Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple introductions, polyploidy and mixed reproductive strategies are linked to genetic diversity and structure in the most widespread invasive plant across Southern Ocean archipelagos

Biological invasions in remote areas that experience low human activity provide unique opportunities to elucidate processes responsible for invasion success. Here we study the most widespread invasive plant species across the isolated islands of the Southern Ocean, the annual bluegrass, Poa annua. To analyse geographical variation in genome size, genetic diversity and reproductive strategies, we sampled all major sub‐Antarctic archipelagos in this region and generated microsatellite data for 470 individual plants representing 31 populations. We also estimated genome sizes for a subset of individuals using flow cytometry. Occasional events of island colonization are expected to result in high genetic structure among islands, overall low genetic diversity and increased self‐fertilization, but we show that this is not the case for P. annua. Microsatellite data indicated low population genetic structure and lack of isolation by distance among the sub‐Antarctic archipelagos we sampled, but high population structure within each archipelago. We identified high levels of genetic diversity, low clonality and low selfing rates in sub‐Antarctic P. annua populations (contrary to rates typical of continental populations). In turn, estimates of selfing declined in populations as genetic diversity increased. Additionally, we found that most P. annua individuals are probably tetraploid and that only slight variation exists in genome size across the Southern Ocean. Our findings suggest multiple independent introductions of P. annua into the sub‐Antarctic, which promoted the establishment of genetically diverse populations. Despite multiple introductions, the adoption of convergent reproductive strategies (outcrossing) happened independently in each major archipelago. The combination of polyploidy and a mixed reproductive strategy probably benefited P. annua in the Southern Ocean by increasing genetic diversity and its ability to cope with the novel environmental conditions.
Double-pump-pass singly resonant optical parametric oscillator for efficient generation of infrared light at 2300 nm based on PPMgSLT

The pump laser was a cw-diode-pumped, acousto-optically Q-switched Nd:YAG laser. The laser had a pulse width of ~85 ns when operating at 10 kHz repetition rates. For infrared output of 2300 nm, we used 35-mm-long PPMgSLT which has a grating period of 32.7 μm for the first-order quasi-phase matching, resulting in the signal wavelength of 1980 nm at the crystal temperature of 76.5oC. Our optical parametric oscillator (OPO) was of a simple linear extra-cavity structure, formed by two flat dichroic mirrors with a separation of ~45 mm. The input coupling mirror had a high transmission of 98% for the pump, high reflectance of 98% at the signal and idler wavelengths, whereas the output coupler had a high reflectance of 98% at the pump wavelength. Hence, the OPO can be considered as singly resonant with double-pass pumping. In order to find an optimum reflectance for the efficient generation of infrared radiation of 2300 nm, we used the three different output mirrors whose reflectivity are ranging from 90% to 38% at the signal wavelength. We measured the signal and idler power as a function of the pumping power of Nd:YAG laser for three different output couplers. A maximum extraction efficiency with an optimum reflectance of output mirror was 27% for the idler, corresponding to 5.6 W of average output power. The fluctuations in the idler root-mean-square output power were measured to be below 1.5%. Our result is comparable with the recent one based on PPLN even with a simple cavity.
Temperature-dependent energy band gap variation in self-organized InAs quantum dots

We investigated the temperature-dependent variation of the photoluminescence emission energy of self-organized InAs/GaAs quantum dots (QDs) grown by conventional Stranski-Krastanov (SK) molecular beam epitaxy and migration-enhanced molecular beam epitaxy (MEMBE) and that of MEMBE InAs QDs in a symmetric and an asymmetric In0.2Ga0. 8As/GaAs well. The temperature-dependent energy variation of each QD is analyzed in low and high temperature regions, including a sigmoidal behavior of conventional SK quantum dots with the well-known Varshni and semi-empirical Fan models.
Increase in the extraction efficiency of GaN-based light-emitting diodes via surface roughening

Roughened surfaces of light-emitting diodes (LEDs) provide substantial improvement in light extraction efficiency. By using the laser-lift-off technique followed by an anisotropic etching process to roughen the surface, an n-side-up GaN-based LED with a hexagonal “conelike” surface has been fabricated. The enhancement of the LED output power depends on the surface conditions. The output power of an optimally roughened surface LED shows a twofold to threefold increase compared to that of an LED before surface roughening.
Nonlinear wave-particle interaction upstream from the Earth's bow shock

Well-defined ring-like backstreaming ion distributions have been recently reported from observations made by the 3DP/PESA-High analyzer onboard the WIND spacecraft in the Earth's foreshock at large distances from the bow shock, which suggests a local production mechanism. The maximum phase space density for these distributions remains localized at a nearly constant pitch-angle value for a large number of gyroperiods while the shape of the distribution remains very steady. These distributions are also observed in association with quasi-monochromatic low frequency (~ 50 mHz) waves with substantial amplitude (dB/B>0.2). The analysis of the magnetic field data has shown that the waves are propagating parallel to the background field in the right-hand mode. Parallel ion beams are also often observed in the same region before the observation of both the ring-like distributions and the waves. The waves appear in cyclotron resonance with the ion parallel beams. We investigate first the possibility that the ion beams could provide the free energy source for driving an ion/ion instability responsible for the ULF wave occurrence. For that, we solve the wave dispersion relation with the observed parameters. Second, we show that the ring-like distributions could then be produced by a coherent nonlinear wave-particle interaction. It tends to trap the ions into narrow cells in velocity space centered on a well-defined pitch-angle, directly related to the saturation wave amplitude in the analytical theory. The theoretical predictions are in good quantitative agreement with the observations
Compact and Low Coupled Monopole Antennas for MIMO System Applications

A novel compact MIMO antenna with high port isolation is presented in this paper. The designed antenna operates at 2.4 GHz with a bandwidth of 2.37–2.46 GHz. In order to improve the isolation between the ports of the two monopoles, a decoupling network is added into the circuit, and a slot is etched on the ground. Simulated and measured results illustrate that the proposed antenna obtains isolation higher than 35 dB while maintaining good impedance matching. The predicted results are compared with the measured data, and good agreement is found.
Evaluation of subgrid-scale models using an accurately simulated turbulent flow

We use a calculation of periodic homogeneous isotropic turbulence to simulate the experimental decay of grid turbulence. The calculation is found to match the experiment in a number of important aspects and the computed flow field is then treated as a realization of a physical turbulent flow. From this flow, we compute the large eddy field and the various averages of the subgrid-scale turbulence that occur in the large eddy simulation equations. These quantities are compared with the predictions of the models that are usually applied in large eddy simulation. The results show that the terms which involve the large-scale field are accurately modelled but the subgridscale Reynolds stresses are only moderately well modelled. It is also possible to use the method to predict the constants of the models without reference to experiment. Attempts to find improved models have not met with success.
A non-minimal state variable feedback approach to multivariable control of glasshouse climate

The paper discusses the multivariable modelling and control of a glasshouse micro-climate. A linear reduced-order control model is obtained from a nonlinear simulation model using novel data-based model reduction and linearisation techniques. This control model is then used to design two multivariable non-minimal state variable feedback (SVF) control systems. The first utilises an LQoptimal Proportional-Integral-Plus (PIP) design method incorporating multi-objective optimisation of the weighting matrices, achieving partial dynamic decoupling; while the second uses an algebraic approach to combined pole-assignment and full dynamic decoupling. These controllers are evaluated, to ensure robustness, using the nonlinear simulation model, prior to implementation and evaluation on the real glasshouse during the 1993-94 winter growing season. Control results are excellent with very tight control to the desired setpoints in all three climate variables. For example, air temperature is controlled to within 0.5°C of the setpoint for 85% of the validation period, and is shown to be very robust to model uncertainty and extreme weather conditions.
Parametric Study of Gold Nanoparticles Synthesis under Micro-Continuous Flow Conditions

The synthesis of gold nanoparticles (GNPs) using chemical reduction in batch and microreactor methods has been reported. A parametric study of the effect of several parameters on the size of gold nanoparticles was performed in batch synthesis mode using the modified Martin method. The best-obtained conditions were used to synthesize gold nanoparticles using a glass chip microreactor, and the size of the resulting GNPs from both methods was compared. The presence of polyvinyl alcohol (SC) was used as a capping agent, and sodium borohydride (SB) was used as a reducing agent. Several parameters were studied, including HAuCl4, SC, SB concentrations, the volumetric ratio of SB to gold precursor, pH, temperature, and mixing speed. Various techniques were used to characterize the resulting nanoparticles, including Atomic Absorbance spectroscopy (AAS), Ultraviolet-visible spectroscopy (UV-Vis), and dynamic light scratching (DLS). Optimum conditions were obtained for the synthesis of gold nanoparticles. Under similar reaction conditions, the microreactor consistently produced smaller nanoparticles in the range of 10.42–11.31 nm with a reaction time of less than 1 min.
Elimination of the Fabry–Perot effect in the 4×4 matrix method for inhomogeneous uniaxial media

Based on the 4×4 matrix method for inhomogeneous uniaxial media by Berreman [J. Opt. Soc. Am. 62, 502 (1972); 63, 1374 (1973)] and by Wohler et al. [J. Opt. Soc. Am. A 5, 1554 (1988)], a simple method to eliminate the Fabry–Perot effect caused by optical discontinuities at the input and output interfaces has been developed. It facilitates an easy comparison between the results of the Jones matrix method and the 4×4 matrix method without the time‐consuming spectral average for the latter. Modeling the case of liquid‐crystal displays with incoherent back‐light sources, this new method will either improve the accuracy with similar computation time or save computation time with similar accuracy, as compared to the ordinary ‘‘faster’’ 4×4 matrix method.
Model-Free Predictive Control of Power Converters with Multifrequency Extended State Observers

The performance of model-free predictive control (MFPC), which is based on the ultralocal model, is highly dependent on the effectiveness of the extended-state observer (ESO). The standard linear ESO has a high-gain which enhances disturbance rejection attributes. Nevertheless, this ESO has two main limitations: 1) it amplifies high-frequency measurement noises, and 2) it deteriorates disturbance rejection performance when the noise immunity is improved. Therefore, this article introduces a new technique to improve both the disturbance rejection and noise suppression of ESO without increasing the bandwidth: the multifrequency-based ESO (MF-ESO). Two novel ESO structures that operate on the MF-ESO principle are analyzed: 1) parallel and 2) cascade ESOs. Extensive frequency domain analyses unravel the comparative capabilities of the MF-ESO structures for improved disturbance rejection and/or high-frequency noise suppression. A novel adaptive gain is proposed to improve CESO's dynamic performance. The superior features of the proposed MF-ESO are experimentally validated by the MFPC of a grid-connected power converter.
Magnetomotive Ultrasound Shear Wave Elastography (MMUS-SWE): A Validation Study From Simulations to Experiments

Ultrasound elastography is a functional imaging method that enables the measurement of soft tissue elasticity, which is associated with the pathological process of many diseases. However, the measurement area of the conventional elastography method is subjectively selected. Inspired by the targeted imaging technology, we propose a method of magnetomotive ultrasound shear wave elastography (MMUS-SWE). This method utilizes the magnetic force between the magnetic nanoparticles (MNPs) and the external magnetic field to generate shear waves. Then, it can detect the distribution of MNPs and the elasticity of the tissue around the MNPs. As MNPs have been widely used for targeted labeling, the strategy to induce local vibration by MNPs will be more specific than that of the conventional SWE. In this study, the theoretical feasibility was verified by the finite element simulation model. Then, an experimental system was built, and the experimental feasibility of the method was demonstrated through phantom experiments, in vitro tissue experiments, and in vivo experiments. The results show that the distribution of the MNPs and the elastic information of tissues surrounding the MNPs can be detected simultaneously. This technology is expected to realize targeted elasticity measurement based on the MNPs and has potential applications for disease diagnosis.
Task Effects in Irony Comprehension in English as a Foreign Language

Irony comprehension involves understanding implicit attitudes communicated on top of the explicit, literal meaning. Because of the double-binding stemming from the explicit–implicit incongruity, irony is assumed to be cognitively taxing when communicated in the native language (NL), and even more so in the foreign language (FL). Prior studies investigating irony comprehension in the FL indicated that irony may be processed with similar speed and accuracy in the foreign and the native language, and that irony comprehension efficiency in the former might be lower. Building on these findings, this study investigates if the tasks participants perform when reading irony in their FL affect the efficiency of irony comprehension. We invited 150 advanced Polish users of English to take part in one of two tasks. Participants were asked to read 3- to 5-sentence-long-scenarios, ending in literal (Literal Praise, Literal Criticism) or ironic comments (Ironic Praise, Ironic Criticism) and to either (1) make true/false judgments (T/F task; N = 83), or to (2) judge the emotional value in emotive decision task (EDT; N = 67). A full spectrum of verbal irony employed to communicate ironic praise and criticism, and their literal equivalents: literal praise and literal criticism, was tested. A three-way mixed ANOVA with 2× Valence (Praise, Criticism), 2× Mode (Literal, Ironic) as within-subject repeated-measures, and 2× Task (True/False, Emotive Decision) as a between-subject independent measure, revealed that efficiency of irony comprehension was differently modified by the two tasks. Therefore, we argue that irony comprehension in English as a foreign language is task-constrained.
Passive User Authentication Utilizing Two-Dimensional Features for IIoT Systems

Passive user authentication is critical for the secure operation of Industrial Internet of Things (IIoT) systems. By jointly utilizing both the time-varying characteristics of the user sequential operation actions and spatial variation characteristics of channel state information (CSI) caused by these actions, this article proposes a novel two-dimensional passive authentication framework for IIoT systems. In particular, we construct the time-varying operation action sequences from the routine work process of a user and apply the Hidden Markov Model to characterize behavioral biometric characteristics of the user, and also employ the eXtreme Gradient Boosting model to depict the spatial variation characteristics of CSI related to the user. By designing two classifiers corresponding these two characteristics and assigning each classifier an appropriate weight, we propose a two-dimensional user authentication framework for continuous and non-intrusive user authentication in IIoT scenarios. Extensive experiments are conducted to illustrate the authentication performance of the proposed authentication framework in terms of false acceptance rate, false rejection rate and equal-error rate. We further investigate the related authentication efficiency issues like the sensitivity to the weights for classifiers, the sensitivity to authentication time and the capability of resisting against impersonation attacks.
OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans

The foot is a vital organ, as it stabilizes the impact forces between the human skeletal system and the ground. Hence, precise foot dimensions are essential not only for custom footwear design, but also for the clinical treatment of foot health. Most existing research on measuring foot dimensions depends on a heavy setup environment, which is costly and ineffective for daily use. In addition, there are several smartphone applications online, but they are not suitable for measuring the exact foot shape for custom footwear, both in clinical practice and public use. In this study, we designed and implemented computer-vision-based smartphone application OptiFit that provides the functionality to automatically measure the four essential dimensions (length, width, arch height, and instep girth) of a human foot from images and 3D scans. We present an instep girth measurement algorithm, and we used a pixel per metric algorithm for measurement; these algorithms were accordingly integrated with the application. Afterwards, we evaluated our application using 19 medical-grade silicon foot models (12 males and 7 females) from different age groups. Our experimental evaluation shows that OptiFit could measure the length, width, arch height, and instep girth with an accuracy of 95.23%, 96.54%, 89.14%, and 99.52%, respectively. A two-tailed paired t-test was conducted, and only the instep girth dimension showed a significant discrepancy between the manual measurement (MM) and the application-based measurement (AM). We developed a linear regression model to adjust the error. Further, we performed comparative analysis demonstrating that there were no significant errors between MM and AM, and the application offers satisfactory performance as a foot-measuring application. Unlike other applications, the iOS application we developed, OptiFit, fulfils the requirements to automatically measure the exact foot dimensions for individually fitted footwear. Therefore, the application can facilitate proper foot measurement and enhance awareness to prevent foot-related problems caused by inappropriate footwear.
Crack propagation in graphene

The crack initiation and growth mechanisms in an 2D graphene lattice structure are studied based on molecular dynamics simulations. Crack growth in an initial edge crack model in the arm-chair and the zig-zag lattice configurations of graphene are considered. Influence of the time steps on the post yielding behaviour of graphene is studied. Based on the results, a time step of 0.1 fs is recommended for consistent and accurate simulation of crack propagation. Effect of temperature on the crack propagation in graphene is also studied, considering adiabatic and isothermal conditions. Total energy and stress fields are analyzed. A systematic study of the bond stretching and bond reorientation phenomena is performed, which shows that the crack propagates after significant bond elongation and rotation in graphene. Variation of the crack speed with the change in crack length is estimated. (C) 2015 AIP Publishing LLC.
Molecular methods to study protein trafficking between organs

Interorgan communication networks are key regulators of organismal homeostasis, and their dysregulation is associated with a variety of pathologies. While mass spectrometry proteomics identifies circulating proteins and can correlate their abundance with disease phenotypes, the tissues of origin and destinations of these secreted proteins remain largely unknown. In vitro approaches to study protein secretion are valuable, however, they may not mimic the complexity of in vivo environments. More recently, the development of engineered promiscuous BirA* biotin ligase derivatives has enabled tissue‐specific tagging of cellular secreted proteomes in vivo. The use of biotin as a molecular tag provides information on the tissue of origin and destination, and enables the enrichment of low‐abundance hormone proteins. Therefore, promiscuous protein biotinylation is a valuable tool to study protein secretion in vivo.
Nature-Inspired Cloud–Crowd Computing for Intelligent Transportation System

Nowadays, it is crucial to have effective road traffic signal timing, especially in an ideal traffic light cycle. This problem can be resolved with modern technologies such as artificial intelligence, cloud and crowd computing. We hereby present a functional model named Cloud–Crowd Computing-based Intelligent Transportation System (CCCITS). This model aims to organize traffic by changing the phase of traffic lights in real-time based on road conditions and incidental crowdsourcing sentiment. Crowd computing is responsible for fine-tuning the system with feedback. In contrast, the cloud is responsible for the computation, which can use AI to secure efficient and effective paths for users. As a result of its installation, traffic management becomes more efficient, and traffic lights change dynamically depending on the traffic volume at the junction. The cloud medium collects updates about mishaps through the crowd computing system and incorporates updates to refine the model. It is observed that nature-inspired algorithms are very useful in solving complex transportation problems and can deal with NP-hard situations efficiently. To establish the feasibility of CCCITS, the SUMO simulation environment was used with nature-inspired algorithms (NIA), namely, Particle Swarm Optimization (PSO), Ant Colony Optimization and Genetic Algorithm (GA), and found satisfactory results.