Miracle-dz/UniFAR-FTUs huggingface dataset:
Carbon-based perovskite solar cells with electron and hole-transporting/-blocking layers

Towards commercialization of perovskite solar cells (PSCs), further reducing the cost and increasing the stability of PSCs have been the most important tasks of researchers, as the efficiency of single-junction PSCs has reached a competitive level among all kinds of single-junction solar cells. Carbon-electrode-based PSCs (CPSCs), as one of the most promising constructions for achieving stable economical PSCs, now attract enormous attention for their cost-effectiveness and stability. Here, we briefly review the development of CPSCs and reveal the importance of n-i-p architecture for state-of-the-art CPSCs. However, despite their promising potential, challenges still exist in CPSCs in the n-i-p architecture, which mainly stem from the incompact contact of the hole-transporting layer (HTL)/carbon electrode. Thus, new carbon materials and/or novel manufacturing methods should be proposed. In addition, HTL is yet to be appropriate for state-of-the-art CPSCs because the fabrication of carbon electrode could result in the destruction of the underlayer. To further enhance the performance of CPSCs, both the HTL and electron transport layer as well as their interfaces with perovskite active layer need to be improved. We recommend that the perovskite active layer, with its long carrier lifetime, strong carrier transport capability, and long-term stability, is necessary as well for improved performance of CPSCs. We also highlight current researches on CPSCs and provide a systematic review of various types of regulation tools.
Target Localization Based on Angle of Arrivals

Mobile location using angle of arrival (AOA) measurements has received considerable attention. This paper presents an approximation of maximum likelihood estimator (MLE) for localizing a source based on AOA measurements. By introducing an intermediate variable, the nonlinear equations relating AOA estimates can be transformed into a set of equations which are linear in the unknown parameters. It is an approximate realization of the MLE. Simulations show that the proposed algorithm outperforms the previous contribution.
Acoustic emission for the 1990s

An overview of recent results which provide new directions for acoustic emission (AE) technology during this decade is given. The 1990s will see new quantitative acoustic emission test methods develop as new technology takes advantage of progress in understanding AE practice. New aspects of AE described herein include different theoretical perspectives, accurate source location in anisotropic materials, broadband waveform measurements, and filtering out background noise. Also mentioned are the technologies needed in order to realize the practical contributions this technique can make to society. <<ETX>>
Elasticity: Hooke’s law

IN the first article of this series (July 1987 TLE), the central topic was traveling waves on a string. These waves propagate along the string, i.e., travel from one end to the other (and back). However, each point on the string vibrates at right angles to the direction of wave motion. This type of wave, in which particle motion is perpendicular to wave motion, is called a transverse wave.
Intercomparison of Spatial Forecast Verification Methods

Abstract Advancements in weather forecast models and their enhanced resolution have led to substantially improved and more realistic-appearing forecasts for some variables. However, traditional verification scores often indicate poor performance because of the increased small-scale variability so that the true quality of the forecasts is not always characterized well. As a result, numerous new methods for verifying these forecasts have been proposed. These new methods can mostly be classified into two overall categories: filtering methods and displacement methods. The filtering methods can be further delineated into neighborhood and scale separation, and the displacement methods can be divided into features based and field deformation. Each method gives considerably more information than the traditional scores, but it is not clear which method(s) should be used for which purpose. A verification methods intercomparison project has been established in order to glean a better understanding of the proposed me.
Assessing the Stability of Herbicide-Tolerant Lentil Accessions (Lens culinaris Medik.) under Diverse Environments

Assessing the adaptability and stability of herbicide-tolerant lentil accessions to two broad-spectrum post-emergence herbicides in multi-environment trials has become a must in a breeding program to improve its selection. The adaptability and stability of 42 herbicide-tolerant lentil accessions were investigated using five stability parameters under eight different environments. Significant Genotype–Environment (GE) interaction was found for days to flowering (DFLR), days to maturity (DMAT), and seed yield per plant (SY). The analyzed stability parameters such as Cultivar superiority, Finlay–Wilkinson, Shukla, Static Stability, and Wricke’s Ecovalence ranked the tested accessions differently, confirming the importance of using a combination of stability parameters when evaluating the performance of a group of accessions. GGE biplot of the SY trait accounted for 60.79% of sums of squares of the GE interaction and showed that cool and high rainfall environments are ideal for testing the agronomic performance of tolerant accessions. The GGE biplot of SY showed that IG4605(19), IG195(6), and IG156635(12) were specifically adapted to one mega environment, whereas IG70056(38) was identified as a superior line having a high and stable yield. These lines should be included in lentil crossing programs to develop herbicide-tolerant cultivars adapted to diverse environments.
Multiwavelength erbium-doped fiber laser with 0.8-nm spacing using sampled Bragg grating and photonic crystal fiber

We propose and demonstrate a novel room-temperature multiwavelength erbium-doped fiber laser (EDFL) with a 0.8-nm wavelength spacing based on four-wave mixing (FWM) in a length of high-nonlinear photonic crystal fiber and sampled-fiber Bragg grating. The FWM processes suppress the wavelength competition of the EDFL and increase the number of lasing wavelength. By adjusting the FWM efficiency, the number of the concurrent lasing wavelengths can be changed, and the peak power differences among the main oscillation wavelengths are less than 2.0 dB.
Semi-focusing billiards: ergodicity

Abstract In Bunimovich and Del Magno [Semi-focusing billiards: hyperbolicity. Comm. Math. Phys.262 (2006), 17–32], we proved that billiards in certain three-dimensional convex domains are hyperbolic. In this paper, we continue the study of these systems, and prove that they enjoy the Bernoulli property. This result answers affirmatively a long-standing question on the existence of ergodic billiards in convex domains in dimensions greater than two. Besides, it shows that the chaotic components of the first rigorously investigated three-dimensional billiards with mixed phase space (mushroom billiards), introduced in Bunimovich and Del Magno, are in fact Bernoulli.
Vector-potential boundary-integral evaluation of eddy-current interaction with a crack

In eddy-current nondestructive evaluation, an excitation coil, used to induce current in a conductor, changes impedance in the presence of a crack. The impedance change can be calculated from a knowledge of the coil parameters, the excitation frequency, and the crack geometry. Two boundary integral formulations of the problem are compared. The first formulation uses an electric field integral equation, and the second expresses the magnetic vector potential in integral form using an integral kernel with a weaker singularity. The vector potential formulation, presented here for the first time, leads to a more complicated equation but has a singular kernel that is easier to deal with. In addition, the new approach opens up a number of possibilities for further analytical developments. An example calculation is performed for a long, surface-breaking crack, and the results are compared to available analytical solutions. Very good agreement is found between the numerical solution of the integral equation and the analytical results.
New Digital Multisignature Scheme with Distinguished Signing Responsibilities

Summary A multisignature scheme is a digital signature scheme that allows multiple signers to generate a single signature in a collaborative and simultaneous manner. In this paper we first review of the digital multisignature schemes using elliptic curvers and elliptic curve version of the multisignature scheme with distinguished signing responsibilities. Then, we propose a new multisignature scheme with distinguished signing responsibilities. In this scheme, each group member has distinguished signing responsibility and partial contents of the message can be verified without revealing the whole message. Our proposed scheme is more efficient than the scheme reviewed and capable of application in practice.
Pattern formation and directional and spatial ordering of edge dislocations in bulk GaN: Microphotoluminescence spectra and continuum elastic calculations

We present a detailed microphotoluminescence study of the long-range strain fields surrounding threading dislocations as well as their interaction and pattern formation in GaN bulk crystals. The stress patterns are detected by tiny energy shifts of the near-band-edge spectral lines and show a dipolelike stress state around the dislocation core of edge- or mixed-type dislocations, with an angular orientation coinciding with high-symmetry crystal directions. We detect tens of micrometers long linear lineups of edge dislocations with sizable effects on the local strain states and photoluminescence peak positions. With continuum elastic strain simulations, we demonstrate that the observed patterns of threading dislocations are energetically favorable. We calculated a binding energy per threading dislocation length of $50\phantom{\rule{0.3em}{0ex}}\mathrm{meV}∕\ensuremath{\mu}\mathrm{m}$ against gliding of an edge dislocation within a lineup of edge dislocations of parallel Burgers vector orientation.
Normal force in single-sided linear induction motors

It is shown that the normal force in a single-sided linear induction motor can be appreciable, and that it is highly dependent on the speed and terminal conditions. Two simple theories are presented, and these are compared with experimental results. Tests were performed on both static and dynamic machines showing the variation of normal force with frequency and speed, and the effects of pole changing and plugging. It is concluded that the normal force and the possible changes that can occur in its magnitude and direction are highly significant design factors.
Ancient fires enhance Amazon forest drought resistance

Drought and fire reduce productivity and increase tree mortality in tropical forests. Fires also produce pyrogenic carbon (PyC), which persists in situ for centuries to millennia, and represents a legacy of past fires, potentially improving soil fertility and water holding capacity and selecting for the survival and recruitment of certain tree life-history (or successional) strategies. We investigated whether PyC is correlated with physicochemical soil properties, wood density, aboveground carbon (AGC) dynamics and forest resistance to severe drought. To achieve our aim, we used an Amazon-wide, long-term plot network, in forests without known recent fires, integrating site-specific measures of forest dynamics, soil properties and a unique soil PyC concentration database. We found that forests with higher concentrations of soil PyC had both higher soil fertility and lower wood density. Soil PyC was not associated with AGC dynamics in non-drought years. However, during extreme drought events (10% driest years), forests with higher concentrations of soil PyC experienced lower reductions in AGC gains (woody growth and recruitment), with this drought-immunizing effect increasing with drought severity. Forests with a legacy of ancient fires are therefore more likely to continue to grow and recruit under increased drought severity. Forests with high soil PyC concentrations (third quartile) had 3.8% greater AGC gains under mean drought, but 33.7% greater under the most extreme drought than forests with low soil PyC concentrations (first quartile), offsetting losses of up to 0.68 Mg C ha–1yr–1 of AGC under extreme drought events. This suggests that ancient fires have legacy effects on current forest dynamics, by altering soil fertility and favoring tree species capable of continued growth and recruitment during droughts. Therefore, mature forest that experienced fires centuries or millennia ago may have greater resistance to current short-term droughts.
Poincaré Series and Deformations of Gorenstein Local Algebras

Let (A, 𝔪, K) be an Artinian Gorenstein local ring with K an algebraically closed field of characteristic 0. In the present article, we prove a structure theorem describing the Artinian Gorenstein local K-algebras satisfying 𝔪4 = 0. We use this result in order to prove that such a K-algebra has rational Poincaré series and it is smoothable in any embedding dimension, provided dim K 𝔪2/𝔪3 ≤ 4. We also prove that the generic Artinian Gorenstein local K-algebra with 𝔪4 = 0 has rational Poincaré series.
Tagging Multi-Label Categories to Points of Interest From Check-In Data

Category tag of Point Of Interest (POI) serves a crucial role in numerous Location Based Services (LBS) like finding a place of interest, POI recommendation, location-based advertisement, etc. However, it has been found that many POIs (around 30%) do not have any category information. Manual tagging of these categories is a very costly affair as it requires a physical visit to each POI. Hence, an automated method for category tagging of POIs has been identified as an important research problem. The problem of category tagging of POIs is still in its primary stage, requiring further exploration. In this work, we solve the problem in three broad steps i). feature identification, ii). feature extraction, and iii). tag assignment. For the first step, we consider sequential features, temporal features, and spatial features, which can be constructed using check-in data. For the second step, we generate POI embedding representing its features, using a graph-based unsupervised approach. For the final step, the problem is considered a multi-label classification problem. For this, we have used Classifier Chain algorithms which preserves inter-tag correlation. Comparison with state-of-the-art methodologies along with multiple variants of features and classification algorithms show a significant improvement of $5-34\%$ by standard metric of average F1-score.
Investigation of the different discharge mechanisms in pseudospark discharges

The intention of this paper is to give an overview of recent experiments explaining the development and transition of the discharge phases in a pseudospark. The reported experiments include single gap pseudospark discharges in ultra-high-vacuum systems with hydrogen as working gas, as well as multigap pseudospark discharges in argon. Temporally and spatially resolved framing photography, spectrometry, raster electron microscopy and time resolved electrical measurements are presented. The experiments comprise a current range of some hundreds of amps to 60 kA. The results are used to specify the four characteristic phases of the pseudospark: Townsend-, hollow cathode-, high current- and metal vapor arc phase. >
Personal air pollution exposure and metals in the nasal epithelial lining fluid of COPD patients

Sampling of the nasal epithelial lining fluid is a potential method to assess exposure to air pollution within the respiratory tract among high risk populations. We investigated associations of short- and long-term particulate matter exposure (PM) and pollution-related metals in the nasal fluid of people with chronic obstructive pulmonary disease (COPD). This study included 20 participants with moderate-to-severe COPD from a larger study who measured long-term personal exposure to PM2.5 using portable air monitors and short-term PM2.5 and black carbon (BC) using in-home samplers for the seven days preceding nasal fluid collection. Nasal fluid was sampled from both nares by nasosorption, and inductively coupled plasma mass spectrometry was used to determine the concentration of metals with major airborne sources. Correlations of selected elements (Fe, Ba, Ni, Pb, V, Zn, Cu) were determined within the nasal fluid. Associations between personal long-term PM2.5 and seven day home PM2.5 and BC exposure and nasal fluid metal concentrations were determined by linear regression. Within nasal fluid samples, concentrations of vanadium and nickel (r = 0.8) and lead and zinc (r = 0.7) were correlated. Seven day and long-term PM2.5 exposure were both associated with higher levels of copper, lead, and vanadium in the nasal fluid. BC exposure was associated with higher levels of nickel in the nasal fluid. Levels of certain metals in the nasal fluid may serve as biomarkers of air pollution exposure in the upper respiratory tract.
On noisy pattern matching under geometrical constraints

Least-squares pattern matching over the Euclidean space E/sup n/ for unordered sets of cardinality p is commonly formulated as a combinatorial optimization problem having complexity p times p! , p>>n. Since p may be 10/sup 3/ or larger in typical applications, less than satisfactory suboptimal methods are usually used. A powerful hybrid approach is described which casts the pattern matching problem in a differentiable setting using rigid motion constraints which often apply and reduces the complexity to l/sub 21/n/sup 4/+l/sub 12/p/sup 3/, where l/sub 12/ and l/sub 21/ are the number of iterations required by procedures based on steepest ascent and singular value decomposition (SVD), respectively. <<ETX>>
Deployment control of a cable connecting a ship to an underwater vehicle

This paper describes the development of an underwater cable dynamics model and a realistic control system which allows deployment, regulation, and retrieval of an unmanned underwater vehicle tethered to a ship. An order-n algorithm for a variable mass cable subject to hydrodynamic forces and motion constraints is used to simulate the dynamics of the system. The dynamics of the underwater vehicle is separately given with the cable tension nonlinearly affecting the vehicle speed. This creates a constraint on the cable motion that depends nonlinearly on the constraint force, a problem that is iteratively solved using constraint stabilization. The cable dynamics model and the controller presented in this paper can be used to answer many design questions relating to tethered underwater vehicles.
Ecophysiological basis of spatiotemporal patterns in picophytoplankton pigments in the global ocean

Information on the intracellular content and functional diversity of phytoplankton pigments can provide valuable insight on the ecophysiological state of primary producers and the flow of energy within aquatic ecosystems. Combined global datasets of analytical flow cytometry (AFC) cell counts and High-Performance Liquid Chromatography (HPLC) pigment concentrations were used to examine vertical and seasonal variability in the ratios of phytoplankton pigments in relation to indices of cellular photoacclimation. Across all open ocean datasets, the weight-to-weight ratio of photoprotective to photosynthetic pigments showed a strong depth dependence that tracked the vertical decline in the relative availability of light. The Bermuda Atlantic Time-series Study (BATS) dataset revealed a general increase in surface values of the relative concentrations of photoprotective carotenoids from the winter-spring phytoplankton communities dominated by low-light acclimated eukaryotic microalgae to the summer and early autumn communities dominated by high-light acclimated picocyanobacteria. In Prochlorococcus-dominated waters, the vertical decline in the relative contribution of photoprotective pigments to total pigment concentration could be attributed in large part to changes in the cellular content of photosynthetic pigments (PSP) rather than photoprotective pigments (PPP), as evidenced by a depth-dependent increase of the intracellular concentration of the divinyl chlorophyll-a (DVChl-a) whilst the intracellular concentration of the PPP zeaxanthin remained relatively uniform with depth. The ability of Prochlorococcus cells to adjust their DVChl-a cell-1 over a large gradient in light intensity was reflected in more highly variable estimates of carbon-to-Chl-a ratio compared to those reported for other phytoplankton groups. This cellular property is likely the combined result of photoacclimatory changes at the cellular level and a shift in dominant ecotypes. Developing a mechanistic understanding of sources of variability in pigmentation of picocyanobacteria is critical if the pigment markers and bio-optical properties of these cells are to be used to map their biogeography and serve as indicators of photoacclimatory state of subtropical phytoplankton communities more broadly. It would also allow better assessment of effects on, and adaptability of phytoplankton communities in the tropical/subtropical ocean due to climate change.
Stress recognition with multi‐modal sensing using bootstrapped ensemble deep learning model

The factors that influence a person's mental health are numerous, interconnected, and multi‐dimensional. Recognition of stress is one of the facets in developing the Mental Healthcare (MHC) system framework. With the advent of technology, smart wearable devices have paved a way to collect data in real‐time to provide the cutting‐edge reports about the individual. Due to the physiological sensors present in the smart wearable devices, it is now possible to have a robust system to recognize the stress of the smart wearable devices user thus consecutively leading to recognition of factors in leading to stress. However, the current MHC system for recognition and identification of stress have several drawbacks. First, stress recognition is mostly designed for a particular group of individuals like occupational stress, perinatal maternal stress, or health worker stress and fails to propose a framework that would not be targeted for a particular group of individual. Second, most of the previous work done on stress recognition focuses on the extraction of handcrafted features thus requiring human intervention and expertise. To address these issues, this study proposes, a hybrid deep learning based ensemble approach for automated extraction of features and classification into various state of stress for MHC system. The proposed framework takes input from wearable physiological sensors and is provided to deep learning classifier of convolutional neural network (CNN) and CNN‐long short term memory based ensemble model. The proposed framework has been experimented on the wearable stress and affect detection dataset and reports an accuracy of 91.52% that is 7.20% higher than earlier reported accuracies from other machine learning and deep learning models.