Miracle-dz/UniFAR-FTUs huggingface dataset:
Atrial fibrillation episode status and incidence of coronary slow flow: A propensity score-matched analysis

Background Previous studies have shown that patients with a history of atrial fibrillation (AF) have a higher risk of developing coronary slow flow (CSF). However, whether AF episode status affects the incidence of CSF has not been confirmed. This study investigated the correlation between AF episode status and the incidence of CSF. Methods We enrolled patients with AF who underwent coronary angiography for symptoms of myocardial ischemia between January 1, 2017, and April 30, 2022, at our institution and classified them according to whether they had an episode of AF in the perioperative period. The outcomes were defined the occurrence of CSF overall and in each of the three coronary arteries. The analysis was repeated after adjusting the baseline information by the propensity score matching method in a 1:1 ratio. Results 214 patients who met the inclusion and exclusion criteria were included in the study (AF episode group: 100 patients, AF non-episode group: 114 patients). Before matching, age, left atrial size, ejection fraction, heart rate, CSF incidence, and mean corrected thrombolysis in myocardial infarction frame counts were higher in patients with intraoperative AF episodes than in patients without episodes. To prevent the dependent variable (CSF incidence) from being confounded by confounding factors, we matched the two groups for age, left atrial size, and ejection fraction. In the logistic regression analysis, the incidence of CSF was significantly higher in the intraoperative AF episode group (P = 0.010, OR = 2.327, 95% CI: 1.226–4.416) than in the non-episode group. Conclusion In patients with AF, AF episode status is significantly correlated with an increased overall incidence of CSF.
Analysis of Electromagnetic Scattering from Three-dimensional Time-varying Magnetized Plasma by Newton-ADE-FDTD Method

In this paper, Newton’s equations of motion, which describe electron motion when electromagnetic wave propagates in magnetized plasma, are combined with the traditional auxiliary differential equation method (ADEFDTD). An iterative formula of finite difference time domain (FDTD) algorithm for the three dimensional time-varying magnetized plasma is derived, which is called Newton-ADEFDTD method. The correctness of the algorithm is verified by calculating the radar cross section (RCS) of the time-varying magnetized plasma sphere. At the same time, the electromagnetic scattering characteristics of metal spheres coated with plasma are calculated by using this algorithm. The results show that the metal spheres coated with magnetized plasma have better stealth effect than those coated with uncoated plasma and coated with non-magnetized plasma.
HashDroid:Extraction of malicious features of Android applications based on function call graph pruning

With the Android system becoming the most popular operating system for mobile smart terminals, it is more likely to be targeted by malware. Therefore, many researches of malicous detection have emerged. Most of the features extracted of current malicious detection are discrete, such as single permission, single API, single component, API sequences and so on. These features can only detect the maliciousness of Android applications, but cannot characterize the malicious behavior of Android applications through these features. In this paper,we propose a method to automatically mine malicious features by pruning the function call graph(FCG) of Android applications. These extracted features not only have a good representation for the malicious behavior of Android applications, but also can efficiently detect the malicious. The method uses simhash to characterize the pruned subgraphs of FCG, and selects the subgraphs which play a decisive role in determining maliciousness as malicious features. These malicious features are then used for malicious detection of Android applications. The verification on public datasets shows that our method has a good effect of more than 97% in malicous detection of Android applications.
Photosynthetic Physiological Basis of No Tillage with Wheat Straw Returning to Improve Maize Yield with Plastic Film Mulching in Arid Irrigated Areas

Surface mulch is an efficient plant production technique widely used in arid and water-scarce areas. In this study, a field experiment was conducted to determine whether plastic film combined with wheat straw returning could boost grain yield of maize via optimizing photosynthetic physiological characteristics and coordinating yield components. The results showed that no tillage with wheat straw mulching and straw standing treatments had better regulation on photosynthetic physiological characteristics and had a greater impact on the increase in grain yield than conventional tillage with wheat straw incorporation and without wheat straw returning (the control treatment) in plastic film-mulched maize. Meanwhile, no tillage with wheat straw mulching had a relatively higher yield than no tillage with wheat straw standing through better regulation of photosynthetic physiological characteristics. No tillage with wheat straw mulching decreased the leaf area index (LAI) and leaf area duration (LAD) of maize before the VT stage and maintained higher LAI and LAD after the VT stage, which effectively regulated the growth and development of maize at early and late stages of development. From VT to R4 stage of maize, no tillage with wheat straw mulching had greater chlorophyll relative content, net photosynthetic rate, and transpiration rate by 7.9–17.5%, 7.7–19.2%, and 5.5–12.1% than the control, respectively. In addition, leaf water use efficiency was increased by 6.2–6.7% from the R2 to R4 stage of no tillage with wheat straw mulching in comparison to the control treatment. Thus, no tillage with wheat straw mulching had a greater grain yield of maize by 15.6% than the control, and the high yield was attributed to the synchronous increase and cooperative development of ear number, grain number per ear, and 100-grain weight. Collectively, no tillage with wheat straw mulching had a positive effect on regulating the photosynthetic physiological traits and can be recommended to enhance the grain yield of maize in arid conditions.
Simple Refraction Law for Uniaxial Anisotropic Absorbing Media

In anisotropic media, there exist ordinary and extraordinary rays. Until now, there has been no simple refraction law like Snell's law for the extraordinary ray. In this study, with the Fresnel model, we made a simple refraction law applicable to both ordinary and extraordinary rays, though it is limited for uniaxial media. The obtained formula could explain the differences between the two rays and would be very useful in extending the traditional isotropic electromagnetic theories to the uniaxial anisotropic electromagnetic theories.
Evaluation of the Architecture Alternatives for Real-Time Intrusion Detection Systems for Vehicles

Attackers demonstrated the use of remote access to the in-vehicle network of connected vehicles to take control of these vehicles. Machine-learning-based Intrusion Detection Systems (IDSs) techniques have been proposed for the detection of such attacks. The evaluations of some of these IDSs showed their efficacy in terms of accuracy in detecting message injections but were performed offline, which limits the confidence in their use for real-time protection scenarios. This paper evaluates four architecture designs for real-time IDS for connected vehicles using Controller Area Network (CAN) datasets collected from a moving vehicle under malicious speed reading message injections. The evaluation shows that a real-time IDS for a connected vehicle designed as a separate process for CAN Bus monitoring and another one for anomaly detection engine is reliable (does not lose messages) and could be used for real-time resilience mechanisms as a response to cyber-attacks.
Comparing HTTP And COAP For IoT Low-power and Lossy Networks Using The Cooja Simulator

The Internet of Things is made up of linked physical objects like cars, appliances, and other things that transmit data (IoT), These products, which contain electronics, software, sensors, and actuators, are efficient with regard to resources. But many IoT devices are too small to create a secure connection. This implied that action needed to be taken right now. As a result, The Internet Engineering Task Force developed the Constrained Application Protocol (CoAP). The Http protocol and CoAP are contrasted in this article.
Long-distance WDM transmission experiments using the dispersion slope compensator

Recently, long-haul transmission experiments of more than 100-Gbit/s capacity were reported. Wavelength-division multiplexing (WDM) is a key technology to achieve this kind of high-capacity transmission. One technical problem of the long distance WDM transmission is the dispersion slope of the transmission fiber. It causes the difference of the chromatic dispersion accumulation upon the WDM channels, and it will lead to transmission performance degradation. In order to solve the problem, equalization of the dispersion slope should be quite effective. This paper describes the results of the long-distance transmission experiments using the dispersion slope equalization. Both IM-DD WDM and optical soliton WDM are discussed.
Point and interval estimation of the population size using the truncated Poisson regression model

A method is presented to derive point and interval estimates of the total number of individuals in a heterogenous Poisson population. The method is based on the Horvitz-Thompson approach. The zero-truncated Poisson regression model is fitted and results are used to obtain point and interval estimates for the total number of individuals in the population. The method is assessed by performing a simulation experiment computing coverage probabilities of Horvitz-Thompson confidence intervals for cases with different sample sizes and Poisson parameters. We illustrate our method using capture-recapture data from the police registration system providing information on illegal immigrants in four large cities in the Netherlands.
One Pot Self-Assembling Fe@PANI Core–Shell Nanowires for Radar Absorption Application

The one-pot process, which combines the polymerization of polyaniline (i.e., PANI) with subsequent reduction of iron nanowire (i.e., Fe NW) under a magnetic field, was developed to produce Fe@PANI core–shell nanowires. The synthesized nanowires with various PANI additions (0–30 wt.%) were characterized and used as microwave absorbers. Epoxy composites with 10 wt. % absorbers were prepared and examined using the coaxial method to reveal their microwave absorbing performance. Experimental results showed that the Fe NWs with PANI additions (0–30 wt.%) had average diameters ranging from 124.72 to 309.73 nm. As PANI addition increases, the α-Fe phase content and the grain size decrease, while the specific surface area increases. The nanowire-added composites exhibited superior microwave absorption performance with wide effective absorption bandwidths. Among them, Fe@PANI-90/10 exhibits the best overall microwave absorption performance. With a thickness of 2.3 mm, effective absorption bandwidth was the widest and reached 3.73 GHz, ranging from 9.73 to 13.46 GHz. Whereas with a thickness of 5.4 mm, Fe@PANI-90/10 reached the best reflection loss of −31.87 dB at 4.53 GHz.
A Comparative Study on the Security of Cryptocurrency Wallets in Android System

The security of crypto wallets is a major concern in light of the recent prevalence of thefts. Aiming at the problem that there is no complete and reliable security detection model for Android-based crypto wallets, this study provides an evaluation framework based on the standard Android application security detection and unique security assessment of crypto wallets. The framework presents an attack-based detection approach, which identifies potential wallet security issues by simulating attacks and exploiting vulnerabilities. Ten popular Android crypto wallets are evaluated and compared to validate the framework’s practicability and accuracy. The test results demonstrate that the framework can accurately reflect the performance security of wallets. Additionally, the study proposes the corresponding actions to address the identified common security threats in crypto wallets.
Mode locking of semiconductor diode lasers using saturable excitonic nonlinearities

Multiple-quantum-well (MQW) structures of GaAs and GaAlAs have been used for passive mode locking of commercial GaAs semiconductor diode lasers. We present an extended discussion of this application of the sensitive room-temperature excitonic absorption saturation in MQW material. We review the criteria for passive mode locking and discuss two methods—carrier diffusion and proton bombardment—for reducing the aborption recovery time without destroying the excitonic nonlinearity. A simple probabilistic theory is derived for the effect of bombardment on the excitonic effects that is in order-of-magnitude agreement with experiment. We have performed experiments using MQW material to mode lock a GaAs laser. A continuous train of pulses as narrow as 1.6 psec has been obtained with a pulse-repetition rate of 2 GHz.
Fibrinogen Is Associated with Prognosis of Critically Ill Patients with Sepsis: A Study Based on Cox Regression and Propensity Score Matching

Introduction Sepsis is a common syndrome in critically ill patients. Fibrinogen was reported to be associated with the prognosis of sepsis patients. Materials and Methods Data was acquired from Multiparameter Intelligent Monitoring in Intensive Care Database IV (MIMIC-IV) version 1.0. Cox proportional hazards regression was utilized to estimate the relationship between fibrinogen and inhospital mortality. The cumulative incidence of mortality by fibrinogen level was estimated through the Kaplan-Meier curve. Restricted cubic spline (RCS) was used to assess nonlinear relationship. Subgroup analysis was also conducted to evaluate the robustness of the association between fibrinogen and inhospital mortality. Propensity score matching (PSM) was applied to adjust for confounding factors. Results A total of 3365 patients, including 2031 survivors and 1334 nonsurvivors, were enrolled in our study. The survivors had a significantly elevated levels of fibrinogen compared with the deceased. The elevated level of fibrinogen was significantly associated with a decrease in mortality in multivariate Cox regression before and after PSM (HR 0.66, P < 0.001 and HR 0.73, P < 0.001, respectively). RCS showed a nearly linear relationship. Subgroup analysis demonstrated the robustness of the association in most subpopulations. However, the association between decreased levels of fibrinogen and increased inhospital mortality was denied after PSM. Conclusion The elevated level of fibrinogen hints at better overall survival in critically ill patients with sepsis. Decreased levels of fibrinogen may be of little value in identifying patients with a high risk of death.
An Improved S-Plane Controller for High-Speed Multi-Purpose AUVs with Situational Static Loads

The classic S-plane control method combines PD structure with fuzzy control theory, with the advantages of a simple control structure and fewer parameters to be adjusted. It has been proved as a practical method in an autonomous underwater vehicle (AUV) motion control at low and medium speeds, but it takes no account of the situational static load and varying hydrodynamic forces which influence the control quality and even result in a “dolphin effect” at the time of high-speed movement. For this reason, an improved S-plane controller is designed based on the sliding mode variable structure, sliding mode surface, and control items in order to respond to the situational static load and high-speed movement. The improved S-plane controller is verified by Lyapunov stability analysis. The thrust allocation strategies are also discussed with constraints introduced in accordance with task requirements. In order to verify the practicability and effectiveness of the improved S-plane controller, both simulation experiments and field trials of AUV motion control, long-range cruise, and path point following were carried out. The results have demonstrated the superiority of the improved S-plane controller over the classic S-plane controller.
Dynamic relationships between gross primary production and energy partitioning in three different ecosystems based on eddy covariance time series analysis

Ecosystems are responsible for strong feedback processes that affect climate. The mechanisms and consequences of this feedback are uncertain and must be studied to evaluate their influence on global climate change. The main objective of this study is to assess the gross primary production (GPP) dynamics and the energy partitioning patterns in three different European forest ecosystems through time series analysis. The forest types are an Evergreen Needleleaf Forest in Finland (ENF_FI), a Deciduous Broadleaf Forest in Denmark (DBF_DK), and a Mediterranean Savanna Forest in Spain (SAV_SP). Buys-Ballot tables were used to study the intra-annual variability of meteorological data, energy fluxes, and GPP, whereas the autocorrelation function was used to assess the inter-annual dynamics. Finally, the causality of GPP and energy fluxes was studied with Granger causality tests. The autocorrelation function of the GPP, meteorological variables, and energy fluxes revealed that the Mediterranean ecosystem is more irregular and shows lower memory in the long term than in the short term. On the other hand, the Granger causality tests showed that the vegetation feedback to the atmosphere was more noticeable in the ENF_FI and the DBF_DK in the short term, influencing latent and sensible heat fluxes. In conclusion, the impact of the vegetation on the atmosphere influences the energy partitioning in a different way depending on the vegetation type, which makes the study of the vegetation dynamics essential at the local scale to parameterize these processes with more detail and build improved global models.
Developing ERP success model in Indian manufacturing sector

Manufacturing companies invest a lot of time and money into implementing ERP with the expectation that this will boost productivity. However, the failure rate of ERP adoption is typically very high. Critical success factors (CSF), factors related to risk and factors related to ERP project selection can help in achieving project management success in number of ways. This paper focuses on how CSF, risk factors and project selection factors have an impact on the project management success. Further this study has shown the mediating role of user satisfaction on realizing the benefits of ERP implementation.
The Effect of Increasing Sample Size on the Precision of an Estimator

of n real variables x1,x2,. xn, and use the fact that g (E(Xi), E (X2). I. E (Xn) ) _< E(g(X-,X,,X. * .,X,,) ). to obtain (1) . Similarly consider the convex function h(y) = \/y of a single real variable y, use the fact n that h (E (Y)) E (h (Y) ), and replace Y by E X,2 to j 1 obtain (2). There is however a more elementary method for proving (1) and (2), which does not depend on the concept of convexity. It is as follows: By Schwarz's inequality for any two vectors
Sub-10-nm Tunnel Field-Effect Transistor with Schottky Drain

An SD-TFET, which is a tunnel field effect transistor with Schottky drain, is proposed in this paper for sub-10-nm applications. On-off switching characteristics were examined by examining some of the critical device parameters, including the metal work-function in a Schottky drain. When designing SD- TFETs for low-power integrated circuits, a moderate Schottky drain work-function is preferred.
Self-Driving Car: Simulation of Highly Automated Vehicle Technology using Convolution Neural Networks

Driver behaviour is a significant factor in the smooth driving of vehicles on the roads. 94 % of crashes and road accidents are prone to drivers' rash driving behaviour. To address issues related to road accidents and crashing of vehicles on the road, Highly Automated Vehicle (HAV) Technologies have been proposed. Self-Driving Cars are part of Highly Automated Tech-nologies having promising benefits ranging from Greater Road Safety, Greater Independence, Saving money, More Productivity, Reduced Congestion and Green House Gains. The current study focuses on the deployment of self-driving automobiles based on the Deep Learning paradigm. The automobile has been simulated on the Udacity simulator for convenience and safety. On the Udacity platform, a technique for training and simulating an unmanned vehicle model using a convolutional neural network has been developed. The data used to train the model is captured in the simulator and fed as input into the Deep CNN. Following data collection, Deep CNN is trained to have Safety Navigation by passing Steering, Throttle, Brake and Speed as Control Inputs. The use of three cameras considerably improves the precision of the navigation job. To manage the car, the steering wheel amount will be modified such that it runs in the centre of the lane. We evaluated the model using UDACITY's simulation system. The proposed model has been evaluated considering the-No of epochs vs loss calculation, as performance metrics, and was found that the proposed model has shown superiority with the existing works.
An Ontological Analysis of Safety-Critical Software and Its Anomalies

The progressively dominant role of software in safety-critical systems raise concerns about the software dependability. There are limited mature practices and guides for assessing software dependability and analyzing system-level hazards triggered by software anomalies. A problem is that faults, errors, and failures that represent software anomalies, albeit with different natures, are usually used indistinctly to predict software dependability, leading to unsolid results. The lack of such consensual conceptualization also leads to poor interoperability between supporting tools, and, consequently, difficulties in anomaly management and software maintenance. Anomaly analysis and management is more tough for safety-critical software due to its higher complexity and the safety-critical nature. The complex context of safety-critical software causes difficulties in determining the evolution/propagation path of software anomalies and the impact on system safety. To capture the nature of safety-critical software and support an understanding of mechanisms of software anomalies and associated hazards, we propose three reference ontologies: Safety-critical Software Ontology, Software Fault Ontology and Software-failure-induced Hazard Ontology, which are built based on international standards, guides, and relevant conceptual models. We also discuss the relationships among them. That will facilitate a better understanding of the software anomaly mechanisms and the design of intervening/mitigation solutions. We demonstrate how these ontologies can help analyze software problems of real-world safety-critical systems.
Markovian Projection Onto a Heston Model

We develop a systematic approach to the reduction of dimensionality of smile-enabled models by projecting them onto a displaced version of the two-dimensional Heston process. The projection is the key for deriving efficient, analytical approximations to European option prices in such models. This is a further development of the method of Markovian projection previously used for projecting on the displaced-diffusion process (with skew but without smile). The method is derived in a generic form and has a wide range of suitable applications. Examples for spread and basket options are given.