Miracle-dz/UniFAR-FTUs huggingface dataset:
Local energy-based image region segmentation using Legendre polynomials

Abstract. Segmentation of images is a critical pre-processing step in image processing. The objective of segmentation is to divide an image into two homogeneous segments based on similar features. Recently, energy-based segmentation methods, such as the level set algorithm, have exhibited remarkable performance in segmenting various types of image data. However, such methods fail to produce satisfactory results on textured images, leading to inaccurate foreground and background segmentation. To address this issue, the proposed method utilizes a feature space based on image local energy, which is independent of image intensity. This feature space provides a more robust representation of texture in the image. By taking advantage of a unique feature space, images can be represented with a sum of Legendre polynomials. The reproduced image is injected into the L2S algorithm. The level set function is optimized from the average difference of Legendre polynomial coefficients to provide the best representation of the image. Consequently, the proposed method results in better segmentation accuracy, with an average increase of 19.33 compared to existing state-of-the-art methods.
Energy Availability and Nutritional Intake during Different Training Phases of Wheelchair Athletes

Optimizing nutritional intake and timing helps athletes to improve performance and long-term health. Different training phases can require varying nutritional needs. In this study, we conducted a descriptive assessment of dietary intake, energy availability (EA), and blood biochemical parameters in elite wheelchair athletes during distinct training phases. Data analyzed in this study were collected as part of a randomized controlled crossover trial exploring the feasibility of probiotics and prebiotic supplementation. Data were obtained from consecutive three-day diaries and blood samples, both collected at four different time points across four consecutive months. We included 14 athletes (mean (standard deviation) age 34 (9) years, eight females, and six males) active in different wheelchair sports. The mean daily nutritional intake (g/kg body mass) for females and males was 2.7 (0.9) and 4.0 (0.7) for carbohydrates, 1.1 (0.3) and 1.5 (0.3) for protein, and 0.8 (0.3) and 1.4 (0.2) for fat. EA did not change across the four time points in either female (p = 0.30) or male (p = 0.05) athletes. The mean EA was lower in female athletes compared to male athletes (p = 0.03). Low EA (≤30 kcal/ kg fat-free mass/day) was observed in female (58 (29) % of days) and male (34 (23) % of days) athletes. Iron deficiency with anemia was observed in two female athletes. Mean vitamin D levels were insufficient (<75 nmol/L). Macronutrient intake, EA, and blood biochemical parameters were suboptimal in this cohort of elite wheelchair athletes, especially in female athletes.
3-D Objects Detection and Tracking Using Solid-State LiDAR and RGB Camera

Objects detection and tracking using 3-D LiDAR has gained momentum lately while it has not been extensively applied, and the main challenge is that conventional mechanical LiDAR is expensive and it is difficult for single sensor to obtain good tracking performance over a long period of time. In this article, we propose a multisensor fusion 3-D objects detection and tracking framework using solid-state LiDAR and RGB camera. We use a low-cost solid-state LiDAR with irregular scan pattern and propose a universal clustering method which determines the searching radius by laser density and range. To improve the overall tracking performance, range and visual information are both utilized to associate 3-D objects across different frames. We avoid introducing odometry errors into the system and use visual difference rather than estimated trajectory to distinguish between closely located objects. And we have designed a re-detection process to locate objects that were missed by the clustering algorithm. We evaluated the proposed method on five sequences captured by our ego-vehicle and three additional sequences from open-source datasets. Our results demonstrate that the adaptive searching radius enhances recall and the overall tracking performance is improved by fusing LiDAR and camera.
Preparation of a Molecularly Imprinted Silica Nanoparticles Embedded Microfiltration Membrane for Selective Separation of Tetrabromobisphenol A from Water

The ubiquitous presence of tetrabromobisphenol A (TBBPA) in aquatic environments has caused severe environmental and public health concerns; it is therefore of great significance to develop effective techniques to remove this compound from contaminated waters. Herein, a TBBPA imprinted membrane was successfully fabricated via incorporating imprinted silica nanoparticles (SiO2 NPs). The TBBPA imprinted layer was synthesized on the 3-(methacryloyloxy) propyltrimethoxysilane (KH-570) modified SiO2 NPs via surface imprinting. Eluted TBBPA molecularly imprinted nanoparticles (E-TBBPA-MINs) were incorporated onto a polyvinylidene difluoride (PVDF) microfiltration membrane via vacuum-assisted filtration. The obtained E-TBBPA-MINs embedded membrane (E-TBBPA-MIM) showed appreciable permeation selectivity toward the structurally analogous to TBBPA (i.e., 6.74, 5.24 and 6.31 of the permselectivity factors for p-tert-butylphenol (BP), bisphenol A (BPA) and 4,4′-dihydroxybiphenyl (DDBP), respectively), far superior to the non-imprinted membrane (i.e., 1.47, 1.17 and 1.56 for BP, BPA and DDBP, respectively). The permselectivity mechanism of E-TBBPA-MIM could be attributed to the specific chemical adsorption and spatial complementation of TBBPA molecules by the imprinted cavities. The resulting E-TBBPA-MIM exhibited good stability after five adsorption/desorption cycles. The findings of this study validated the feasibility of developing nanoparticles embedded molecularly imprinted membrane for efficient separation and removal of TBBPA from water.
Low-frequency trapping phenomena in AlSb/InAs HEMTs

Low-frequency trapping effects in AlSb/InAs/GaAs HEMTs were examined by measuring the transconductance in the frequency range from 1 Hz to 100 KHz. Several device variations with differing cap layers and doping techniques were compared. By varying the bias and temperature, information on the physical location and trap parameters was obtained. A level with an activation energy of 0.12 eV and associated with the AlSb or its interfaces was found. Several other levels associated with different cap layers were also observed.
The Glutamate Dependence Hypothesis May Explain Overeating Browned Food Only and the Worldwide Heart Disease Pandemic

The following study tried to determine whether Maillard reaction end product-embodied food is significantly more alluring, rewarding, addictive, and cardiovascular taxing than Maillard reaction end product-free meals. As importantly, does Maillard end product-containing fare exhibit more tolerance measured by increased total calorie consumption per day, progression measured by rising amounts of overweight, and withdrawal measured by more frequent urges to snack and dine than Maillard reaction end product-free provisions? The data presented here suggests an intimate association between dietary Maillard-reaction end product-induced glutamate dependence, overeating browned food only, and cardiovascular disease. Phosphorous and glutamate-prompted redox imbalance, hyperlipidemia, immune system activation, chronic inflammatory disease, vascular calcification, hypertension, ischemic heart disease, atrial fibrillation, and stroke may be symptoms of Glutamate dependence.
Asymptotically Efficient Estimator for Range-Based Robot Relative Localization

This study investigates the 2-D relative localization problem, which estimates the relative orientation and position between two moving robots using inter-robot range measurements. We propose a novel formulation and a robust weighted semidefinite relaxation solution for the relative localization problem in the presence of range measurement error and robot state transition error. Theoretical analysis and simulations show that the weighted semidefinite relaxation solution achieves Cramér–Rao lower bound performance when the measurement noise and the odometry uncertainty follow Gaussian distributions with moderate noise power. Demonstrations using data from a laboratory environment validate the promising and robust performance of the weighted semidefinite relaxation method. The root-mean-square errors in estimating the orientation and position are $3.97^\circ$ and 0.22 m with affordable hardware.
Permission analysis based on android app store

As the number of users using Android continues to grow, the Android app market is becoming the dominant platform in the smartphone market and the correct use of Android app permissions is one of the key factors in the success of Android apps. When installing or running their apps, users need to agree to these permission requests. However, in practice, despite the Android platform introducing official documentation on how to use these permissions properly, there are still many cases of permission abuse. The average user does not have any tools to detect excessive permissions in apps, so most users grant any permissions declared by the app, which exacerbates the risk of private information leakage. Although some previous studies have attempted to address the issue of granting excessive privileges, their methods are now inapplicable due to advances in app protection technology and updates to the Android system. Most existing permission testing techniques are generally based on application development documentation or user decision feedback data, but application development documentation is generally missing, incomplete in description and unreliable in user behaviour data mainly due to its large number of irrelevant characters and non-standardised language text. Many misuses have been reported, and these occur even for the most popular permissions This paper presents a static analysis of permissions based on the classification of apps in the Android App Store.
Rational Structure of Multi-Layer Artificial Neural Network

Selecting rational hidden structure is very important question on multilayer neural network in application. Applying optimum algorithm of neural network and algebra equation theory, nonlinear equations expressing the relationships between computing output and ideal output of neural network were developed. The immanent connection of weights and threshold variables, standard sample numbers and node numbers of output layer are suggested. Hidden structure basis equation is given. A kind of analyzing method of rational construct of multilayer neural network is proposed. Direct and indirect computing method were studied to compute quantitatively the numbers of hidden layers and the unit numbers per hidden layer. The analysis validity was showed through comparison of rational structure with various possible structures of neural network examples. 
A Novel Adaptive Spectral Drift Correction Method for Recalibrating the MarSCoDe LIBS Data in China's Tianwen-1 Mars Mission

The Tianwen-1 mission, China's first interplanetary endeavor and Mars mission, touched the surface of the Red Planet on May 15, 2021. With the successful landing of the Zhurong rover on the southern Utopian Planitia of Mars, the Mars Surface Composition Detector (MarSCoDe) on board the rover has started to analyze the material composition of the Martian surface by using the laser-induced breakdown spectroscopy (LIBS). However, changes in instrument temperature and external environment during operation will cause spectral drift in LIBS data, leading to inaccurate material composition inversion results due to shifts in elemental characteristic peak positions. To address this problem, an adaptive spectral drift correction (ASDC) approach is proposed. By considering the distribution of characteristic peaks and drift differences between different elements, the proposed ASDC method corrects the spectral drift in LIBS science data according to an adaptive spectral segmentation strategy. Experimental results obtained on 36 real LIBS science data acquired over 19 exploration activities confirmed the effectiveness of the proposed approach in terms of lower average drift values, by comparing it with two reference methods. Taking the onboard calibration data as a reference, the average spectral drift values of the LIBS science data before and after applying ASDC decreased from 0.1012 nm to 0.0179 nm, 0.0926 nm to 0.0158 nm, and 0.1697 nm to 0.0103 nm in three LIBS channels, respectively. Furthermore, the resulting decrease in the standard deviation and rms error of the average drift values also proved the robustness of the proposed method.
Rewilding giant tortoises engineers plant communities at local to landscape scales

Trophic rewilding is increasingly being used to promote megafauna reintroductions to island ecosystems, yet ecosystem response to population restoration once megafauna reintroduction occurs remains understudied. In this study of a population of Galapagos giant tortoises reintroduced to an arid island, tortoise exclosures monitored over an 8‐year‐long period revealed that, in response to the presence of tortoises, herbaceous plant cover and numbers of regenerating woody plants decreased, whereas extent of grass cover increased. Vegetation mapping over a 15‐year‐long period across the island indicated a threshold density of 1–2 tortoises per hectare halted incursion of woody plants and triggered a shift in this savannah‐type ecosystem toward more grasses. Restoration of this giant tortoise population has shaped plant communities at both local and landscape scales with cascading effects on many components of biodiversity on the island.
Role of artificial intelligence based image-processing techniques for port development activities in physical tidal models

ABSTRACT The Cochin Port physical tidal model available at Central Water and Power Research Station (CWPRS), Ministry of Jal Shakti, Government of India, is used to simulate the tidal conditions of real-time Cochin Port. Analysis of physical tidal model takes time and requires specialised knowledge in order to analyse and identify the velocity profile through manual instrumentation. The use of artificial intelligence (AI) based image processing techniques may reduce the analysis time and improve the accuracy of physical tidal model. An attempt was made to determine the velocity profile of Cochin Port model (scaled down model) at CWPRS through AI-based video image-processing analysis using MATLAB. Based on the analysis, it was observed that magnitude of horizontal velocity is varying for 1579 times in about 30.36 sec duration from 0.01156 m/s to 0.32986 m/s with a mean velocity magnitude of about 0.20357 m/s. The results indicated that digital videography-based image processing approach with the assistance of trained AI algorithms gives the précised velocity profile having 578 unique magnitude variations out of 1579 readings in 30.36 sec, which is far better than the manual instrumentation, and therefore, manual instrumentation may be substituted with the developed artificial intelligence (AI) based image processing technique.
A slope filtering method for point cloud of dense vegetation terrain based on airborne LiDAR

In order to obtain the real ground point cloud, it is necessary to filter the original point cloud data to remove the non ground points. In the subtropical evergreen broad-leaved forest belt, the vegetation is dense, and the ground points are seriously sheltered. The ground points and non ground points are staggered. According to the characteristics of point clouds in the natural belt of the study area, this paper proposes a slope filtering method for dense vegetation terrain point clouds of airborne LiDAR. First, the virtual grid is introduced to segment the point cloud data, and the grid index of each point is calculated; Then calculate the elevation of the lowest point in each grid to calculate the height difference between each point and the lowest point in each grid. Then, the slope values of all points in each grid are obtained, and the local slope statistics are carried out to calculate the slope threshold; Finally, ground point filtering is carried out according to the adaptive slope threshold obtained by preset height difference threshold, k-means clustering and normal distribution. The flat terrain area and undulating terrain area are used for experimental analysis respectively. The results show that this method solves the problem of dense filtering of non surface points, and can not only remove dense vegetation but also retain terrain details.
Tracheal hemangioma: a case report and literature review

Introduction and importance: Hemangiomas are the most common vascular tumors in children. Although hemangiomas are common, they are rarely seen in areas like the trachea and larynx.The most common clinical manifestations in tracheal hemangiomas are stridor and respiratory distress. The main diagnostic method is bronchoscopy. Other imaging techniques like computed tomography scans and MRIs are also helpful. Various treatment options are now used for treating the disease, including beta blockers like propranolol, local and systemic steroids, and surgical resection. Case presentation: An 8-year-old boy with the chief complaint of severe progressive dyspnea and a history of neonatal postbreastfeeding cyanosis was admitted. On physical examination, he had tachypnea, and stridor was heard upon auscultation. There was no history of fever, chest pain, or coughing. He underwent a rigid bronchoscopy followed by a neck computed tomography scan. The results indicated a soft tissue mass with a vascular nature. An MRI of the neck confirmed the diagnosis of tracheal hemangioma. The mass was not resectable during surgery; hence, angioembolization was carried out. Treatment was successful and there was no recurrence on the follow-up. Clinical discussion: Based on the findings in this literature review tracheal hemangiomas present with stridor, progressive respiratory distress, dyspnea, hemoptysis, and chronic coughs. Advanced tracheal hemangiomas commonly do not reduce in size by themselves and need treatment. A close follow-up ranging from 3 months to 1 year is recommended. Conclusion: Although tracheal hemangiomas are rare they should be considered in the differential diagnosis of severe dyspnea and stridor.
Temporal Coordination and Markedness in Moenat Ladin Consonant Clusters

In this paper we examine the phonotactics of consonant clusters in Moenat Ladin in terms of their markedness and temporal coordination. Moenat Ladin word-initial clusters include sibilant-stop (SC), stop-/r/ (Cr), stop-/l/ (Cl), and sibilant-stop-/r/ (SCr). However, despite SC and Cl sequences being well-formed in Moenat, sibilant-stop-/l/ (SCl) clusters are almost entirely unattested. We hypothesize that the rarity of SCl clusters owes to a cumulative markedness effect that arises from the combination of marked structures involved in SC and Cl sequences. Our investigation centers chiefly on the status of word-initial SC sequences in Moenat Ladin, for which we hypothesize that the sibilant is organized external to the syllable onset. This hypothesis is supported by an acoustic study of temporal coordination of Moenat, employing the methodology of Ruthan et al. (2019) and Durvasula et al. (2021). We propose a formal account in Harmonic Grammar (Legendre et al. 1990) such that SCl clusters exceed a markedness threshold in contrast to permissible clusters. In this account we employ a model of phonotactics in which a phonotactically non-permissible cluster is modeled as selection of the null parse (e.g. Albright 2008, 2012, Breiss & Albright 2022).
Temporal relaxation of plasma electrons acted upon by direct current electric and magnetic fields

On the basis of the time-dependent electron Boltzmann equation the temporal relaxation of the electrons in the presence of electric and magnetic fields in weakly ionized, collision dominated plasmas has been studied. The relaxation process is treated by using a strict time-dependent two-term approximation of the velocity distribution function expansion in spherical harmonics. A new technique for solving the time-dependent electron kinetic equation in this two-term approximation for arbitrary angles between the electric and magnetic fields has been developed and the main aspects of the efficient solution method are presented. Using this new approach and starting from steady-state plasmas under the action of time-independent electric fields only, the impact of superimposed DC magnetic fields on the electron relaxation is analyzed with regard to the control of a neon plasma. The investigations reveal an important effect of the magnetic field on the temporal relaxation process. In particular, it has been found that the relaxation time of the electron component with respect to the establishment of steady-state can be enlarged by some orders of magnitude when increasing the magnetic field strength.
Solution of small sample size problem in face recognition using Gabor wavelet transform

A novel algorithm for solving the small sample size problem in face recognition is proposed.The size of each face sample is increased greatly and the small sample size problem is resolved by regarding every Gabor wavelet transformed output image as an independent sample.A special nearest neighbor classifier using whitened cosine distance is designed for the classification of face feature vector groups.The experiments comparing the prosposed approach with the direct PCA method in FERET face database show that the average correct face recognition rate of the proposed algorithm can reach 97%,which is superior to the direct PCA method.
The Effect of Regional Genuine Income, Profit-Sharing Funds, General Allocation Funds, and Budget Return Calculations on Official Travel Expenditure

This study examines the effect of Regional Own Revenue, Profit Sharing Funds, General Allocation Funds, and the excess budget calculations on Official Travel Expenditures for District/City Governments in Aceh Province from 2016 to 2019. The type of research used is hypothesis testing. The total research sample for regional/city governments in Aceh Province is 23 regional/city governments. The study used secondary data from LRAs of 92 documents in LKPD for the 2016 to 2019 Fiscal Year (Audited) in 23 districts/City Governments in Aceh Province and analyzed using multiple linear regression analysis. The results show that (1) PAD has no effect on Business Travel Expenditure, (2) DBH influences Business Travel Expenditure, (3) DAU influences Business Travel Expenditure, (4) SiLPA influences Business Travel Expenditure, and (5) PAD, DBH, DAU and SiLPA jointly influence Official Travel Expenditures. So that this research has implications for adding insight to District/City Governments in Aceh Province about the factors that contribute to Official Travel Expenditures and Helps improve accountability and transparency of budget use in official travel.