Miracle-dz/UniFAR-FTUs huggingface dataset:
The Fried Frailty Phenotype in Patients Undergoing Cardiac Surgery: A Systematic Review and Meta-Analysis.

OBJECTIVE Frailty is an increasingly recognized marker of poor surgical outcomes in cardiac surgery. Frailty first was described in the seminal "Fried" paper, which constitutes the longest-standing and most well-recognized definition. This study aimed to assess the impact of the Fried and modified Fried frailty classifications on patient outcomes following cardiac surgery. METHODS The PUBMED, MEDLINE, and EMBASE databases were searched from January 2000 until August 2021 for studies evaluating postoperative outcomes using the Fried or modified Fried frailty indexes in open cardiac surgical procedures. Primary outcomes were one-year survival and postoperative quality of life. Secondary outcomes included postoperative complications, intensive care unit (ICU) length of stay (LOS), total hospital LOS, and institutional discharge. RESULTS Eight eligible studies were identified. Meta-analysis identified that frailty was associated with an increased risk of one-year mortality (Risk Ratio [RR]:2.23;95% confidence interval [CI]1.17 -4.23), postoperative complications (RR 1.78;95% CI 1.27 - 2.50), ICU LOS (Mean difference [MD] 21.2 hours;95% CI 8.42 - 33.94), hospital LOS (MD 3.29 days; 95% CI 2.19 - 4.94), and institutional discharge (RR 3.29;95% CI 2.19 - 4.94). A narrative review of quality of life suggested an improvement following surgery, with frail patients demonstrating a greater improvement from baseline over non-frail patients. CONCLUSIONS Frailty is associated with a higher degree of surgical morbidity, and frail patients are twice as likely to experience mortality within one-year post-operatively. Despite this, quality of life also improves dramatically in frail patients. Frailty, in itself, does not constitute a contraindication to cardiac surgery.
A Novel Air-Door Opening and Closing Identification Algorithm Using a Single Wind-Velocity Sensor

The air-door is an important device for adjusting the air flow in a mine. It opens and closes within a short time owing to transportation and other factors. Although the switching sensor alone can identify the air-door opening and closing, it cannot relate it to abnormal fluctuations in the wind speed. Large fluctuations in the wind-velocity sensor data during this time can lead to false alarms. To overcome this problem, we propose a method for identifying air-door opening and closing using a single wind-velocity sensor. A multi-scale sliding window (MSSW) is employed to divide the samples. Then, the data global features and fluctuation features are extracted using statistics and the discrete wavelet transform (DWT). In addition, a machine learning model is adopted to classify each sample. Further, the identification results are selected by merging the classification results using the non-maximum suppression method. Finally, considering the safety accidents caused by the air-door opening and closing in an actual production mine, a large number of experiments were carried out to verify the effect of the algorithm using a simulated tunnel model. The results show that the proposed algorithm exhibits superior performance when the gradient boosting decision tree (GBDT) is selected for classification. In the data set composed of air-door opening and closing experimental data, the accuracy, precision, and recall rates of the air-door opening and closing identification are 91.89%, 93.07%, and 91.07%, respectively. In the data set composed of air-door opening and closing and other mine production activity experimental data, the accuracy, precision, and recall rates of the air-door opening and closing identification are 89.61%, 90.31%, and 88.39%, respectively.
Assessment of Enamel Color Stability of Resins Infiltration Treatment in Human Teeth: A Systematic Review

(1) The evolution of techniques and materials used in dentistry has led to the introduction of a technique known as micro-infiltration, using ICON infiltrating resin. The purpose of this study was to evaluate whether the resin infiltrant can remain stable in the enamel color of human teeth over time or if it causes discoloration and review current knowledge on color stability based on the literature selected solely on studies performed on human teeth and to provide a perspective on the methods proposed by clinicians in the infiltration procedure; (2) Methods: This systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement; (3) Results: Twelve studies were selected for this review. The study results suggest that the device content is sufficiently comprehensive. The reviewers expressed strong support for the device’s content for assessing the quality of reviews. The paper summarizes current reports regarding the color stability assessment of enamel treated by in- filtration resin confirmed in in vitro and in vivo studies; (4) Conclusions: Based on these considerations, the resin infiltration method can be recommended to improve the appearance of enamel lesions. The infiltrated lesions remained chromatically stable, showing no significant color changes in the long term.
Robust Backstepping Control Applied to UAVs for Pest Recognition in Maize Crops

In this paper, a robust control technique is developed to achieve the quadrotor stabilization against unmodeled matching vanishing dynamics. The synthesis of the proposed robust control is based on the Lyapunov approach and the backstepping method allowing to construct an iterative control algorithm. To compare the performance of the proposed controller, a Proportional Derivative (PD) controller is used to obtain experimental results in an outdoor environment. To compare the closed-loop system responses with both controllers, the Integral Absolute Error is computed and several tests are conducted to calculate the error standard deviation. Ultimately, employing the robust backstepping control approach in pest recognition in maize crops, which is a specific task of precision agriculture, demonstrates its effectiveness in improving the trajectory tracking of the vehicle while it captures images of the crops.
Integrals on $p$-adic upper half planes and Hida families over totally real fields

Bertolini-Darmon and Mok proved a formula of the second derivative of the two-variable $p$-adic $L$-function of a modular elliptic curve over a totally real field along the Hida family in terms of the image of a global point by some $p$-adic logarithm map. The theory of $p$-adic indefinite integrals and $p$-adic multiplicative integrals on $p$-adic upper half planes plays an important role in their work. In this paper, we generalize these integrals for $p$-adic measures which are not necessarily $\mathbf{Z}$-valued, and prove a formula of the second derivative of the two-variable $p$-adic $L$-function of an abelian variety of ${\rm GL}(2)$-type associated to a Hilbert modular form of weight 2.
The effects of worry, risk perception, information-seeking experience, and trust in misinformation on COVID-19 fact-checking: a survey study in China

Abstract Health misinformation is a serious problem that can cause confusion and risk-taking behaviors, undermining public health efforts. Fact-checking has been highlighted as an effective tool for coping with the challenge of misinformation. However, few studies have examined the factors influencing individuals’ health fact-checking behaviors. Using the comprehensive model of information seeking, we conducted a two-wave panel survey in China during the COVID-19 pandemic and explored the underlying process that might hinder COVID-19 fact-checking. The results showed that risk perception and worry about COVID-19 triggered a negative COVID-19 information-seeking experience, which reduced COVID-19 fact-checking. Moreover, the propensity to trust COVID-19 misinformation played a moderating role, such that negative information-seeking experience had a stronger negative effect on fact-checking behaviors for people with a greater propensity to trust misinformation. This study demonstrates the dark side of cognitive and affective responses to risks and health information-seeking experiences. The findings offer important implications for future health communication initiatives to effectively promote health fact-checking behaviors.
Kalman Filter-Based Super-Twisting Sliding Mode Control of Shunt Active Power Filter for Electric Vehicle Charging Station Applications

Electric vehicle (EV) charging stations draw nonlinear currents, which makes the distribution network unbalanced, distorted, and results in power quality (PQ) issues. These PQ issues are mitigated in this work through high-performance control of the shunt active power filter (SAPF). In the proposed method, a linear Kalman filter (LKF) has been applied to grid voltage and load current signals for harmonic and disturbance robust estimation purpose. Unlike the conventionally used orthogonal vector model, in this work, phase angle vector model together with a simple to tune phase-locked loop (PLL) has been considered for the LKF implementation. DC-link voltage regulation and charging of the DC-link capacitor has been obtained by proposing a Luenberger observer-based super twisting sliding mode control (ST-SMC), which has fast dynamic response and lower voltage ripples compared to similar other existing control methods. This results in significant reduction in size, cost and loss together with lifetime enhancement of the DC-link capacitor. Rigorous sensitivity analysis is conducted to analyze the robustness of the developed method. The proposed control technique achieves fast response time and satisfy the harmonic requirements as specified in the IEEE Std. 519 under various grid and load disturbances. Comparative quasi-real time validation results are presented by using digital signal processor (DSP) based processor-in-the-loop (PIL) with another recently proposed control strategy to verify the performance enhancement by the developed method.
Learning-Based Secure Control for Multichannel Networked Systems Under Smart Attacks

This article is concerned with the security control of a class of discrete-time linear cyberphysical systems (CPSs) subject to denial-of-service attacks. To enhance the inherent resistance of the CPS against damage and attacks, a multichannel network is employed for remote information interaction between the ingredients of the system. In this way, a complex interaction process will be formed between the signal sender and the smart malicious adversary. Specifically, in the context of using the multichannel network, the malicious adversary has to maximize the attack success probability within its energy constraint. As a counterpart, the system tries to mitigate the negative impact of such attacks on CPS control performance. For the purpose of designing a control strategy to cope with the attacks, this interaction process is formulated as a zero-sum stochastic game, while the Nash equilibrium solution of this problem is found with the help of the proposed learning algorithm, and the optimal mixed strategies for both attackers and defenders are derived. Furthermore, for the CPS driven by the obtained decision-making strategies, a Kalman filter-based active dynamic output feedback resilient controller is proposed. Finally, the effectiveness of the developed optimal defense strategies and the resilient controller is demonstrated by extensive case studies on the servo motor experimental platform.
Continuum modeling of coupled oscillator arrays with coupling delay

The previously published linearized continuum model of a linear (one‐dimensional) array of mutually injection locked oscillators is generalized to include the effects of time delay in the interoscillator coupling. This generalization is motivated by a desire for causal solutions describing the dynamics of the phase distribution in the aperture of a phase array antenna driven by such an array of oscillators. The solutions for the phase dynamics will, in general, be noncausal unless the coupling delay is taken into account. In the present formulation the coupling delay is represented by an exponential factor introduced in the Laplace transform of the partial differential equation arising in the continuum model. As a result of this, the transform of the phase distribution exhibits an infinite set of branch points in the complex frequency plane and the inverse transform is computed as the sum of the integrals around the branch cuts.
Control Law Synthesis for a Discrete Event System

In this work we investigate whether it is possible to synthesize the control law for a discrete event system, using a polynomial representation of the system and controller. By working through a relatively simple example we propose a synthesis method based on the polynomial representation and repeated Grobner basis calculations. The control objective is given in terms of forbidden states and the controller should actively be able to avoid these. We reduce the manifold of solutions by imposing a weight function on the state space and by proposing a priority among the actuators. In this way we improve the computational performance radically. The computational load lies in the design phase where we use Grobner bases. The resulting controller description is suited for real time applications since the computations needed are evaluations of a limited number of polynomials. During the design phase we also obtain a polynomial describing where in the state space the computed control law is valid. This makes it possible to examine controllability of the system.
Electronic and Optical Properties of BP, InSe Monolayer and BP/InSe Heterojunction with Promising Photoelectronic Performance

Two-dimensional (2D) materials provide a new strategy for developing photodetectors at the nanoscale. The electronic and optical properties of black phosphorus (BP), indium selenide (InSe) monolayer and BP/InSe heterojunction were investigated via first-principles calculations. The geometric characteristic shows that the BP, InSe monolayer and BP/InSe heterojunction have high structural symmetry, and the band gap values are 1.592, 2.139, and 1.136 eV, respectively. The results of band offset, band decomposed charge and electrostatic potential imply that the heterojunction structure can effectively inhibit the recombination of electron–-hole pairs, which is beneficial for carrier mobility of photoelectric devices. Moreover, the optical properties, including refractive index, reflectivity, electron energy loss, extinction coefficient, absorption coefficient and photon optical conductivity, show excellent performance. These findings reveal the optimistic application potential for future photoelectric devices. The results of the present study provide new insight into challenges related to the peculiar behavior of the aforementioned materials with applications.
Sim-to-Real Transfer for Fixed-Wing Uncrewed Aerial Vehicle: Pitch Control by High-Fidelity Modelling and Domain Randomization

Deep reinforcement learning has great potential to automatically generate flight controllers for uncrewed aerial vehicles (UAVs), however these controllers often fail to perform as expected in real world environments due to differences between the simulation environment and reality. This letter experimentally investigated how this reality gap effect could be mitigated, focusing on fixed-wing UAV pitch control in wind tunnel tests. Three different training approaches were conducted: a baseline approach that used simple linear dynamics, a high-fidelity modeling approach, and a domain randomization approach. It was found that the base line controller was susceptible to the reality gap, while the other two approaches successfully transferred to real tests. To further examine the controllers' capabilities to generalize, a variety of configuration changes were experimentally implemented on the UAV, such as increased inertia, extended elevator area, and aileron offset. While the high-fidelity controller failed to cope with these changes, the controller with domain randomization maintained its performance. These results highlight the importance of selecting appropriate sim-to-real transfer approaches and how domain randomization is applicable to fixed-wing UAV control with uncertainty in real environments.
Image De-Noising Techniques: A Review Paper

Image de-noising is an important image processing task, both as a process itself, and as a component in other processes. In today’s scenario transmission of information through images has become a major medium of communication. But during transmission of images they get affected by some external means called as noise. The search for effective and efficient image denoising methods is a great challenge for researchers. Different algorithms are available and each algorithm has its assumptions, advantages and limitations. This paper presents a review of some significant work in the field of Image De-noising. The brief introduction of some popular approaches is provided and discussed. KeywordsSpatial filtering, linear filtering, non-linear filtering.
Exploring factors affecting customer trust in social distancing technology and impact on hotel booking intentions

Abstract The outbreak of COVID-19 in 2019 has posed an unprecedented threat to the global economy. Due to the pandemic, the hotel industry has undergone fundamental changes. In particular, social distancing technology (SDT) has become an indispensable tool in this industry and has played a vital role in its recovery. This study explores the factors that affect customer trust in using SDT in hotels during COVID-19 and how this trust affects their booking intention. The research uses social exchange theory (SET) as the theoretical basis and measures the benefits and perceived risks of using SDT through the benefit-risk method. In addition, the technology acceptance model (TAM) is introduced, and two attributes are added: perceived ease of use and perceived usefulness. A total of 437 questionnaires were distributed, of which 405 were valid. Research results show that benefits, perceived usefulness, and perceived ease of use positively affect trust in SDT, while privacy concerns have a negative impact. Health risks and social rewards are not directly related to trust in SDT.This study provides ideas for future research on the health aspects of SDT by studying the benefits and health risks brought about by its use. For relevant practitioners, hotels should reasonably incorporate SDT into their daily operations and conduct regular disinfection to reduce the risks caused by direct and indirect contact to protect the lives and health of both customers and workers.
DNA intercalators alkaloids as Potential candidates to fight COVID-19 disease: Systematic review

The main objective of the current systematic review was to report the antiviral and anti-inflammatory effects of bioactive molecules class known as alkaloids against SARS-COV-2 disease. These bioactive compounds were characterized by their potential replication inhibitory ability by DNA intercalating effect, and might be powerful agents against infections caused by several viruses, therefore it can be a viable strategy for COVID-19 management. PubMed, ScienceDirect, Google Scholar and SpringerLink, databases have been chosen to look for keywords like DNA intercalators, alkaloids, antiviral activity, anti-inflammatory effect, coronavirus, SARS-CoV-2. Two reviewers have evaluated the quality of 60 articles extracted from the four databases till 15th of May 2021, using inclusions and exclusions criteria, 25 papers were accepted and treated in this systematic review, performed based on PRISMA protocol. Results disclosed that alkaloids have key roles in viral replication inhibition, quinine and emetine showed a noticeable therapeutic effect against SARS-COV-2 virus, however emetine revealed modifications in the electrocardiogram (ECG), unlike sanguinarine and berberine that showed low human toxicity. Tetrandrine, fangchinoline and cepharantine could be classified as remedies in case of Coronavirus ailment. Chelidonine, coptisine, skimmianine, protropine, palmatine, cinchonine, harmine and dictamine represented important agents for clinical researches or as precursors for antiviral drug’s formulation.
A remote sensing based study of tropospheric ozone concentration amid COVID-19 lockdown over India using Sentinel-5P satellite data

Abstract Amid the COVID-19 crisis, governments all over the world, and not excluding India, took to lockdown measures to deaccelerate the spread of the COVID-19 virus. This led to reduction of atmospheric pollution by declining the harmful Nitrogen and Sulphur Oxide (NOX and SOX) concentrations. However, one hand while the stratospheric Ozone (O3) showed repair, the lower atmospheric O3 concentrations demonstrated a remarkable increase during lockdown phase over India. This study aims to estimate the O3 concentration during the Covid-19 lockdown over Pune city in India using freely available Sentinel-5P satellite datasets. The study makes use of the Ordinary Least Squares (OLS) and Random Forest (RF) regressions and compares the findings of the two algorithms based on estimation results. This study utilizes lower atmospheric O3 concentration data from Sentinel-5P satellite of the European Space Agency (ESA) over the Indian mainland for a month of lockdown scenario (March 22nd, 2020, to April 25th, 2020) and shows the remarkable increase in concentration of O3 gas as a pollutant. Despite the complete lockdown over India during this given time frame, there has been enough emission of O3 precursors from other sources such as stubble burning. The estimates of tropospheric O3 concentration for May 2020 for Pune city, using OLS and RF Regressions, have been validated with May 2020 data. The results have provided a RMSE of 1.05 and 1.23 with R2-statistics of 0.90 and 0.857 in training and testing phases for OLS and RMSE of 0.98 and MAE of 1.07 with R2-statistics of 0.968 and 0.895 in training and testing phases of the RF. The outcome of this study has proven that O3 gas concentrations in the atmosphere depends upon various other causative factors apart from the precursor gases. The study also shows that the remotely sensed Sentinel-5P datasets, supplemented with ground-based sensor data can help in time and cost saving estimation of O3 concentrations in the troposphere with considerable accuracy.
Using scales in the multi-objective approach

Scales are used to reduce the conservatism encountered in most multi-objective approaches. While the most general case (i.e., matrix scales) results in a nonconvex problem, use of scalar scales lead to convex searches in the analysis and state feedback problems. Numerical examples to show the effectiveness of the suggested approach, and output feedback synthesis is also discussed.
Temporal changes in factor adjustment of the Japanese manufacturing industry

Abstract This study investigated temporal changes in factor adjustment of the Japanese manufacturing industry by applying a dynamic factor model, in which labor and capital were quasi-fixed to a panel of industries from 1972 to 2012. Estimations show that the adjustment speeds, with which factors approach their optimum levels, have increased over the period. Particularly, factor adjustment rates have significantly increased since 2000. The estimations suggest that Japanese manufacturers have become more flexible in hiring workers and faster in making investments, which reduces adjustment cost significantly. This dynamic gain is ignored from static analysis, underestimating the benefit of labor market reform. The study suggests that policymakers should consider dynamic factor adjustment in assessing policy impacts accurately when implementing an industrial policy.