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DEHISCENCE AND PROTRUSION OF NEUROVASCULAR STRUCTURES ADJACENT TO THE SPHENOID SINUS: COMPUTED TOMOGRAPHY ANGIOGRAPHY FINDINGS
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Classification of User Consumption Data-Based Consumer Profiles Using AI
No full textOver-the-top (OTT) apps, which give users access to a variety of multimedia content, have seen a sharp increase in appeal in recent years. Therefore, it has become crucial for platform suppliers and advertising to comprehend customer behavior. This research suggests the development of a user consumption categorization system based on machine learning (ML) such as Decision Tree (DT), Random Forest (RF), Regression Algorithm, k-Nearest Neighbour (KNN), Bayesian Algorithm (BA), Gradient Boosting (GB), and XGBoost Classifier in order to categorize users based on their consumption rate, which may be classified as low, medium, or high. The study will use data preprocessing methods to customize the data and prepare it for clustering. The next step is to compare the accuracy of various ML models to determine which one best predicts the user’s usage rate. We will explore the boundaries of each algorithm and merge the system with data mining and analytics tools. This study will progress the field of machine learning by providing a practical application for categorizing user consumption patterns and may be helpful to OTT platform providers, marketers, and data analytics specialists
Logistics performance and agricultural exports: evidence from Sub-Saharan Africa
No full textThis paper investigates the relationship between logistics performance and agricultural exports in Sub-Saharan Africa. Using dynamic panel data from 2012 to 2022, we examine the impact of various components of logistics performance on aggregate agricultural exports. We also analyse how logistics performance affects exports in agricultural subsectors. Our results show that improvements in logistics infrastructure, customs procedures, and international shipping services significantly increase agricultural export performance. The food and live animals subsector benefits the most, followed by crude materials and animal and vegetable oils and fats subsectors. We also find that financial development, foreign direct investment, and world demand are important drivers of agricultural exports in Sub-Saharan Africa. We include institutional quality indicators in our analysis for robustness checks, showing that governance factors also play a significant role in boosting exports. These findings highlight the need for targeted investment in logistics and complementary economic policies, supported by good governance, to harness the region's agricultural export potential and promote sustainable economic development
Evaluating the Sustainability Consequences of Omitting Structural Analysis in Reinforced Concrete Projects in Burundi
Get PDFSustainable construction has evolved into a global priority to mitigate the impacts of climate change, as the construction industry significantly contributes to environmental degradation and the overexploitation of resources. This study considers the effects on sustainability, particularly the inadequate management of resources, the ecological impact, and the anticipated degradation of the structures, all of which are due to the omission of the structural analysis during the design phase of the reinforced concrete (RC) structure. A methodical survey was conducted in three major cities among 258 professionals in the construction sector in Burundi, a developing country that has suffered socio-political and infrastructural challenges. The study examines the impact of these challenges on construction results. Quantitative analysis was carried out using SPSS v.30 and Amos 26 Software. For this research, reliability analysis, Kaiser-Meyer-Olkin test (KMO), Bartlett test, Exploratory Factor Analysis (EFA), Principal Component Analysis (PCA), and the Relative Importance Index (RII) were used to ensure the reliability and accuracy of the data. The results indicate that many projects are taking place in the absence of proper structural analysis due to financial constraints, poor quality materials, lack of qualified personnel, poor enforcement of regulations, and insufficient monitoring. These parameters have led to structural deficiencies compromising sustainability. The study recommends that government agencies, professional construction workers, and building owners improve regulation, teaching effectiveness, and professional responsibility to ensure that fundamental practices, such as structural analysis and the use of right sustainable materials, are logically applied to improve public safety and environmental resilience
Ritz Variational Formulation and Solutions for a Seventh Order Polynomial Shear Deformable Beam Buckling Model
No full textThe aim of this paper is to develop Ritz variational formulation of a seventh-order polynomial shear deformable beam buckling model and use the Ritz method to obtain the buckling load solutions for simply supported boundary conditions. The work is inspired by the need to develop buckling equations and solutions for thick beams, since the classical thin beam theory (CBT) overestimates their buckling load capacities and is unsafe for use in the stability analysis and design of thick beams. The key contribution of the work is that a seventh-order polynomial shape function is used to represent the shear stress variation through the beam thickness resulting in a higher order polynomial shear deformable model. The polynomial constants are determined using a rigorous requirement that the resulting transverse shear stress is zero at the top and bottom surfaces of the beam. Another merit of the work is that the model thus satisfies the transverse shear stress-free conditions at the beam surfaces and does not need transverse shear stress correction factors. The model assumes small displacement elasticity behavior in constructing the strains from the displacements and one-dimensional constitutive law to find the stresses. The total potential energy functional is then found as the sum of the strain energy and the work potential of the in-plane compressive load. The integrand in is a function of the transverse displacement w(x) and the rotation of the middle surfaces The equations of stability are obtained by seeking a minimization of with respect to the displacement parameters of w(x) and The resulting eigenvalue problem is used to find the buckling loads at any buckling mode, n; the critical buckling load occurs at the first buckling mode, n = 1. The critical buckling load coefficients Kcr are closely identical to previous results. It is found that for l/h = 4, the present results for Kcr is 15.74% lower than the Kcr results by CBT, showing that CBT is not safe for buckling analysis and design of thick beams. It is also found that for l/h = 100, the present results are close to the Kcr results by CBT; showing that the present model adequately caters for thin beam buckling problems as well. The implication of this study is that it has effectively demonstrated that for thick beams with l/h = 4, the critical buckling load Ncr is 15.74% lower than the Ncr found by CBT, rendering CBT unsafe for the critical buckling analyses of thick beams. Another significant finding in this study is that the model gives the same results as the CBT when the l/h ratios are within the range of thin beam theory, making the model generally applicable to both thick and thin beam buckling problem
Multiview Spinal Fracture Detection in Radiographic Projections Using Graph-Based Convolutional Fusion of X-Ray Views
No full textThis research proposes a high-accuracy graph-based deep learning framework for multiview spinal fracture detection, integrating anatomical graph construction, convolutional encoders, and attention-guided fusion across radiographic projections. Utilizing a hybrid CNN-GCN architecture, the system models vertebral structures as nodes within a spatially coherent graph, enabling topological reasoning and cross-view feature alignment. Evaluated on multiview datasets comprising AP, lateral, and oblique projections, the model achieved vertebral-level detection accuracies up to 96.3%, with F1-scores exceeding 0.903 across diverse fracture types, including compression, burst, and multisegment injuries. Compared to conventional single-view CNN approaches, this framework demonstrated a 5.1%-5.5% improvement in diagnostic accuracy and a 24% increase in sensitivity for subtle or complex fracture patterns. The inclusion of inter-view consistency constraints and multiscale fusion layers enabled robust generalization across varied patient anatomies and projection combinations. With inference times below 200ms per multiview study and end-to-end trainability, the model supports real-time deployment within radiology workflows. Its modular, view-invariant design ensures compatibility with evolving imaging protocols and scalability for large-scale clinical deployment
Traces of earthquake: traumatic life experiences and their effects on volunteer nurses in the earthquake zone-an interpretative phenomenological study
No full textIntroduction: It is crucial to understand the effects that traumatic events related to natural disasters have on individuals in as much detail as possible. However, the literature investigating the traumatic life experiences of nurses, who play a key role in disaster management, is still limited.
Objective: The aim of this study was to explore in depth the traumatic life experiences of volunteer nurses who participated in relief efforts after two major earthquakes in the southeastern region of Türkiye.
Methods: This qualitative study was conducted using a phenomenological design. The study sample consisted of 16 nurses selected by the purposive and snowball sampling methods. The data were evaluated using interpretative phenomenological analysis in the Maxqda 2020 program.
Results: Four themes were generated: (1) shocking facts, (2) coping methods, (3) traumatic stress reactions, and (4) traumatic growth.
Conclusion: While traumatic life experiences in the earthquake area led to acute stress reactions in the volunteer nurses, these experiences also contributed to their traumatic growth and development. Healthcare managers and policymakers should develop comprehensive strategies and intervention programs to safeguard the mental health of nurses in the context of natural disasters. It may also be useful to improve clinical education programs and support systems by reviewing international policies and procedures
Benzothiophene semiconductor polymer design by machine learning with low exciton binding energy: A vast chemical space generation for new structures
No full textThe development of new organic semiconductors with low exciton binding energies (Eb) is crucial for improving the efficiency of organic photovoltaic (PV) devices. Here, we report the generation of a chemical space of benzothiophene (BDT)-based organic semiconductors with lowest Eb energies using machine learning (ML). Our study involves the design of over 500 organic semiconductor structures with low Eb energies and their synthetic accessibility scores. For this, we collect 1061 BDT based compounds from literature, calculated their Eb energies, and predicted them using ML with Random Forest (RF) regression, yielding the best results. Our analysis, using SHAP values, reveals that heavy atoms are the main factors in lowering Eb values. Furthermore, we tested new organic chromophore structures, which showed an efficient shift of their molecular charges. The UV–Vis spectra of these structures exhibits a redshift in the range of 358–667 nm, while their open-circuit voltage (Voc) and light-harvesting efficiency (LHE) ranges from 1.64 to 1.954 V and 52–91 %, respectively. Current study provides a valuable chemical space for the development of new organic semiconductors with improved efficiency. © 2025 Elsevier Lt
Unique MIMO system using Gaussian signals and the advantage of these signals in sensing CSI and multipath fading
No full textTo improve communication network efficiency, researchers must look at all aspects of transmission and the mechanisms that regulate their evolution as a whole. These features include solutions for dealing with the channel's noise and interference. To decrease interference and increase spectrum efficiency, orthogonal frequency division multiple access (OFDMA) systems employ orthogonal signals. While transmitting and receiving signals, noise and numerous feeds can be done in diverse ways. It has become increasingly common to use 256 quadratic modulation (QAM), which is more vulnerable to noise and has a higher bit error rate (BER). BERs in OFDM systems were high when multiple feeds and noise were present, as demonstrated in this article. Starting with the transmission and reception of Gaussian subband signals, an improved system has been designed that includes numerous stages of development. Thus, the need for “orthogonally” of transmitted signals to increase spectrum efficiency has been eliminated, as has the effect of surrounding channels. We have created a header for every frame that has been transmitted. Several transmitters and numerous receivers send these frames in parallel so that the channel state information (CSI) attributes may be evaluated using parallel processing. Using the identical transmission conditions for both OFDM systems and the proposed system, the simulation results reveal a significant reduction in BER values. This results in BER values of fewer than 10−1 when there are two tabs and 10−1 when there are three tabs for multiple feeding in the OFDM system. This corresponds to BER values of 10−11 in a suggested system when there are three tabs. Some improvements have been made to the proposed design to make it distinctive and qualified to be regarded as a multiaccess system in today's contemporary communication infrastructures
Spillover Effects of Civil Wars: The Case of Syria
No full textThis study endeavors to scrutinize the repercussions of the Syrian Civil War on its neighboring countries, focusing particularly on pivotal developments spanning from 2012 to 2018. The findings reveal that Syria’s neighboring countries were exposed to comparable risks and threats, albeit with notable variations in their intensity and magnitude. All neighboring countries of Syria encountered deliberate or inadvertent violence stemming from Syrian territory. Armed non-state actors directed cross-border attacks or launched assaults within these nations. With the exception of Israel, all experienced substantial influxes of migration. The domestic societies of these countries, excluding Israel, became directly or indirectly entangled in the civil war, either through active participation in conflicts or by organizing demonstrations. Furthermore, all nations resorted to unilateral or multilateral force to counter threats originating from Syria. The primary distinctions among Syria’s neighbors during the civil war period revolved around the number of conflicting parties in border regions and the severity of violence among these warring factions. Notably, the Syrian government, with the assistance of Hezbollah, managed to establish control in the southern part of Syria. However, in the northern regions, complete control eluded the government, leading to protracted conflicts involving the Syrian government, the opposition, the YPG, Daesh, and supporters of these various civil war factions. Consequently, irrespective of the stance adopted by Syria’s neighbors towards the civil war, Turkey emerged as the nation most profoundly impacted by the spillover effects of the conflict