memory-related brain regions, stimulating cognitive improvements. This paper explores the potential of serious games and robotic devices in cognitive rehabilitation of stroke, detailing their ability to provide engaging and effective therapy. Several serious games combining memory tasks, reach, and pegboard fitting were developed, with careful consideration of design, therapeutic benefits, and clinical findings. Two stroke groups underwent an intervention with the serious games developed, demonstrating significant improvements (p < 0.05) in cognitive and motor performance across multiple parameters. Approved by the Research Ethics Committee of the Federal University of Uberlândia (ethics approval numbers 51133821.4.0000.5152 | 00914818.5.0000.5152).
Free-Living Muscle Activity in Type 2 Diabetes: Sitting, Standing and Walking
Authors: Lamberg Suvi , Brakenridge Christian , Gao Ying , Dunstan David W. , Finni Taija , Healy Genevieve N. , Owen Neville , Pesola Arto J.
Published: January 2025

AIMS: Using thigh-worn accelerometers and wearable electromyographic (EMG) shorts, we investigated muscle activity during sitting, standing and walking in adults with type 2 diabetes.
METHODS: Isometric maximal voluntary contraction measures for quadriceps, hamstring, and gluteal muscle groups normalized the EMG signal to individual maximum capacity. Participants concurrently wore accelerometers and EMG shorts for 3.2 days, and average EMG amplitude (aEMG) was assessed from quadriceps, hamstring, and gluteal muscle groups within accelerometer-derived sitting, standing, walking times.
RESULTS: Muscle groups examined used only 2.7–4.4% of their maximum voluntary capacity (%EMGMVC) and were inactive for 75-80% of the measurement time. Sitting time was significantly correlated with muscle inactivity across all three muscle groups, but inversely so for hamstring aEMG (r = -0.51). Standing (r = 0.51) and walking (r = 0.48) were correlated with daily aEMG only in hamstrings. Relative to sitting, standing aEMG was 1.3–5.6 times higher and walking aEMG was 3.1–15.2 times higher, indicating varied inter-individual responsiveness.
CONCLUSIONS: Reducing daily sitting, especially in favor of walking, may benefit hamstring and gluteal muscle engagement and help to prevent high levels of muscle inactivity in type 2 diabetes. Individual variability in EMG responses highlights the potential to personalize recommendations on sitting, standing and walking.
Modeling the trend of Iraqi GDP for 1970-2020
Authors: Gatea, et. al. Ahlam Hanash
Published: January 2025

The study of economic growth indicators is of fundamental importance in estimating the effectiveness of economic development plans, as well as the great role it plays in determining appropriate economic policies in order to optimally use the factors that lead to the dynamics of growth in Iraq, especially during a certain period of time. The gross domestic product (GDP) at current prices), which is considered a part of the national accounts, which is considered as an integrated dynamic of statistics that produces in front of policy makers the possibility of determining whether the economy is witnessing a state of expansion or evaluating economic activity and its efficiency in order to reach the size of the overall economy.The research aims to determine the best and most efficient statistical model to be used in forecasting the GDP in Iraq based on time series data for the period from (1970-2020) years. Where the general trend models (Linear trend, Quadratic trend and Exponential Trend) were applied, and the three models were compared to choose the best model using some statistical criteria, including the Akiaki Information Standard (AIC) and Schwartz Standard (SBS). The results showed that the appropriate model is the Quadratic trend model, were predicting and forecasting values are close to the real values of the GDP series.
New strategic approaches for implementing intelligent streetscape towards livable streets in City of Riyadh
Authors: Alshammari Talal Obaid
Published: January 2025

Streetscape can be considered as a term “which can be used to clarify and explain the street's built-in and the basic structure, also it is known as the design of the visual appeal and quality of the street effect. A good tool for improving urban quality and establishing a feeling of place is design of streetscape. People's re-quirements for public areas have changed as internet usage has continued to expand. The numbers of people who use cars has increased a lot in Riyadh city. This leads to some problems in a direct and an indirect way, such as car accidents, traffic overcrowding, lack of services for bicyclists and pedestrians, weak social rela-tionships between the people, and high obesity levels. Reconsider design of streetscape in Riyadh city espe-cially in the era of digital information technology will revitalize regions by providing reshaping the urban experience toward higher livability that respond to and connect with onlookers in order to increase under-standing of onlookers' activities in the streets, promote their sense of place, and improve safety and livabil-ity in urban areas.. The presented study focuses on the qualitative approach that is according to the related theoretical exploration and research; so, this paper combines the design of streetscape with digital infor-mation technology, with new ideas of intelligent streetscape’s design for enhancing Riyadh city to make the user's life livable. The current paper ended with proposed strategic approaches and suggestions to enhance the city of Riyadh's streetscape style as an outcome of the theoretical research. Results indicated that streets, which contain a close combination with the resident’s daily life activities and the important consequences on their mental comfort, have not attracted any care in terms of academic research. This resulted in a failure in providing solid strategic approaches for intelligent design of streetscape in Riyadh city.
Study of chemical and physical parameters affected on purification of water from inorganic contaminants
Authors: Abdullah, et. al. Waleed R.
Published: January 2025

The ability to remove perchlorate anions was investigated by the adsorption technique in a laboratory scale and by a batch type unit from contaminated aqueous solutions prepared at specific concentrations. The ad-sorption process was carried out using banana peels, which were chosen as an available, cheap, and low-cost adsorption media. The studied operating conditions in the treatment process were the acidic function, shaking speed, contact time, temperature, in addition to the initial concentration of perchlorate, which rang-ing from 1-10, 100-400 rpm, 10-180 min, 20-50 ºC, 50-1000 ppb respectively, while the dose of adsorbent media ranged between 0.5-6 g and the particle size ranged from 0-Pan. The experimental results showed that the removal efficiency of perchlorate changes directly with the shaking speed, contact time, particle size and the dose of adsorbent, while it was inversely with the remaining variables for certain levels. Thus, two types of contaminants were disposed of simultaneously in a beneficial, and eco- friendly manner, reaching to Zero Residue Level (ZRL).
Automatic image annotation system using deep learning method to analyse ambiguous images
Authors: Al-Shammary, et. al. Ali Abbas
Published: January 2025

Image annotation has gotten a lot of attention recently because of how quickly picture data has expanded. Together with image analysis and interpretation, image annotation, which may semantically describe imag-es, has a variety of uses in allied industries including urban planning engineering. Even without big data and image identification technologies, it is challenging to manually analyze a diverse variety of photos. The improvements to the Automated Image Annotation (AIA) label system have been the subject of several scholarly research. The authors will discuss how to use image databases and the AIA system in this essay. The proposed method extracts image features from photos using an improved VGG-19, and then uses near-by features to automatically forecast picture labels. The proposed study accounts for both correlations be-tween labels and images as well as correlations within images. The number of labels is also estimated using a label quantity prediction (LQP) model, which improves label prediction precision. The suggested method addresses automatic annotation methodologies for pixel-level images of unusual things while incorporating supervisory information via interactive spherical skins. The genuine things that were converted into metada-ta and identified as being connected to pre-existing categories were categorized by the authors using a deep learning approach called a conventional neural network (CNN) - supervised. Certain object monitoring sys-tems strive for a high item detection rate (true-positive), followed by a low availability rate (false-positive). The authors created a KD-tree based on k-nearest neighbors (KNN) to speed up annotating. In order to take into account for the collected image backdrop. The proposed method transforms the conventional two-class object detection problem into a multi-class classification problem, breaking the separated and identical dis-tribution estimations on machine learning methodologies. It is also simple to use because it only requires pixel information and ignores any other supporting elements from various color schemes. The following factors are taken into consideration while comparing the five different AIA approaches: main idea, signifi-cant contribution, computational framework, computing speed, and annotation accuracy. A set of publicly accessible photos that serve as standards for assessing AIA methods is also provided, along with a brief description of the four common assessment signs.
The role of digital content systems used in managing Arab academic scientific journals: An analytical study
Authors: Kanber, et. al. Huda Abbas
Published: January 2025

The current research aims to highlight the role of digital content management systems adopted in the man-agement of Arab scientific journals and to indicate its features and characteristics. As well as learning about the available global systems for managing the digital content of scientific journals. The researchers adopted the descriptive approach to achieve the objectives of the research, and the questionnaire was a data collec-tion tool. The questionnaire was distributed to a proportional random sample that included (30) researchers who use digital content management systems for three research sample sites with two journals for each site. The journals are from the OJS platform (Professor for Humanities and Social Sciences and Al-Kufa Journal of Mathematics and Computer), the ASJP platform (the Algerian Journal of Social and Human Sciences, and the Review of Scientific and Technical Information), and the ARID platform (ARID International Journal of Humanities and Social Sciences, and the Arad International Journal of Sciences and technology). The re-search data was presented in the form of tables and graphs and analyzed statistically based on several meth-ods. The research came out with several results, the most important of which is that the Algerian scientific journals website management system (ASJP) represents the best system for researchers to manage journals from the two systems (OJS, ARID).
Experimental investigation and statistical modelling for assessing the sliding wear of Futilized Filament Fabrication (FFF) fabricated parts
Authors: Ali, et. al. Hind B.
Published: January 2025

A significant historical enabler for the improvement of industrial goods has been the characterization of novel materials. For example, a large variety of polymeric materials are readily accessible to manufacture the appropriate items depending on the production method. Due to its capacity to produce components with complicated geometries without the need for tools or a human interface, fused filament fabrication (FFF) is acquiring a unique edge in the industrial sector. By adjusting process parameters at the right values, the qualities of FFF-built items may be enhanced since they rely heavily on these factors. Increasing the service life of functioning components requires taking wear resistance into account. Because of this, the current work concentrates on a thorough investigation to comprehend the impact of 3 crucial elements, including layer thickness, printing speed, also infill density, infill density, and the sliding wear of test specimens. A mechanism of wear is explained by utilizing microphotographs.
Estimation and prediction of temperature in Iraq using the multi-layered neural network model
Authors: AL-Saffar, et. al. Rawaa Salh
Published: January 2025

The forecasting using the multi-layered neural network model is one of the methods used recently in fore-casting, especially in climate forecasts for certain regions, because of its accuracy in forecasting, which sometimes reaches levels close to the real collected data. In this research, the daily temperatures in the cli-mate of Iraq were predicted, by taking data from the Iraqi Meteorological Authority by (228) observations, which represent the daily temperatures of Karbala Governorate in the year (2021), The results of the auto-correlation and partial autocorrelation showed that the daily temperature series of Karbala governorate is unstable, and this was confirmed by conducting the augmented Dickey Fuller test. The data was analyzed using the multi-layered neural network model in two stages, and it was later shown that the accuracy of estimation and prediction using the multi-layered neural network even if the time series is not stable, The results showed an indication of an rising increase in temperatures during the coming years. The researcher concluded that it is necessary to pay attention to the vegetation cover and to conduct many predictive studies of the climate using the multi-layered neural network.
Design of an AS/RS machine for storage and extraction of items in a warehouse using Finite Element Analysis (FEA)
Authors: Maradey – Lázaro, et. al. J. G.
Published: January 2025

The globalization of markets and high competitiveness impose new challenges every day on companies that develop their activities in the field of logistics, e-commerce, service, and product distribution. The imple-mentation of automated systems becomes relevant when the objective is to increase productivity, efficiency and reduce costs associated with handling, picking and overhead. The AS / RS systems (i.e., Automated Storage and Retrieval System) are automated machines able to move in the 3 coordinate axes (x, y, z), which are responsible for arranging the items in large warehouses generating a decrease in time delivery and storage.The aim of the article is to show the design of a prototype of an AS / RS (CAD) machine based on Finite Element Analysis (FEA) to verify the behavior before static loads according to Von Misses criteria and to guarantee the appropriate administration, storage, and extraction of each item in the warehouse, respective-ly. Also, it shows the use of the selection matrix that facilitates the interaction with the articles and executes the primary functions according to customer requirements. The result of this research shows the advantages and disadvantages of the implementation of these systems for companies that manage high volumes of stor-age, limited physical space and that require an appropriate management of the elements through the help of an easy-to-implement human-machine interface (HMI) that has control over open loop.
Exploring the potential of offline cryptography techniques for securing ECG signals in healthcare
Authors: Abdulbaqi, et. al. Azmi Shawkat
Published: January 2025

In the research, a software for ECG signal based on Chaos encryption based on C#-programmed and Kit of Microsoft Visual Studio Development was implemented. A chaos logic map (ChLMp ) and its initial value are utilized to create Level-1 ECG signal based on Chaos encryption bit streams. A ChLMp, an initial value, a ChLMp bifurcation parameter, and two encryption level parameters are utilized to create level-2 ECG signal based on Chaos encryption bit streams. The level-3 ECG signal based on Chaos encryption software utilizes two parameters for the level of encryption, a permutation mechanism, an initial value, a bifurcation parameter of the level of encryption, and a ChLMp. We assess 16-channel ECG signals with great resolution utilizing encryption software. The level-3 ECG signal based on Chaos encryption program has the slowest and most reliable encryption speed. The encryption effect is superior, according to test findings, and when the right decoding parameter is utilized, the ECG signals may be completely recovered. The high resolution 16-channel ECG signals (HRMCECG) won't be recovered if an invalid input parameter occurred, such as a 0.00001% initial point error, which will result in chaotic encryption bit streams.
Flexural behavior of CFRP-strengthened reinforced concrete beams rubberized with finely minced rubber tire
Authors: Adday, et. al. Adnan Abdullah
Published: January 2025

Although using rubber to create reinforced concrete substrates has many benefits, using rubberized concrete substrates, such as beams, is still limited. Where concrete with rubber included in it starts to lose a percent-age of its mechanical qualities, such as flexural strength. Conversely, a significant portion of structural uses for strengthening reinforced concrete beams using exterior carbon fiber reinforced polymer (CFRP) sheets are for flexural strengthening. This study used externally bonded carbon fiber-reinforced polymer (CFRP) sheets to compensate for the reduction in flexural strength when creating rubberized concrete beams. The reinforced concrete beams used in this study were divided into three groups, each with three beams. Waste tire rubber was replaced (5%) of the fine aggregate volume in the first group and replaced (10%) in the sec-ond group. The reference group consists of the third set of beams. The first concrete beam in any group was always devoid of external strengthening, the second beam had one layer and the third beam had two layers of (CFRP) sheet. The third layer of strengthening was numerically represented using ABAQUS, a finite element analysis program. The results indicate that for two-volume replacement rates of fine aggregate (5 and 10) %, a decrease in ductility will have been accompanied by an improvement in the flexural strength of the rubberized concrete beam when externally strengthening with one, two, and three layers of (CFRP) sheets.
Monopole antenna design with flexible frequency selective surface
Authors: Alrababah Ahmad
Published: January 2025

A flexible monopole antenna combined with a flexible frequency selective surface (FSS) is presented in this work. Initially, the FSS structure is examined by constructing a unit cell of the periodic FSS structure with (3x3) arrays of square loops. On a thickness of 0.13 mm, a fast film with a permittivity of 2.7 is printed, and the substrate of the monopole antenna is FR-4 with a dielectric constant of 4.3. The monopole antenna is then densely and parallelly positioned 26 mm above the FSS structure. After studying the monopole an-tenna's return loss, efficiency, bandwidth, and antenna gain, the design is included in the FSS framework to obtain a steady frequency response. When the distance between both the antenna and the FSS structure is extended, the frequency response of the antenna is moved, and the return loss is determined to be less than -52 dB. Furthermore, the fractional bandwidth is extended from 62% to 103%, and the gain is increased greatly to 2.4 dB. This design structure demonstrated exceptional wireless communication performance.
Research of influence of different shaped charge liner materials on penetration depth using numerical simulations
Authors: Catovic Alan
Published: January 2025

Numerical simulations, using the Ansys AUTODYN program, of Panzerfaust 30 (klein) anti-tank warhead, were performed to determine the influence of different liner materials on the penetration depth into a steel target. It has been shown that the choice of liner material can significantly affect the performance of the ammunition. Along with other methods of optimizing shaped charge ammunition (optimization of the shape, thickness and angle of the tip of the liner, use of more potent explosive and deviator, optimization of casing thickness and stand-off distance, etc.), the use of appropriate liner material is certainly one of the most im-portant parameters of shaped charge warheads to consider. Together with analytical calculations and experi-mental tests, simulations are a valuable tool. Using data obtained from numerical simulations, researchers can save both time and resources during the process of munition design and optimization.
The effect of independent audit quality on the quality of financial reporting in the listed companies in Tehran and Baghdad stock exchanges
Authors: Abbas Siraj , Izadinia Nasser , Kiani Gholamhossein
Published: January 2025

The primary purpose of this research is to investigate the relationship between the quality of the external audit and the quality of the financial reporting done by companies that are traded on the Tehran and Bagh-dad Stock Exchanges. The experience of the auditor in the sector, the auditor's reputation, and the auditor's length of service were utilized as determining factors for the quality of the external audit. In order to deter-mine whether or not the reporting of financial data can be trusted, discretionary accruals are analyzed. The companies that are members of the Tehran Stock Exchange and the Baghdad Stock Exchange make up the statistical population for the current study. They were chosen using the process of systematic elimination, which was applied to 102 firms that were admitted to the Tehran Stock Exchange and 35 companies that were admitted to the Baghdad Stock Exchange. In order to examine the data, multiple regression analyses were performed. According to the findings of the study, the quality of financial reporting at the Baghdad Stock Exchange is not significantly impacted by the standard of external auditing. In addition, the independ-ence of the Tehran Stock Exchange's financial reporting is directly and considerably impacted by the quality of the audits conducted by external parties. The findings, taken as a whole, suggested that in order for enter-prises to function properly in Iraq they need a secure and politically stable environment. This, in turn, has an effect on the accuracy of the reports they provide. On the other hand, the profession of auditing in Iraq is still in its formative stages, and auditors need to have a deeper understanding of their respective industries.
Long-term effect of economic status on auditors' professional skepticism
Authors: Khaleel Rasool Abbas , Aghaei Mohamad Ali , Rami Behrouz Khoda , Sepasi Sahar
Published: January 2025

The goal of the current study was to look into how financial stability affected auditors' professional skepti-cism. One of the elements that reflects the level of an auditor's professional skepticism in the auditor's choices is prior job experience. Regarding this, 759 businesses registered on the Iraq Stock Exchange were chosen between 2011 and 2021 using the systematic elimination approach. Due to the 2D structure of the logistic dependent variable, the research's regression model was put to the test. The outcome of the research hypothesis test revealed that the auditor's decision-making and judgment were significantly impacted by the economic climate at the start of their assignment. Additionally, it was discovered that businesses that have their financial reports audited by auditors during a recession are less inclined to do so. Our study supported prior research on a range of demographics, including economists, scientists, attorneys, investment bankers, and corporate executives, by demonstrating that the early career stage is a crucial era for auditors' formative development. Our findings may have wide-ranging repercussions for the auditing industry. Our findings imply that there may be a dearth of skeptic auditors in a region following extended periods of economic expansion. Our research serves as a first step in the direction of a deeper comprehension of the formation and recruitment of auditors in the labor market.
The effect of financial budgets on tightening the internal control system
Authors: Yaqoob Raed Muhammad , Benmabrouk Ouda
Published: January 2025

This study seeks to provide a primary goal, which is to increase the effectiveness of financial budgets in terms of provisions of internal control over service units in terms of preparation and implementation. (lik-erT) in measuring the answers, as well as analyzing the performance of the sample through a set of indica-tors. From this, the researcher concludes that the current traditional budget focuses on financial control and does not pay attention to reviewing and evaluating the results, and because it is unable to diagnose problems and provide solutions due to the inability to follow up and evaluate the performance of government pro-grams and activities.
A new technique for cataract eye disease diagnosis in deep learning
Authors: Mahmood Salwa Shakir , Chaabouni Sihem , Fakhfakh Ahmed
Published: January 2025

Automated diagnosis of eye diseases using fundus images is challenging because manual analysis is time-consuming, prone to errors, and complicated. Thus, computer-aided tools for automatically detecting various ocular disorders from fundus images are needed. Deep learning algorithms enable improved image classifi-cation, making automated targeted ocular disease detection feasible. This study employed state-of-the-art deep learning image classifiers, such as VGG-19, to categorize the highly imbalanced ODIR-5K (Ocular Disease Intelligent Recognition) dataset of 5000 fundus images across eight disease classes, including cata-ract, glaucoma, diabetic retinopathy, and age-related macular degeneration. To address this imbalance, the multiclass problem is converted into binary classification tasks with equal samples in each category. The dataset was preprocessed and augmented to generate balanced datasets. The binary classifiers were trained on flat data using the VGG-19 (Visual Geometry Group) model. This approach achieved an accuracy of 95% for distinguishing normal versus cataract cases in only 15 epochs, outperforming the previous methods. Precision and recall were high for both classes – Normal and Cataract, with F1 scores of 0.95-0.96. Balanc-ing the dataset and using deep VGG-19 classifiers significantly improved automated eye disease diagnosis accuracy from fundus images. With further research, this approach could lead to deploying AI (Artificial intelligence)-assisted tools for ophthalmologists to screen patients and support clinical decision-making.
Special Education Teachers in the First Year of Profession
Authors: Aktaş Burcu , Türker Yıldırım Çiğdem , Çifci Tekinarslan İlknur
Published: January 2025

Introduction: Experiences gained in the first years of the profession affect special education teachers' attitudes toward the profession. Therefore, understanding the first experiences and perceptions of special education teachers is essential for their attitudes towards the profession, retention, and success. This study aimed to examine in depth the experiences of special education teachers in the first year of their profession and their perceptions of success and failure related to these experiences.
Method: In line with the research purpose, the study was designed using phenomenology, one of the qualitative research method designs. The research group consisted of 17 special education teachers. The study group was determined by criterion sampling and snowball sampling methods among the purposeful sampling methods. Research data were collected through semi-structured interview forms developed by the researchers. Individual and focus group interviews were conducted with the study group during the research process. The data obtained from the research were analyzed inductively through thematic analysis. As a result of the thematic analysis of the research data, eight themes were reached.
Findings: The study results show that special education teachers have successful and unsuccessful experiences regarding the teaching process, institutional functioning, and cooperation relationships in the first years of their profession. Experiences gained in the first year of the profession affect teachers' professional goals, emotions, and expectations. In addition, research findings show that school environment, collaboration relationships, and student characteristics affect the experiences of special education teachers.
Discussion: The study's findings show that special education teachers' experiences in the first year of their profession are consistent with the findings of many studies in the literature.
Leveraging level data for accurate downstream flow prediction in the Narmada River Basin with advanced machine learning models
Authors: Kumar Vijendra , Rathnayake Namal , Reddy S. Hariprasad , Kedam Naresh , Rathnayake Upaka , Hoshino Yukinobu
Published: January 2025

Accurate river flow prediction is essential for effective water resource management and flood forecasting. This study investigates advanced machine learning (ML) models CatBoost, LGBM, Random Forest, and XGBoost for predicting downstream flow at ‘Mandleshwar' using level data from key stations in the Narmada River basin. The dataset, spanning 1978–2020 with over 15,000 daily observations, was obtained from India’s Water Resources Information System (WRIS). Rigorous preprocessing ensured high-quality input data for modeling. During training, XGBoost achieved an MAE of 0.0031, MSE of 0.00002, RMSE of 0.0048, and R2 of 0.99, effectively capturing flow dynamics. In validation, LGBM outperformed with an R2 of 0.95, MAE of 0.0646, and RMSE of 0.2262, while CatBoost, XGBoost, and Random Forest followed closely. In testing, XGBoost led with an R2 of 0.96, RMSE of 0.2326, and MAE of 0.0680, while Random Forest and other models also demonstrated strong predictive capability. The findings emphasize the utility of level data for downstream flow prediction and the effectiveness of ML models in hydrological applications. This study provides actionable insights for optimizing reservoir operations, flood mitigation, and sustainable water management, supporting policymakers in developing adaptive strategies for the Narmada River basin.
Assessment of natural fluoride contamination in water intended for human consumption from various regions in Tunisia
Authors: Selmi Rachid , Hadiji Rim , Mamlouk Aymen , Ben Said Mourad , Ben Youssef Samir , Gritli Abderraouf
Published: January 2025

Fluoride is a naturally occurring element present in the Earth's crust, which is released from rocks into the soil and water. Elevated levels of fluoride have been reported in phreatic groundwater worldwide, posing significant health risks to animals, plants, and humans. This study aims to assess the fluoride content in water intended for human consumption from both public networks and groundwater sources in various regions of Tunisia. A total of 46 water samples were collected between 2020 and 2021. The fluoride levels were determined using potentiometry with a combined Fluoride perfectION™ ISE selective electrode. The analysis revealed that fluoride content ranged from 0.351 to 6.016 mg/L. Samples exceeding the regulated limit of 1.5 mg/L were predominantly found in the southern areas of the country (64.3%, averaging 1.755 mg/L), regions known by hydrogeological fluoride deposits (54.8%, averaging 1.715 mg/L), and groundwater sources (75%, averaging 2.103 mg/L). Exposure of animals and humans to such high levels of fluoride poses a serious public health concern. Consequently, the implementation of a national strategy for the monitoring and control of public water resources intended for consumption is essential in mitigating the risks associated with fluoride contamination.
An investigation into the influence of climate extreme on groundwater regimes and human health in the Periyar Basin: A fast growing urban centre in India
Authors: Aditya Sanal Kumar , Krishnakumar Appukuttanpillai , Anoop Krishnan Krishnan
Published: January 2025

A total of 212 groundwater samples were collected during North East Monsoon (NEM), South West Monsoon (SWM), Pre-Monsoon (PREM), and Post-Monsoon (POM) seasons of 2020–2021 from the Periyar River Basin, draining the south western flanks of Western Ghats. The analytical results revealed the order of abundance of cations as Ca2+ > Na+ > Mg2+ > K+ and anions in the order of HCO3− > Cl− > SO42− > NO3− for all seasons. The major hydrochemical facies identified were CaHCO3 and mixed Ca–Mg–Cl in all the seasons with rock–water interaction as the key process regulating water chemistry. Ionic ratios of Ca2+ + Mg2+/Na+ + K+ and Ca2+/Mg2+ suggested significant effect of silicate minerals and other sources. The Water Quality Index (WQI) shows that the majority of the samples, namely, 98% in NEM, 86% in POM, 82% in PREM, and 95% in MON, fall in the categories ranging from excellent to good for drinking purposes. Furthermore, the health risk assessment based on carcinogenic and non-carcinogenic risk of the United States Environmental Protection Agency (US EPA) during monsoon and non-monsoon seasons for adults and children revealed the potential risk posed by Pb via oral exposure in the study area suggesting children being more susceptible to the damaging effects than adults.
Navigating the complex landscape of waterborne disease research
Authors: Khant Naing Aung , Lumongsod Regina Martha , San Arkar , Moon Jinah , Namkoong Sim , Kim Heejung
Published: January 2025

Waterborne pathogens and associated diseases continue to pose a significant global health challenge, requiring effective monitoring, detection, and treatment strategies. This review examines the current state of waterborne pathogen management, highlighting persistent issues and recent advancements. Here, we review cutting-edge detection methods and treatment technology, emphasizing their roles in water safety and outbreak prevention. The impact of climate change on waterborne pathogen dynamics is explored, alongside a discussion of interdisciplinary research approaches. We also aimed to investigate the crucial relationship between waterborne disease control and Sustainable Development Goals (SDGs), focusing on community engagement, well-being, water sanitation, public health policies, and international cooperation. The PRISMA protocol systematic process was used to filter papers for this study and carry out the review process. Machine learning and remote sensing techniques are promising features in the pathogen detection field. SDGs 3, 6, 11, 13, and 17 are the most closely interrelated with waterborne diseases. This review provides an in-depth overview of waterborne pathogen management, contributing to improved global water quality and public health strategies. This integrated approach aims to enhance health outcomes and promote resilience against waterborne diseases, particularly for vulnerable communities.
Institutionalized centralized management of large water network projects: An innovative solution to address water crisis
Authors: Yue Qiu , Changshun Liu , Xiaohui Jiang
Published: January 2025

Building large water diversion projects to form a grand national or regional water network is an important option to address the water crisis. It is necessary to explore the systems for managing large water network projects. This paper studied the management systems for large water network projects based on the institutional change theory. It put forward a set of innovative management options for the South-to-North Water Diversion (SNWD) project, the Three Gorges project and other similar projects in China. A comparative of these options, in both qualitative and quantitative terms, was conducted based on SWOT analysis and comprehensive expert evaluation. This paper finally proposed a recommended option, which requires the SNWD project, the Three Gorges project and the Danjiangkou reservoir to be managed together, and reservoirs along the three projects to be managed by local authorities.
Efficacy of water filters and training interventions in mitigating gastrointestinal symptoms in rural Honduras
Authors: Swearingen Colin , Alsouss Naya , Babic Marko , Clark Jacob , Dwyer Christian , Hudock Chase , Julien Laila , McGraw Patrick , Mekhel Rebecca , Mekhel Veronica , Patel Shubham , Tchepak Vladimir , Urbani Mia , Vasiliauskas Kathryn
Published: January 2025

This study examines the interplay between poverty, economic instability, and the water crisis in Honduras, highlighting the role of water filter interventions and training in mitigating gastrointestinal (GI) symptoms. The aims are to assess the effectiveness of point-of-use (POU) water filters and the impact of additional training on health outcomes. Data on water filter usage and training were collected during medical brigades in rural Honduras in May 2023, where patients reported GI symptoms. Two hypotheses were tested: individuals with POU filters would experience fewer GI-related symptoms, and those receiving additional filter training would report even fewer symptoms. Results showed significant reductions in symptoms, including loss of appetite, vomiting, diarrhea, and stomachaches among water filter users. Initial training was effective, while additional training showed potential benefits but was less consistently significant. This study emphasizes the importance of both providing filters and comprehensive training to maximize health benefits and the need for sustained efforts in promoting effective water treatment practices. These results support the adoption of POU filters and training programs to improve public health outcomes in regions with prevalent waterborne diseases. Future research should focus on the long-term impacts of these interventions to guide more sustainable clean water interventions.
Water quality health challenges in Iran's UNESCO Heritage arid regions: Focus on nitrate and fluoride
Authors: Karbalayi Mohadeseh , Zavar Zahra , Zarei Ahamad , Kobraei Mahshid , Kalankesh Laleh
Published: January 2025

Safe water quality is essential for human consumption. Therefore, this study aimed to investigate water quality and human health risks, including the hazard quotient (HQ) and the hazard index (HI). Samples were collected from six sites (S1–S6) of groundwater resources, including aqueducts (Ganats), cisterns, and the water distribution network of Gonabad city in autumn 2023. Data from the water quality index (WQI) show that the water distribution, cisterns (site 2 and site 3), Ganats (site 2 and site 1), and cistern (site 1) have good (WQI < 50), poor (WQI 50–75), and very poor (WQI > 75) quality for drinking purposes, respectively. The results of health risk models indicate that the HQ value exceeds World Health Organization recommendations for children at site S5. Moreover, the total hazard index (THI) levels ranged from 0.19 to 0.937 for adults and from 0.51 to 2.45 for children. Notably, the outcomes indicated that children were more susceptible to non-carcinogenic health hazards than adults (THI > 1). In conclusion, it is recommended that immediate action be taken to address groundwater resources to protect public health, with a particular focus on implementing measures to reduce exposure for children.
Changing Approach to Assessing Efficiency of State Programs, Illustrated by Implementation of State Programs in St. Petersburg
Authors: Sarimova A. I. , Sedova N. V.
Published: January 2025

Topicality of the research is stipulated by the necessity to elaborate and realize social and economic policy in the region. The principle mechanism of realizing strategy of social and economic development is state programs. The goal of the article is to advance an alternative approach to planning values of state program figures for the coming periods with due regard to factual results of the previous ones. On the basis of consolidated annual reports on state program implementation in St. Petersburg the level of target figures for 2023 was re-calculated. Results of the analysis showed that in calculating the level of attainment leaning on results of 2022 the value of more than 110% was obtained on 5 indicators from 54 in comparison with 17 indicators in calculation based on the fixed plan value. These findings can be used for further investigations, assessment of efficiency of state program implementation, effectiveness of top-officials’ activities and results of executive bodies’ work in entities of the Russian Federation.
Vertical Integration on Russian Metallurgical Market: Preconditions and Consequences
Authors: Braiko E. A.
Published: January 2025

The article analyzes the process of building metallurgical industry in Russia, key landmarks of its formation, which led to its current standing as vertically integrated companies. Key trends of integration were studied – forward and backward, it was explained in what periods of development these vectors were chosen and why. The author gave examples of both positive and negative experience of vertical integration illustrating it by leading Russian metallurgical companies. Apart from that, risks were shown which faced top-management of companies that made a decision about vertical integration. The author described changes that took place on Russian metallurgical market in the time of global economy turbulence in 2020–2023 and gave practical recommendations aimed at overcoming difficulties. The hypothesis was corroborated that structure of Russian metallurgical market as vertically integrated companies proved its stability and adaptive capacity in conditions of fast changing market situation.
Trends in State Support of Drone Aircraft Industry
Authors: Turkanov G. I.
Published: January 2025

The article deals with the development of drone aircraft industry, which is based on a number of fundamental economic and legal theories. Economic theories substantiate the necessity of state support stimulating innovation and protection of national markets, while theories of state and law provide legal base for safe and legal use of drone aircrafts. All together these theoretical approaches form the integral basis for efficient regulation and sustainable development of industry. In Russia the drone aircraft sphere is developing with considerable state support. In response to growing demand for drones in different sectors, such as transport, logistics, agriculture and defense the government take steps aimed at stimulation of production and introduction of drone technologies. Economic theories provide ideas how state and private sector could develop drone aircraft efficiently. They include concepts of state interference, competitive advantage, innovation and economy on scale. Clear understanding of economic aspects of investing in drone aircraft, the role of state grants and other types of support is important for estimating the potential of this industry and its economic impact. The development of drone aircraft systems can both strengthen defense possibilities and stimulate economic growth by creating new jobs and professional trends.
ESG Integration in the Light of Regression Analysis
Authors: Sevostyanov P. I. , Bogaturiya Z. V.
Published: January 2025

Ecological, social and corporate governance (ESG) becomes an important element in strategy of companies aiming at sustainable development. However, the process of ESG initiatives face serious challenges, including the absence of uniform accounting standards, expensive ESG strategy realization and shortage of reliable information. The goal of the present article is to study these problems and their impact on corporate governance. Using data of international consulting companies, such as McKinsey, MSCI, Sustainalytics, Bloomberg the authors analyzed problems dealing with ESG strategy realization and arising risks. The key component of the research is a mathematic model of multiple linear regression, which evaluates the quantitative impact of ESG factors on market company capitalization. The results of the analysis are demonstrated, they show the impact of ESG factors on company capitalization and it can explain the vector of their advance into corporate strategies. Provided conclusions have practical importance for business, researchers and regulating bodies wishing to improve integration of ESG practices in conditions of global economic turbulence. The novelty of the research includes the use of regression coefficient to evaluate ESG factors of market capitalization. These findings underline the necessity of well-balanced investment, data transparency and standard unification for successful ESG integration into corporate governance.