Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Volatile Compounds on Breakdown Field Strength Measurements of Polymers

This study investigates the effects of absorbed water and volatile compounds on measurements of the electrostatic breakdown field strength. Comparisons are made between sets of pristine samples, ones that underwent a thorough vacuum bake out, and ones subsequently exposed to humid conditions to determine how quickly the samples reverted to an unbaked state. Specifically, we compared signatures related to electrostatic breakdown (electrostatic breakdown field strength, frequency of pre-breakdown arcing, and flashover) and images of the arc damage sites. The work reports results for three prototypical polymeric dielectric materials: low density polyethylene (LDPE), polyether-etherketone (PEEK), and Nylon 66, listed in order of decreasing hydrophobicity. Electrostatic breakdown strength was seen to change linearly with effective exposure time; hydrophobic LDPE and intermediate PEEK increased, while more hydrophilic Nylon 66 decreased. Similar trends were observed for the number of pre-breakdown arcs (DC partial discharges) versus effective exposure time.
Exploring the Role of Language Families for Building Indic Speech Synthesisers

Building end-to-end speech synthesisers for Indian languages is challenging, given the lack of adequate clean training data and multiple grapheme representations across languages. This work explores the importance of training multilingual and multi-speaker text-to-speech (TTS) systems based on language families. The objective is to exploit the phonotactic properties of language families, where small amounts of accurately transcribed data across languages can be pooled together to train TTS systems. These systems can then be adapted to new languages belonging to the same family in extremely low-resource scenarios. TTS systems are trained separately for Indo-Aryan and Dravidian language families, and their performance is compared to that of a combined Indo-Aryan+Dravidian voice. We also investigate the amount of training data required for a language in a multilingual setting. Same-family and cross-family synthesis and adaptation to unseen languages are analysed. The analyses show that language family-wise training of Indic systems is the way forward for the Indian subcontinent, where a large number of languages are spoken.
Multifractal subgrid-scale modeling within a variational multiscale method for large-eddy simulation of passive-scalar mixing in turbulent flow at low and high Schmidt numbers

Multifractal subgrid-scale modeling embedded into a variational multiscale method is proposed for large-eddy simulation of passive-scalar mixing in turbulent incompressible flow. In this subgrid-scale modeling approach, subgrid-scale velocity and scalar field are directly approximated by a multifractal reconstruction process replicating the actual physics of turbulent flows. Problems from low to high Schmidt numbers (i.e., Sc ≈ 1 to Sc ≫ 1) are considered in this work. Starting from preceding work, in this study, multifractal subgrid-scale modeling is further detailed by refining the approximation process within the scalar field. Thereby, appropriate multifractal subgrid-scale modeling for passive-scalar mixing is derived in comprehensive form for the entire range of Schmidt numbers. The near-wall behavior of the multifractal subgrid-scale modeling approach is investigated for wall-bounded turbulent flows with passive-scalar mixing. The method is validated for passive-scalar mixing in turbulent channel flow for a broad range of Schmidt numbers in between 1 and 1000. Excellent performance is stated for all Schmidt numbers, in particular when comparing the results obtained with the proposed method to results provided by other methods widely used in the literature. An analysis of the subgrid-scale scalar-variance transfer highlights the influence of the multifractal subgrid-scale modeling within the variational multiscale method. The near-wall behavior of the proposed method is investigated via the transfer coefficient, for which results consistent with the theoretical correlation are obtained.
On the localization of an acoustic target using a single receiver

This paper addresses the localization of an unsynchronized acoustic source using a single receiver and a synthetic baseline. The enclosed work was applied in a real search of an electric glider that was lost at sea and later recovered, using the described approach. The search procedure is presented along with the localization methods and a metric based on the eigenvalues of the Fisher Information Matrix is used to quantify the expected uncertainty of the estimate.
Power Systems Observability Analysis Based on Parallel Gaussian Belief Propagation

Power system state estimation is fundamental for a range of online applications of power systems in energy management systems. The premise of state estimation calculation is that we need to make sure the system of equations should have a feasible solution. As a preprocessing step of the power state estimation algorithm, observability analysis plays a crucial role in power state estimate, which needs to determine whether the equation of state estimation formed by the measurements has a distinct solution. In this paper, we propose a parallel observability analysis based on Gaussian belief propagation to address the low efficiency of observability analysis in large-scale power systems. The Gaussian belief propagation process is implemented with multi-core and multithread parallel computing to achieve efficient observability analysis. Simulation calculations were performed using multiple power systems with 10, 000 to 70, 000 buses. The experimental results show that the proposed parallel observability analysis algorithm is more efficient than the conventional algorithm.
A Multi-Attribute Graph based Handover Scheme for LEO Satellite Communication Networks

The satellite-terrestrial integrated networks, which consists of satellite and terrestrial nodes, has attracted increasing attention in recent years since its wide coverage area and flexible connectivity. However, Due to the mobility of low Earth orbit (LEO) satellite networks, one satellite is unable to provide users with continuous service. In this work, we proposed an intelligent handover scheme with multi-attribute graph (MAG) and genetic algorithm to determine the handover scheme. Firstly, we modeled the handover process as finding an optimal path from the MAG, which including the elevation angle, coverage time, and free channel state. Using the critic method, we weighted each target and transformed it into an optimization problem with a single objective since traditional methods cannot achieve all of the objectives simultaneously. Then the optimal handover path can be selected by genetic algorithm. The simulation results show that our handover scheme reduces communication delay and handover time.
Propagation of Tremors over the Surface of an Elastic Solid.

Wave phenomena which are seen along the surface of a semi-infinite elastic solid when subjected to an impulsive line force in the direction normal to its surface have been studied. The results obtained are as follows. (1) Immediately after the impulsive force is removed, the vertical displacement is downward in the neighbourhood of the origin, and it is upward outside that downward domain. (§3)(2) In the downward (upward) domain, the horizontal displacement is toward (away from) the origin. (§4)(3) The surface deformations thus produced are propagated with the velocity of RAYLEIGH wave without conspicuous changes in form. (§3 and §4)(4) The wave length of the RAYLEIGH wave is proportional to the time of duration of the impulse, and is of the same order of extent as that of the downward domain at the moment when the force is removed. (§3)
Distributionally Robust Unit Commitment Considering Unimodality-Skewness Information of Wind Power Uncertainty

The deepening penetration of renewable energy sources (RESs) into power grids imposes remarkable challenges that merit special attention. In this paper, we work out a distributionally robust chance-constrained (DRCC) day-ahead unit commitment problem while the stochasticity and variability arising from RESs are taken into consideration. The developed framework optimizes the expected objective function and stipulates that the DRCCs will hold within a moment-based ambiguity set, which additionally incorporates the unimodality information and mode skewness. The employed ambiguity set can not only account for the wind power uncertainty but also expressly alleviate the conservatism compared with the single moment metric. By deriving efficient mathematical reformulations to tackle the expected objective function and DRCCs, the proposed model is reduced to an exact mixed-integer second-order cone programming problem that can readily be implemented. Numerical experiments are carried out on two representative test systems to demonstrate the effectiveness and efficiency of the suggested methodology.
The Dynamic Contact Angle of Water Droplets Subjected to AC Electric Fields

The acoustic impact of corona discharge from high voltage (HV) conductors is a cause of increasing environmental concern. Excessive corona discharge is initiated under wet weather when a large amount of droplet protrusions is formed on the surface of an HV conductor. The surface condition of the conductor therefore significantly affects the inception, development and intensification of corona discharges through electrohydrodynamic processes. Existing studies on the dynamic characteristics of rain droplets assumes a constant contact angle, which does not conform with the actual profile observed in experiments. This article investigates the dynamic contact angles of charged droplets through a simplified sphere-plane HV experiment. Pendent droplets with a range of sizes have been studied when subjected to AC electric fields. It is found that the variation of dynamic contact angle is closely related to the volume of the water droplet. Clear sinusoidal variation of contact angle with time is seen throughout the whole power cycle for larger droplets $(\ge 6 \mu \text{L})$, while variation is smaller and more difficult to categorize on the smaller droplets $(\lt 6 \mu \text{L})$. The characteristics of dynamic contact angle obtained here can be used for further analysis within the finite element method to investigate its electrohydrodynamic properties.
No Mitochondrial Related Transcriptional Changes in Human Skeletal Muscle after Local Heat Application

The purpose of the study is to determine the impact of local heating on skeletal muscle transcriptional response related to mitochondrial biogenesis and mitophagy. Twelve healthy subjects (height, 176.0 ± 11.9 cm; weight, 83.6 ± 18.3 kg; and body composition, 19.0 ± 7.7% body fat) rested in a semi-reclined position for 4 h with a heated thermal wrap (HOT) around one thigh and a wrap without temperature regulation (CON) around the other (randomized). Skin temperature, blood flow, intramuscular temperature, and a skeletal muscle biopsy from the vastus lateralis were obtained after the 4 h intervention. Skin temperature via infrared thermometer and thermal camera was higher after HOT (37.3 ± 0.7 and 36.7 ± 1.0 °C, respectively) than CON (34.8 ± 0.7, 35.2 ± 0.8 °C, respectively, p < 0.001). Intramuscular temperature was higher in HOT (36.3 ± 0.4 °C) than CON (35.2 ± 0.8 °C, p < 0.001). Femoral artery blood flow was higher in HOT (304.5 ± 12.5 mL‧min−1) than CON (272.3 ± 14.3 mL‧min−1, p = 0.003). Mean femoral shear rate was higher in HOT (455.8 ± 25.1 s−1) than CON (405.2 ± 15.8 s−1, p = 0.019). However, there were no differences in any of the investigated genes related to mitochondrial biogenesis (PGC-1α, NRF1, GAPBA, ERRα, TFAM, VEGF) or mitophagy (PINK-1, PARK-2, BNIP-3, BNIP-3L) in response to heat (p > 0.05). These data indicate that heat application alone does not impact the transcriptional response related to mitochondrial homeostasis, suggesting that other factors, in combination with skeletal muscle temperature, are involved with previous observations of altered exercise induced gene expression with heat.
Zipfian Distributions in Child-Directed Speech

Abstract Across languages, word frequency and rank follow a power law relation, forming a distribution known as the Zipfian distribution. There is growing experimental evidence that this well-studied phenomenon may be beneficial for language learning. However, most investigations of word distributions in natural language have focused on adult-to-adult speech: Zipf’s law has not been thoroughly evaluated in child-directed speech (CDS) across languages. If Zipfian distributions facilitate learning, they should also be found in CDS. At the same time, several unique properties of CDS may result in a less skewed distribution. Here, we examine the frequency distribution of words in CDS in three studies. We first show that CDS is Zipfian across 15 languages from seven language families. We then show that CDS is Zipfian from early on (six-months) and across development for five languages with sufficient longitudinal data. Finally, we show that the distribution holds across different parts of speech: Nouns, verbs, adjectives and prepositions follow a Zipfian distribution. Together, the results show that the input children hear is skewed in a particular way from early on, providing necessary (but not sufficient) support for the postulated learning advantage of such skew. They highlight the need to study skewed learning environments experimentally.
Influence of pressure and ion bombardment on the growth and properties of nanocrystalline silicon materials

We report on the growth and properties of nanocrystalline silicon:H films deposited using plasma discharge at 45MHz under varying pressure regimes from 50 to 500mTorr. X-ray diffraction data revealed that the primary orientation in these films was ⟨111⟩. The amount of hydrogen dilution needed to crystallize the films was found to be a strong function of deposition pressure, with a significantly higher hydrogen dilution needed to crystallize films at higher pressures. Langmuir probe data showed that these results could be attributed to the increase in density of low-energy hydrogen ions impinging on the substrate at lower pressures.
Prediction and Inference for Truncated Spatial Data

Abstract Spatial data in mining, hydrology, and pollution monitoring commonly have a substantial proportion of zeros. One way to model such data is to suppose that some pointwise transformation of the observations follows the law of a truncated Gaussian random field. This article considers Monte Carlo methods for prediction and inference problems based on this model. In particular, a method for computing the conditional distribution of the random field at an unobserved location, given the data, is described. These results are compared to those obtained by simple kriging and indicator cokriging. Simple kriging is shown to give highly misleading results about conditional distributions; indicator cokriging does quite a bit better but still can give answers that are substantially different from the conditional distributions. A slight modification of this basic technique is developed for calculating the likelihood function for such models, which provides a method for computing maximum likelihood estimates of u.
An Effective Method for Gas-Leak Area Detection and Gas Identification with Mid-Infrared Image

Mid-infrared imaging systems are widely applied in gas-leak detection. However, infrared images generally suffer from low contrast and poor quality. In this paper, an image-enhancement method based on Gaussian filtering and adaptive histogram segmentation is proposed to effectively improve the quality of infrared images. It can effectively improve the quality of infrared images, which contributes to the subsequent gas-image feature extraction. The traditional background modeling algorithm is analyzed, and the ViBe (visual background extractor) algorithm is studied in depth. Based on the advantages and disadvantages of the ViBe algorithm and the characteristics of gas-leak images, a gas-leak region detection method based on the improved ViBe algorithm is proposed. The test results show that it can quickly establish a background model, segment the gas-leak region with motion characteristics, and render the gas-leak region in color based on grayscale mapping to achieve the automatic detection and enhanced display of gas leaks.
Differential Evolution Algorithm with Self-Adaptive Population Resizing Mechanism

A differential evolution (DE) algorithm with self-adaptive population resizing mechanism, SapsDE, is proposed to enhance the performance of DE by dynamically choosing one of two mutation strategies and tuning control parameters in a self-adaptive manner. More specifically, more appropriate mutation strategies along with its parameter settings can be determined adaptively according to the previous status at different stages of the evolution process. To verify the performance of SapsDE, 17 benchmark functions with a wide range of dimensions, and diverse complexities are used. Nonparametric statistical procedures were performed for multiple comparisons between the proposed algorithm and five well-known DE variants from the literature. Simulation results show that SapsDE is effective and efficient. It also exhibits much more superiorresultsthan the other five algorithms employed in the comparison in most of the cases.
Southeastern U.S. Daily Temperature Ranges Associated with the El Nino-Southern Oscillation

AbstractThe daily temperature range (DTR; daily maximum temperature minus daily minimum temperature) at 290 southeastern U.S. stations is examined with respect to the warm and cold phases of the El Nino–Southern Oscillation (ENSO) for the period of 1948–2009. A comparison of El Nino and La Nina DTR distributions during 3-month seasons is conducted using various metrics. Histograms show each station’s particular distribution. To compare directly the normalized distributions of El Nino and La Nina, a new metric (herein called conditional ratio) is produced and results are evaluated for significance at 95% confidence with a bootstrapping technique. Results show that during 3-month winter, spring, and autumn seasons DTRs above 29°F (16.1°C) are significantly more frequent during La Nina events and that DTRs below 15°F (8.3°C) are significantly more frequent during El Nino events. It is hypothesized that these results are associated spatially with cloud cover and storm tracks during each season and ENSO phase.
Infrared Spectra of Monolayers on Metal Mirrors

A double-beam infrared spectrophotometer has been modified so that spectra of films as thin as one or a few monolayers in thickness on metal mirrors can be obtained. It is theoretically predicted and experimentally confirmed that, at the mirror surface, the electric intensity is predominantly perpendicular to the surface. Vibrational modes for which the matrix element of dipole moment is parallel to the surface appear abnormally weak in the spectra. The spectra, therefore, provide information about the orientation as well as the composition of sample films. Spectra of Blodgett films of metal stearates show differences in band positions and band intensities between films one molecular layer in thickness and thicker films. The shifts in band positions are attributed to interactions between carboxylate ions in films thicker than a molecular layer and the absence of such interactions in the first layer. The intensity differences are not explained.
Transport Behavior of Methane Confined in Nanoscale Porous Media: Impact of Pore Evolution Characteristics

As a key technical aspect contributing to shale gas development, nanoconfined methane flow behavior has received tremendous research interest, which remains challenging to understand clearly. The majority of previous contributions put emphasis on the mechanism model for methane confined in a single nanopore; at the same time, the other part focusing on an upscaling approach fails to capture the spatial pore-network characteristics as well as the way to assign pressure conditions to methane flow behavior. In light of the current knowledge gap, pore-network modeling is performed, in which a pore coordination number, indicating the maximum pores a specified pore can connect, gas flow regimes classified by Knudsen numbers, as well as different assigned pressure conditions, are incorporated. Notably, the pore-network modeling is completely self-coded, which is more flexible in adjusting the spatial features of a constructed pore network than a traditional one. In this paper, the nanoconfined methane flow behavior is elaborated first, then the pore network modeling method based on the mass conservation principle is introduced for upscaling, and in-depth analysis is implemented after that. Results show that (a) as for porous media with pore sizes ranging from 5~80 nm, dramatic advancement on apparent gas permeability takes place while pressure is less than 1 MPa; (b) apparent gas permeability evaluated at a specified pressure shall be underestimated by as much as 31.1% on average compared with that under the pressure-difference condition; (c) both a large pore size and a high coordination number are beneficial for strong gas flow capacity through nanoscale porous media, and the rising ratio can reach about 6 times by altering the coordination number from 3 to 7, which is quantified and presented for the first time.
Impact of Insulation Degradation on the Thermal and Moisture Models of Oil Filled Power Transformers

The degradation of transformer oil-paper insulation is one of the major concerns for utilities and transformer owners. Temperature and moisture are amongst the key variables to be considered while determining the load profiles that can be safely applied to transformers. In this paper, important parameters used to monitor the degradation of the oil-paper insulation are introduced in the existing thermal and moisture models reported in the literature. The standard IEC 60076-7 loading guide model is improved by including the viscosity of the liquids with a controlled aging history to estimate the behavior under hot-spot conditions. Similarly, moisture model is improved by including the acidity of oils and degree of polymerization of the paper. This allows a better representation of the relative moisture saturation of the liquids and the bubble inception temperature. In this work, potential models are reported to understand the moisture dynamics of cellulose paper and predict the bubbling inception temperature under specific loading profiles. The simulation analysis is also spanned to different aging conditions of mineral oil and cellulose based oil-paper insulation. The developed models may be helpful to monitor the moisture in paper and predict the bubbling temperature while taking into consideration temperature variations along with the degradation of the insulation system inside the unit.
Enhanced Intraoperative Communication of Tumor Margins Using 3D Scanning and Mapping: The Computer‐Aided Design Margin

We have implemented a novel intraoperative communication system for head and neck surgical pathology using 3D scanning technology and computer-aided design (CAD) software. Here, we highlight our CAD margin protocol, in which we 3D scan head and neck oncologic surgical specimens and map frozen section results. This enhances the communication of margin status between surgeons and pathologists and delivers visual anatomic guidance for re-resection when needed. Laryngoscope, 2022.