Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficiency Bound Estimation for a Practical Microwave and mmWave Wireless Power Transfer System Design

In this study, we present an efficient method to find the power transfer efficiency (PTE) bound for practical microwave and mmWave wireless power transfer (MPT) systems composed of transmitter (Tx) and receiver (Rx) array antennas. The PTE bound of the MPT system is obtained by formulating it as a convex optimization problem (CVP) that maximizes the power received at the Rx array under the transmit power constraint. The channel state information (CSI) between each element of the Tx and the Rx is the input parameter of the proposed CVP. The CSI is estimated using the Friis transmission equation and the active element pattern of the array antenna because the Tx and the Rx are assumed to be large arrays. For an MPT system designed at 10 GHz and 24 GHz, the estimated PTE bound is compared to those in previous studies while varying the distance and tilted angle between the Tx and the Rx. The computation times required for the methods are compared. The numerical results show that the proposed method provides a faster and more accurate PTE bound without full electromagnetic simulation of the MPT system consisting of Tx and Rx array antennas. This study's results will serve as guidelines for practical MPT system design in the future.
Green Processing of Neat Poly(lactic acid) Using Carbon Dioxide under Elevated Pressure for Preparation of Advanced Materials: A Review (2012–2022)

This review provides a concise overview of up-to-date developments in the processing of neat poly(lactic acid) (PLA), improvement in its properties, and preparation of advanced materials using a green medium (CO2 under elevated pressure). Pressurized CO2 in the dense and supercritical state is a superior alternative medium to organic solvents, as it is easily available, fully recyclable, has easily tunable properties, and can be completely removed from the final material without post-processing steps. This review summarizes the state of the art on PLA drying, impregnation, foaming, and particle generation by the employment of dense and supercritical CO2 for the development of new materials. An analysis of the effect of processing methods on the final material properties was focused on neat PLA and PLA with an addition of natural bioactive components. It was demonstrated that CO2-assisted processes enable the control of PLA properties, reduce operating times, and require less energy compared to conventional ones. The described environmentally friendly processing techniques and the versatility of PLA were employed for the preparation of foams, aerogels, scaffolds, microparticles, and nanoparticles, as well as bioactive materials. These PLA-based materials can find application in tissue engineering, drug delivery, active food packaging, compostable packaging, wastewater treatment, or thermal insulation, among others.
On robust stability of uncertain systems with multiple time‐delays

On the basis of an infinite to one mapping and the structure of the null space of a multivariate matrix polynomial (MMP), a novel sufficient condition is derived in this paper for the robust stability of a linear time‐invariant system with multiple uncertain time‐delays, parametric modelling errors and unmodelled dynamics. This condition depends on time‐delay bounds and is less conservative than the existing ones. An attractive property is that this condition becomes also necessary in some physically meaningful situations, such as the case that there is only one uncertain time‐delay and neither parametric perturbations nor unmodelling errors exist. Moreover, using ideas of representing a positive‐definite MMP through matrix sum of squares, an asymptotic necessary and sufficient condition is derived for the robust stability of this system. All the conditions can be converted to linear matrix inequalities. Copyright © 2009 John Wiley & Sons, Ltd.
Flow features resulting from shock wave impact on a cylindrical cavity

The complex flow features that arise from the impact of a shock wave on a concave cavity are determined by means of high-speed video photography. Besides additional information on features that have previously been encountered in specific studies, such as those relating to shock wave reflection from a cylindrical wall and those associated with shock wave focusing, a number of new features become apparent when the interaction is studied over longer times using time-resolved imaging. The most notable of these new features occurs when two strong shear layers meet that have been generated earlier in the motion. Two jets can be formed, one facing forward and the other backward, with the first one folding back on itself. The shear layers themselves develop a Kelvin–Helmholtz instability which can be triggered by interaction with weak shear layers developed earlier in the motion. Movies are available with the online version of the paper.
Goodness of fit tests based on the L2-norm of multivariate probability density functions

Using the well known kernel method of estimation for multivariate probability densities due to Rosenblatt (1956), Parzen (1962) and Cacoullos (1966), testing the goodness of fit in the one sample, two sample, and testing symmetry cases are discussed. Test statistics presented here are based on the L2-norms . The estimates presented here for δ i i=l,2, 3 are modifications on those discussed by Bickel and Rosenblatt (1973), Rosenblatt (1975) and Hall (1984), and are asymptotically normal under the null and also under the alternatives with conditions much simpler than assumed in literature.
Synthesis of Novel Benzo[b][1,6]naphthyridine Derivatives and Investigation of Their Potential as Scaffolds of MAO Inhibitors

In this work, 2-alkyl-10-chloro-1,2,3,4-tetrahydrobenzo[b][1,6]naphthyridines were obtained and their reactivity was studied. Novel derivatives of the tricyclic scaffold, including 1-phenylethynyl (5), 1-indol-3-yl (8), and azocino[4,5-b]quinoline (10) derivatives, were synthesized and characterized herein for the first time. Among the newly synthesized derivatives, 5c–h proved to be MAO B inhibitors with potency in the low micromolar range. In particular, the 1-(2-(4-fluorophenyl)ethynyl) analog 5g achieved an IC50 of 1.35 μM, a value close to that of the well-known MAO B inhibitor pargyline.
Deep Learning Based Fusion Model for Multivariate LTE Traffic Forecasting and Optimized Radio Parameter Estimation

With the evaluation of cellular network internet data traffic, forecasting and understanding traffic patterns become the critical objectives for managing the network-designed Quality of Service (QoS) benchmark. For this purpose, cellular network planners often use different methodologies for predicting data traffic. However, traditional traffic forecasting approaches are erroneous. As well as most of the time, traditional traffic forecasts are high-level or a generously large regional cluster level. Also, eNodeB-level utilization concerning with traffic forecasting is not readily available. As a result, user experience degradation or unnecessary network expansion is triggered based on the traditional method. This research focuses on extensive 6.2 million real network time series Long-Term Evolution (LTE) data traffic and other associate parameters, including eNodeB-wise Physical Resource Block (PRB) utilization, which mainly focuses on building a traffic forecasting model with the help of multivariate feature inputs and deep learning algorithms. A state-of-the-art Deep Learning algorithm-based fusion model is proposed. The combination of different deep learning algorithms, namely Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM) and Gated Recurrent Unit (GRU), enables traffic forecasting at a granular eNodeB-level and also provides eNodeB-wise forecasted PRB utilization. In this research $R^{2}$ score value for the proposed fusion model is 0.8034, which outperforms traditional models. Apart from the PRB utilization, QoS threshold was devised as 70% from a real network experience to trigger soft parameter tuning decisions. Based on the forecasted PRB utilization, this research proposed a unique algorithm that estimates eNodeB-level soft capacity parameter optimization for a short-term step-up solution or long-term network expansion to ensure a guaranteed QoS benchmark.
Hierarchical Models for Educational Data: An Overview

The use of hierarchical models in statistical applications, and for educational data, is a promising but still underutilized approach. However, because these models are more complicated than many standard methods, it is important that we, as users and developers, not rush to use them before we understand them. We emphasize here, in support of the views on hierarchical models expressed in the 3 preceding papers by Draper, by Rogosa and Saner, and by de Leeuw and Kreft, the need to not diminish hard thinking about data and iterative model checking when fitting hierarchical models, the need for more and better software, the need to test methods to assure their proper calibration, and the need to produce supporting materials to aid analysts and users of hierarchical modeling methods.
Nanoparticle-Based Plasmonic Biosensor for the Unamplified Genomic Detection of Carbapenem-Resistant Bacteria

Antimicrobial resistance (AMR) is a global public health issue, and the rise of carbapenem-resistant bacteria needs attention. While progress is being made in the rapid detection of resistant bacteria, affordability and simplicity of detection still need to be addressed. This paper presents a nanoparticle-based plasmonic biosensor for detecting the carbapenemase-producing bacteria, particularly the beta-lactam Klebsiella pneumoniae carbapenemase (blaKPC) gene. The biosensor used dextrin-coated gold nanoparticles (GNPs) and an oligonucleotide probe specific to blaKPC to detect the target DNA in the sample within 30 min. The GNP-based plasmonic biosensor was tested in 47 bacterial isolates: 14 KPC-producing target bacteria and 33 non-target bacteria. The stability of GNPs, confirmed by the maintenance of their red appearance, indicated the presence of target DNA due to probe-binding and GNP protection. The absence of target DNA was indicated by the agglomeration of GNPs, corresponding to a color change from red to blue or purple. The plasmonic detection was quantified with absorbance spectra measurements. The biosensor successfully detected and differentiated the target from non-target samples with a detection limit of 2.5 ng/μL, equivalent to ~103 CFU/mL. The diagnostic sensitivity and specificity were found to be 79% and 97%, respectively. The GNP plasmonic biosensor is simple, rapid, and cost-effective in detecting blaKPC-positive bacteria.
Deep Ground Filtering of Large-Scale ALS Point Clouds via Iterative Sequential Ground Prediction

Ground filtering (GF) is a fundamental step for airborne laser scanning (ALS) data processing. The advent of deep learning techniques provides new solutions to this problem. Existing deep-learning-based methods utilize a segmentation or classification framework to extract ground/non-ground points, which suffers from a dilemma in keeping high spatial resolution while acquiring rich contextual information when dealing with large-scale ALS data due to the computing resource limits. To this end, we propose SeqGP, a novel deep-learning-based GF pipeline that explicitly converts the GF task into an iterative sequential ground prediction (SeqGP) problem using points-profiles. The proposed SeqGP utilizes deep reinforcement learning (DRL) to optimize the prediction sequence and retrieve the bare terrain gradually. The 3D sparse convolution is integrated with the SeqGP strategy to generate high-precision classification results with memory efficiency. Extensive experiments on two challenging test sets demonstrate the state-of-the-art filtering performance and universality of the proposed method in dealing with large-scale ALS data.
Hard x-ray response of pixellated CdZnTe detectors

In recent years, the development of cadmium zinc telluride (CdZnTe) detectors for x-ray and gamma ray spectrometry has grown rapidly. The good room temperature performance and the high spatial resolution of pixellated CdZnTe detectors make them very attractive in space-borne x-ray astronomy, mainly as focal plane detectors for the new generation of hard x-ray focusing telescopes. In this work, we investigated on the spectroscopic performance of two pixellated CdZnTe detectors coupled with a custom low noise and low power readout application specific integrated circuit (ASIC). The detectors (10×10×1 and 10×10×2 mm3 single crystals) have an anode layout based on an array of 256 pixels with a geometric pitch of 0.5 mm. The ASIC, fabricated in 0.8 μm BiCMOS technology, is equipped with eight independent channels (preamplifier and shaper) and characterized by low power consumption (0.5 mW/channel) and low noise (150–500 electrons rms). The spectroscopic results point out the good energy resolution of both dete.
Occurrence of Multidrug-Resistant Strains of Acinetobacter spp.: An Emerging Threat for Nosocomial-Borne Infection in Najran Region, KSA

Multidrug-resistant strains are frequent causes of nosocomial infections. The majority of nosocomial infections, particularly in critical care units (ICU), have been linked to A. baumannii, which has major clinical significance. The current paper attempts to identify the potential risk and prognosis factors for acquiring an infection due to A. baumannii compared to that of other nosocomial bacteria. In our study, we employed antibiotics generally prescribed for the initial course of treatment such as colistin, meropenem, amikacin, trimethoprime-sulfamethoxazole, levofloxacin, gentamicin, ciprofloxacin, and piperacillin-tazobactam. We found that the isolated A. baumannii were resistant at a high rate to meropenem, piperacillin–tazobactam, amikacin, levofloxacin, and ciprofloxacin, while they were partially susceptible to trimethoprim-sulfamethoxazole. Our study revealed that A. baumannii was most susceptible to gentamicin and colistin at 85.8% and 92.9%, respectively, whereas the combination of colistin and trimethoprim/sulfamethoxazole was 100% active. The patients were the primary source of infection with A. baumannii, followed by inanimate objects present in the ICU and hospital premises, and then the hospital staff who were taking care of the ICU patients. Gentamicin and colistin were the most sensitive antibiotics; of the 13 tested in total, the rate of drug resistance was above 50%. The very high rate of antibiotic resistance is alarming.
The local press as an external public governance power

ABSTRACT Do national and local newspapers both impact voter turnout? This paper tackles this question by employing data from a unique dataset that collects detailed national and local newspapers, politico-institutional and socio-economic information for Italy during 1980–2007. We use a Dynamic Panel Data with Instrumental Variables methodology that allows for the consideration of potential sources of endogeneity that may affect the relation between the press and voting behavior. We strengthen this methodology by considering the industry’s entry and exit of newspapers – i.e. turbulence – as an external shock. Our analysis provides robust evidence that local newspaper readership affects both national and local turnout and improves political accountability.
Joint Analysis of Longitudinal Data With Informative Observation Times and a Dependent Terminal Event

In many longitudinal studies, repeated measures are often correlated with observation times. Also, there may exist a dependent terminal event such as death that stops the follow-up. In this article, we propose a new joint model for the analysis of longitudinal data in the presence of both informative observation times and a dependent terminal event via latent variables. Estimating equation approaches are developed for parameter estimation, and the resulting estimators are shown to be consistent and asymptotically normal. In addition, some graphical and numerical procedures are presented for model checking. Simulation studies demonstrate that the proposed method performs well for practical settings. An application to a medical cost study of chronic heart failure patients from the University of Virginia Health System is provided.
Study of lanthanum aluminum silicate glasses for passive and active optical fibers

We report on SiO2-Al2O3-La2O3 glasses – with and without Yb2O3 – suitable for nonlinear and fiber laser applications. We also present successful supercontinuum generation and fiber laser operation around 1060 nm in step-index fibers. We have optimized the glass compositions in terms of thermal and optical requirements for both a high La2O3 (24 mol%) and Yb2O3(6 mol%) concentration. The aluminum concentration was adjusted to about 21 mol% Al2O3 to increase the solubility of lanthanum and ytterbium in the glass beyond possible MCVD based techniques. The glasses have been characterized by dilatometrical methods to find transition temperatures from 860 to 880°C and thermal expansion coefficients between 4.1 and 7.0 × 10-6 K-1. Structured step index fibers with a SiO2-Al2O3-La2O3 core and silica cladding have been realized showing a fiber loss minimum of about 500 dB/km at 1200 nm wavelength. The chromatic dispersion could be adjusted to shift the zero dispersion wavelength (ZDW) close to the pump wavelength of 1550 nm in a supercontinuum generation setup. First fiber laser experiments show an efficiency of about 41 % with a remarkably reduced photodarkening compared to MCVD based fibers.
Fleet: Improving Quality of Experience for Low-Latency Live Video Streaming

Low-latency live video streaming proposes more challenges on designing Adaptive Bit Rate (ABR) algorithms than video-on-demand streaming. In this paper, we present Fleet, a solution that improves user quality of experience (QoE) in terms of video quality, video switches, video freezes, and latency. Fleet is designed to meet two operational challenges at the same time: 1) optimizing QoE under dynamic mobile network conditions and 2) ensuring a low latency experience with minimal visual quality degradation. The core of Fleet is a stochastic model predictive controller that incorporates network conditions and client states for bitrate adaptation. The idle period problem presents great challenges for bandwidth measurement and client state prediction. Fleet consists of an HTTP chunk level bandwidth measurement algorithm, and a practical live video streaming evolution model for client state prediction. Besides, a throughput probability predictor is trained to capture the mobile network’s uncertainty. And, a triple threshold playback speed controller is designed for latency management. Fleet is practically implemented in dash.js and evaluated over both synthetic and real-world mobile network conditions. Our study shows that compared with the state-of-the-art solution, Fleet achieves an average QoE improvement of 39.7% and 37.9%, respectively. Moreover, Fleet has a good generalization, outperforming existing algorithms even on new video traces and network conditions.
Dipole and octapole field reversals in a rotating spherical shell: Magnetohydrodynamic dynamo simulation

Computer simulation results of a compressible magnetohydrodynamic (MHD) dynamo in a rotating spherical shell are presented. The reversal of either the dipole or the octapole field polarity is observed accompanying flip–flop magnetic energy transitions. Three energy transitions are observed. The dipole reversal occurs in the first transition. In the initial stage of the dipole reversal, the magnetic energy is about five times larger than the kinetic energy, and the convection pattern consists essentially of six straight cyclonic and anticyclonic vortex column pairs aligned to the rotation axis. In the intermediate stage, the magnetic energy decreases and the field is observed to change direction in some regions. This is accompanied by reorganization of the vortex columns and a transition to a new energy level. In the final stage, the field is completely reversed, the number of convection columns is increased and the magnetic energy is lower than in the second stage. In the other two magnetic energy transit.
Non-Abelian anomaly and vector-meson decays

We propose an extension of the old, fairly successful, phenomenological prescription for adding spin-1 fields to the chiral Lagrangian of pseudoscalar mesons to the case where the Wess-Zumino term is present. This leads to the possibility of describing within the effective-Lagrangian framework a whole class of ''unnatural-parity'' hadronic reactions. In particular, we study the well-known (pure hadronic) . omega -->. 3.pi. and (radiative) . omega --> pi. /sup 0/. gamma. processes, and find good agreement with experiment, comparable to that for any of the current-algebra ''theorems. '' The construction of the Lagrangian is seen to involve subtle theoretical issues. We are led to examine in more detail Witten's ''trial-and-error'' gauging of the Wess-Zumino term and note that the Bardeen form of the anomaly seems more suitable than the left-right-symmetric form for constructing an effective model with phenomenological spin-1 fields.
Prevalence and global trends of polypharmacy in patients with chronic kidney disease: A systematic review and meta-analysis

Background and objectives: Polypharmacy and chronic kidney disease (CKD) are becoming increasingly common due to an ageing population and the rise of multimorbidity. In line with the therapeutic guidelines, managing CKD and its complications necessitates prescribing multiple medications, which predisposes patients to polypharmacy. The aim of this systematic review and meta-analysis is to describe the prevalence of polypharmacy in patients with CKD and to explore the global trends of factors driving any apparent variability in prevalence estimates. Methods: PubMed, Scopus, the Cochrane Database of Systematic Reviews (CDSR), and Google Scholar were searched from 1999 to November 2021. Study selection, data extraction, and critical appraisal were conducted by two independent reviewers. The pooled prevalence of polypharmacy was estimated utilizing the random effects model using the default double arcsine transformation. Results: This review involved 14 studies comprising of 17 201 participants, a significant proportion of which were males (56.12%). The mean age of the review population was 61.96 (SD ± 11.51) years. The overall pooled prevalence of polypharmacy amongst patients with CKD was 69% (95% CI: 49%–86%) (I2 = 100%, p < 0.0001), with a proportionately higher prevalence in North America and Europe as compared to Asia. Conclusion: The results from this meta-analysis showed a high pooled prevalence estimates of polypharmacy amongst patient cohorts with CKD. The exact interventions that are likely to significantly mitigate its effect remain uncertain and will need exploration by future prospective and systematic studies. Systematic Review Registration: [https://www.crd. york.ac. uk/prospero/], identifier [CRD42022306572].