Methodist University

More frequent extreme rainfall has heightened the need to understand vegetation’s influence on slope stability in steep terrain. Among vegetation-related factors, root-system overlap, the intersection of neighboring root networks, remains understudied despite its potential to influence shallow landslide processes. Here we present laboratory flume experiments testing whether root overlap modulates slope stabilization, using pea plants (Pisum sativum) at 50 (V-005), 200 (V-02), 400 (V-04), and 1100 (V-11) stems/m2 densities. Landslide initiation was most delayed at V-11, while V-02 and V-005 failed at times comparable to the unvegetated control. V-04 had the smallest landslide area, while lower and higher densities produced larger landslides. Higher plant density increased root reinforcement, yet accelerated soil saturation via preferential flow along overlapping roots. The optimal balance of reinforcement, delaying hydrological triggering, and minimizing landslide size occurred between V-04 and V-11. This study reveals how vegetation density influences slope stability through root-driven geotechnical and hydrological processes. Vegetation density influences slope stability with higher root-system overlaps delaying landslide initiation and smaller landslide areas at moderate densities, according to lab flume experiments using pea plants with different densities.

Abstract. The objective need to strengthen the value of the Russian school actualizes the problem of developing the axiological competence of teachers. The purpose of the study: based on the analysis of the deficiencies of the axiological competence of teachers, to determine the current directions for the development of the content of additional professional education. Methodology and methods of research. The methodological basis of the study is the axiological, cultural, competence, activity and personality-oriented approaches. The article reflects the results of an empirical study conducted in the form of a questionnaire among school teachers (2147 participants), other surveys conducted in 17 regions of the Russian Federation in 2025 (more than 5 thousand participants) and the experience of implementing additional professional programs by the Institute of Content and Methods of Teaching named after V. S. Lednev were also taken into account. The results of the study showed that most teachers consider the problem of forming values in schoolchildren as relevant; only a quarter of teachers are confident in their own axiological competence, the majority feel the need for new experience in transmitting values to schoolchildren. Surveys showed the presence of contradictions in the process of developing axiological competence of teachers, which can be resolved in the process of additional professional education. Conclusion. In modern conditions, the axiological competence of teachers is intensively transformed for objective reasons, the emphasis is shifting to the values transmitted by teachers, axiological competence should be considered today as a basic component of the professional competence of teachers, and its new content should be determined by the value core of additional professional education.

ABSTRACT The Tarrant Formation is stratigraphically the lowermost unit of the Upper Cretaceous Eagle Ford Group in Texas, U.S.A. and consists of sandstone formed near the East Texas Embayment of the Late Cretaceous Western Interior Seaway during the middle Cenomanian (ca. 95.78 Ma). We examined the taxonomic composition of vertebrate fossils from the Tarrant Formation based on specimens acquired through surface collecting and bulk sampling from three localities within Tarrant County, Texas. The specimens collected in this study, combined with the published record, reveal a diverse vertebrate assemblage that consists of a minimum of 24 vertebrate taxa, comprising at least eight chondrichthyans (Ptychodus, Microcarcharias, Cretodus, Cretoxyrhina, Cretalamna, and three species of Squalicorax), 12 bony fishes (Protosphyraena, Plethodidae, two pycnodonts, two pachyrhizodontids, two ichthyodectiforms, two enchodontids, and two indeterminate taxa), and four tetrapod taxa (e.g. two plesiosaurs, dolichosaurid, and pterosaur). These taxa occupy a variety of trophic regimes, including piscivorous, durophagous, and opportunistic or scavenging taxa. As the first collective survey of the vertebrates from the Tarrant Formation of Texas, this study offers new insights into the palaeoecology of this area during the middle Cenomanian, a critical point in the early development of the Western Interior Seaway and the East Texas Embayment.

Commercial membrane electrolyzers rely on acidic fluorocarbon membranes and ionomers, requiring the use of expensive IrOx-based oxygen-evolution catalysts. Anion-exchange-membrane water electrolyzers (AEMWEs) operate in an alkaline environment, enabling the use of non-precious-metal catalysts. Here, we study and engineer CoOx-based catalyst-coated anodes deposited via hydrothermal synthesis directly onto porous transport layers both with and without thermal annealing. The self-supported, nanoneedle-structured Co3O4 anode, formed by annealing the as-synthesized cobalt carbonate hydroxide, Co(CO3)x(OH)y, outperforms the baseline Co3O4 nanoparticle ink-based anode in pure-water-fed AEMWE due to the improved catalyst-layer continuity and thus number of electroactive Co species. The as-synthesized and unannealed Co(CO3)x(OH)y, however, appears to undergo substantial conversion to a more-active CoOx(OH)y phase predominantly at the surface, with nominal Co3+ present and higher electrical conductivity, lowering the cell voltage to ∼200 mV at 1.0 A·cm–2 in pure-water-fed AEMWE compared to the conventional Co3O4 nanoparticle anodes. We analyze the differences in electrode electrochemical response between pure-water and KOH feed modes, finding distinct activation and degradation modes. The Co(CO3)x(OH)y anode shows significant activation and slower degradation linked to the conversion to oxyhydroxide. We propose catalyst layer designs that promote both hydroxide and electron transport, alongside interfacial engineering strategies to obtain high performance while mitigating anode degradation.

Hyperspectral image classification has been used in a wide range of applications such as environmental monitoring, agriculture, and defense. Graph convolutional neural networks (GCNNs) have rapidly become one of the most powerful techniques for modeling graph structured data and open up an entire new field in deep learning. This paper offers a comprehensive introduction to the filtering operations developed over graphs within GCNN literature. At the very center of GCNNs are graph filtering operations that play a vital role in processing, learning, and prediction on graphs. These operations are organized into spatial domain filtering, spectral domain filtering, frequency domain filtering, time domain filtering, hybrid filtering and attention mechanisms, graph pooling (DGCNN), and non-local filtering. In each title, different key methodologies are elaborated such as Graph Convolutional Networks (GCN), ChebNet, Graph Wavelets), Graph Attention Networks (GAT), and Non-Local Graph Neural Network (NL-GNN). The paper discusses practical challenges (over-smoothing, generalizability to different graph structures and unseen graphs, efficiency for large-scale graphs, and interpretability) of GCNNs. The overview illustrates this diversity of techniques that can be used for analyzing and learning from graph-structured data while shedding some light on these challenges. Knowledge of the basics of graph filtering explained in this article is an essential prerequisite for some cutting-edge applications like social network analysis, recommendation systems, drug discovery, and image segmentation. Next-generation GCNNs will have to overcome these challenges and improve their model interpretability if they are ever going to be useful in other domains outside graph-based ones.

The growing popularity of edge-based IIoT has created new security challenges due to the distributed and resource-constrained characteristics of edge devices. For this reason, it is crucial to monitor edge physical systems and detect malicious activity using an effective Intrusion Detection System (IDS). In resource-constrained edge networks, existing IDS frequently encounter problems such as excessive latency, scalability problems, and inefficiency because they either employ traditional methods or are not designed for edge-based IIoT deployment. Therefore, this paper presents a lightweight hybrid IDS for Edge-Based IIoT Security using deep learning techniques. In this study, the Enhanced Artificial Rabbit Optimization Algorithm (EAROA) determines the significance value for every input feature in order to determine the optimal feature subset. It makes it possible to eliminate unwanted and redundant attributes. A lightweight Modified MixNet network then analyzes these characteristics to determine the behavior of IIoT networks. In addition, we have addressed the issue of unbalanced data using a Conditional Tabular Generative Adversarial Network (CTGAN)-based data augmentation technique. Two publicly accessible datasets, the WUSTL-IIoT 2021 and Edge-IIoT datasets, are utilized to analyze the model’s effectiveness. The suggested model produced better results and detected attacks more effectively than current methods. These results demonstrate that the suggested approach is effective at detecting cyberattacks and demonstrates flexibility in identifying a wide range of cyberattacks in actual IIoT scenarios.

المستخلص هدفت الورقة البحثية الحالية إلى استقصاء مدى أثر استخدام نموذج الفورمات لمكارثي لتنمية مهارات الكتابة باللغة الإنجليزية لدى تلاميذ الصفوف العليا بالمرحلة الابتدائية. أربعة وستون تلميذا وتلميذة من تلاميذ الصف السادس الابتدائي تم اختيارهم كمشاركين في الدراسة البحثية. وقسموا بالتساوي إلي مجموعتي إحداهما تجريبه والأخرى ضابطة. اعتمدت الدراسة البحثية الحالية على التصميم شبه التجريبي ذي المجموعتين. المجموعة التجريبية 32 تلميذا وتلميذة من مدرسة عمر بن عبد العزيز الإبتدائية بمحافظة أسيوط, و32 تلميذا تلميذة من مدرسة الزهراء الإبتدائية بمحافظة أسيوط كمجموعة ضابطة وقامت الباحثة بتطبيق اختبار قبلي- بعدي لمهارات الكتابة قبل وبعد مادة المعالجة التجريبية وذلك في الفصل الدراسي الثاني من العام الدراسي 2024-2023. واستخدامت الباحثة أساليب إحصائية متنوعة لتحليل البيانات منها: المتوسطات الحسابية، والانحرافات المعيارية، وحجم الأثر، وقد تم عرض النتائج. وتوصلت الدراسة البحثية الحالية إلى أنه هناك فروق ذات دلالة إحصائية (عند مستوى الدلالة 0.01) بين متوسطي درجات مجموعتي البحث في التطبيق القبلي والبعدي لاختبار الكتابة لصالح الاختبار البعدي في المجموعة التجريبية. وبذلك تم التحقق من فروض البحث الخاصة بمهارات الكتابة. كما أوصت الدراسة البحثية الحالية بعمل دراسات مستقبلية علي توظيف تطبيقات أنماط التعلم في ضوء نموذج الفورمات لمكارثي في المنهج والمحتوى التعليمي، وكذلك البحث في تأثيرها على المهارات الأخرى.

Front Cover: The cover image is based on the Article Interaction of Phosphorylated C5aR1 With β‐Arrestin1: A Comparative Structural Modeling Study by Soumendra Rana et al., https://doi.org/10.1002/prot.70007. image

BackgroundAn estimated 2.3 million neonates die worldwide each year (47% of under-five mortality), with 75% occurring during the first week of life. The burden is highest in sub-Saharan Africa (n/N = 27/1000 neonatal mortality rate) and largely results from preventable conditions, such as prematurity, birth asphyxia, and infections. The Newborn Essential Solutions and Technologies (NEST360) programme supports health systems in resource-constrained settings (RCSs) through appropriate technologies, training, data use, and mentorship to reduce preventable neonatal deaths. The NEST360 programme, in partnership with the Kenya Ministry of Health, both inspired and enabled the development of evidence-based comprehensive newborn care protocols (NBU-Protocols) and a dissemination training. This article documents the development of the protocols and lessons learned to inform scalable solutions for RCSs.MethodsThe NBU-Protocols and their dissemination programme were developed through a review of evidence on the care for small and sick newborns, followed by iterative feedback from stakeholders, including frontline health workers, academics, and researchers. The protocols were piloted and further revised following a national stakeholder workshop.ResultsThe NBU-Protocols comprise three chapters: clinical care pathways; standard operating procedures for NBU equipment; and step-by-step instructions for common clinical procedures performed in level 2 NBUs. The protocols were grounded in family-centred care and infection prevention and control principles. They were presented as e-protocols with hyperlinks, bookmarks, and cross-references to facilitate ease of use. The protocols dissemination programme, called Newborn ETAT+, was a three-pronged training approach taught by experts in the following groups: clinical care pathways by paediatricians; equipment parts and functions by biomedical engineers; and equipment use and care by NBU nurses. A third of the training was dedicated to interactive lectures, with the remainder focussed on demonstrations, simulations, clinical procedures on manikins, and hands-on experience with NBU equipment.ConclusionsThe NBU-Protocols and training model highlight the potential of context-specific, multidisciplinary strategies to improve collaboration and standardise care in NBUs in low- and middle-income countries (LMICs).