Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Analysis of Wirelessly Powered Cognitive Radio Network with Statistical CSI and Random Mobility

The relentless expansion of communications services and applications in 5G networks and their further projected growth bring the challenge of necessary spectrum scarcity, a challenge which might be overcome using the concept of cognitive radio. Furthermore, an extremely high number of low-power devices are introduced by the concept of the Internet of Things (IoT), which also requires efficient energy usage and practically applicable device powering. Motivated by these facts, in this paper, we analyze a wirelessly powered underlay cognitive system based on a realistic case in which statistical channel state information (CSI) is available. In the system considered, the primary and the cognitive networks share the same spectrum band under the constraint of an interference threshold and a maximal tolerable outage permitted by the primary user. To adopt the system model in realistic IoT application scenarios in which network nodes are mobile, we consider the randomly moving cognitive user receiver. For the analyzed system, we derive the closed-form expressions for the outage probability, the outage capacity, and the ergodic capacity. The obtained analytical results are corroborated by an independent simulation method.
A conforming auxiliary space preconditioner for the mass conserving stress‐yielding method

We are studying the efficient solution of the system of linear equations stemming from the mass conserving stress‐yielding (MCS) discretization of the Stokes equations. We perform static condensation to arrive at a system for the pressure and velocity unknowns. An auxiliary space preconditioner for the positive definite velocity block makes use of efficient and scalable solvers for conforming Finite Element spaces of low order and is analyzed with emphasis placed on robustness in the polynomial degree of the discretization. Numerical experiments demonstrate the potential of this approach and the efficiency of the implementation.
Cellular Network Deployment from Fixed Wing Uncrewed System for Network Denied Areas

Modern society heavily relies on cell phone technology to provide personal, business, and emergency services. The traditional rollout of cellular networks requires strategically and statically placed towers and access points around an area of operation. In the event of disaster (natural or otherwise), the current setup can be compromised and an alternative cannot easily be deployed. In order to provide dynamic cellular service in the aftermath of these disasters, fixed wing uncrewed aircraft equipped with mobile network technology can provide the needed wireless service. One research question remains, given a particular network scheme, what altitude is needed to provide this coverage? This paper studies the integration of a 4G LTE base station into a fixed wing uncrewed aircraft and the signal strength (RSRP) and data throughput to eight ground based end users. In this study two altitudes were researched: 2500 feet and 5000 feet. Additionally, this study shows that a 5000 feet altitude produces a more consistent network coverage than 2500 feet and agrees with the two-ray model.
Assessment of spatial acuity in typically developing children: a comparative study of sound-field and closed-field sound source identification paradigms

Abstract Objective Two main techniques to assess auditory spatial acuity include real-source localisation in the sound-field and virtual-source localisation under headphones.The present study aimed to compare the efficacy of the two assessment paradigms (sound-field localisation and closed-field lateralisation) to measure the spatial abilities of normal-hearing school-aged children. Methods Spatial acuity was assessed in twenty-seven normal-hearing children aged 7–13 years (Mage: 10.4; SD: 1.6) using two paradigms; 1) localisation test (a sound field paradigm) and 2) virtual auditory space identification test (VASI,a closed-field paradigm). The accuracy scores and error rates were calculated from confusion matrices for each participant in both paradigms. Results The Wilcoxon sign rank test showed no statistically significant difference between the two tests in the error rates. However, there was a significant difference in the accuracy scores between the two paradigms for azimuths/locations: Right45°, Right135°, Left45°, and Left135°. Spearman correlation showed a mild to moderate positive correlation between all the measures of the two paradigms. Conclusion The results show that VASI and sound-field localisation paradigms are comparable in assessing spatial acuity in children. A further experiment is warranted to establish its validity in the clinical population as a test for spatial acuity.
A Non-linear Interpolation Algorithm for Tweenframes of 3D Animation

Key-frame animation is the common mode for making 3D animation, and tween-frame interpolation is the most important part.This paper presents a non-linear interpolation algorithm aiming at the non-skeleton 3D mesh mode.This algorithm is used to carry on auto-interpolation to key-frame posture and to form tween-frame animation serial.This algorithm firstly calculates the affine transformation of each triangle of mesh mode in adjacent key-frame and then creates deformation gradient vector.The deformation gradient vector is regarded as deforming information of mesh mode which reveals the local correlation between mesh vertices in deformation.In the following,each affine transformation is decomposed to rotation component and stretch scale component.The latter is made linear interpolation,while the former is made non-linear interpolation using quaternion interpolation algorithm.By this strategy,the deformation gradient vector of tween-frame posture is composed,according to which the tween-frame mesh mode is calculated.This algorithm can make stable and vivid key-frame animation when there is great difference in posture between adjacent key-frame.This algorithm can reduce the number of key-frame and improve the efficiency of animation making.
Protective Effect of Quercetin and Ginger (Zingiber officinale) Extract against Dimethoate Potentiated Fluoride-Induced Nephrotoxicity in Rats

This study aimed to determine the potential of quercetin and Zingiber officinale (ZO) Roscoe extract to alleviate the renal damage induced by dimethoate (DM) and fluoride (F-) alone and by their combined exposure in rats. A total of 54 adult Wistar rats were randomly allocated to nine groups (n = 6). A sub-lethal dose of DM (1/10th of the median lethal dose) was administered by oral gavage alone and along with F- (4.5 ppm, three-fold the permissible limit) in their drinking water continuously for 28 days. Chromatographical analysis revealed the presence of quercetin, curcumin, and other phytochemicals with strong antioxidant properties in ZO-rhizome extract. Severe changes were observed in the levels of the renal biomarkers and histoarchitecture after co-administration of the toxicants, indicating greater kidney damage. The administration of ZO extract (300 mg/kg) along with either or both toxicants led to a significant restoration of the biochemical markers and renal antioxidant profile and histology.
Historical Selection, Adaptation Signatures, and Ambiguity of Introgressions in Wheat

Wheat was one of the crops domesticated in the Fertile Crescent region approximately 10,000 years ago. Despite undergoing recent polyploidization, hull-to-free-thresh transition events, and domestication bottlenecks, wheat is now grown in over 130 countries and accounts for a quarter of the world’s cereal production. The main reason for its widespread success is its broad genetic diversity that allows it to thrive in different environments. To trace historical selection and hybridization signatures, genome scans were performed on two datasets: approximately 113K SNPs from 921 predominantly bread wheat accessions and approximately 110K SNPs from about 400 wheat accessions representing all ploidy levels. To identify environmental factors associated with the loci, a genome–environment association (GEA) was also performed. The genome scans on both datasets identified a highly differentiated region on chromosome 4A where accessions in the first dataset were dichotomized into a group (n = 691), comprising nearly all cultivars, wild emmer, and most landraces, and a second group (n = 230), dominated by landraces and spelt accessions. The grouping of cultivars is likely linked to their potential ancestor, bread wheat cv. Norin-10. The 4A region harbored important genes involved in adaptations to environmental conditions. The GEA detected loci associated with latitude and temperature. The genetic signatures detected in this study provide insight into the historical selection and hybridization events in the wheat genome that shaped its current genetic structure and facilitated its success in a wide spectrum of environmental conditions. The genome scans and GEA approaches applied in this study can help in screening the germplasm housed in gene banks for breeding, and for conservation purposes.
Carrier Generation Ability of CNTs to Harvest Maximum Energy from Solar Spectrum

With outstanding transport and optical capabilities, thin film networks of highly pure semiconducting carbon nanotubes (CNTs) are being investigated for use in energy harvesting and optoelectronic devices. Although the pathways and methods for charge generation remain mostly unknown, the proximity of the nanotubes in this model allows energy to flow across the solar cell. Here, we acquire light spectra in two dimensions at femtosecond time scales using a broadband continuum. Bandgap (S1) and higher (S2) transition energy can be resolved across the wide range of 400-1500 nm continuum. Article discussed about anti-correlated energy states, rapid energy redistribution between S2 states, and non-forster charge transfer between S1 states. The charge generation taken by S2 excitons vary with the bandgap, as seen in the two-dimensional spectra. When the chirality of CNTs is changed charge generation rate vary in different spectrum of solar light. Using SWCNT samples of varying thickness, this study analyzes the charge generation characteristics of carbon nanotubes. A carbon nanotube is found to have a carbon absorption coefficient greater than 24 x 104 cm-1.
Adaptation of Hemodynamics to extreme Exercise according to Impedance Cardiography

The study of baroreflex regulation of human hemodynamics is an important area of research for clinical cardiology, healthy person healthcare and sports medicine. Since baroreceptors of different location and function are involved in the processes of such regulation, and effector mechanisms include both fast muscle reactions and slow hormonal and humoral influences, the building of models suitable for diagnosis, prognosis, and development of control actions is significantly difficult. The authors conducted a preliminary study to observe the reactions of individual mechanisms of hemodynamics in the process of adaptation to extreme exercise. The results allow us to speak about the prospects of the proposed method for approaching a solution to the aforementioned problem.
Non-Phenomenological Description of the Time-Resolved Emission in Solution with Quantum–Classical Vibronic Approaches—Application to Coumarin C153 in Methanol

We report a joint experimental and theoretical work on the steady-state spectroscopy and time-resolved emission of the coumarin C153 dye in methanol. The lowest energy excited state of this molecule is characterized by an intramolecular charge transfer thus leading to remarkable shifts of the time-resolved emission spectra, dictated by the methanol reorganization dynamics. We selected this system as a prototypical test case for the first application of a novel computational protocol aimed at the prediction of transient emission spectral shapes, including both vibronic and solvent effects, without applying any phenomenological broadening. It combines a recently developed quantum–classical approach, the adiabatic molecular dynamics generalized vertical Hessian method (Ad-MD|gVH), with nonequilibrium molecular dynamics simulations. For the steady-state spectra we show that the Ad-MD|gVH approach is able to reproduce quite accurately the spectral shapes and the Stokes shift, while a ∼0.15 eV error is found on the prediction of the solvent shift going from gas phase to methanol. The spectral shape of the time-resolved emission signals is, overall, well reproduced, although the simulated spectra are slightly too broad and asymmetric at low energies with respect to experiments. As far as the spectral shift is concerned, the calculated spectra from 4 ps to 100 ps are in excellent agreement with experiments, correctly predicting the end of the solvent reorganization after about 20 ps. On the other hand, before 4 ps solvent dynamics is predicted to be too fast in the simulations and, in the sub-ps timescale, the uncertainty due to the experimental time resolution (300 fs) makes the comparison less straightforward. Finally, analysis of the reorganization of the first solvation shell surrounding the excited solute, based on atomic radial distribution functions and orientational correlations, indicates a fast solvent response (≈100 fs) characterized by the strengthening of the carbonyl–methanol hydrogen bond interactions, followed by the solvent reorientation, occurring on the ps timescale, to maximize local dipolar interactions.
Surveying a Sample of the Spanish Ophthalmologic Community about Vaccination against Herpes Zoster

There are currently two authorized vaccines against herpes zoster (HZ) that have been shown to be safe and effective in its prevention: Zostavax, a zoster vaccine live (ZVL), and Shingrix, a recombinant zoster Vaccine (RZV). Because ophthalmologists work with vision-threatening complications of zoster, such as herpes zoster ophthalmicus (HZO), they are in a good position to advocate for vaccination. Our aim was to determine the current knowledge among Spanish ophthalmologists about the effectiveness of the available vaccines against HZ. A Google Forms questionnaire was created and used as the survey platform for this study. It was an anonymous online survey of 16 questions, which was shared among Spanish ophthalmologists in-training and consultants from 27 April 2022 to 25 May 2022. The survey was completed by a total of 206 ophthalmologists of all subspecialties. We obtained responses from 17 of the 19 regions of Spain. Fifty-five percent of the respondents agreed that HZ is a frequent cause of vision loss. However, 27% of the professionals were unaware of the existence of vaccines against HZ and 71% of them did not know in which cases it could be indicated. Only nine ophthalmologists (4%) had ever suggested vaccination against HZ to their patients. Despite this, 93% considered it important to recommend vaccination against HZ if it proved to be safe and effective. Considering the sequelae, complications, and the existence of safe and effective vaccines against HZ, vaccination of the target population could be considered an important public health measure. We are convinced that it is time for ophthalmologists to take an active role in HZO prevention.
Porous Zirconia Scaffolds Functionalized with Calcium Phosphate Layers and PLGA Nanoparticles Loaded with Hydrophobic Gentamicin

Implant-related infections are a worldwide issue that is considered very challenging. Conventional therapies commonly end up failing; thus, new solutions are being investigated to overcome this problem. The in situ delivery of the drug at the implant site appears to be more sufficient compared to systemic antibiotic therapy. In this study, we manufactured porous zirconia scaffolds using the foam replication method. To improve their overall bioactivity, they were coated with a calcium phosphate (CaP) layer containing antibiotic-loaded degradable polymer nanoparticles (NPs) obtained by the double emulsion method to achieve the antibacterial effect additionally. Encapsulation efficiency (EE) and drug loading (DL) were superior and were equal to 99.9 ± 0.1% and 9.1 ± 0.1%, respectively. Scaffolds were analyzed with scanning electron microscopy, and their porosity was evaluated. The porosity of investigated samples was over 90% and resembled the microstructure of spongy bone. Furthermore, we investigated the cytocompatibility with osteoblast-like MG-63 cells and antimicrobial properties with Staphylococcus aureus. Scaffolds coated with a CaP layer were found non-toxic for MG-63 cells. Moreover, the presence of antibiotic-loaded nanoparticles had no significant influence on cell viability, and the obtained scaffolds inhibited bacteria growth. Provided processes of fabrication of highly porous zirconia scaffolds and surface functionalization allow minimizing the risk of implant-related infection.
SIGNet: A Siamese Graph Convolutional Network for Multi-Class Urban Change Detection

Detecting changes in urban areas presents many challenges, including complex features, fast-changing rates, and human-induced interference. At present, most of the research on change detection has focused on traditional binary change detection (BCD), which becomes increasingly unsuitable for the diverse urban change detection tasks as cities grow. Previous change detection networks often rely on convolutional operations, which struggle to capture global contextual information and underutilize category semantic information. In this paper, we propose SIGNet, a Siamese graph convolutional network, to solve the above problems and improve the accuracy of urban multi-class change detection (MCD) tasks. After maximizing the fusion of change differences at different scales using joint pyramidal upsampling (JPU), SIGNet uses a graph convolution-based graph reasoning (GR) method to construct static connections of urban features in space and a graph cross-attention method to couple the dynamic connections of different types of features during the change process. Experimental results show that SIGNet achieves state-of-the-art accuracy on different MCD datasets when capturing contextual relationships between different regions and semantic correlations between different categories. There are currently few pixel-level datasets in the MCD domain. We introduce a new well-labeled dataset, CNAM-CD, which is a large MCD dataset containing 2508 pairs of high-resolution images.
Enhancing Knowledge Management in Healthcare: An Embedding Fusion Approach to Business Rule Representation

Enterprise Decision Management systems are vital for delivering efficient healthcare services. However, the ever-changing clinical terminology creates complex business rules, making healthcare IT systems difficult to maintain. In this study, we present an embedding fusion technique using unsupervised Natural Language Processing (NLP) to represent business rules as semantic vectors by incorporating multiple text data sources for each rule. We apply this method to a dental insurance administration case study and find that our approach is over 200 times more likely to identify redundant rule pairs compared to random pairs. This case study suggests that an embedding-based technique can significantly improve knowledge management efficiency in healthcare IT systems.
A Predictive Study of Feature Encoding and Selection Methods on PTM Lysine Glutarylation Site Allocation

The post-translational modification, Lysine Glutarylation is an active outcome of protein acylation. To determine the functional behaviors at the molecular level, it is required to have a proper visualization of the translation sites of the PTM. In this regard, machine learning algorithms and methodologies play an inevitable role. A wide range of conventions in machine learning is constantly being used to determine the PTM sites. However, in this study, the incorporated feature encoding methods are CKSAAP (Composition of K-Spaced Amino Acid Pairs) and PseKRAAC (Pseudo K-tuple Reduced Amino Acid Composition). Specifically, the main intention of the study is to trial two feature extraction methods with two feature selection processes (RFECV and mRMR), so that better performance is gained regardless of other feature screening methods. Consequently, the sequence received, is likely to have more related information regarding the specified PTM. The approach implemented has 4 comparative combinations that are determined with the AUC (Area Under Curve). One of the conclusions is the combined prediction of CKSAAP and RFECV which derives an exceptional remark. Whereas, the merged case of PseKRAAC and RFECV through a noteworthy output of 0.908 AUC. The notable portion is that, when the RFECV is used in both cases (CKSAAP and PseKRAAC), the chances to have an outperformed prediction is achieved as RFECV extracts optimal features by cross val-idations. However, the mRMR selection method for CKSAAP results in 0.779 AUC, and PseKRAAC results in 0.786 AUC. So, the comparative study depicts that RFECV is more impactful than mRMR and more precisely, the achievable accuracy is for the combination of PseKRAAC and RFECV.
Iterative Reweighted Least-Squares Gaussian Beam Migration and Velocity Inversion in the Image Domain Based on Point Spread Functions

Amplitude-preserving migration is very important for reservoir characterization, which can faithfully provide information on the strength of the reflectors. However, conventional migration algorithms do not compensate for variable illumination effects and can hardly obtain true amplitudes of medium parameter. Least-squares migration (LSM) is an effective method to address this issue. Unfortunately, there is a key problem with LSM methods: most LSM methods only consider illumination compensation but not consider the accuracy of migration velocity model. The accuracy of the migration velocity model directly affects the quality of migrated images. Moreover, changes in velocity are more indicative of reservoir properties than reflectivity. Therefore, it is necessary to incorporate velocity estimation into migration imaging to realize joint inversions. Based on these facts, we present an iterative reweighted LSM method by approximating the local Hessian using point spread functions. Then, we related the LSM results to the scattering potential, simultaneously achieving velocity update with illumination compensation. Based on the gradually changing characteristics of rock properties, we adopted a sparse derivative constraint rather than requiring the result to be sparse. Consequently, this processing caused the results to contain broader bandwidths, giving the image a more continuous and textured appearance. Next, we evaluated the proposed method using the Marmousi2 model. The results had a higher resolution and a more reliable amplitude than the initial migration images. Hence, we efficaciously completed the velocity model update, with our method achieving encouraging results under both relatively accurate migration velocity and highly smoothed migration velocity model tests.