bluuebunny/crossref_metadata_2025 huggingface dataset:
Semantic Segmentation Uncertainty Assessment of Different U-net Architectures for Extracting Building Footprints
Authors: Haghighi Gashti Ehsan , Delavar Mahmoud Reza , Guan Haiyan , Li Jonathan
Published: October 2024

Abstract. Automatic extraction of building footprints from aerial and space imageries has been found ever increasing importance in urban planning, disaster management, and environmental monitoring. However, achieving accurate building footprint extraction poses significant challenges due to diverse building characteristics and their similarities to their background elements. While conventional methods in building footprint extraction have mainly relied on image processing techniques, recent advancements in deep learning, particularly semantic segmentation algorithms like U-Net, have shown promise in addressing these challenges through machine learning. This study explores different depths of the U-Net model for building footprint extraction, aiming to identify the optimum architecture while investigating the semantic uncertainty of the building footprint extraction. Utilizing aerial imagery from cities including Berlin, Paris, Chicago, and Zurich, collected from Google Maps and OpenStreetMap (OSM) data, five U-Net models have been compared with varying depths. In addition, the impact of dataset sizes and learning rates on model performance has been investigated. Results confirmed that the U-Net-32-1024 model achieves the highest intersection over union (IoU), Accuracy, and F1-score. Moreover, increasing the training dataset size leads to significant improvements in model performance with IoU, Accuracy and F1-score reaching their values of 73.73%, 88.65% and 88.53%. However, challenges remain in accurately delineating buildings in dense urban areas. Nonetheless, our findings demonstrated the effectiveness of U-Net models in building footprint extraction.
Data-driven Strategies for Affordable Housing: A Hybrid Genetic Algorithm-Machine Learning Optimization Model in the Melbourne Metropolitan Area
Authors: Jafary Peyman , Shojaei Davood , Pishgahi Sara , Rajabifard Abbas , Ngo Tuan
Published: October 2024

Abstract. The escalating rental crisis in Australia, rooted in demographic dynamics, a scarcity of lands suitable for development and the influence of interest rates and government subsidies, necessitates innovative solutions for housing affordability. One promising approach is to increase the supply of affordable rental housing. Nevertheless, these efforts must be guided by well-informed policies as they are required to cater to the diverse needs of the stakeholders involved. Accordingly, this study aims to prioritize suburbs in the Melbourne Metropolitan area for the construction of apartment/unit buildings, benefiting both builders/investors and renters. Leveraging a hybrid Genetic Algorithm-Machine Learning (GA-ML) framework, multi-objective optimization models are developed to rank 105 suburbs based on key parameters for both builders/investors and renters. The optimization process seeks to maximize economic outlook and rental yields for builders/investors while minimizing rents and commuting distances for renters, in addition to proximity to essential amenities. First, an initial optimization using GA based on six key parameters is performed considering a linear multi-objective function. Subsequently, ML-based objective functions are defined using Random Forest (RF) and extreme Gradient Boosting (XGBoost) models to refine the optimization model for suburb rankings. The evaluation reveals strong correlations between GA and GA-XGB rankings, suggesting the effectiveness of the GA-XGBoost model in prioritizing suburbs. Notably, suburbs consistently prioritized across all models include Brunswick, Coburg, Preston and Reservoir, highlighting their suitability for apartment/unit building construction. By directing attention to specific suburbs aligned with different stakeholders' needs and preferences, this study contributes to a more sustainable and equitable housing landscape.
3D Building Modelling from ALS Point Clouds by Delaunay Triangulation and Graph Theories
Authors: Kong Gefei , Fan Hongchao , Lobaccaro Gabriele
Published: October 2024

Abstract. As an important task in 3D building reconstruction, 3D roof reconstruction attracts increasing attention. Existing methods have the issue of additional errors caused by multi-step processes, resulting in relatively high uncertainty and potentially affecting the reconstruction accuracy. Deep learning-based methods to achieve the direct extraction of roof vertices and edges for reconstructing 3D roof structures tackle the issue of additional errors while leading to another problem: the reliance on large labeled datasets for training. In this study, a fully rule-based method is proposed to achieve automatic 3D roof reconstruction. Roof vertices with their edges parallel to the x-y plane are first extracted from the point clouds, and subsequently, the left roof edges connecting vertices are inferred by using Delaunay triangulation. Finally, the 3D roof structure is reconstructed by using graph analysis based on the information of roof vertices and edges. This method simplifies the process of 3D roof reconstruction, and the experiment results demonstrate that the proposed method can effectively reconstruct 3D roof structures from point clouds.
Exploring Urban Vitality Characteristics and Interactive Mechanisms at the Community Scale through the Lens of Human Behaviour: A Case Study of Chongqing, China
Authors: Sheng Jiahui , He Yuqi , Lu Tao , Wang Fang , Huang Yunjing , Leng Bingrong , Zhang Xiang , Chen Yiqun
Published: October 2024

Abstract. Exploring urban vitality characteristics and interactive mechanisms are helpful for formulating policy, advancing urban planning and promoting sustainable development. However, the characteristics and influencing factors of urban vitality have not been thoroughly explored at finer spatial scales, especially for mountainous cities. In this work, the central urban area of Chongqing is selected as a case study, social, economic, cultural and comprehensive urban vitalities are quantitatively assessed at the community scale. Then, the OLS-XGBoost-SHAP model is innovatively utilized to identify the top influencing factors that interact strongly with urban vitality. Incorporating mountain city footpath and terrain factors, the nonlinear interactions among various factors and vitality are elucidated. The results indicate: (1) the central urban area of Chongqing presents a structure of two main areas, five subareas, and seven clusters. (2) The interaction between the POI diversity index and vitality exhibits a notable threshold effect. When the POI diversity index reaches 0.7, this factor significantly boosts community vitality. (3) The tolerance of transportation in mountainous cities is higher than that in plain cities. When the distance to the nearest subway station and bus station is less than 2000 meters and 650 meters, respectively, these two indicators have a significantly positive impact on urban vitality. (4) Considering mountain city footpath and DEM factors exhibit a strong interactive relationship with POI density, urban planners need to collaboratively optimize the construction layout of these three elements. These findings may provide important insights for people-oriented urban development and planning.
The Accuracy of RTK enabled Mobile Phones in RTK denied Areas
Authors: Strecha Christoph , Rehak Martin , Cucci Davide
Published: October 2024

Abstract. Surveyors often encounter challenges when tasked with measuring points in regions where buildings disrupt satellite visibility. The precise surveying of points in these areas typically relies on employing total stations. This method effectively extends high precision from unaffected zones (where satellite visibility is assured) to those areas where disruption occurs due to buildings. Total stations achieve this by executing distance and angle measurements from a reference point coordinate to the location where satellite visibility is compromised. The process is notably time-consuming, thereby incurring significant costs. Moreover, the intricate nature of this surveying process necessitates specialized skills and expertise, contributing further to the overall expense. In this study, we investigate an approach based on RTK (Real-Time Kinematic) enabled mobile phones and photogrammetry to achieve the same. In principle, this approach has a similar philosophy. However, instead of working with a few points with good satellite visibility that are obtained by a GNSS (Global Navigation Satellite System) rover, the procedure works with hundreds of observations with varying accuracy. Those accuracies depend on the satellite visibility. Each observation captures an image from the mobile phone together with the GNSS signal and its accuracy. Angle and distance measurements that traditionally are observed by a total station are retrieved by photogrammetry on the total image collection.
Spatial-temporal Data Model for Indoor Fire Response Considering Multi-Factors
Authors: Wang Jiahui , Jiang Jie , Guo Xian
Published: October 2024

Abstract. The complexity of high-rise building structures and functions significantly increases the challenges in emergency responses to indoor fire incidents. This complexity is due to multiple factors that must be evaluated for decision-making within the fire scenario, such as the entities within the building, the status of environment, and the actions of people. An effective and precise indoor fire emergency management model should fully take into consideration of multiple factors, aiming to ensure the safety and effectiveness of emergency response action.This paper proposes a spatial-temporal data model to integrate the entity-status-action, for designing the most suitable action strategies in various environmental status by considering all related entities in the indoor fire scenario. Firstly, a list of factors is designed to represent the scenario features including spatial location, semantic description, attribute characteristics, geometric form, evolutionary process, and the relationships among objects. Then, employs an ontology-based descriptive method to integrate multi-dimensions and effectively represents the interrelations among entities, actions, and environmental status within the context of an indoor fire scenario. These environmental status considered in the model focus on the supporting path-planning during execution of direct response actions. Finally, a set of path-planning rules has been developed to infer a series of environmental status supporting to formulate the optimal evacuation strategy to minimize the risk of evacuation failure. The case study shows that the proposed model is effective in unified expression for multitude of factors associated with emergency response in indoor fire scenario and supporting the decision-making of the emergency response actions.
Multi-Source Fusion Enhanced Feature Segmentation in Remote Sensing Imagery
Authors: Wang Siman , Zhou Qian
Published: October 2024

Abstract. With deepening application of deep learning technology in the field of remote sensing, several challenges persist in the segmentation of remote sensing optical images. These challenges include: (1) insufficient availability of deep learning-based remote sensing semantic segmentation datasets; (2) inadequate utilization of multi-source remote sensing data in the field of semantic segmentation; (3) limited sample size for effective model training, as well as the need to enhance both the speed and accuracy of model training. To address these challenges, this study introduces a multi-source remote sensing dataset consisting of 15000 data pairs, each comprising remote sensing multispectral data, synthetic aperture radar(SAR) images, land use and land cover(LULC) data, digital elevation model (DEM) data as well as the analysis data including Slope, Aspect, and Hillshade. Through the application of an end-to-end network based on pix2pix, effective fusion and feature enhancement of multi-source remote sensing data were achieved. The structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and Spectral Angle Mapper(SAM) values reached 0.84, 23.14, and 0.19, respectively, representing significant improvements over the baseline Pix2pix model’s performance metrics of 0.62, 18.84, and 0.23. In downstream semantic segmentation applications, the enhanced dataset was utilized to train semantic segmentation models for remote sensing image analysis. This approach effectively improved the training speed and segmentation accuracy of the models, with the mean intersection over union (mIoU) increasing from 0.467 to 0.481 and accuracy rising from 0.734 to 0.746. Moreover, the visual representation of remote sensing image segmentation demonstrated noticeable enhancements.
The Concept of Levels of Detail for 3D Niche Models in CityGML
Authors: Yang Su , Chen Jun , Hou Miaole , Fan Hongchao , Li Songnian , Sun Yingkui
Published: October 2024

Abstract. Buddhist niches in grottoes can be represented in three-dimensional (3D) for their detailed geometries on surfaces by using triangular meshes generated from point clouds. However, not all applications require 3D models with high geometric detail. The mesh models of niches have drawbacks such as large data volumes, lack of semantic information, and absence of spatial relationships between structural components and members within niches. Those limitations make mesh models suitable only for visualization and challenging to use directly in tasks like spatial analysis, simulation experiments, mechanical analysis, and disease investigation. To address this problem, this study defines four Levels of Detail (LoDs) for Buddhist niches, ranging from LoD0 to LoD3, drawing on the concept of LoDs for urban buildings in CityGML 3.0. As the LoD level increases, 3D models contain more detailed geometries, including spatial points, bounding boxes, niche structural components, and component members. Those 3D models at different LoDs can represent niches with varying degrees of abstraction, making them suitable for different applications and guiding the production of standardized 3D semantic models. To validate the feasibility of the LoDs definition for Buddha niches, this paper reconstructs 3D models of niches at different LoDs based on high-precision mesh models. Finally, a comparison is made between the original mesh model and models at different LoDs in terms of data size and potential application scenarios.
Spatial Big Data and Analysis Strategies Supporting Geographic Information System for Transportation (GIS-T) in Conceptual Design, Modelling, and Decision-making: A Review
Authors: Zhang Zehua , Song Yongze
Published: October 2024

Abstract. Transportation is a key component in urban design for cities’ efficiency and residents’ life quality, and GIS has the capability of handling data management, model design, and scientific decision-making for transportation studies. This article reviews how spatial big data and analysis strategies help GIS-T studies from the phases of conceptual design, modelling, and decision-making. In this research, we firstly summarized categorizes of data objects and relevant information for real-world issues from transportation applications in the conceptual design phase. In the modelling phase, optimization strategies for transport planning and accessibility measures through network data were also summarized. Finally, we reviewed spatial analysis methods in supporting transport decision-making, and how spatial methods take advantage of geography features of transport variables in previous studies. Our research primarily focuses on geography research with transportation topics as applications, and this work can help transport experts to have a better understanding of GIS values for transportation modelling and planning.
Geometry, Topology and p-Adic Numbers in Geospatial Data Modelling, Management and Processing: Review and Future Approaches
Authors: Bradley Patrick , Jahn Markus , Breunig Martin , Al-Doori Mulhim , Stefanakis Emmanuel , Kuper Paul
Published: October 2024

Abstract. Geometry and topology are both central concepts in geospatial data modelling and management. While geometry is the central concept for computational geometry applications, e.g. to intersect surfaces and solids in 3D space, topology is helpful for many application classes starting from city modelling to subsurface modelling and indoor navigation. Furthermore, p-adic numbers are useful for describing hierarchical processes on topological models. In this paper we first shortly review geometry- and topology-based approaches used for geospatial applications. We then describe our approach on turning geometry “upside down” focusing on topology during the whole process of distributed geospatial computing, data modelling, data management, and simulation. Furthermore, the way to use p-adic numbers for the description of hierarchical processes on topological models is shown for the example of simulation and the idea of p-adic analysis in distributed simulations is presented in the context of topological city and building models. The approach opens new insights such as topological relationships, components, and efficiently studying of the approximate behaviour of processes in the built environment using distributed computational systems. Finally, exemplary applications are presented to underline the importance of this new approach.
Comparison Study of Three Building Regularization Algorithms
Authors: Bulatov Dimitri , Mousa Yousif A. , Helmholz Petra
Published: October 2024

Abstract. Building outline generation and regularization is an ongoing topic in remote sensing applications. The success of the methods used for building outline detection impacts studies that depend on the accuracy of the methods applied, such as urban planning, geospatial analysis, and 3D city modeling. The results of the building outline detection methods can vary due to several factors, such as the area to which they are applied and/or the parameters used for the methods. Since there are well-established deep-learning based software and plugins for building outlining, this paper compares the results of such a method, namely an open-source AI implementation (Mapflow), with the standard non-deep-learning based tools introduced by (Mousa et al., 2019) and (Bulatov et al., 2014). We present a comparative analysis of these two methods for regularizing building outlines in terms of accuracy, efficiency, and robustness in dealing with different levels of buildings’ complexity and structures. While the results of (Mousa et al., 2019) and (Bulatov et al., 2014) are comparable and outperform the AI method, (Mousa et al., 2019) is the method least impacted by the different parameters, however, has a higher computing time.
Crowd Controls Crowd: Quality Improvement of Polygon Integration in Paid Crowdsourcing
Authors: Collmar David , Walter Volker , Soergel Uwe
Published: October 2024

Abstract. In this study, we introduce a crowd-driven data enhancement strategy for the integration of polygons in paid crowdsourcing. First, we capture redundant polygons with a web-based tool using one set of crowdworkers. Then, we present the acquired polygons to other crowdworkers in a polygon editing tool, with instructions to validate and improve those acquisitions. This procedure is repeated by showing a third set of crowdworkers the already edited polygon geometries. Furthermore, a polygon integration procedure is performed for every step, i.e., the unedited polygons, those edited once and those edited twice, allowing for a comparative qualitative analysis. This analysis is conducted with a focus on both quality and cost control, aiming for small sample sizes in order to optimize costs. Additionally, we conduct further investigations to assess the effectiveness of our approach in different use cases, and explore potential adaptions for further enhancement.
Hospital Accessibility Catchment Areas as a Fuzzy Lattice Data Structure
Authors: de Klerk Michelle , Fabris-Rotelli Inger
Published: October 2024

Abstract. The accessibility to basic facilities and services plays a pivotal role in every society and city planning. Spatial accessibility can vary between cities and countries and is mainly defined by the ease at which facilities can be accessed by communities. Facilities can provide essential services and/or products such as pharmacies, clinics, schools, universities, etc. Spatial accessibility is dependent on the spatial impedance between a facility and the target population and can be illustrated with catchment areas. We propose a fuzzy lattice catchment area method which uses a semi-supervised learning algorithm to create overlapping catchment areas. This methodology is applied to determine the accessibility to hospitals in South Africa and provides an illustration on the difference for regions with high accessibility compared to low accessibility. The application can easily be adapted in a variety of fields based on industry type, drive-time thresholds, supply capacity and the target population.
Sentiment Analysis of Google Maps User Reviews on the Play Store Using Support Vector Machine and Latent Dirichlet Allocation Topic Modeling
Authors: Zahrah Violita Aditya , Nurdin Nurdin , Risawandi Risawandi
Published: October 2024

These days, traveling is made easier by utilizing easily accessible online directions such as Google Maps. Google Maps provides real-time routes by displaying and presenting the closest routes that users can take. However, lately, the routes provided by Google Maps services often get users lost by presenting routes such as forests, narrow roads, and even dead ends. Therefore, this study aims to determine the level of user satisfaction and sentiment into two categories, namely positive and negative, based on reviews on the Google Play Store platform using the Support Vector Machine (SVM) algorithm and topic modeling using Latent Dirichlet Allocation (LDA) to find out the collection of topics that are the main topics of conversation by users regarding Google Maps services. The results of this study show that the SVM algorithm is feasible to use in sentiment analysis classification with an accuracy value of 86%, precision of 93%, recall of 53%, and f1-score of 52%. In addition, topic modeling is applied to generate coherence values for each topic, which shows that the higher the coherence value, the more specific the topic is. The highest coherence value generated in this study was two topic models with a coherence value of 35.15%, but this study took five with a coherence value of 33.39%. The five topic models to be applied in this study are selected because they have a good enough coherence value to identify the main topics and hidden topics in Google Maps user reviews with the Latent Dirichlet Allocation model. The topic model shows five aspects users often discuss: Google Maps route accuracy, system and service errors, navigation application directions, lost time history, and convoluted route provision.
Effectiveness and efficiency of patient care while enrolled in an orthopedic physical therapy fellowship program
Authors: Edmond Susan L. , Whitman Julie , Werneke Mark , Rodeghero Jason
Published: October 2024

Rationale: Post-professional orthopedic manual physical therapy education programs have proliferated, in part due to increasing therapist demand. Despite the time, effort, and money required to complete these programs, there is scant research addressing their impact.
We investigated whether physical therapists enrolled in an accredited manual physical therapy fellowship program achieved better outcomes, determined by patient changes in function, number of physical therapy visits, and episode of care duration while enrolled in the program. We also examined whether outcomes varied by clinician demographics, clinician life circumstances, and clinic characteristics.
Methods: Forty-two therapists contributed patient data addressing functional status, number of visits, and episode of care duration. We compared data from the first 30 patients with data from the last 30 patients seen by each therapist while enrolled in the program. We also surveyed therapists regarding their demographics, life circumstances, and clinic characteristics.
Results: There were no clinically meaningful or statistically significant differences in change in functional status when comparing results from the first 30 patients with the last 30 patients seen by therapists. However, there was a significant reduction in the number of visits and episode of care duration. Outcomes were influenced by entry-level degree and the presence of children at home.
Conclusion: In our study, enrollment in a physical therapy fellowship program did not improve patient functional status but did reduce the number of visits and episode of care duration. Outcomes were influenced by some clinician life circumstances and clinic characteristics.
PILOT PROJECT OF ASSESSING INTERNATIONAL TEACHERS’ RESEARCH COMPETENCIES
Authors:   A.Margulan Pavlodar Pedagogical University, Alimova Sholpan , Akhmetova Aigul ,   A.Margulan Pavlodar Pedagogical University, Cesur Kursat ,   Canakkale Onsekiz Mart University
Published: October 2024

The article reveals the importance of research competencies among domestic and international teachers of different educational institutions. The purpose of the article is to assess the demand and significance of research skills among teachers for future application in their professional activities. The review of the issue in recent literature and the analysis of questionnaires were completed to reach this purpose. The article considers the State obligatory standard of higher education, which establishes the standards for knowledge, skills, and levels, and indicates the necessity of finding solutions in the realm of research activities. During the study, the authors analyzed teacher questionnaires from various levels of educational institutions and demonstrated the rankings of the given general and professional competencies. The authors conducted the survey with open-ended and closed-ended questions to determine the interest of teachers in research activities. Additionally, the study processed statistical data using SPSS Statistics software. The measurement of reliability as Cronbach’s alpha coefficient was utilized, which indicated the consistency of the questionnaire items and the appropriateness of responses. The answers of Kazakhstani and foreign teachers were compared and contrasted by the researchers. According to survey results of teachers from seventeen different countries, teachers engage in scientific research activities during the teaching process that change the way teachers perform their duties. They showed 100% interest in research activities, and 70.6% of the teachers were adamant that university influences education students’ decisions to pursue careers as researchers.
APPROACHES TO TEACHING EUROPEAN CONCEPTSCONSIDERING NATIONAL CHARACTERISTICS
Authors:   Akhmet Baitursynuly Kostanay Regional University, Nurseitova Aishagul , Kaipbayeva Aizhamal ,   Akhmet Baitursynuly Kostanay Regional University, Akdauletova Zhanar ,   Akhmet Baitursynuly Kostanay Regional University, Tasmagambetova Zeinat ,   Akhmet Baitursynuly Kostanay Regional University
Published: October 2024

The article cites examples of the issued related to the communicative competence formation.These issues have been effectively examined through various research methods, including logical and comparative analysis, formal interviews, and informal conversations. These approaches allow for a comparison of the characteristics of both countries, incorporating the views and experiences of the students themselves. Through a functional methodological approach, the purpose and objectives of the article have been determined. This enabled to fully reveal all aspects of the issue under review. Also, a systematic methodological approach formed the basis of the direct workflow. At the same time, the methods of forming communicative competence were examined. The core concepts associated with the research problem were thoroughly examined using an analytical approach. The comparison method is integral to this study, as the article highlights examples of communicative competence, clarifies European terms, and presents methods for understanding them while taking into account Kazakh national beliefs and values. A survey was conducted among students, and a methodological conclusion was drawn based on the findings. The article emphasizes the importance of the issues discussed, noting that each nation has its own distinct characteristics. In light of ongoing efforts to revive traditional Kazakh customs and practices, the topics covered in this article are particularly relevant.
PARENT PARTNERSHIP IN PSYCHOLOGICAL AND PEDAGOGICAL SUPPORT IN THE CONTEXT OF INCLUSIVE EDUCATION
Authors:   Arkalyk I.Altynsarin Pedagogical Institute, Musirova Gulim , Tauekelova Anar ,   Arkalyk I.Altynsarin Pedagogical Institute, Akylbekova Elmira ,   Arkalyk I.Altynsarin Pedagogical Institute, Seidina Balmuzdak ,   Arkalyk I.Altynsarin Pedagogical Institute
Published: October 2024

The article pays special attention to the place and importance of parents in the psychological and pedagogical support in the context of inclusive education. Children with disabilities have an impact on the quantitative and qualitative indicators of students with special educational needs, a global problem is widespread in our country. A child requiring special attention is highly dependent on their parents, making their proper attitude and support invaluable in the child's life. The article analyzes the need for comprehensive psychological and pedagogical assistance for such families. The purpose of the study is to address the issue of partnership in supporting parents with children in the context of inclusive education. Task: to study the importance of the rehabilitation potential of parents with children within an inclusive education environment, to analyze the impact on child support. The study highlights the forecast for the effectiveness of parent partnerships in psychological and pedagogical support within inclusive education. It was noted that in an inclusive setting, positive parental influence on the child optimizes their relationship with the social environment. The implementation of established patterns in a civilized state increasingly emphasizes the importance of psychological and pedagogical support in inclusive education. Maximizing this development, while ensuring the successful completion of the general education program tailored to the individual characteristics of each child, is among the key issues in modern education.
PSYCHOLINGUISTIC MARKER OF CYBERBULLYING IN THE SCHOOL ENVIRONMENT: EMPIRICAL STUDY RESULTS
Authors:   Akhmet Baitursynuly Kostanay Regional University NLC, Kalimzhanova Roza , Rakisheva Gulmira ,   Sh.Ualikhanov Kokshetau University NLC, Sabitova Diana ,   Sh.Ualikhanov Kokshetau University NLC, Zhantemirova Madina ,   Sh.Ualikhanov Kokshetau University NLC
Published: October 2024

The article presents the results of a psycholinguistic analysis of network communication among schoolchildren. Internet communication is an important component of communications in the modern world. As they interact with others, schoolchildren form a variety of social relationships, both in real life and online. Through these interactions, they develop a system of values and gain a sense of their role within social and interpersonal dynamics. However, these environments can also give rise to conflicts, misunderstandings, differing opinions, and expressions of negativity, aggression, and confrontation. As a rule, destructive communicative behavior in the virtual space is expressed in posting obscene language, provocative content of a manipulative, propagandistic nature, as well as offensive messages aimed at personal insulting other users. The relevance of the study is related to the need to identify and prevent the spread of aggressive behavior of schoolchildren on the Internet, the urgent need to create a favorable climate in cyberspace and a safe educational environment. The empirical data obtained as a result of the study allowed to identify a psycholinguistic marker of cyberbullying to study its impact on the socialization of adolescents; the issues of strengthening the psychological health of schoolchildren as a factor in the prevention of cyberbullying are highlighted. The authors believe that the summarized results of this study can serve as guidelines for the development of an effective system for the prevention of cyber threats in the network socialization of schoolchildren.
NATURAL REGENERATION OF FRAXINUS SOGDIANA ASH-TREE IN THE RELICT ASH GROVE
Authors:   S.Seifullin Kazakh Agro Technical Research University, Mazarzhanova Kuralay , Amirova Zhuldyz ,   S.Seifullin Kazakh Agro Technical Research University, Sartbayev Zhiger ,   Charyn State National Natural Park RSU, Nurlabi Ainur ,   S.Seifullin Kazakh Agro Technical Research University
Published: October 2024

The article reviews the literature data and the process of natural regeneration of growing conditions of the Sogdian ash-tree located in the Charyn ash grove, Almaty region. Research purpose: to determine the natural regeneration and adaptation to the environment of Sogdian ash-tree. Objectives: establishment of sample areas along the terraces, determination of tree, shrub species growing on the grove territory, calculating natural regeneration, analyzing adaptability to the environment. In the Charyn State National Nature Park research on natural regeneration of Sogdian ash-tree (Fraxinus Sogdiana Bunge) was conducted on cordons 1,2,6 in the Sarytogay valley. To study the natural regeneration process of the ash grove along the terraces, test plots of different sizes were established: 100 m x 100 m, 50 m x 50 m, and 25 m x 100 m. On these plots, measurements of young ash growth were conducted at 10-meter intervals using 2 m x 2 m sample areas. The data collected provided indicators of the viability of young ash shoots. In the course of the research work the natural process of Sogdian ash-tree regeneration, i.e. the state of growth of viable young shoots was studied. All obtained results are reflected in the form of a table, statistical analysis was carried out. The process of natural regeneration of the Sogdian ash-tree, a valuable species of the state forest fund, is multifaceted, encompassing biological, forestry, ecological, economic, and social aspects. The results obtained can be used in research by students, master's students, doctoral candidates, as well as forestry specialists.
PRODUCTIVITY OF FORAGE CROPS IN THE STEPPE ZONE OF THE NORTHERN KAZAKHSTAN
Authors:   L.N. Gumilyov Eurasian National University, Tynykulov Marat , Malitskaya Natalya ,   M. Kozybayev North Kazakhstan State University, Tleppayeva Aigul ,   S. Seifullin Kazakh Agro Technical University, Auzhanova Mariya ,   Sh. Ualikhanov Kokshetau State University
Published: October 2024

The article presents the results of a comparative evaluation of unconventional annual forage crops based on their productivity in the steppe zone of the Northern Kazakhstan. The subjects of the study were varieties and hybrids of Sorghum-sudan grass hybrids, Zea mays, Echinochloa frumentacea and Pennisétum gláucum. The relevance of the topic lies in the selection and introduction of new, more productive and drought-resistant forage crops for the steppe zone of the Northern Kazakhstan. The objectives of the study are to examine the features of growing forage crops in the steppe zone of the Northern Kazakhstan; conduct a comparative assessment of the productivity of forage crops; and identify the most promising forage crops for cultivation in the steppe zone of the Northern Kazakhstan. The scientific significance of the paper lies in obtaining new data on the comparative productivity of various forage crops in the conditions of the steppe zone of the Northern Kazakhstan. The study used the following research methods: the experimental method by B.A. Dospekhov, the vegetation accounting method by D. Braun, and the soil moisture determination method by N.M. Bakayev; laboratory analyses; and mathematical processing of yield data. The study results showed that the sorghum-sudan grass hybrid had the highest yield: 209.1 c/ha of green mass and 32.6 c/ha of dry matter. Corn and the sorghum-sudan grass hybrid showed a balanced content of crude protein and crude fiber in the forage. The yield of Echinochloa frumentacea and Pennisétum gláucum is lower but still sufficiently high compared to corn and the sorghum-sudan grass hybrid.
Development of the whole-brain functional connectome explored via graph theory analysis
Authors: Hassett Jordan D. , Craig Brandon T. , Hilderley Alicia , Kinney-Lang Eli , Yeates Keith O. , MacMaster Frank P. , Miller Jillian , Noel Melanie , Brooks Brian L. , Barlow Karen , Lebel Catherine , Kirton Adam , Carlson Helen L.
Published: October 2024

Introduction

Adolescence is a period of remarkable development as children’s brains change to resemble adult brains. Resting state fMRI measures fluctuations in blood-oxygen signal from which we can infer functional connectivity (FC). Graph theory is a branch of mathematics that can quantify the complex patterns of connectivity and network architecture inherent in the functional connectome. An ideal graph theory analysis explores edges that are weighted, directional, and heterogenous (can be positive or negative). Recent developmental studies have applied graph theory to the functional connectome, yet due to the considerable complexity added by each facet, most ignore one or more aspects of an ideal graph theory analysis (directionality and heterogeneity).

Methods

The present cross-sectional study measured FC in typically developing children, adolescents, and young adults (age 6-24 years) using 150+ echo-planar volumes (3.6mm isotropic voxels, repetition/echo time=2000/30ms) acquired at rest. A standard pre-processing pipeline was used, and the functional connectome was quantified using a weighted, directed graph analysis, including both positive and negative connections. Five different graph theory metrics were utilized to quantify developmental trajectories: connection density, modularity, clustering coefficient, global efficiency, and betweenness centrality. Positive and negative connections were analyzed separately, and age and sex associations were explored.

Results

The total sample comprised 219 participants (mean age (SD) [range] = 14.1 (3.3) [6.5-24.0] years, 50% female). For positive connections, modularity and betweenness centrality increased with age (both p<0.001), while connection density, clustering coefficient, and global efficiency decreased with age (all p<0.001). By contrast, for negative connections, modularity and betweenness centrality decreased with age (p=0.002, p=0.003), while connection density, clustering coefficient , and global efficiency increased with age (p<0.001, p<0.001, p=0.003). Effects of sex, hemisphere, and their interaction were minimal, though global efficiency for negative connections was higher in the right hemisphere than the left (p<0.001).

Conclusion

Graph theory appears to be a useful tool for quantifying the complex development of the functional connectome. The developmental changes presented here may be driven by an intrinsic pressure to balance functionality with low metabolic cost to maintain the network. The positive connection network appears to shift towards a more efficient conformation resembling “small-world” architecture. In contrast, the negative connection network seems to shift away from such efficient architecture, possibly to prioritize improving functionality before later refinement.
Proximate Constituent and Mineral Content of the Seeds of Africa Yam Bean (Sphenostylis Stenocarpa) Purchased in Ebonyi State, Eastern Nigeria
Authors: O. T. Okoaluu, , A. I. Izundu,
Published: October 2024

In sub-Saharan Africa there have been various calls for development of a crop which will be high yielding with increased protein content. One of such plants currently being speculated to be an important source of high protein, carbohydrates, as well as other nutritional substances is African yam bean (Sphenostylis stenocarpa Hochst ex A. Rich. Harms). This work is therefore designed to ascertain the proximate, mineral, vitamin and phytochemical composition of the seed of African yam bean. The seeds of African beans were analyzed for proximate mineral vectorment and phytochemical composition using standard methods. Data were subjected to statistical analysis using ANOVA. The results of the percentage proximate composition showed that the seeds contain 8.67% moisture, crude protein 22.22%, crude fiber 3.89%, ash 4.58%, fat 4.20%, and carbohydrate 56.44%. The mineral contents (mg/100g) were found to be 32.07 mg/100g (Sodium), 231.20 mg/100g (Potassium), 78.67 mg/100g (Magnesium), 159.66 mg/100g (Calcium), 133.53 mg/100g (Phosphorus), 2.32 mg/100g (Zinc), and 6.13 mg/100g (Iron). Africa yam bean is an important source of high-quality protein and carbohydrate, as well as other nutritious substances. The present constituent, especially their quantitative composition, may be an indication of the nutritional as well as medicinal importance of the seeds of Africa yam bean. Such interesting high content of certain bioactive compounds, such as phenol and flavonoid as well as elevated protein content, calls for improved cultivation of this crop for maximum yield and availability.
Lantana Camara Linn: A Review on Chemical Constituents and Medicinal Approach
Authors: Patel Suhana Ajaj , Nawale Sejal Navnath
Published: October 2024

The use of plant-based medicine has a long history in India. Few herbal medications out of the many that are used in India have received thorough research to far. An evergreen plant native to India is called Lantana camara. Scientific evidence has backed the traditional uses of it in the treatment of a wide range of illnesses. There are phytoconstituents in every area of Lantana camara, according to a number of literatures. Scientists and researchers have been extensively studying the chemical makeup of the entire L. camara plant as well as its biological pharmacological properties for the past few decades, all over the world. As a prospective candidate for drug discovery, these research demonstrated the medicinal potential of Lantana camara in contemporary medicine. This page discusses Lantana camara’s toxicological and pharmacological properties.
Remediation Strategies of Xenobiotics in Urban Soils and Water: A Review
Authors: Kumari Raj , Mittal Abhilasha , Sharma Meenakshi
Published: October 2024

Xenobiotic substances are synthetic chemicals that are not native to a specificecological system yet have biological activity. Drugs, industrial chemicals, naturally occurring toxins, and environmental contaminants are all examples of xenobiotics. By disrupting or interfering with many cellular communication routes that control growth, development, and normal physiological function, xenobiotics can have a negative impact on human health. These chemicals are extremely poisonous in nature and can harm both lower and higher eukaryotes. These substances are persistent, allowing for bioaccumulation or biomagnification in the environment over time. They also find their way into food chains, where their concentrations are found to be high even in creatures that do not come into direct contact with xenobiotics. Industries regularly release xenobiotics into the environment, increasing the danger of human and other biota exposure. Despite the use of a variety of traditional and modern environment remediation technologies, some of them are unsuccessful at eliminating xenobiotics, while others are too expensive to use on a wide scale. Maize Stover and Rice Husk are abundantly generated across the world, making them attractive and cost-effective feedstocks for large scale biochar synthesis for environmental clean-up. Because virgin Maize Stover and Rice Husk biochar may not be successful in removing some xenobiotics, adding modifiers to MS/RH biochar can help to generate composite MS/RH biochar, which can aid to disinfect water and soil more effectively. Some microbes have the ability to partially or completely break down xenobiotic substances. The most dependable ways for degrading these chemicals are biological and non-biological remediation procedures. Bacterial biodegradation is a cost-effective approach for land filling and composting that employs both wild type and genetically engineered bacterial strains. Many non-biological approaches that are suited for xenobiotic degradation have been categorised under thermal and non-thermal procedures.
A Comprehensive Review on Phytochemicals and Pharmacological Activities of Digera muricata (L.)
Authors: S. Ippar Anita , S. Shaikh Habeeba
Published: October 2024

Digera muricata (L.) Mart belonging to the Pigweed family that is the Amaranthaceae. These are commonly known as “False Amaranth” or “Tartara”. It is an annual medicinal herb native to Egypt to E. Kenya and Malesia. In India it is found throughout states as a weed. It is traditionally folk system of medicine. D.muricata (L.) Mart is a medicinal plant use as cooling agent and astringent in Ayurveda. D. muricata (L.) Mart is pharmacologically known for it's Antimicrobial, Antibacterial,Antifungal, Antidiabetic, Anti-fertility, Antioxidant ,Anticancer, Antileishmanial, Antitesticular, Prophylactic agent, Allopathic and Protective effect. It also used in Nephrotoxicity, laxative, diuretic, treat renal disorder, and prevent pus formation locally. Boiled root infusion of D. muricata (L.) Mart is used in mother child birth for lactation purpose. The phytochemical screening of D. muricata (L.) Mart revealed the presence of various primary metabolite such a Proteins, Carbohydrates, Chlorophylls, Amino acids, Reducing sugars, Lipids and Secondary metabolite such as Phenols, Flavonoids, Terpenoids, Saponins, Tannins,Cardiac glycosides, Anthraquinone. It also contains an Alpha and beta Spinosterol,Rutin, Vitamins like Ascorbic acid, Thiamine, Riboflavin also Enzymes superoxide, Peroxidase. It contains a mineral such as K>Ca>Mg>Na>P>Fe>Zn>Cu.