Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparative Study of OMA and NOMA in 5G Networks, Analyzing Performance and Optimizing Wireless Network Capacity using NOMA

The expanding need for high-speed and dependable wireless communication systems has led to the exploration of innovative multiple-access strategies. This paper presents a comprehensive performance comparison between Non-Orthogonal Multiple Access (NOMA) and traditional Orthogonal Multiple Access (OMA) techniques. NOMA is a promising technology that allows numerous users to access identical time-frequency resources at varying power extents, achieving higher spectral efficiency and accommodating more users compared to OMA. Additionally, this paper provides a mathematical model of the NOMA approach in a fixed-cell downlink (DL) configuration with a sole base station (BS), two subscribers, and a single antenna system shared by all terminals. The research methodology involves the development of MATLAB-based simulations to evaluate the viability of both NOMA and OMA under various scenarios. The performance metrics considered include sum rate (SR), individual user rate, outage probability, and system capacity. The key objective of this study is to recognize whether NOMA can increase wireless network capacity and perform better compared to OMA. We also evaluate the influence of imperfect Successive interference cancellation (SIC) on the attainable data rate of two-user NOMA.
Remote Heart Rate Estimation Based on ROI Extraction

Remote photoplethysmography (rPPG) has acquired much attention in health monitoring and emotion detection in recent years due to its convenience by non-contact approaches. Most studies have primarily concentrated on the estimation of pulse signals methods from the region of interest (ROI). Due to the unequal distribution of rPPG signals on the facial parts, accurate extraction of the ROI is a critical process for acquiring dependable pulse signals. However, many of those methods for ROI extraction encounter challenges, such as background pixels and non-critical skin pixels existing in the ROI. This paper proposes an effective framework integrating face detection and segmentation to address the remote heart rate estimation in presence of the ROI extraction issues. The experimental results demonstrate the proposed framework can efficiently extract skin pixels carrying high-quality heart rate information. As a result, it achieves a significant improvement in the performance of heart rate estimation.
Features for Read Reference Voltage Estimation in NAND Flash Memory

Reliability is a crucial aspect of non-volatile NAND flash memories, and it is essential to thoroughly analyze the channel to prevent errors and ensure accurate readout. Es-timating the read reference voltages (RRV s) is a significant challenge due to the multitude of physical effects involved. The question arises which features are useful and necessary for the RRV estimation. Various possible features require specialized hardware or specific readout techniques to be usable. In contrast we consider sparse histograms based on the decision thresholds for hard-input and soft-input decoding. These offer a distinct advantage as they are derived directly from the raw readout data without the need for decoding. This paper focuses on the information-theoretic study of different features, especially on the exploration of the mutual information (MI) between feature vector and RRV. In particular, we investigate the dependency of the MI on the resolution of the histograms. With respect to the RRV estimation, sparse histograms provide sufficient information for near-optimum estimation.
A Review of Cluster based Routing Protocols in Heterogeneous Wireless Sensor Networks

We seek efficient as well as inexpensive strategies that reveal novel methods and concepts in the target sector, since the focus of contemporary technological and scientific endeavors, particularly Wireless Sensor Networks (WSNs), focuses on the enhancement of already-existing systems. Research based on questionnaires is a fast and thorough way to get exposure to such ideas in the intended context. For this reason, and because of the part that clusters plays in regulating and monitoring WSNs' power consumption, we present a comprehensive evaluation of clustering as well as cluster-based multi-hop protocols for routing. Network-layer navigation technologies plays a crucial role in the design of sensor networks that are wireless. Cluster-based routing algorithms are a dynamic subfield of transportation technologies that has achieved notable success in areas such as network structure administration, energy savings, collection of data, as well as so on. This study examines the pros and cons of cluster-based transport techniques in WSNs. The three main methods used by clusters-based routing protocols are cluster head choosing, clusters creation, and information transfer. Through these lenses, we examine and contrast the features and uses of certain cutting-edge cluster-based protocols for routing. Lastly, several directions for further study are suggested.
Lipids in Health and Disease

Backgound: The effects of extremely low-frequency electromagnetic fields (ELF-EMF) on the blood serum and liver lipid concentrations of male Wistar rats were assessed. Methods: Animals were exposed to a single stimulation (2 h) of ELF-EMF (60 Hz, 2.4 mT) or shamstimulated and thereafter sacrificed at different times (24, 48 or 96 h after beginning the exposure). Results: Blood lipids showed, at 48 h stimulated animals, a significant increase of cholesterol associated to high density lipoproteins (HDL-C) than those observed at any other studied time. Free fatty acid serum presented at 24 h significant increases in comparison with control group. The other serum lipids, triacylglycerols and total cholesterol did not show differences between groups, at any time evaluated. No statistical differences were shown on total lipids of the liver but total cholesterol was elevated at 24 h with a significant decrease at 96 h (p = 0.026). The ELF-EMF stimulation increased the liver content of lipoperoxides at 24 h. Conclusion: Single exposures to ELF-EMF increases the serum values of HDL-C, the liver content of lipoperoxides and decreases total cholesterol of the liver. The mechanisms for the effects of ELFEMF on lipid metabolism are not well understand yet, but could be associated to the nitric oxide synthase EMF-stimulation. Background Some recent epidemiologic studies have suggested that the exposure to extremely low frequency (ELF) electromagnetic fields (EMF) affect human health, because of the incidence of certain types of cancer, depression, and miscarriage have been increased among individuals living or working in environments exposed to such fields [1-3]. Some of these studies have shown associations between exposure to power-frequency (50–60 Hz) magnetic fields and increased health risk [4,5], but other studies have not shown such a link [6]. The results described above are not Published: 16 November 2007 Lipids in Health and Disease 2007, 6:31 doi:10.1186/1476-511X-6-31 Received: 17 August 2007 Accepted: 16 November 2007 This article is available from: http://www.lipidworld. com/content/6/1/31 © 2007 Torres-Duran et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comparative Assessment of Commercial High Energy and High Power Lithium-ion Batteries

This work aims to investigate the fundamental characteristics of Lithium-ion (Li-ion) battery cells, which are generally distinct by their energy and power capability. The commercial high energy and high power Li-ion battery cells were characterised their physical, electrical and chemical properties. Physical properties, such as geometry and capacity of each cell were measured. Electrical properties, such as internal resistances, power characteristics were also tested. The results on energy and power densities of each battery cell and power-to-energy ratio (P/E ratio) could be simultaneously obtained. The cells were subsequently disassembled in order to characterise their internal properties. The thicknesses of electrodes, separator and current collectors were measured. The morphology of cathode and anode was observed by the scanning electron microscope (SEM) as well as the visible particle size. Chemical analysis was conducted by energy dispersive spectroscopy to identify the chemistry of the electrodes. Finally, all the characteristics measured and obtained were explained in relation with the P/E ratio. It was found that battery cells with high energy tended to have high internal resistances, large particle size of active materials in both cathode and anode. The cells contained the thick cathode and anode and thin current collectors and separator due to the benefit of high amount of energy capacity coatings. Conversely, the battery with high power tended to show the opposite characteristics. The relationship between these properties versus P/E ratio was attempted to develop. It showed a well-correlated result for some extents. However, due to the difference of battery chemistries and different manufacturer, it was still hard to make a strong correlation between the properties and P/E ratio, which need to be more clarified.
Bedrock mapping in the Walmsley Lake area, southeastern Slave Province, Northwest Territories

Bedrock mapping in the Walmsley Lake map sheet (NTS 75 N) was completed during the 2002 field season. Highlights include the identification and delineation of an Archean mafic to ultramafic gabbro-anorthosite suite, and delineation and closure of the Cook volcanic belt. Deformation fabrics in the southern and western portions of the map sheet, where mapping was concentrated in 2002, define broad, open domes and basins, and metamorphic assemblages indicate temperatures above minimum melting con­ ditions. Field relationships suggest the peak of metamorphism and synmetamorphic deformation occurred later in this area than farther north, where greenschist facies assemblages formed before ca. 2605 Ma. Mapping of Proterozoic mafic dykes revealed evidence that at least two dyke swarms may have seen multiple generations of intrusion. The fracture systems that host the mafic dyke swarms may have served as conduits for more than one generation of mantle-derived magma. Résumé : Pendant la saison de travaux sur le terrain 2002, on a complété le levé géologique du substra­ tum rocheux dans la région cartographique de Walmsley Lake (SNRC 75 N). Parmi les faits saillants de cette campagne, mentionnons l’identification et la délimitation d’une suite de gabbro mafique-ultramafique et d’anorthosite de l’Archéen, ainsi que l’établissement des limites latérales et de la terminaison de la ceinture volcanique de Cook. Dans les parties sud et ouest du feuillet cartographique, là où la plupart des travaux de cartographie ont été exécutés en 2002, les fabriques de déformation définissent des dômes et des bassins évasés et ouverts, tandis que les paragenèses métamorphiques indiquent des températures aux conditions minimales de fusion. Les relations de terrain laissent supposer que, dans cette région, le métamorphisme maximal et la déformation concomitante se sont déroulés plus tard qu’au nord, là où des paragenèses du faciès des schistes verts se sont formées avant 2 605 Ma environ. La cartographie de dykes mafiques du Protérozoïque a révélé qu’au moins deux essaims de dykes sont présents et qu’ils sont probablement le résultat de nombreux épisodes d’intrusion. Le magma d’origine mantellique a pu remonter à plus d’une reprise dans les conduits nourriciers que constituent les systèmes de fractures hôtes des essaims de dykes mafiques.
Reflectometric Measurements of Fibre-Based Four-Wave Mixing Systems

A convenient way of achieving polarization-insensitive four-wave mixing in optical fibers is through the use of two orthogonally polarized pumps. However, the interplay between fiber birefringence and the four-wave mixing processes makes polarization insensitivity challenging to achieve. The strict control of the input pumps' states of polarization has been used to minimize polarization sensitivity. Nonetheless, a comprehensive analysis of the complex interplay between birefringence and four-wave mixing, both theoretically and experimentally, is still missing. Here, we adopt an optical time domain reflectometry technique to address this issue by measuring the Rayleigh back-scattered power of the phase-conjugated idler generated by a four-wave mixing process. A system with approximately 50 cm spatial resolution capable of measuring the onset of polarization dependency of orthogonal-pump four-wave mixing systems in the saturation regime is experimentally demonstrated. The obtained results are compared with a detailed fibre model, and close agreement is confirmed. This study will further the understanding of the polarization sensitivity of multi-wave mixing dynamics in optical fibers and support the design of optimized fiber-based parametric devices.
UCERF3: A New Earthquake Forecast for California's Complex Fault System

With innovations, fresh data, and lessons learned from recent earthquakes, scientists have developed a new earthquake forecast model for California, a region under constant threat from potentially damaging events. The new model, referred to as the third Uniform California Earthquake Rupture Forecast, or “UCERF3” (http://www.WGCEP.org/ UCERF3), provides authoritative estimates of the magnitude, location, and likelihood of earthquake fault rupture throughout the state. Overall the results confirm previous findings, but with some significant changes because of model improvements. For example, compared to the previous forecast (UCERF2), the likelihood of moderate-sized earthquakes (magnitude 6.5 to 7.5) is lower, whereas that of larger events is higher. This is because of the inclusion of multifault ruptures, where earthquakes are no longer confined to separate, individual faults, but can occasionally rupture multiple faults simultaneously. The public-safety implications of this and other model improvements depend on several factors, including site location and type of structure (for example, family dwelling compared to a long-span bridge). Building codes, earthquake insurance products, emergency plans, and other risk-mitigation efforts will be updated accordingly. This model also serves as a reminder that damaging earthquakes are inevitable for California. Fortunately, there are many simple steps residents can take to protect lives and property.
Anatomical Landmark Localization for Knee X-ray Images via Heatmap Regression Refined with Graph Convolutional Network

Accurate detection of anatomical landmarks for knee X-ray images holds paramount significance for the comprehensive assessment of knee osteoarthritis. Nevertheless, prevailing heatmap regression methodologies often fall short in fully leveraging the holistic structural information of landmarks, leading to potential inaccuracies in offsets owing to predicted integer coordinates. In this paper, we present a sophisticated end-to-end differential landmark localization model which amalgamates heatmap regression with a graph convolution network to precisely pinpoint anatomical landmarks in knee joint X-ray images. Our innovative approach represents the landmarks as a graph, enabling the capture of crucial structural information. It progressively refines the initially coarse integer landmark coordinates derived from heatmaps using cascade GCNs. Additionally, we incorporate the attention layer within the feature sampling module to augment the precision of regression outcomes. Our method attains remarkable results on the OAI dataset, achieving the Mean Radial Error of 0.84mm and the Successful Detection Rate of 71.18% at 1mm. These outcomes surpass the performance of alternative heatmap regression methods, significantly contributing to the facilitation of osteoarthritis assessment.
Deep Learning-Based Automated Early-Stage Diagnosis of Multiple Diseases

Cancer has been a destructive sickness. Indeed, even in the present days of innovative advancements, malignant growth can be lethal in the event if we don't find it at a beginning phase. Identifying destructive cell(s) at the earlier stage as fast as conceivable might possibly save a huge number of lives. The growth of the harmful cells assumes to be an imperative part in deciding the effectiveness of the malignant growth. Just Bounding boxes will be created, which won't help in recognizing the growth of the cells. Segmentation Image methods have a great effect. They aid us with moving towards this issue in a granular way and obtain results that are more significant. In this undertaking, we will utilize progressed picture division calculation, for example, transformers to decide the presence of cancer in the mind checks. The setting highlights are taken advantage of utilizing the CNN calculations and the encoder and decoder of the transformers utilized to dynamically portion the growth present in the picture precisely. Our motive is to design a neural network which will efficiently design the features of spatial and properties of global data with depth dimensions using transformer. The multimodal mind picture datasets are utilized for the reason therefore multiple diseases in tumor will be predicted accurately. The CT pictures will be prepared utilizing calculation after which division is applied to fragment the malignant growth areas of the intertwined picture. Hence, this task helps in distinguishing the presence of disease in a more effective manner, along these lines saving the existence of the patient at the earliest then multi diseases in brain that is multi tumorous diseases in brain will be predicted with the help segmentation
3D Auto Segmentation Module for Ischemic Stroke Lesions from MONAI

Neuroimaging importance for stroke is growing widely. The difficulty of quantifying and describing ischemic stroke lesions is yet an unsolved and semi-automated time-consuming process. However, Ischemic Stroke Lesion Segmentation (ISLES) offered a program for researchers to analyze their solution for Ischemia lesion segmentation from 3D Magnetic Resonance Images (MRIs). This paper introduces a Deep Learning based automated system called 3D Auto Segmentation Module (3D ASM) for lesion identification and extraction, which utilizes two MRI imaging modalities named Diffusion Weighted Imaging (DWI) and Apparent Diffusion Coefficient (ADC) as input from ISLES 2022. It resampled all the images to the same resolution, then divided the data into seven random folds. Trained the data folds in the semantic segmentation network of SegResNet from MONAI and implemented the module along with Auto3DSeg. Five runs of seven-fold cross-validation results were obtained from the assemblage of twelve Convolution Neural Network models to make the final decision. The proposed 3D ASM achieved supremacy in the Dice Similarity Coefficient (DSC) of 0.854, among other existing segmentation techniques.
Recognition Elements for Elongation Factor P on the Ribosome

Translation elongation is a multi-step process orchestrated by elongation factors. Elongation factors G and Tu are required for each round of translation elongation, whereas elongation factor P is only required to assist the translation of poly(Pro) sequences. Upon incorporation of consecutive proline residues the ribosome is stalled; this stalling is alleviated by EF P. While the catalytic mechanism of EF-P is well described, the determinants of EF-P binding remain unknown. Structural data and biochemical studies suggest the E-site codon, the peptidyl tRNA, the ribosomal protein L1 and the post-translational modification of EF-P as key interaction partners during binding and EF P assisted catalysis. In this thesis we developed a FRET based EF-P binding assay using fluorescence-labeled ribosome complexes and a quencher-labeled EF-P. We combined the binding assay with different EF-P activity assays to determine the contribution of each of the proposed interactions to the binding and the catalytic activity of EF-P. We found that EF-P binds to different ribosome complexes with similar rates. EF-P has a short residence time on complexes without poly(Pro) stalling sequences, which is significantly increased on poly(Pro) stalled complexes. This high affinity state depends on the presence of several recognition elements in poly(Pro)-stalled complexes, in particular tRNAPro in the P site and the polypeptide chain containing several sequential proline residues. The context-independent association rates and the determined cellular concentration of EF-P suggest that the sampling of ribosome complexes by EF-P is kinetically controlled by the availability of a vacant E site. However, only poly(Pro)-stalled ribosome complexes provide the interactions required for the high-affinity binding of EF-P. The dissociation rates from Pro-stalled and non-stalled complexes match the reported rates of EF P assisted peptide bond formation. This suggests a mechanism in which the prolonged residence time for stalled complexes allows EF-P to position the peptidyl-tRNA in a catalytically active conformation and thereby to alleviate the stalling. After peptide bond formation the complex returns to the low affinity state, inducing dissociation of EF-P. The proposed kinetic regime allows EF-P to efficiently sample ribosomes with empty E sites, to recognize Pro-stalled complexes with high turnover rates and to alleviate stalling in a single functional cycle. Thus, our work demonstrates that the recruitment of EF-P is kinetically controlled contributing to a harmonized rate of translation.
Toward a Matrix-Free Covariance Matrix Adaptation Evolution Strategy

In this paper, we discuss a method for generating new individuals such that their mean vector and the covariance matrix are defined by formulas analogous to the covariance matrix adaptation evolution strategy (CMA-ES). In contrast to CMA-ES, which generates new individuals using multivariate Gaussian distribution with an explicitly defined covariance matrix, the introduced method uses combinations of difference vectors between archived individuals and univariate Gaussian random vectors along directions of past shifts of the population midpoints. We use this method to formulate the differential evolution strategy (DES)—an algorithm that is a crossover between differential evolution (DE) and CMA-ES. The numerical results presented in this paper indicate that DES is competitive against CMA-ES in performing both local and global optimization.