Miracle-dz/UniFAR-FTUs huggingface dataset:
Three-dimensional point cloud registration algorithm based on the correlation coefficient

Abstract. Point cloud registration is an important research problem in machine vision. One of the most widely used methods for point set registration is the iterative closest point (ICP) algorithm. However, ICP is known to be susceptible to local minima because it is based on the local iterative optimization technique and its performance critically relies on the quality of the initialization. To reduce the possibility of the algorithm falling into local minima, we propose an iterative algorithm based on geometric distance and local feature weighting named weighted correlation coefficient iterative closest point algorithm (WCC_ICP). The algorithm first establishes the corresponding relationship of points using linear representation and constructs an optimization model with constraints. Subsequently, the constrained optimization model is converted into an unconstrained optimization model by Lagrangian multiplication. Finally, an iterative technique is used to solve the optimal rigid body transformation of the optimized model. In addition, in each iteration, the identification ability of the local feature operator of points is used to repair the corresponding relation of points, which reduces the risk of the iterative algorithm falling into the local minima. Numerical experiments show that the proposed WCC_ICP algorithm reduces the risk of the iterative algorithm falling into local minima.
Temperature Fiber Sensor Based on 1-D CNN Incorporated Time-Stretch Method for Accurate Detection

In this article, we propose a novel method for temperature detection based on 1-D CNN and time-stretch method. Differing from traditional optical fiber temperature sensors that are demodulated by an optical spectrum analyzer (OSA) that needs long time to scan and a benchmark spectrum in advance, the demonstrated method can effectively solve the problem in demodulation and improve the detection speed. Besides, mapping the demodulation in the traditional spectral domain to the temporal domain through dispersion optical fiber can greatly reduce the system cost and the demodulation speed can be as high as 50 MHz. Furthermore, the designed peanut-shaped structured Mach–Zehnder interferometer (MZI) is simple to achieve, highly responsive to temperature, and easy to be mass produced at low cost. In the range of 10 °C–18 °C, the temperature sensitivity is up to 1.038 nm/°C, and the detection accuracy is up to 99.07% after using the 1-D CNN algorithm. The proposed sensor system is expected to play a potential role in important scenarios such as temperature monitoring of military weapons and space vehicle system management and control.
Classical N-particle cosmology in 2+1 dimensions

In 2+1 dimensional cosmology particles are topological defects in a universe that is nearly everywhere flat. The author uses a time dependent triangulation procedure of space to formulate the laws of evolution and to construct the phase space of this system. A theorem is derived from which it follows that many configurations may have a big bang in their past or a big crunch in their future. The dimensionality of phase space for N particles is 4N-11+12g, where g is the genus of 2-space. This suggests to consider 2N-6+6g pairs of canonical variables and one time variable. The quantum version of this model is speculated about.
Equivalent orbitals in molecules of known symmetry

The paper aims at providing a connecting link between the theory of molecular orbitals and the theory of localized bonds. An examination is made of the fundamental equations which must be satisfied by molecular orbitals in fields of known symmetry, particularly in molecules of the type XY n. It is shown by the methods of the group theory that these equations can be transformed to others which involve sets of equivalent functions. These are associated with equivalent orbitals which have the property of being identical as regards distribution in space and differ only in their orientation. It is shown that under certain conditions these can be regarded as localized orbitals associated with particular bonds. General formulae are obtained and applied to the particular cases of molecules of trigonal, tetrahedral and octahedral symmetry.
Hierarchal vector basis functions of arbitrary order for triangular and tetrahedral finite elements

New vector finite elements are proposed for electromagnetics. The new elements are triangular or tetrahedral edge elements (tangential vector elements) of arbitrary polynomial order. They are hierarchal, so that different orders can be used together in the same mesh and p-adaption is possible. They provide separate representation of the gradient and rotational parts of the vector field. Explicit formulas are presented for generating the basis functions to arbitrary order. The basis functions can be used directly or after a further stage of partial orthogonalization to improve the matrix conditioning. Matrix assembly for the frequency-domain curl-curl equation is conveniently carried out by means of universal matrices. Application of the new elements to the solution of a parallel-plate waveguide problem demonstrates the expected convergence rate of the phase of the reflection coefficient, for tetrahedral elements to order 4. In particular, the full-order elements have only the same asymptotic convergence rate as elements with a reduced gradient space (such as the Whitney element). However, further tests reveal that the optimum balance of the gradient and rotational components is problem-dependent.
Association between Meteorological Factors and Outpatient Visits for Herpes Zoster in Hefei, China: A Time-Series Analysis

This study sought to investigate the relationship between meteorological factors and outpatient visits for herpes zoster. In this time-series analysis, we used data from two major hospitals in Hefei, collected between 2015 and 2019, to evaluate the impact of meteorological factors on the risk of herpes zoster. After controlling for confounders, we adopted a distributed lag nonlinear model to probe the relationship between meteorological factors and outpatient visits for herpes zoster. The analysis was stratified according to age (<40 years, ≥40 years) and sex (male, female). A total of 43,547 cases of herpes zoster were reported, and compared with the median value, a high temperature and high relative humidity had a significant risk effect on the incidence of herpes zoster. The maximum harmful effect of high temperature on herpes zoster occurred on the lag0 (RR: 1.027, 95% CI: 1.002–1.053) and further declined over the following days. The cumulative effect increased with the extension of lag days, and the cumulative RR was the largest on the sixth day of lag (RR1.031, 95% CI: 1.006–1.056) when the relative humidity was 85.7% (77.0% as the reference). The stratified analysis results reveal that females and the elderly (≥40 years) were more susceptible to temperature and relative humidity. This study shows that high-temperatures may lead to herpes zoster, indicating that those infected with varicella zoster virus need to take measures over the course of several days when not exposed to the best appropriate temperature conditions.
Improving the accuracy of the Water Detect algorithm using Sentinel-2, Planetscope and sharpened imagery: a case study in an intermittent river

ABSTRACT Mapping surface water using remotely sensed optical imagery is a particular challenge in intermittent rivers because water contracts down to narrow linear features and isolated pools, which require accurate water detection methods and reliable image datasets. Of the many methods that use optical sensors to identify water, the Water Detect algorithm stands out as one of the best options due to its classification accuracy, open-source code, and because it does not require ancillary data. However, in the original study, the Water Detect algorithm was only tested with Sentinel-2 imagery. High-resolution and high-frequency imagery, such as Planetscope, combined with sharpening and band synthesizing techniques have the potential to improve the accuracy of surface water mapping, but their benefit to the Water Detect algorithm remains unknown. Uncertainty also exists about the extent to which different input parameters (i.e. maximum clustering and regularization) influence the accuracy of Water Detect. Practitioners seeking to map surface water in intermittent rivers need guidance on a best-practice approach to improve the accuracy of Water Detect. To meet this need, we automated an existing method for sharpening and synthesizing bands and applied it to a series of multispectral Sentinel-2 and Planetscope images. We then developed a sensitivity analysis algorithm that compared the accuracy for all possible combinations of input parameters in a given range for the water detection process – enabling optimal parameters to be identified. We applied this workflow to an 81 km stretch of the lower Fitzroy River (Western Australia) to periods when spatial water extent varied markedly, i.e. mid-wet (February), early-dry (June), and late-dry season (October), across three years with variable wet season flow. We found that the ability to accurately detect surface water using multispectral imagery was increased by using input parameters identified by the sensitivity analysis and using Visible + Near-infrared (VNIR) bands, with relatively little gained by image sharpening unless the area of interest was burnt or experienced considerable shading. Also, the regularization parameter exerted less influence on results than maximum clustering. Importantly, the accuracy of the Water Detect algorithm can vary drastically if input parameters are not calibrated to local conditions. Results also revealed that our approach was adept at detecting linear features in intermittent rivers. We recommend that practitioners using Water Detect to identify surface water undertake a workflow similar to that described here to improve the accuracy of the Water Detect algorithm. The automated routines provided by this study will significantly assist practitioners in doing so. Increasing the accuracy with which we detect and map water in intermittent rivers will improve our understanding and management of these important systems which are under increasing threat.
An ANN – Constant power generation control for LVRT of grid-connected PVG

This paper discusses an approach low-voltage ride-through control of a boost-converter for a two-stage grid-connected PV system under balanced grid voltage dips (BGVD). A combination of a maximum power point tracking (MPPT) and constant power generation (CPG) to control the boost-converter, respectively, in normal operation mode and BGVD under rapidly changing climatic conditions is proposed. MPPT and CPG commands based on artificial neural network algorithms are developed. Their goal is to maintain the operation of the low-voltage grid-connected photovoltaic system under instantaneously BGVD. This approach ensures a balance between the PV power generation and the injected active power when BGVD appears at the common coupling point (CCP). It permits to regulate the PV power to a specific value, to limit the over current at the CCP and to avoid energy aggregation at the DC-link bus. Simulations of 2.5 kW of a two-stage grid-connected PV system to verify the effectiveness of the command approach are presented.
Why linear sampling works

The linear sampling method is a method to reconstruct the shape of an obstacle in time-harmonic inverse scattering without a priori knowledge of either the physical properties or the number of disconnected components of the scatterer. Although it has been proven numerically to be a fast and reliable method in many situations, no mathematical argument has yet been found to prove why this is so. Using results obtained by Kirsch in deriving the related factorization method, we show in this paper that for a large class of scattering problems, linear sampling can be interpreted rigorously as a numerical method to reconstruct the shape of an obstacle; or in other words that linear sampling must work for problems in this class.
Environment-Human Bioaccumulation of Lead Resulting from Artisanal Lead-Zinc Mining Activities in Ebonyi State, Southeastern Nigeria

ABSTRACT The proliferation of shallow mine pits and indiscriminate dumping of mine tailings in the environment due to artisanal Lead-Zinc mining activities within the study area puts the immediate environment at risk of lead toxicity. Considering the adverse effect of Lead toxicity on humans, it has become imperative to evaluate the availability of Lead within the environment and to ascertain the potential pathway through which the contaminant can enter the human body. For this reason, soil, plant, groundwater, surface water, and human blood samples were collected within and beyond the mine catchment area in order to determine the amount of Lead in the environment. Samples were chemically digested and thereafter subjected to spectroscopic analysis using the atomic absorption spectroscopy method for the plant, soil, and water samples, whereas inductive coupled plasma mass spectroscopy was employed for blood sample analysis. Analysis of the laboratory results revealed that the average lead concentration in the environment was 0.49 mg/kg, 0.03 mg/L, 0.04 mg/L, and 0.01 mg/L in soil, plant, surface water, and groundwater, respectively. The correlation coefficient of 0.9 between the lead concentration in plant and soil and an average bioconcentration factor of 0.20 was evidence of soil-to-plant transfer of lead. Total environment-human bioaccumulation of Lead was 3.95 of which 48%, 37%, and 15% of it were contributed by ingestion of surface water, plants, and groundwater, respectively. The average concentration of Pb2+ in the blood of the residents within the study area (0.36 mg/L) was above the normal permissible limit in human blood.
Room-temperature continuous-wave operation of InGaN multi-quantum-well structure laser diodes with a lifetime of 27 hours

The continuous-wave (cw) operation of InGaN multi-quantum-well structure laser diodes (LDs) was demonstrated at room temperature (RT) with a lifetime of 27 h. The threshold current and the voltage of the LDs were 80 mA and 5.5 V, respectively. The threshold current density was 3.6 kA/cm2. Longitudinal modes with a mode separation of 0.042 nm were observed under cw operation at RT. When the temperature of the LDs was varied, large mode hopping of the emission wavelength was observed between adjacent quantum well or quantum dot subbands. The carrier lifetime and the threshold carrier density were estimated to be 10 ns and 2×1020/cm3, respectively.
Generating the structural graph‐based model from a program source‐code using chaotic forrest optimization algorithm

One of the most important and costly stages in software development is maintenance. Understanding the structure of software will make it easier to maintain it more efficiently. Clustering software modules is thought to be an effective reverse engineering technique for deriving structural models of software from source code. In software module clustering, the most essential objectives are to minimize connections between produced clusters, maximize internal connections within created clusters, and maximize clustering quality. Finding the appropriate software system clustering model is considered an NP‐complete task. The previously proposed approaches' key limitations are their low success rate, low stability, and poor modularization quality. In this paper, for optimal clustering of software modules, Chaotic based heuristic method using a forest optimization algorithm is proposed. The impact of chaos theory on the performance of the other SFLA‐GA and PSO‐GA has also been investigated. The results show that using the logistic chaos approach improves the performance of these methods in the software‐module clustering problem. The performance of chaotic based FOA, SFLA‐GA and PSO‐GA is superior to the other heuristic methods in terms of modularization quality and stability of the results.
Effect of Methionine Hydroxy Analog on Hu Sheep Digestibility, Rumen Fermentation, and Rumen Microbial Community In Vitro

This experiment was conducted to evaluate the effects of a methionine hydroxy analog (MHA) on in vitro gas production, rumen fermentation parameters, and rumen microbiota. Two different MHA, 2-hydroxy-4-(methylthio) butanoic acid isopropyl ester (HMBi) and the calcium salt of the hydroxy analog of methionine (MHA-Ca), were selected for in vitro experiments. The treatments were the Control group (0% of MHA), HMBi group (2%HMBi), and MHA-Ca group (2%MHA-Ca). Dry matter digestibility was measured after 12 h and 24 h of fermentation, and fermentation parameters and microbial composition were analyzed after 24 h. HMBi and MHA-Ca showed increased (p = 0.001) cumulative gas production in 3 h. The total volatile fatty acids, microbial protein (MCP) concentration, acetate, and acetate to propionate ratio in the HMBi and MHA-Ca groups were significantly higher than those in the Control group (p = 0.006, p = 0.002, p = 0.001, p = 0.004), and the NH3-N concentrations in the HMBi and MHA-Ca groups were significantly lower than those in the Control group (p = 0.004). The 16S rRNA sequencing revealed that the HMBi group had a higher (p = 0.039, p = 0.001, p = 0.027) relative abundance of Bacteroidetes, Firmicutes, and Synergistetes and a lower relative abundance of Proteobacteria (p = 0.001) than the Control group. At the genus level, Prevotella abundance was higher (p = 0.001), while Ruminobacter abundance was lower (p = 0.001), in the HMBi and MHA-Ca groups than in the Control group. Spearman’s correlation analysis showed that the relative abundance of Prevotella_1, Streptococcus, and Desulfovibrio was positively correlated with dry matter digestibility, MCP, and fermentation parameters. MHA, thus, significantly increased gas production and altered the rumen fermentation parameters and microbiota composition of sheep.
Long-Term Outcomes among Patients with Prolonged Disorders of Consciousness

Purpose: To evaluate the long-term survival and functional outcomes of patients with prolonged disorders of consciousness (pDoC) 1–8 years after brain injuries. Methods: Retrospective study to assess the long-term survival and functional outcomes of patients with pDoC was conducted. We performed Cox regression and multivariate logistic regression to calculate hazard ratios (HRs) for the outcome of survival and to identify risk factors of the functional outcome. Results: We recruited 154 patients with pDoC. The duration of follow-up from disease onset was 1–8 years. The median age was 46 years (IQR, 32–59), and 65.6% (n = 101) of them were men. During the follow-up period, one hundred and ten patients (71.4%) survived; among them, 52 patients had a good outcome. From the overall survival curve, the 1-, 3-, and 8-year survival rates of patients were about 80.5%, 72.0%, and 69.7%, respectively. Cox regression analysis revealed a significant association between the lower APACHE II score (p = 0.005) (cut-off score ≥ 18) and the presence of sleep spindles (p = 0.001) with survival. Logistic regression analysis demonstrated a higher CRS-R score (cut-off score ≥ 7), and presence of sleep spindles were related to a favorable outcome among patients with pDoC. Conclusions: Sleep spindles are correlated with both long-term survival and long-term functional outcome in pDoC patients.
Association of Individual and Neighborhood Characteristics to Problematic Internet Use among Youths and Adolescents: Evidence from Vietnam

Introduction: This study aimed to determine latent profiles from the Problematic Internet Use Questionnaire Short Form-6 (PIUQ-SF-6) score of Vietnamese youths and adolescents, which supports the diagnosis of problematic internet use among a large sample size. Moreover, it also explored factors that affect each latent profile of the PIUQ-SF-6 score among participants. Methods: A sample of 1477 Vietnamese people, aged 14 to 24, across five provinces participated in the study. Multinomial logistic regression determined factors related to the levels of the Problematic Internet Use Questionnaire Short Form-6 (PIUQ-SF-6) after using latent profile analysis. Results: Participants were divided into three profiles, including those at low, moderate, and high risk of internet addiction. The high-risk latent profile was obtained for 23.1% of adolescents, and the remaining percentages were, respectively, 40.2% and 36.7% of adolescents belonging to the moderate and low-risk groups. Moreover, factors including age, living alone, high Kessler psychological distress scale, excessive time on the internet, living in central cities, and high neighborhood disorder scores were found to be related to moderate- and high-risk internet addiction profiles. Conclusions: Factors analyzed according to individual and social characteristics further explore the reasons underlying increasing internet addiction among Vietnamese youths and inform early interventions.
Endothelial Cell Phenotypes Demonstrate Different Metabolic Patterns and Predict Mortality in Trauma Patients

In trauma patients, shock-induced endotheliopathy (SHINE) is associated with a poor prognosis. We have previously identified four metabolic phenotypes in a small cohort of trauma patients (N = 20) and displayed the intracellular metabolic profile of the endothelial cell by integrating quantified plasma metabolomic profiles into a genome-scale metabolic model (iEC-GEM). A retrospective observational study of 99 trauma patients admitted to a Level 1 Trauma Center. Mass spectrometry was conducted on admission samples of plasma metabolites. Quantified metabolites were analyzed by computational network analysis of the iEC-GEM. Four plasma metabolic phenotypes (A–D) were identified, of which phenotype D was associated with an increased injury severity score (p < 0.001); 90% (91.6%) of the patients who died within 72 h possessed this phenotype. The inferred EC metabolic patterns were found to be different between phenotype A and D. Phenotype D was unable to maintain adequate redox homeostasis. We confirm that trauma patients presented four metabolic phenotypes at admission. Phenotype D was associated with increased mortality. Different EC metabolic patterns were identified between phenotypes A and D, and the inability to maintain adequate redox balance may be linked to the high mortality.
Uncooled 100-GBaud Directly Modulated Membrane Lasers on SiC Substrate

We investigate the temperature dependence of the dynamic characteristics of a 1.3-μm InGaAlAs-based directly modulated membrane laser on a SiC substrate. The laser is fabricated by combining direct wafer bonding of SiC and InP substrates using a very thin (∼10 nm) oxide layer and epitaxial regrowth of a membrane InP layer on the InP/SiC template. The membrane laser structure on SiC with a high thermal conductivity (490 Wm−1K−1) and a moderate refractive index (∼2.6) ensures both high thermal dissipation and a large optical confinement factor in the active region, which are ideal for increasing the relaxation oscillation frequency even at high operating temperatures. We further leverage the optical feedback effect from the output facet of a waveguide to enhance the bandwidth and enable signal modulation at 100 GBaud and beyond. Owing to the high relaxation oscillation frequency and the photon-photon resonance effect, it is possible to obtain a flat frequency response at temperatures ranging from 25 to 85 °C. The fabricated membrane laser on SiC with an active-region length of 50 μm exhibits 3 dB bandwidths of >110, 97, and 74 GHz at 25, 55, and 85 °C, respectively. We successfully demonstrate 2-km transmissions of 100-Gbit/s NRZ signals under uncooled conditions (25 to 85 °C). Furthermore, the laser is capable of 112-Gbit/s NRZ modulation at 85 °C.