Miracle-dz/UniFAR-FTUs huggingface dataset:
A Single Phase Transformerless CSI Inverter Topology for Minimization of Leakage Current in Grid Integrated PV Systems

This paper presents the design and analysis of a new five-level single-phase transformer-less current source inverter (CSI) topology for the minimization of ground/leakage current in PV grid integration systems. The topology is configured using inductors & high and low-frequency groups of switches. The Pulse Width Modulation (PWM) is applied to a high-frequency group of switches to fulfill the charging & discharging of inductor currents and the low-frequency group of switches is operated to obtain bi-directional current/voltage at the output. The topology is controlled to limit the common-mode voltage (CMV) frequency at line frequency and thereby the leakage currents are shown minimized. The operation of the converter and MATLAB-based simulation results are presented in the work to showcase the merits of the proposed topology in improving the voltage/current profiles in comparison with the existing ones.
Robust adaptive formation control and collision avoidance for electrically driven non-holonomic mobile robots

This study proposes a robust adaptive formation controller for electrically driven non-holonomic mobile robots to achieve desired formation tracking and collision avoidance with static and moving obstacles. The projection algorithm is employed to estimate the time-varying velocities of the leader robot. The robust adaptive technique is adopted to deal with parametric uncertainties and external disturbances. Moreover, the avoidance function is used to avoid the collisions even though many obstacles exist within the detection region of the mobile robot. It is shown using Lyapunov stability theory that formation errors are uniformly ultimately bounded and collision avoidance is guaranteed. Simulations are included to illustrate the control method.
The pragmatics of reference

It is generally assumed that the "lexical component" of a grammar may be treated on the analogue of the syntac­ tic and phonological components, as a device that pairs words with specifications of the things and classes of things that they can normally be used to refer to; if an item can be used to refer to more than one extension, then, it must be accorded more than one lexical entry. We begin by showing how these assumptions come to grief over the prob­ lems posed by the phenomenon of polysemy, when one word, like chicken, is used to refer at one time to a kind of bird and at another to a kind of meat. It is argued, first that the inclusion of multiple lexical entries leads to undesirable complications in the syntax, and second that pragmatic schemata that generate multiple uses must be inde­ pendently available, since the same phenomena appear in ostensive reference. An account of "deferred ostension" is presented, in which it is shown why you can point at some things to identify others; this account is then extended to the multiple uses of "descriptive terms. " We proceed to argue that with descriptions, there is no way to tell which of the uses of a word is specified by the rules of language, either in practice or in principle; the semantics/pragmatics distinction cannot be drawn. In that case, we argue, the idealization to the knowledge of the ideal speaker-listener in a perfectly homogeneous speech-community is considerably more pernicious for semantics than for syntax or phonology, as we must pre­ sume as well a community in which extralinguistic beliefs and practices are uniform. We conclude that it is more reasonable to describe the speaker's knowledge of wordmeanings as part of his knowledge of the (heterogeneous) collective beliefs of the community, which we can idealize as his "system of normal beliefs," borrowing our model from game theory. Against this idealization, we show, it is possible to explain a number of disparate linguistic phenom­ ena, such as speaker judgments that some word uses are "acceptable," the phenomena associated with "partial moti­ vation," metaphorical word-uses, and change in meaning. Adviser: Professor D. Terence Langendoen Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Understanding and Use of Nutrition Labels of Prepackaged Food by University Students: A Cross-Sectional Study in Chongqing, China

Object: The correct use of nutrition labels for prepackaged food helps university students develop healthy eating habits and prevent the occurrence of chronic non-communicable diseases. This study evaluates the understanding and use of nutrition labels of prepackaged food by university students in four different fields of study in Chongqing, China. Methods: This cross-sectional study used an online survey platform conducted in July 2022 in colleges and universities in Chongqing, China. The convenience sampling method was used to select students in four different fields of study, including medicine, humanities, science and technology, and arts and sports. Ten questions were used to assess participants’ understanding of nutrition labels. A score of six or above (60%) indicates that the respondent has a basic understanding of the nutritional labels of prepackaged food. Descriptive statistics and generalized linear models (GLMs) were used to assess participants’ understanding and use of nutrition labels for prepackaged foods and their influencing factors. Results: A total of 1262 valid questionnaires was collected. The average age of the participants was 21.8 years (SD: 2.43), 50.1% were male, 80.8% were ethnic Han, and 50.9% were from rural areas. Only 21.3% of the university students in Chongqing had a good understanding of the nutrition labels of prepackaged food, where medical students were the highest (39.9%) and science and engineering students were the lowest (15.6%). Gender, ethnicity, grade, major, and whether received courses related to nutrition were influential factors in the understanding and use of nutrition labels of prepackaged food. Medical students also had more positive attitudes toward nutritional labels of prepackaged food. Conclusions: Understanding and use of nutrition labels for prepackaged food by university students in Chongqing are unsatisfactory. Student’s major was a significant influencing factor in nutrition label comprehension, with medical students having the greatest understanding. Based on these results, we suggest that nutrition and health courses should be popularized among non-medical students to narrow the differences between different fields of study. For university students in all fields of study, education and publicity of nutrition labels of prepackaged food are needed, not only in the classroom but also in daily life.
Three-dimensional simulations of rockfalls in Ischia, Southern Italy, and preliminary susceptibility zonation

Abstract Ischia Island is a volcano-tectonic horst in the Phlegrean Volcanic District, Italy. We investigated rockfalls in Ischia using STONE, a three-dimensional model for simulating trajectories for given detachment locations of blocks. We propose methodological advances regarding the use of high-resolution LiDAR elevation data, the localization of possible detachments sources, and the inclusion of scenario-based seismic shaking as a trigger for rockfalls. We demonstrated that raw LiDAR data are useful to distinguish areas covered by tall vegetation, allowing realistic simulation of trajectories. We found that the areas most susceptibile to rockfalls are located along the N, N-W and S-W steep flanks of Mt. Epomeo, the S and S-W coast, and the sides of some steep exposed hydrographic channels located in the southern sector of the island. A novel procedure for dynamic activation of sources depending on ground shaking, in the event of an earthquake, helped inferring a seismically-triggered source map and the corresponding rockfall trajectories, for a scenario with 475 y return time. Thus, we obtained preliminary rockfall suceptibility in Ischia both in a “static” (trigger-independent) scenario, and in a seismic shaking triggering scenario. They must not be considered a risk map, but a starting point for a detailed field analysis.
Asymptotic giant branch stars at low metallicity: the challenging interplay between the mass-loss and molecular opacities

We investigate the main physical properties of low-metallicity asymptotic giant branch (AGB) stars with the aim of quantifying the uncertainties that presently affect the predicted chemical yields of these stars, associated with the mass-loss and description of molecular opacities. We find that above a threshold mass, M≃ 3.5 M⊙ for Z= 0.001, the results are little dependent on the opacity treatment, as long as the hot-bottom burning (HBB) prevents the surface C/O ratio from exceeding unity; the yields of these massive AGB stars are expected to be mostly determined by the efficiency of convection, with a relatively mild dependence on the mass-loss description. A much higher degree of uncertainty is associated with the yields of less-massive models, which critically depend on the adopted molecular opacities. An interval of masses exists, say, 2.0–3.0 M⊙ (the exact range depends on the mass-loss), in which the HBB may be even extinguished following the cooling produced by the opacity of C-bearing molecules. The yields of these stars are the most uncertain, the variation range being the largest (up to ∼2 dex) for the nitrogen and sodium yields. For very low mass models, not experiencing the HBB (M≤ 1.5 M⊙), the description of mass-loss and the treatment of the convective boundaries are crucial for the occurrence of the third dredge-up, with a sizeable impact on the CNO yields.
Auto-regressive versus random regression test-day models for the prediction of milk yields

Character process models attempt to model the covariance function of test-day records, while random regression models attempt to model the production curves of individual animals. The simplest character process model is probably the auto-regressive (AR) model. We used AR here to model the covariance function, and to predict missing records, where the pattern of missing records resembled that of not yet completed lactations. Since the AR model gives about one equation per test-day (or test-week here), a new model was developed which only evaluated the covariance function at 9 knots along the lactation trajectory (ARrt). By choosing the knots at unequal time intervals, the assumption of a stationary process was alleviated. The AR and ARrt models were compared to a random regression model that fitted a 4-th order Legendre polynomial (LEG(4)). LEG(4), AR and ARrt gave quite different covariance functions, but all three the models seemed approximately equally well equipped to predict missing records from part lactations. LEG(4) fitted 16 variance components, and 4,755 random effects equations. For AR these figures were 4 and 42,795, respectively, and for ARrt they were 4 and 9,510, i.e. AR and ARrt fitted fewer variance components at the cost of more random effects equations. This may prove an advantage for AR and ARrt in small data sets, where the accurate estimation of many variance components is not possible. On the other hand, many equations may lead to computational problems in large-scale applications. The use of weights for the allocation of records to knots resulted in biased parameter estimates for the ARrt model. ________________________________________________________________________________
Dynamic Coupling Analysis on Thermo–Chemo–Mechanical Field and Fluid–Structure Interaction for Aero-Engine Turbine Blade with Functional Gradient Thermal Barrier Coatings

In this study, an extended layerwise/solid-element (XLW/SE) method is developed for the thermo–chemo–mechanical (TCM) coupling problem of an aero-engine turbine blade with thermal barrier coatings (TBCs). The method consists of two parts, the extended layerwise (XLW) method and the three-dimensional (3D) solid-element (SE) method, which are adopted to formulate the governing equations of TBCs and substrate, respectively. Then, according to the compatibility conditions of displacement, temperature, concentration and internal force equilibrium at the TBCs/substrate interface, the governing equation of the final blade structure is assembled. Through a time integration, the dynamic responses of displacement, temperature and concentration can be calculated. In addition, the fluid–structure coupling analysis is conducted by using COMSOL. The nonuniform thermal load is imported into the XLW/SE method to calculate the mechanical response of blade structure. Finally, the corresponding computing program is compiled with C++. In numerical examples, the TCM coupling analysis is conducted on the blade structure with and without interfacial debonding and delamination damages. To validate the effectiveness of the proposed method, the dynamic TCM responses of the XLW/SE model is compared with those of a 3D elastic model generated by COMSOL, which shows that the two models are in good agreement.
The Design of a Deep Learning Model to Classify Passion Fruit for the Ageing Society

The objective of this research is to design of a deep learning model to classify passion fruit for the ageing society. The phenomenon of an increasingly aging population affects the way of life and well-being of all societies around the world. The growing trend of the elderly leads to risks and health problems. Many substances in the passion fruit can help with sleep problems, wrinkled skin, and lower high blood pressure. Eating purple passion fruit after harvest is found to be more sour than sweet, but the longer it is stored, the sweeter it tastes. It is expected that the 4-passion fruit group, which is categorized by post-harvest period, can be classified by convolutional neural networks (CNNs), which is a network in network (NiN) architecture in the Python program. The implications of the study are that classifying the passion fruit is appropriate for an ageing society. The NiN models can generate the accuracy of a trained dataset of 96.76% and a validation dataset of 95.89%. This model is used to make computer programs that make it easy to choose passion fruit and other fruits for the fruit juice industry.
Discovery of a Be/X-ray pulsar binary and associated supernova remnant in the Wing of the SMC

We report on a new Be/X-ray pulsar binary located in the Wing of the Small Magellanic Cloud (SMC). The strong pulsed X-ray source was discovered with the Chandra and XMM-Newton X-ray observatories. The X-ray pulse period of 1062 s is consistently determined from both Chandra and XMM-Newton observations, revealing one of the slowest rotating X-ray pulsars known in the SMC. The optical counterpart of the X-ray source is the emission-line star 2dFS 3831. Its B0-0.5(III)e+ spectral type is determined from VLT-FLAMES and 2dF optical spectroscopy, establishing the system as a Be/X-ray binary (Be-XRB). The hard X-ray spectrum is well fitted by a power-law with additional thermal and blackbody components, the latter reminiscent of persistent Be-XRBs. This system is the first evidence of a recent supernova in the low density surroundings of NGC 602. We detect a shell nebula around 2dFS 3831 in H-alpha and [O III] images and conclude that it is most likely a supernova remnant. If it is linked to the supernova explosion that created this new X-ray pulsar, its kinematic age of (2-4)x10^4 yr provides a constraint on the age of the pulsar.
Study of the impact of the post-MS evolution of the host star on the orbits of close-in planets - II. A giant planet in a close-in orbit around the RGB star HIP 63242

Context. More than 40 planets have been found around giant stars, revealing a lack of systems orbiting interior to ∼0.6 AU. This observational fact contrasts with the planetary population around solar-type stars and has been interpreted as the result of the orbital evolution of planets through the interaction with the host star and/or because of a different formation/migration scenario of planets around more massive stars. Aims. We are conducting a radial velocity study of a sample of 166 giant stars aimed at studying the population of close-in planets orbiting post-main sequence stars. Methods. We computed precision radial velocities from multi-epoch spectroscopic data to search for planets around giant stars. Results. We present the discovery of a massive planet around the intermediate-mass giant star HIP 63242. The best Keplerian fit to the data leads to an orbital distance of 0.57 AU, an eccentricity of 0.23 and a projected mass of 9.2 MJ. HIP 63242 b is the innermost planet detected around any intermediate-mass giant star and also the first planet detected in our survey.
Hierarchical Porous Heteroatoms—Co-Doped Activated Carbon Synthesized from Coconut Shell and Its Application for Supercapacitors

Coconut husk biomass waste was used as the carbon precursor to develop a simple and economical process for the preparation of hierarchical porous activated carbon, and the electrochemical properties of the electrode material were explored. The important process variables of carbonization, the weight ratios of the coconut shell/KOH, the amount of source dopant, and the carbonization temperature were investigated in order to reveal the influence of the as-obtained microporous/mesoporous/macroporous hierarchical porous carbon materials on the powder properties. Using a BET specific surface area analyzer, Raman analysis, XPS and SEM, surface morphology, pore distribution and specific surface area of the hierarchical porous carbon materials are discussed. The results show that the as-prepared N-, S- and O-heteroatom-co-doped activated carbon electrode was manufactured at 700 °C for electrochemical characteristics. The electrochemical behavior has the characteristics of pseudo-capacitance, and could reach 186 F g−1 at 1 A g−1 when measured by the galvanostatic charge–discharge (GCD) test. After 7000 cycles of the charge–discharge test, the initial capacitance value retention rate was 95.6%. It is predicted that capacitor materials made when using coconut shell as a carbon source will have better energy storage performance than traditional carbon supercapacitors.
A Bridgeless Semi-Quadratic Gain High Power Factor AC-DC Converter Based LEVs Charging Solution

A charger topology using a single stage and transformer-less design employing bridgeless semi quadratic voltage gain with high power factor (HPF) AC-DC converter, is demonstrated in this paper for the charging system of light electric vehicles (LEVs). In order to achieve transformer-less structure and wide voltage gain (particularly step-down gain) between high AC input and low DC output (LEVs battery packs), an integrated structure comprising of a bridgeless SEPIC (single ended primary inductor converter) and a buck converter, is effectively utilized to achieve desired charging characteristics at the battery end and maintaining high power factor at AC end of the charger. The bridgeless along with the transformer less structure, together helps in reducing the size, and the cost of the charger and to improve its overall efficiency. Unlike existing SEPIC and Cuk HPF AC-DC converter based battery chargers, the presented charging system ensures continuous current characteristic both at AC side and battery end, and also has the freedom of operating in the discontinuous inductor current mode (DICM) operation. The continuous current characteristic considerably reduces the size of filters and minimizes associated losses, whereas the DICM operation enables control simplicity. Further, the DICM operation optimizes the volume of magnetics and ensures zero current switching of semiconductor devices. Lastly, the design, operating modes, and performance of the charging circuitry are verified through simulation and corresponding results are discussed here for performance verification.
Stiffness-Observer-Based Adaptive Control of an Intrinsically Compliant Parallel Wrist Rehabilitation Robot

Disability from injuries and diseases is a global problem affecting a large population; however, due to a lack of therapists and labor-intensive procedures, only a few benefits from rehabilitation. Robots can assist therapists in treating many patients simultaneously, but the existing solutions need improvements in their mechanism, actuation, and control. This article presents a four-link parallel end-effector robot for wrist joint rehabilitation. The proposed robot employs biomimetic muscle actuators (BMA) that provide intrinsic compliance to the robotic system. A fuzzy-based model is developed to identify the nonlinear nature of BMAs. The stiffness-observer learns subject-specific stiffness, which is used to modify the robot reference trajectories. An adaptive controller uses the fuzzy model and stiffness-observer and simultaneously controls the four BMAs to provide three degrees of rotational freedom to the robot end-effector. The feasibility of the robot mechanism and the controller was evaluated through proof of concept experiments conducted with three unimpaired human subjects. It was found that the controller was able to guide the robot–human system on the commanded trajectories in the presence of parallel actuation of compliant and nonlinear BMAs. Furthermore, the controller was also able to modify the commanded trajectories in the higher stiffness regions of the wrist workspace.
An Insight into Animal Glutamate Receptors Homolog of Arabidopsis thaliana and Their Potential Applications—A Review

Most excitatory impulses received by neurons are mediated by ionotropic glutamate receptors (iGluRs). These receptors are located at the apex and play an important role in memory, neuronal development, and synaptic plasticity. These receptors are ligand-dependent ion channels that allow a wide range of cations to pass through. Glutamate, a neurotransmitter, activates three central ionotropic receptors: N-methyl-D-aspartic acid (NMDA), -amino-3-hydroxy-5-methylisoxazole-4-propionate (AMPA), and kainic acid (KA). According to the available research, excessive glutamate release causes neuronal cell death and promotes neurodegenerative disorders. Arabidopsis thaliana contains 20 glutamate receptor genes (AtGluR) comparable to the human ionotropic glutamate (iGluRs) receptor. Many studies have proved that AtGL-rec genes are involved in a number of plant growth and physiological activities, such as in the germination of seeds, roots, abiotic and biotic stress, and cell signaling, which clarify the place of these genes in plant biology. In spite of these, the iGluRs, Arabidopsis glutamate receptors (AtGluR), is associated with the ligand binding activity, which confirms the evolutionary relationship between animal and plant glutamate receptors. Along with the above activities, the impact of mammalian agonists and antagonists on Arabidopsis suggests a correlation between plant and animal glutamate receptors. In addition, these glutamate receptors (plant/animal) are being utilized for the early detection of neurogenerative diseases using the fluorescence resonance energy transfer (FRET) approach. However, a number of scientific laboratories and institutes are consistently working on glutamate receptors with different aspects. Currently, we are also focusing on Arabidopsis glutamate receptors. The current review is focused on updating knowledge on AtGluR genes, their evolution, functions, and expression, and as well as in comparison with iGluRs. Furthermore, a high throughput approach based on FRET nanosensors developed for understanding neurotransmitter signaling in animals and plants via glutamate receptors has been discussed. The updated information will aid in the future comprehension of the complex molecular dynamics of glutamate receptors and the exploration of new facts in plant/animal biology.