Miracle-dz/UniFAR-FTUs huggingface dataset:
Dust distribution in L1217/L1219: Nice vs. Nicer

The dust in molecular clouds reliably traces the molecular gas within. We used this assumption to get an estimate of the dense cores size and mass in L1217/L1219 by deriving the total optical extinction, and therefore, the total column density. In this, two methods were used, the "standard" Near Infrared Color Excess (NICE) and the Near-Infrared Color Excess Revisited (NICER). Results confirm that NICER is better in tracing the low level extinction areas, consequently making the total cloud's mass significantly larger, as compared to the NICE derived value.
The acquisition of finite complement clauses in English: A corpus-based analysis

Abstract This article examines the development of finite complement clauses in the speech of seven English-speaking children aged 1;2 to 5;2. It shows that in most of children's complex utterances that seem to include a finite complement clause, the main clause does not express a full proposition; rather, it functions as an epistemic marker, attention getter, or marker of illocutionary force. The whole construction thus contains only a single proposition expressed by the apparent complement clause. As children grow older, some of the “main clauses” become more substantial and new complement-taking verbs emerge that occur with truly embedded complement clauses. However, since the use of these constructions is limited to only a few verbs, we argue that they are not yet licensed by a general schema or rule; rather, they are “constructional islands” organized around individual verbs.
Deriving a unit hydrograph for Tazlău River Basin using ArcGIS

: Hydrographs are used in hydrological studies to illustrate the fluctuation of the stream during rainfall. A hydrograph's total flow includes runoff and base flow. The unit hydrograph (UH) only measures direct surface runoff. Modeling rain events by using unit hydrograph theory has the advantage of being easier to determine than hydraulic distributed modeling and can yield desirable outcomes for objectives of applied hydrology. The purpose of this research is to genera te a unit hydrograph for a section of the Tazlău River Basin by utilizing the physical properties of its basin. For this purpose, parameters such as peak discharge, time to peak discharge and the base width of the unit hydrograph were determined. This research explored the use of Geographic Information System (GIS) and Digital Elevation Model (DEM) in the development of unit hydrograph. This research explored the use of GIS and Digital Elevation Model in the development of unit hydrograph for uses in streamflow predictions and rainfall runoff modeling. The most common uses after creating a unit hydrograph are designing flood prediction, which estimates flood flows in real time based on rainfall records, runoff assessment from ungauged watersheds and supplement the incomplete archives.
Responses of Maize (Zea mays L.) Roots to Nitrogen Heterogeneity and Intraspecific Competition: Evidence from a Pot Experiment Using the ‘Root Splitting’ Approach

A heterogeneous distribution of nutrients in the soil and the root interactions of crops coexist in agroecosystems. A ‘root splitting’ approach, i.e., splitting the root system into different nutrient compartments, was used to study nutrient heterogeneity distributions and root interactions. We evaluated root foraging behavior, individual growth, and root development mechanisms in response to soil nitrogen heterogeneity, and intraspecific competition in maize. A heterogeneous distribution of nitrogen increased the foraging precision of roots at flowering and mature stages (Foraging precision > 1), and significantly increased root biomass and surface area on the intraspecific competition and no competition on the high nitrogen side. The heterogeneous distribution had no effect on yield, total root biomass, specific root length, total surface area, or average diameter. Intraspecific competition increased inter-crop competition (RII < 0) and reduced total root biomass, total plant biomass, and the root/shoot ratio. These results inform root trait development studies and provide valid evidence for optimizing and managing fertilizer application in agroecosystems, helping to maximize crop yield and nutrient use efficiency.
Research on Attitude Detection and Flight Experiment of Coaxial Twin-Rotor UAV

Aiming at the problem that the single sensor of the coaxial UAV cannot accurately measure attitude information, a pose estimation algorithm based on unscented Kalman filter information fusion is proposed. The kinematics and dynamics characteristics of coaxial folding twin-rotor UAV are studied, and a mathematical model is established. The common attitude estimation methods are analyzed, and the extended Kalman filter algorithm and unscented Kalman filter algorithm are established. In order to complete the test of the prototype of a small coaxial twin-rotor UAV, a test platform for the dynamic performance and attitude angle of the semi-physical flight of the UAV was established. The platform can analyze the mechanical vibration, attitude angle and noise of the aircraft. It can also test and analyze the characteristics of the mechanical vibration and noise produced by the UAV at different rotor speeds. Furthermore, the static and time-varying trends of the pitch angle and yaw angle of the Kalman filter attitude estimation algorithm is further analyzed through static and dynamic experiments. The analysis results show that the attitude estimation of the UKF is better than that of the EKF when the throttle is between 0. 2σ and 0. 9σ. The error of the algorithm is less than 0.6°. The experiment and analysis provide a reference for the optimization of the control parameters and flight control strategy of the coaxial folding dual-rotor aircraft.
Human Fall Detection Using 3D Multi-Stream Convolutional Neural Networks with Fusion

Human falls, especially for elderly people, can cause serious injuries that might lead to permanent disability. Approximately 20–30% of the aged people in the United States who experienced fall accidents suffer from head trauma, injuries, or bruises. Fall detection is becoming an important public healthcare problem. Timely and accurate fall incident detection could enable the instant delivery of medical services to the injured. New advances in vision-based technologies, including deep learning, have shown significant results in action recognition, where some focus on the detection of fall actions. In this paper, we propose an automatic human fall detection system using multi-stream convolutional neural networks with fusion. The system is based on a multi-level image-fusion approach of every 16 frames of an input video to highlight movement differences within this range. This results of four consecutive preprocessed images are fed to a new proposed and efficient lightweight multi-stream CNN model that is based on a four-branch architecture (4S-3DCNN) that classifies whether there is an incident of a human fall. The evaluation included the use of more than 6392 generated sequences from the Le2i fall detection dataset, which is a publicly available fall video dataset. The proposed method, using three-fold cross-validation to validate generalization and susceptibility to overfitting, achieved a 99.03%, 99.00%, 99.68%, and 99.00% accuracy, sensitivity, specificity, and precision, respectively. The experimental results prove that the proposed model outperforms state-of-the-art models, including GoogleNet, SqueezeNet, ResNet18, and DarkNet19, for fall incident detection.
A large-scale ASON platform in Tsinghua University

This paper presents a large scale automatically switched optical network (ASON) test-bed made by Tsinghua University. The testbed is composed of hardware platform, control plane and management plane. The hardware platform is constructed with switches, computers and optical nodes as well. The software modules of the control plane for the testbed mainly include hierarchical routing, signaling with the separation of the call control and the connection control, and the link management supporting hierarchical control. The management plane is a distributed system with locally centralized management functions. The testbed can provide main large scale ASON functions and record the kinds and the amount of signaling, total and separate block probabilities for the sake of research.
AUTOMATIC CLASSIFICATION OF BREAST CANCER

: Breast cancer ranks first among the most common types of cancer, globally, regionally. Artificial intelligence plays an important role in medical sector, especially in improving healthcare for patients, in which the early detection and diagnosis of disease increasing the probability of recovery. This paper with the help of machine learning technique proposes to present a non-invasive method for diagnosing and classify breast diseases based on mammograms and ultrasound images, to extract the statistical features of them (smoothness, perimeter, area, concavity, compactness, symmetry, size, diameter, concave and radius), to identify the breast tissue as malignant tumor, or a benign tumor and predicting in the future at the long term to prevent it. Learning algorithms are used mainly: support vector machine (SVM), multilayer perceptron (MLP), naïve Bayes (NB) and Decision tree (DT) algorithms to build model capable of classifying the breast tissue into malignant or a benign, based on several features reached up to 30 features. The Results showed that SVM achieved higher accuracy which is reached up to 95.89%, followed by MLP classifier with 93.61%, and the NB accuracy which is reached up to 90.62%.
PZT piezoelectric films on glass for Gen-X imaging

The proposed adaptive optics system for the Gen-X telescope uses piezoelectric lead zirconate titanate (PZT) films deposited on flexible glass substrates. The low softening transition of the glass substrates imposes several processing challenges that require the development of new approaches to deposit high quality PZT thin films. Synthesis and optimization of chemical solution deposited 1 μm thick films of PbZr0.52Ti0. 48O3 on small area (1 in2) and large area (16 in2) Pt/Ti/glass substrates has been performed. In order to avoid warping of the glass at temperatures typically used to crystallize PZT films (~700°C), a lower temperature, two-step crystallization process was employed. An ~80 nm thick seed layer of PbZr0.30Ti0. 70O3 was deposited to promote the growth of the perovskite phase. After the deposition of the seed layer, the films were annealed in a rapid thermal annealing (RTA) furnace at 550°C for 3 minutes to nucleate the perovskite phase. This was followed by isothermal annealing at 550°C for 1 hour to complete crystallization. For the subsequent PbZr0.52Ti0. 48O3 layers, the same RTA protocol was performed, with the isothermal crystallization implemented following the deposition of three PbZr0.52Ti0. 48O3 spin-coated layers. Over the frequency range of 1 kHz to 100 kHz, films exhibit relative permittivity values near 800 with loss tangents below 0.07. Hysteresis loops show low levels of imprint with coercive fields of 40-50 kV/cm in the forward direction and 50-70 kV/cm in the reverse direction. The remanent polarization varied from 25-35 μC/cm2 and e31,f values were approximately -5.0 C/m2. In scaling up the growth procedure to large area films, where warping becomes more pronounced due to the increased size of the substrate, the pyrolysis and crystallization conditions were performed in a box furnace to improve the temperature uniformity. By depositing films on both sides of the glass substrate, the tensile stresses are balanced, providing a sufficiently flat surface to continue PZT deposition. The properties of the large area film are comparable to those obtained on small substrates. While sol-gel processing is a viable approach to the deposition of high quality PZT thin films on glass substrates, preliminary results using RF magnetron sputter deposition demonstrate comparable properties with a significantly simpler process that offers a superior route for large scale production.
Direct Numerical Simulation and Large-Eddy Simulation of Supersonic Channel Flow

Compressible isothermal-wall channel flows are studied with direct numerical simulation and large-eddy simulation tools. Computations are carried out using a high-order, low-dissipation, bandwidth-optimized weighted essentially nonoscillatory numerical scheme to describe the hyperbolic terms of the Navier–Stokes equations. Periodic supersonic channel flow direct numerical simulation (M=1.5, Reτ=221, Tw=500 K, and Tc=700 K) is used to validate the procedure and the numerical scheme; a new subgrid term contribution based on pressure drop is proposed for the driving term required in momentum and energy equations for large-eddy simulation. Coherent structures of the flowfield are analyzed with scatter plots, Q criterion, and vorticity fields. As expected, the strong Reynolds analogy is not valid for this nonadiabatic flow. Streaks and horseshoe-like structures are highlighted and detailed. The authors propose a scenario for the formation of horseshoe-like structures. With large-eddy simulation tools, a dyna.
EFFECT OF QUINOA ON BIOLOGICAL, BIOCHEMICAL AND HISTOLOGICAL PARAMETERS OF ALBINO MALE RATS

: This study was aimed to determine the effect of adding quinoa seeds powder (QSP) on biological, biochemical and histological parameters of albino male rats as well as preparing functional biscuit supplemented with quinoa powder. The results of QSP in the current study show that DPPH radical scavenging activity (%) was gradually increased with the increasing the concentration from 1.5 to 10. Whereas, IC 50 was recorded 4.39. Wheat flour was substituted with quinoa powder at a rate of 10,15 and 20% in tested biscuit. The panel test revel that 20% quinoa biscuit was recorded the highest general acceptability values by the panelists. So, this quinoa percentage was used in the biological experimental design. Twelve male rats weighting 120±10g were divided into two main groups (6 each). The first group was fed on basal diet and the second group was fed on basal diet containing 20% QSP. Nutritional, biochemical and histological parameters revel that feed intake, body weight, feed efficiency ratio, AST, ALT, Creatinine(Cr), TG, TC, LDL and VLDL were insignificant decreased compared with control group. Whereas, urea, Blood Urea Nitrogen (BUN) and HDL were insignificant increased compared with control group. The results of histological examination for liver and kidney were similar to those of the previous studies. According to these findings quinoa may be used in several food products and might has a beneficial food property.
Molecular clouds in the Carina arm - Large-scale properties of molecular gas and comparison with H I

Results from the first large-scale survey in the CO (J = 1 - 0) line of the Vela-Carina-Centaurus region of the southern Milky Way are reported. The results demonstrate that molecular clouds in the Galaxy are largely confined to the spiral arms and that CO is therefore an extremely good tracer of the large-scale structure of the system. The Carina arm is the dominant feature in the data. Its abrupt tangent at l of roughly 280 deg and characteristic loop in the (l, v) diagram are unmistakable evidence for CO spiral structure. When the emission is integrated over velocity and latitude, the height of the step seen in the tangent direction indicate that the arm-interarm contrast is at least 13:1. 44 references.
High-Energy Gamma-Ray Emission from Galactic Kerr-Newman Black Holes. I. The Central Engine

A model of the central engine of the unidentified high-latitude galactic hard γ-ray (EGRET) sources based on black hole electrodynamics is presented. The γ-ray emission is produced in a bipolar outflow from a charged, rotating black hole (a Kerr-Newman black hole) in a low-density region of the Galaxy, the details of which are provided in a companion paper. The model proposed in this article and its companion is a synthesis of pair creation scenarios for pulsars, the theory of black hole magnetospheres and synchrotron self-Compton large-scale jets. This article describes the physics of the putative central engine. Kerr-Newman black holes are plausible endpoints of the catastrophic gravitational collapse of the most massive magnetized rotating stars. In the following, the ability of a Kerr-Newman black hole to drive a magnetically dominated plasma wind in the charge-starved limit is explored for the first time. Although there are important analogies to magnetohydrodynamic (MHD) wind theory of Kerr (uncharged rotating) black holes, there are also enormous distinctions. However, previous experience with the MHD Kerr case is exploited to render this more complicated problem tractable. The most important parameter for quantifying the wind energy is the magnetic field line angular velocity, ΩF (and unfortunately the most difficult to calculate). The determination of ΩF is tied directly to the process by which a pair plasma is created on large-scale magnetic field lines through high-energy quantum electrodynamic processes typical of pulsar magnetospheres. It is argued in principle how ΩF is determined by the plasma injection mechanism. Furthermore, the most significant result of this effort is the calculation of ΩF for a model that is determined by a plausible set of astronomical parameters. It is essential to realize a distinction from some charge-starved pulsar models: the energy source for the wind is quantified by the field line rotation rate (the cross-field potential), ultimately powered by the rotation of the hole through dissipative gravitomagnetic processes and not the volage drop across the vacuum pair creation gap.
Temperature dependence of cavity ionization chamber response

The temperature dependence of the cavity ion chamber response was measured at room temperature in the range 17 °C to 27 °C. By analysing the variation of the ionization current with temperature produced in the cavity chamber, the temperature coefficient of the cavity chamber response was evaluated. The values were 4.1 × 10−4 °C−1, 4.3 × 10−4 °C−1 and 2 × 10−5 °C−1 for chambers made of C552 air equivalent plastic, polyoxymethylene and graphite, respectively.
Path Following Control of a Mobile Robot Using Contractive Model Predictive Control

In this paper, we propose a novel controller based on contractive model predictive control for the path following problem of a mobile robot. Besides dealing with path following, we also fulfill the following objectives: bounded control signals and optimal forward velocity. These three objectives are all achieved through integrating into our model predictive control framework as constraints. However, the major concern in the use of model predictive control is whether such an open-loop control scheme can guarantee system stability. In this case, we apply the idea of a contractive constraint to guarantee the stability of our MPC framework. To illustrate its effectiveness, several simulation scenarios have been conducted.
From the conservation laws to the Hamiltonian structures of discrete soliton systems

We describe an approach to investigate the Hamiltonian structures of discrete soliton systems, which is deduced from the relation between the conservation laws and the Hamiltonian structures. As to its applications, the Toda lattice, the Blaszak–Marciniak lattice and the Blaszak–Marciniak (II) are discussed.
HERDING IN CRYPTOCURRENCIES: CSSD AND CSAD APPROACHES

: This paper uses CSSD developed by Christie and Huang (1995) and CSAD developed by Chang, Cheng, and Khorana (2000) to test for herding in cryptocurrencies over the period 21/09/2018-21/09/2022. Two sets of cryptocurrencies were considered, one containing the 34 largest cryptocurrencies by market capitalisation and the other containing 15 cryptocurrencies with market capitalisations under $200 million. Any cryptocurrencies launched after 21/09/2018 were excluded from the samples in the interests of consistency. Using CSSD, no herding was detected while with CSAD a weak herding effect was observed, though the results were not statistically significant. This paper has important implications for cryptocurrency investors
Velocity gradient dynamics in compressible turbulence: Characterization of pressure-Hessian tensor

Pressure-Hessian tensor produces the most significant difference between incompressible and compressible velocity gradient dynamics in turbulent flows. Characterization of pressure-Hessian tensor as a function of the level of compressibility is therefore of much interest. Using direct numerical simulation results, we demonstrate that the pressure-Hessian tensor behavior can be most exclusively characterized in terms of the compressibility parameter δ which is defined to be the growth-rate of dilatation-rate. A key compressibility effect is the distinct change in the alignment between pressure-Hessian and velocity gradient tensors with increasing δ. In incompressible turbulence, the pressure-Hessian eigenvectors exhibit a mild tendency to align at 45° angle with the principal directions of strain rate. With increasing δ, the pressure-Hessian tensor shows progressively stronger tendency to align along principal directions of the local strain-rate tensor. We show that this change in pressure-Hessian orientation causes the compressible velocity gradient dynamics to significantly differ from its incompressible counterpart. In incompressible turbulence, pressure mildly moderates the inherent gradient-steepening tendencies of the nonlinear inertial term. On the other hand, in highly compressible turbulence (extreme values of δ), pressure effects can lead to intense gradient steepening or smoothing depending upon the growth-rate of dilatation rate, thereby profoundly altering the cascade process.
High Fidelity Ion Qubit State Detection

This work demonstrates highdelity ion-qubit measurement, crucial not only for the readout of states in the course of a computation, but also for e ective quantum error correction. We trap and cool a single, or few, 88Sr+ ions. A quantum bit is encoded in the two spin states of the single valence electron of the ion. Qubit readout is performed by shelving one of the qubit states to a metastable D level using a narrow linewidth laser at 674 nm followed by state-selective uorescence detection. To reach high delity qubit readout, the laser frequency has to be highly stabilized, and the linewidth of the laser has to be narrowed to the order of 1kHz. For this purpose we use an external cavity diode laser at 674nm and lock it to an ultra low expansion glass reference cavity, thus reaching a relative frequency uncertainty of ∼ 10−12. Careful analysis of the statistics of the photons detected at the uorescence stage, allows us to reach a detection error of 2 · 10−3, compatible with recent estimates of the detection error threshold required for fault-tolerant computation.