Miracle-dz/UniFAR-FTUs huggingface dataset:
Transmission of 51.2 Gb/s 16 QAM single carrier signal in a MIMO radio‐over‐fiber system at W‐band

We experimentally demonstrate a 2 × 2 Multiple‐Input Multiple‐Output radio‐over‐fiber system at W‐band and successfully realize a single carrier 16 quadrature amplitude modulation transmission through 100 km single‐mode fiber and 40m W‐band wireless link with a net bitrate of 51.2 Gb/s. Two pairs of Cassegrain antennas are used in the wireless link, between which the isolation can be promised by adopting antenna polarization (H&V) multiplexing.
Perception of Terror Risk and of the Security of Counter-Terrorism Design in Public Spaces

At a time of terror, research on the perception of terror risk makes an important contribution to increase understanding of the public perception of terror threat. This kind of research can be utilized to improve strategies for raising the sense of security in public spaces. Since 9/11, efforts to promote this sense of security have been implemented through the development of security features embedded in public spaces, known as counter-terrorism design. It is assumed that terror risk perception can affect the perception of security in this design strategy. To investigate this issue, research was conducted on three business districts which represented high-profile terror attack targets in Jakarta. The primary findings of the study confirm the research assumption, but the role of terror risk perception was less strong than expected as the main predictor to determine the perceived security of counter-terrorism design. In addition, the study also found that gender had a significant but low influence on the security perception of counter-terrorism design.
Evidence for B- → τ-ν̄τ with a semileptonic tagging method

We present a measurement of the decay B- -> tau(-)(nu) over bar (tau) using a data sample containing 657 x 10(6) B (B) over bar pairs collected at the gamma(4S) resonance with the Belle detector at the KEKB asymmetric-energy e(+)e(-) collider. A sample of B+B- pairs are tagged by reconstructing one B+ meson decaying semileptonically. We detect the B- -> tau(-)(nu) over bar (tau) candidate in the recoil. We obtain a signal with a significance of 3.6 standard deviations including systematic uncertainties, and measure the branching fraction to be B- -> tau(-)(nu) over bar (tau) [1.54(-0.37)(+0.38) (stat) (+0.29)(-0.31) (syst) x 10(-4). This result confirms the evidence for B- -> tau(-)(nu) over bar (tau) obtained in a previous Belle measurement that used a hadronic B tagging method.
A Generalized Framework of Multifidelity Max-Value Entropy Search Through Joint Entropy

Abstract Bayesian optimization (BO) is a popular method for expensive black-box optimization problems; however, querying the objective function at every iteration can be a bottleneck that hinders efficient search capabilities. In this regard, multifidelity Bayesian optimization (MFBO) aims to accelerate BO by incorporating lower-fidelity observations available with a lower sampling cost. In our previous work, we proposed an information-theoretic approach to MFBO, referred to as multifidelity max-value entropy search (MF-MES), which inherits practical effectiveness and computational simplicity of the well-known max-value entropy search (MES) for the single-fidelity BO. However, the applicability of MF-MES is still limited to the case that a single observation is sequentially obtained. In this letter, we generalize MF-MES so that information gain can be evaluated even when multiple observations are simultaneously obtained. This generalization enables MF-MES to address two practical problem settings: synchronous parallelization and trace-aware querying. We show that the acquisition functions for these extensions inherit the simplicity of MF-MES without introducing additional assumptions. We also provide computational techniques for entropy evaluation and posterior sampling in the acquisition functions, which can be commonly used for all variants of MF-MES. The effectiveness of MF-MES is demonstrated using benchmark functions and real-world applications such as materials science data and hyperparameter tuning of machine-learning algorithms.
Deconstruct, Imagine, Build: Bringing Advanced Manufacturing to the Maker Community

Author(s): Lo, Joanne | Advisor(s): Paulos, Eric | Abstract: Physical prototypes serve as a common starting point for the process of innovation, improvement of an existing product, and experimentation of new interactions. As the shapes, forms, and functions of the electronic landscape rapidly evolve, fabrication and prototyping methods need to keep up with the changing needs as well. This dissertation contributes concepts and techniques that answer two research questions: 1. What type of prototyping processes and tools could support the rapidly evolving field of interactive technology? 2. How can these prototyping processes and tools be selected to add value to the broader community - one that includes engineers, designers, and hobbyists? In this thesis, I will demonstrate that by using concepts inspired by various advanced manufacturing fields - such as MEMS, structural electronics, and flexible electronics - novel interaction modalities can be prototyped with commercially accessible materials. Electronics presented in this dissertation include circuit boards with mechanically functional shapes, non-emissive textile displays, and on-skin electronic devices. Moreover, this thesis also describes a web-based digital tool that allows users to free-form sketch basic circuits and also provides step-by-step fabrication and debugging guidance. Using this tool, users will be able to sketch, design, and prototype electronics with materials such as silver/graphite pen, conductive thread, paper, and fabric. We hope that this thesis will inspire the community to create innovative interactions that utilize readily available prototyping tools.
H\"older Continuity of the Data to Solution Map for HR in the Weak Topology

It is shown that the data to solution map for the hyperelastic rod equation is H\"older continuous from bounded sets of Sobolev spaces with exponent $s > 3/2$ measured in a weaker Sobolev norm with index $r < s$ in both the periodic and non-periodic cases. The proof is based on energy estimates coupled with a delicate commutator estimate and multiplier estimate.
Epidemiological expectations and consumption dynamics

In this paper, we propose an alternative theory of consumption that is consistent with excess sensitivity and smoothness of aggregate consumption. At the same time, consumption of individual households follows a random walk as in Dynan (2000). The model is based on the assumption that consumers’ expectations are not completely up-to-date at every instant of time. Our formalization follows the recent literature on modeling in‡ation expectations (Roberts (1998), Mankiw and Reis (2003)). We show that the degree of serial correlation in aggregate consumption growth is an approximate measure of the fraction of the population that does not update its macroeconomic expectations in any given period. Our point estimates indicate a highly statistically signi.cant serial correlation coe¢cient in the range of 0.7 to 0.8 in quarterly aggregate U.S. data. This would imply that approximately 25% of households are up-to-date in their information set in any given quarter.
Estimateur à noyau discret standard pour une densité de probabilité discrète

In this paper we introduce a discrete kernel estimator for which the discrete smoothing parameter is adapted to the target for a given type of discrete kernel. We show some basical properties of this estimator using finite difference approximation instead of the derivation. In particular, bias, variance and mean integrated squared error are investigated under general considerations. Some aspects of obtained results are illustrated through the standard discrete kernels like Poisson or equidispersed, binomial or underdispersed, and negative binomial or overdispersed. We provide a simple measure of the relative efficiency between two discrete kernels. Choices of discrete smoothing bandwidths are studied according to several usual criteria as the cross-validation method and a method in the situation of zeros excess. Their performances are finally compared by using simulated and real count data. For a sample size not so large, certains discrete kernel estimators are more efficient than the empirical estimator which is the limit one.
Evaluation of missile aerodynamic characteristics using rapid prediction techniques

A general overview of missile aerodynamic predictive methodology is made. Nine state-of-the-art rapid prediction codes are surveyed, and the NSWC Aeroprediction and NEAR Missile II codes are selected for detailed evaluation. The abilities and weaknesses of the codes to predict six-component aerodynamics of a diverse range of missile configurations (Sparrow III, Army Generalized, Maverick, and WASP) are examined. In general, both codes compared favorably in predicting longitudinal aerodynamics for angles of attack less than 10-15 deg. Both codes possess state-of-the-art and compatible methodology bases. Recommendations are given for an improved aerodynamic prediction code for future missiles.
Soft-robotic ciliated epidermis for reconfigurable coordinated fluid manipulation

The fluid manipulation capabilities of current artificial cilia are severely handicapped by the inability to reconfigure near-surface flow on various static or dynamically deforming three-dimensional (3D) substrates. To overcome this challenge, we propose an electrically driven soft-robotic ciliated epidermis with multiple independently controlled polypyrrole bending actuators. The beating kinematics and the coordination of multiple actuators can be dynamically reconfigured to control the strength and direction of fluid transportation. We achieve fluid transportation along and perpendicular to the beating directions of the actuator arrays, and toward or away from the substrate. The ciliated epidermises are bendable and stretchable and can be deployed on various static or dynamically deforming 3D surfaces. They enable previously difficult to obtain fluid manipulation functionalities, such as transporting fluid in tubular structures or enhancing fluid transportation near dynamically bending and expanding surfaces.
Effect of simulated lenticular debris on corneal endothelial cells: experimental study in rabbit eyes

A study using live rabbits, with subsequent analysis of excised corneas stained with trypan blue/alizarin red, showing simulated swirling lenticular debris may contribute significantly to corneal endothelium damage during phacoemulsification. Purpose: To evaluate mechanical damage of simulated lenticular debris on corneal endothelial cells during phacoemulsification. Setting: University setting, Salt Lake City, Utah. Design: Experimental study. Methods: 12 New Zealand rabbits underwent bilateral surgery. After incision, 10 1.0 mm beads were injected into the anterior chamber of test eyes to simulate lenticular debris. A balanced salt solution was injected into the contralateral eyes with the same injector. The Intrepid Balanced Tip of the Centurion Ozil handpiece was inserted into the anterior chamber, and 60% torsional ultrasound was applied for 20 seconds with 50 mL/min flow, 70 mm Hg intraocular pressure, and 600 mm Hg vacuum. Cumulative dissipated energy (CDE) was noted. After euthanasia and enucleation, the corneas were removed, stained with trypan blue/alizarin red, and photographed in a standardized manner (×400 photographs from 5 specific areas and 1 overview photograph from each corneal button). The ImageJ program was used to evaluate cell damage and loss in the photographs. Results: CDE was 4.64 ± 0.19 for test eyes with beads and 4.66 ± 0.17 for control eyes without beads (P = .58). The percentage of intact cells was statistically higher in the control group (P = .0005), whereas the percentages of damaged and lost cells were statistically higher in the test group (P = .0010 and .0005, respectively). This was observed in the analysis of the ×400 photographs and overview photographs. Conclusions: This study suggests that lenticular debris swirling around the anterior chamber may cause significant damage to the corneal endothelium, providing further insight on mechanisms of damage during phacoemulsification.
Understanding and Applying Deep Learning

Abstract The past 10 years have witnessed an explosion in deep learning neural network model development. The most common perceptual models with vision, speech, and text inputs are not general-purpose AI systems but tools. They automatically extract clues from inputs and compute probabilities of class labels. Successful applications require representative training data, an understanding of the limitations and capabilities of deep learning, and careful attention to a complex development process. The goal of this view is to foster an intuitive understanding of convolutional network deep learning models and how to use them with the goal of engaging a wider creative community. A focus is to make it possible for experts in areas such as health, education, poverty, and agriculture to understand the process of deep learning model development so they can help transition effective solutions to practice.
Safety and immunogenicity of a recombinant receptor‐binding domain‐based protein subunit vaccine (Noora vaccine™) against COVID‐19 in adults: A randomized, double‐blind, placebo‐controlled, Phase 1 trial

The development of a safe and effective vaccine is essential to protect populations against coronavirus disease 2019 (COVID‐19). There are several vaccine candidates under investigation with different mechanisms of action. In the present study, we have evaluated the safety and immunogenicity of a recombinant receptor‐binding domain (RBD)‐based protein subunit vaccine (Noora vaccine) against COVID‐19 in adults. This Phase 1 trial is a randomized, double‐blind, placebo‐controlled study to evaluate the safety and immunogenicity of the recombinant RBD‐based protein subunit vaccine (Noora vaccine) against COVID‐19 in healthy adults volunteers. Eligible participants were included in this study after evaluating their health status and considering the exclusion criteria. They were then randomized into three groups and received three doses of vaccine (80 µg, 120 µg, and placebo) on Days 0, 21, and 35. Primary outcomes including solicited, unsolicited, and medically attended adverse events were recorded during this study. Secondary outcomes including the humoral and cellular immunity (including anti‐RBD IgG antibody and neutralizing antibody) were measured on Days 0, 21, 28, 35, 42, and 49 by using the ELISA kit and the Virus Neutralization Test (VNT) was performed on day 49. Totally 70 cases were included in this Phase 1 trial and 60 of them completed the study. Safety assessments showed no severe adverse events. Local pain at the vaccine injection site occurred in 80% of the vaccinated volunteers. Induration and redness at the injection site were the other adverse reactions of this vaccine. There was no significant difference between the studied groups regarding adverse reactions. Anti‐RBD IgG antibody and neutralizing antibody assessment showed significant seroconversion in comparison to the placebo group (80%, and 100% respectively, p < 0.001). The cellular immunity panel also showed mild to moderate induction of TH1 responses and the VNT showed 78% of seroprotection. The results of this Phase 1 trial showed acceptable safety without serious adverse events and significant seroconversions in the humoral and cellular immunity panel. The dose of 80 µg is an appropriate dose for injection in the next phases of the trial.
Nonstationary waveform analysis and synthesis using generalized harmonic analysis

This article presents a new method of spectrum analysis for nonstationary signals, the generalized harmonic analysis (GHA) method. The short-time Fourier transform suffers from truncation effects in spectrum analysis; however, GHA using almost-periodic functions can analyze and synthesize signals without the truncation effects. We have applied GHA to nonstationary signals, such as a piano tone and a singing voice, and found that the time-varying spectra, as well as the pitch, can be visualized with high frequency resolution. <<ETX>>
Simple invariant solutions embedded in 2D Kolmogorov turbulence

We consider long simulations of 2D Kolmogorov turbulence body-forced by $\sin4y \ex$ on the torus $(x,y) \in [0,2\pi]^2$ with the purpose of extracting simple invariant sets or `exact recurrent flows' embedded in this turbulence. Each recurrent flow represents a sustained closed cycle of dynamical processes which underpins the turbulence. These are used to reconstruct the turbulence statistics in the spirit of Periodic Orbit Theory derived for certain types of low dimensional chaos. The approach is found to be reasonably successful at a low value of the forcing where the flow is close to but not fully in its asymptotic (strongly) turbulent regime. Here, a total of 50 recurrent flows are found with the majority buried in the part of phase space most populated by the turbulence giving rise to a good reproduction of the energy and dissipation probability density functions. However, at higher forcing amplitudes now in the asymptotic turbulent regime, the generated turbulence data set proves insufficiently long to yield enough recurrent flows to make viable predictions. Despite this, the general approach seems promising providing enough simulation data is available since it is open to extensive automation and naturally generates dynamically important exact solutions for the flow.
Disease severity and efficacy of homologous vaccination among patients infected with SARS‐CoV‐2 Delta or Omicron VOCs, compared to unvaccinated using main biomarkers

From March 2021, various countries including Iraq issued prompted recommendations for increased COVID‐19 vaccine protection in individuals especially those at risk of catching the virus (i.e., lifestyle, health sector workers, and chronic diseases). It is critically important to understand the impact of COVID‐19 vaccinations with the most commonly used vaccines (Pfizer and AstraZeneca) among populations either on the severity of the disease or the transmissibility of SARS‐CoV‐2 variants of concern (VOCs) and in sequential waves. This study was conducted to establish the clinical severity of COVID‐19 caused by Delta and Omicron SARS‐CoV‐2 variants among patients who either attended or were admitted to hospitals and to compare the effectiveness of Pfizer and AstraZeneca COVID‐19 vaccines (single or double doses) at least to prevent hospitalizations if not eradicating the pandemic. A case–control study was done of 570 hospitalized patients; including 328 COVID‐19 confirmed patients (166 males, 160 females) who received homologous vaccinations and 242 unvaccinated patients (128 males, 114 females) during the studied waves. The study showed that unvaccinated COVID‐19 patients in both waves had expressed significantly a higher number and longer periods of symptoms than vaccinated ones. Additionally, there was no significant effect of vaccine types, Pfizer and AstraZeneca or vaccine shot numbers on the PCR‐Ct in the last (Omicron) wave of the pandemic. However, in the previous (Delta) wave of the pandemic, fully vaccinated (double doses) COVID‐19 patients had higher PCR‐Ct values. Whether among vaccinated or unvaccinated patients, lower CRP levels recorded during the Omicron wave than that of the Delta wave, and regardless of the vaccine type or shot numbers, there were no significant differences between the two waves. Lower WBCs were observed in patients (vaccinated and unvaccinated) infected with the Delta variant in comparison to those infected with the Omicron variant and without any remarkable effect of the vaccine type or shot numbers. This is the first molecular and investigational study of the Delta variant and circulated Omicron in Iraq, regarding the severity of these two waves of SARS‐CoV‐2 pandemic and the efficacy of homologous vaccination, indicating the insufficiency of two doses and the demand for booster dose(s) as the most effective way of keeping on the safe‐side against SARS‐CoV‐2.
Neural Information Processing and Computations of Two-Input Synapses

Abstract Information processing in artificial neural networks is largely dependent on the nature of neuron models. While commonly used models are designed for linear integration of synaptic inputs, accumulating experimental evidence suggests that biological neurons are capable of nonlinear computations for many converging synaptic inputs via homo- and heterosynaptic mechanisms. This nonlinear neuronal computation may play an important role in complex information processing at the neural circuit level. Here we characterize the dynamics and coding properties of neuron models on synaptic transmissions delivered from two hidden states. The neuronal information processing is influenced by the cooperative and competitive interactions among synapses and the coherence of the hidden states. Furthermore, we demonstrate that neuronal information processing under two-input synaptic transmission can be mapped to linearly nonseparable XOR as well as basic AND/OR operations. In particular, the mixtures of linear and nonlinear neuron models outperform the fashion-MNIST test compared to the neural networks consisting of only one type. This study provides a computational framework for assessing information processing of neuron and synapse models that may be beneficial for the design of brain-inspired artificial intelligence algorithms and neuromorphic systems.
Recent Advances on Type-2 Cannabinoid (CB2) Receptor Agonists and Their Therapeutic Potential.

In the last decade, selective modulators of type-2 cannabinoid receptor (CB2) have become a major focus to target endocannabinoid signaling in humans. Indeed, heterogeneously expressed within our body, CB2 actively regulates several physio-pathological processes, thus representing a promising target for developing specific and safe therapeutic drugs. If CB2 modulation has been extensively studied since the very beginning for the treatment of pain and inflammation, the more recent involvement of this receptor in other pathological conditions has further strengthened the pursuit of novel CB2 agonists in the last five years. Against this background, here we discuss the most recent evidence of the protective effects of CB2 against pathological conditions, emphasizing central nervous system disorders, bone and synovial diseases, and cancer. We also summarize the most recent advances in the development of CB2 agonists, focusing on the correlation between different chemical classes and diverse therapeutic applications. Data mining includes a review of the CB2 ligands disclosed in patents also released in the last five years. Finally, we discuss how the recent elucidation of CB2 tertiary structure has provided new details for the rational design of novel and more selective CB2 agonists, thus supporting innovative strategies to develop effective therapeutics. Our overview of the current knowledge on CB2 agonists provides pivotal information on the structure and function of different classes of molecules and opens possible avenues for future research.