Miracle-dz/UniFAR-FTUs huggingface dataset:
Voltage controlled biaxial strain in VO2 films grown on 0.72Pb(Mg1∕3Nb2∕3)-0.28PbTiO3 crystals and its effect on the transition temperature

Vanadium oxide thin films (VO2) were deposited on 0.72Pb(Mg1∕3Nb2∕3)-0.28PbTiO3 (PMN-PT) crystalline substrates using pulsed laser deposition method. Due to their huge piezoelectric coefficients in the order of 2500 pm/V, the PMN-PT substrates are used to impose additional amount of biaxial strain to the VO2 films by applying an external bias to the substrates. The influence of the biaxial strain on the transition temperature and on the conductive properties of the VO2 films is investigated in this work. Thus, a change in the biaxial strain of −0.8 × 10−3 applied in the (110) plane of the rutile cell of the VO2 lowered the metal-to-insulator transition temperature by 1.35 °C.
Voltage controlled metamaterial

A tunable metamaterial based on conducting coils loaded by an electronic circuit containing a varicap diode has been demonstrated. The agility exceeds one octave inside the 100–500 MHz range. Permeability levels are significantly increased when the loop is loaded by a proper magnetic material. A model gives a good desription of the observed permeability spectra.
A Novel Cuproptosis-Associated Gene Signature to Predict Prognosis in Patients with Pancreatic Cancer

Background Pancreatic cancer (PAAD) is a malignant tumor with a poor prognosis and lacks sensitive biomarkers for diagnosis and targeted therapy. Cuproptosis, a recently proposed form of cell death based on cellular copper ion concentration, plays a key role in cancer biology. This study is aimed at constructing a risk model for predicting the prognosis of PAAD patients based on cuproptosis-related genes. Methods Pancreatic-related data from UCSC-TCGA and UCSC-GTEx databases were extracted for analysis, and TCGA-PAAD samples were randomly divided into the training and validation groups. Pearson correlation analysis was used to obtain cuproptosis-related genes coexpressed with 19 copper death genes. Univariate Cox and Lasso regression analyses were used to obtain cuproptosis-related prognostic genes. Multivariate Cox regression analysis was used to construct the final prognostic risk model. The risk score curve, Kaplan-Meier survival curves, and ROC curve were used to evaluate the predictive ability of the Cox risk model. Finally, the functional annotation of the risk model was obtained through enrichment analysis. Results The Cox risk model has an eight prognostic cuproptosis-related gene signature. Kaplan-Meier survival curves demonstrated that the high-risk group had a shorter survival time. The ROC curve of the risk score was well created to predict one-, three-, and five-year survival rates, and AUC of the risk score was higher than other clinical characteristics. Cox regression analysis revealed that the risk score has an independent prognostic value for PAAD. GSEA reveals specific tumor pathways associated with the risk model (Myc targets v1, mTORC1 signaling, and E2F targets). Conclusions We constructed a prognostic model containing eight cuproptosis-related genes (AKR1B10, KLHL29, PROM2, PIP5K1C, KIF18B, AMIGO2, MRPL3, and PI4KB) that can accurately predict the prognosis of PAAD patients. The results will provide new perspectives for individualized outcome prediction and new therapy development for PAAD patients.
An Automatic Rice Plant Disease Detection Model Built With Unstructured Data Using IMDT Tiling and CNN Cognitive Object Detection

Nowadays agriculture and processes are getting more intelligent mechanisms to improve the yield and reduce manual work. Smart agriculture provides numerous modern ideologies to farmers. But still, farmers face one important issue crop disease. Many researchers provide plenty of ways to recover and tackle the situation to come out of this problem. Therefore, they proceed with image processing to identify diseases from rice plant images. Farmers mainly face problems to take proper images for classification. Because of various reasons like various environmental factors, farmers ignorance, field size, capturing angle, device limitations, etc. are affecting the quality of the disease detection system, and these factors degrade overall performance. For this problem, introducing the Intelligent multi-dimensional tiling (IMDT) technique with an advanced convolution neural network with cognitive object detection (CNN-COD). IMDT technique developed with an intelligent expert system that adjusts input image size, capturing angles and other factors automatically. This advanced tiling technique supports to do the cropping and fluttering of input images for resizing. And CNN-COD model was used to calculate rice leaf width size and rescaled at the time of image segmentation with the Residual network (ResNet) model. Created dynamic tiled images are uniformly and scaled dimensional objects. These input values are used to train the CNN-COD rice plant disease, prediction model. Our proposed models were appraised on more than 4960 images which contain 8 various types of rice crop diseases. The experimental result portrayed out the CNN-COD model receives significant improvement in objection detection and image classification for the rice plant disease detection system. Mean average precision (MAP) values compared the CNN-COD model with the YOLOv4 model it got improved by 3.7% with the tiled input dataset.
Kolmogoroff's theory of locally isotropic turbulence

A new and fruitful theory of turbulent motion was published in 1941 by A. N. Kolmogoroff. It does not seem to be as widely known outside the U.S.S.R. as its importance warrants, and the present paper therefore describes the theory in some detail before presenting a number of extensions and making a comparison of experimental results with some of the theoretical predictions. Kolmogoroff's basic notion is that at high Reynolds number all kinds of turbulent motion, of arbitrary mean-flow characteristics, show a similar structure if attention is confined to the smallest eddies. The motion due to these eddies of limited size is conceived to be isotropic and statistically steady. Within this range of eddies we recognize two limiting processes. The influence of viscosity on the larger eddies of the range is negligible if the Reynolds number is large enough, so that their motion is determined entirely by the amount of energy which they are continually passing on to smaller eddies. This quantity of energy is the local mean energy dissipation due to turbulence. On the other hand, the smaller eddies of the range dissipate through the action of viscosity a considerable proportion of the energy which they receive, and the motion of the very smallest eddies is entirely laminar. The analytical expression of this physical picture is that the motion due to eddies less than a certain limiting size in an arbitrary field of turbulence is determined uniquely by two quantities, the viscosity and the local mean energy dissipation per unit mass of the fluid. The mathematical method of describing the motion due to eddies of a particular size is to construct correlations between the differences of parallel-velocity components at two points at an appropriate distance apart. Kinematical results analogous to those for turbulence which is isotropic in the ordinary sense are obtained, and then the scalar functions occurring in the expressions for the correlations are determined by dimensional analysis. The consequences of the theory in the case of turbulence which possesses ordinary isotropy are analysed and various predictions are made. One of these, namely that dimensionless ratios of moments of the probability distribution of the rate of extension of the fluid in any direction are universal constants, is confirmed by recent experiments, so far as the second and third moments are concerned. In several other cases it can be said that relations predicted by the theory have the correct form, but further experiments at Reynolds numbers higher than those hitherto used will be required before the theory can be regarded as fully confirmed. If valid, Kolmogoroff's theory of locally isotropic turbulence will provide a powerful tool for the analysis of problems of non-uniform turbulent flow, and for the determination of statistical characteristics of space and time derivatives of quantities influenced by the turbulence.
A Modular Circuit Synthesis Oriented Modelling Approach for Non-Isolated DC-DC Converters in CCM

The continued commissioning of DC microgrids in an effort to achieve net-zero carbon levels in the atmosphere demands the large-scale deployment of converters to make the power from renewable energy sources, such as solar PV, usable. To control these inherently non-linear converters using classical linear control methods, averaged modelling techniques are employed. These methods are laborious and easily become intractable when applied to converters with increased energy storage elements. A modular modelling approach is proposed. This approach is based on the synthesis of converters using refined basic building blocks. The refined basic building blocks are independently modelled as two-port networks and used in a circuit synthesis-oriented manner to derive power stage models of commonly used DC-DC converters. It is found that most of the converters considered in the study can be described as a cascade combination of these basic building blocks. As such, transmission parameters are mainly used to model the two-port networks. Moreover, it is also found that using this modelling technique enables the computation of generalized expressions for all power stage models of interest. The use of two-port networks curtails the size of the matrices describing the basic building blocks to 2 × 2, and thus simplifies the entire modelling procedure. Additionally, two-port network analysis makes this modelling technique modular, thus making it more suited to be employed in DC microgrids. The independence of the two-port models on the circuit topology and functionality makes it possible to even model new converters containing the described basic building blocks solely based on circuit connection.
Extreme Ultraviolet Explorer observations of the RS Canum Venaticorum systems AR Lacertae and II Pegasi

We report observations of two RS CVn systems, II Peg and AR Lac, which were calibration targets during the in-orbit checkout phase of the Extreme Ultraviolet Explorer (EUVE). We have determined count rates, and, based on these count rates, preliminary emission measure analyses have been done. The Lexan/boron band count rates were 0.0849 +/- 0.0023 counts/s for AR Lac and 0.218 +/- 0.031 counts/s for II Peg during its quiescent state. Temperatures and emission measures derived from the EUVE data are consistent with previously published values. We also report a flare seen during the II Peg observations which has characteristics similar to previously observed flares on II Peg. During the flare the Lexan/boron count rate increased by at least a factor of 2.5, and the minimum total duration was about 34,000 s (about 9.4 hr).
Conducted Noise Prediction for DC–DC Converter by Noise Source Model Accounting for Switching Fluctuation

The switching fluctuation of a dc–dc converter causes jitter and makes the conducted noise time-variant. Averaging-mode measurement with an oscilloscope or other instruments partially removes higher-frequency noise. Therefore, switching fluctuation affects the accuracy of noise prediction in using a black-box noise source model with measurement-based parameter identification. To address this issue, we proposed an approach to address the switching fluctuation effect on conducted emissions from the dc–dc converter. First, we investigate the effect of switching fluctuation by studying the difference between noise signals with and without fluctuation and estimating the reduction due to fluctuation. Then, to facilitate model parameter identification, we focus on the peak detected noise signal and improve the prediction accuracy of the peak detected noise by decomposing the measured noise signal into ripple noise and turn-on and turn-off spike noises. As a result, the peak detected noise spectrum after removing switching fluctuation can be predicted within a 3-dB error up to 200 MHz. Our experimental results show that the noise spectrum predicted by accounting for the reduction due to switching fluctuation agrees well with the spectrum obtained by averaging-mode measurement.
The Dirac oscillator

Dirac's free particle equation originated in an attempt to express linearly the relativistic quadratic relation between energy and momentum. The authors introduce a Dirac equation which, besides the momentum, is also linear in the coordinates. They call it the Dirac oscillator because in the nonrelativistic limit it becomes a harmonic oscillator with a very strong spin-orbit coupling term. The eigenstates and eigenvalues of the Dirac oscillator can be obtained in an elementary fashion, with the degeneracy of the latter being quite different from that of the ordinary oscillator. They briefly mention the symmetry Lie algebra responsible for this degeneracy and the generalisation of the problem to many-particle systems.
Geochemical Modeling of Heavy Metal Removal from Acid Mine Drainage in an Ethanol-Supplemented Sulfate-Reducing Column Test

A passive treatment process using sulfate-reducing bacteria (SRB) is known to be effective in removing heavy metals from acid mine drainage (AMD), though there has been little discussion of the mechanism involved to date. In this work, a sulfate-reducing column test was carried out using supplementary ethanol as an electron donor for microorganisms, and the reaction mechanism was examined using geochemical modeling and X-ray absorption fine structure (XAFS) analysis. The results showed that Cu was readily removed from the AMD on the top surface of the column (0–0.2 m), while Zn and Cd depletion was initiated in the middle of the column (0.2–0.4 m), where sulfide formation by SRB became noticeable. Calculations by a developed geochemical model suggested that ethanol decomposition by aerobic microbes contributed to the reduction of Cu, while sulfide produced by SRB was the major cause of Zn and Cd removal. XAFS analysis of column residue detected ZnS, ZnSO4 (ZnS oxidized by atmospheric exposure during the drying process), and CuCO3, thus confirming the validity of the developed geochemical model. Based on these results, the application of the constructed geochemical model to AMD treatment with SRB could be a useful approach in predicting the behavior of heavy metal removal.
O-Linked Glycans of Candida albicans Interact with Specific GPCRs in the Coronary Endothelium and Inhibit the Cardiac Response to Agonists

Candida albicans is an opportunistic fungal pathogen that may cause invasive infections in immunocompromised patients, disseminating through the bloodstream to other organs. In the heart, the initial step prior to invasion is the adhesion of the fungus to endothelial cells. Being the fungal cell wall’s outermost structure and the first to come in contact with host cells, it greatly modulates the interplay that later will derive in the colonization of the host tissue. In this work, we studied the functional contribution of N-linked and O-linked mannans of the cell wall of C. albicans to the interaction with the coronary endothelium. An isolated rat heart model was used to assess cardiac parameters related to vascular and inotropic effects in response to phenylephrine (Phe), acetylcholine (aCh) and angiotensin II (Ang II) when treatments consisting of: (1) live and heat-killed (HK) C. albicans wild-type yeasts; (2) live C. albicans pmr1Δ yeasts (displaying shorter N-linked and O-linked mannans); (3) live C. albicans without N-linked and O-linked mannans; and (4) isolated N-linked and O-linked mannans were administered to the heart. Our results showed that C. albicans WT alters heart coronary perfusion pressure (vascular effect) and left ventricular pressure (inotropic effect) parameters in response to Phe and Ang II but not aCh, and these effects can be reversed by mannose. Similar results were observed when isolated cell walls, live C. albicans without N-linked mannans or isolated O-linked mannans were perfused into the heart. In contrast, C. albicans HK, C. albicans pmr1Δ, C. albicans without O-linked mannans or isolated N-linked mannans were not able to alter the CPP and LVP in response to the same agonists. Taken together, our data suggest that C. albicans interaction occurs with specific receptors on coronary endothelium and that O-linked mannan contributes to a greater extent to this interaction. Further studies are necessary to elucidate why specific receptors preferentially interact with this fungal cell wall structure.
Virome Profiling of an Eastern Roe Deer Reveals Spillover of Viruses from Domestic Animals to Wildlife

Eastern roe deer (Capreolus pygargus) is a small ruminant and is widespread across China. This creature plays an important role in our ecological system. Although a few studies have been conducted to investigate pathogens harbored by this species, our knowledge of the virus diversity is still very sparse. In this study, we conducted the whole virome profiling of a rescue-failed roe deer, which revealed a kobuvirus (KoV), a bocaparvovirus (BoV), and multiple circular single-stranded viruses. These viruses were mainly recovered from the rectum, but PCR detection showed systematic infection of the KoV. Particularly, the KoV and BoV exhibited closely genetic relationships with bovine and canine viruses, respectively, highly suggesting the spillover of viruses from domestic animals to wildlife. Although these viruses were unlikely to have been responsible for the death of the animal, they provide additional data to understand the virus spectrum harbored by roe deer. The transmission of viruses between domestic animals and wildlife highlights the need for extensive investigation of wildlife viruses.
A result on bicanonical maps of surfaces of general type

Pluricanonical maps of surfaces of general type have been studied for quite a long time. After Bombieri's remarkable work [2], recently, I. Reider [5] uses a new method, i.e., residues, zero cycles and rank two vector bundles, to deal with them successfully. Now such problems are left open only for bicanonical maps with small Aj(<4), and for canonical maps. For bicanonical maps, the non-trivial cases are these surfaces with pg(S) = Q and . Kf = 3,4. As there are no examples and suitable methods, in these cases, we have the following
Residual stresses and distortions in additive manufactured Inconel 718

ABSTRACT Direct energy deposition is an additive manufacturing technique, follows layer-wise deposition to avail design freedom and minimizes material wastage. Despite the unique advantages, repeated heating and cooling induces thermal strains in the components. The present investigation is to understand the thermal-induced distortions and residual stresses in Inconel 718 components fabricated through direct energy deposition. The distortions and temperature measurements are carried out in situ and residual stresses are measured using micro-indentation technique. The distortions are increasing with number of layers, and the distortion rate is varying along the height of deposition. The temperature data indicated rapid heating and cooling. The residual stresses measured are compressive in nature, and are approximately 40% of yield strength in magnitude. The ultimate strength, yield strengths are 800 ± 30 MPa, 580 ± 50 MPa respectively, and maximum hardness obtained is 349 HV. Microstructure Characterizations showed continuous growth of columnar dendrites through multiple layers, and Nb segregation at interdendrites.
Global stabilization and asymptotic tracking for a class of nonlinear systems by means of time‐varying feedback

A simple backstepping design scheme is proposed and sufficient conditions for non‐uniform in time global stabilization for parameterized systems by means of time‐varying feedback are established. Our methodology is applicable to a special class of systems that in general cannot be stabilized by static feedback and includes non‐holonomic systems in chained form. For this class of systems the main results on feedback stabilization enable us to derive sufficient conditions for the solvability of the tracking problem. Copyright © 2003 John Wiley & Sons, Ltd.
Computational Learning of Languages

This thesis focuses on the Gold model of inductive inference from positive data. There are several aspects in which the model appears unsatisfactory for language learning: the class of families of learnable languages is highly restricted; even if a family is learnable, there exists no uniform method to obtain a learner for it, and the learner itself is complex. In this thesis, some such criticisms are being addressed. It is shown that no automatic synthesis of a learner from the description of a learnable family is possible. Nevertheless, in some special cases, this synthesis can be achieved and a general result is developed. In order to make the learner simpler, it is stipulated that the learner can change its guess only when the guess is inconsistent with the input evidence. Such a conservative learner never overgeneralizes. Exactly learnable families are characterized for prudent learners with the following types of constraints: (0) conservative, (1) conservative and consistent, (2) conservative and responsive, and (3) conservative, consistent, and responsive. It is also shown that, when exactness is not required, prudence, consistency, and responsiveness, even together, do not restrict the power of conservative learners. Conservative learners are simple in only one respect; even though it is easy to determine when to make a new guess, it is still hard to know what this guess should be. Finally, a learner that exploits pattern evident in the input is developed. Absence of a particular string over a suitable interval of the input can be viewed as a kind of 'indirect negative evidence'. Now, the learning criterion needs to be weakened to allow limited failure. It is shown that any family of languages can be learned with probability 1 from stochastic input, provided something is known about the probability distribution according to which the input is presented. Given the family, the learner is uniformly constructible. Further, the behavior of the learner is simpler in many aspects. It is expected that a variety of other natural constraints can be imposed on this learner without additional cost.
DECOMPOSITION OF WHITE OAT PHENOTYPIC VARIABILITY BY ENVIRONMENTAL COVARIATES

The study aims to quantify the effects of environmental variables on the interaction between genotypes x environments and to evaluate the sensitivity of white oat genotypes to grain yield in 10 years of cultivation. The experiment took place in the municipality of Augusto Pestana, Rio Grande do Sul State, Brazil. The experimental design used was in randomized blocks, being evaluated the grain yield of 26 white oat genotypes in 20 complex environments. Greater phenotypic stability was observed for the URS 21 genotype, by the AMMI and GGE methodologies. The URS Corona genotype showed general adaptation, high genetic value and predictable environmental variations by the GGE method and reaction norm. Higher minimum air temperature and lower medium temperature and relative air humidity enhance the productive performance of white oat genotypes. The genotypes URS 22, Fapa Slava, IPR Afrodite and Estampa express positive responses to the covariates temperature medium, maximum, minimum and relative air humidity, respectively. Relative humidity explains more than 50% of the biological variation of white oat genotypes.