Miracle-dz/UniFAR-FTUs huggingface dataset:
Image Processing Technology in Emission of Intelligent Traffic Diesel Vehicle

: Traditional smoke measurement methods for diesel vehicles mainly include Lingman blackness telescope and smoke meter. The Lingman Blackness Telescope uses a binocular prism telescope system. On the telescope partition board, a gray scale step block with corresponding Lingman smoke concentration of 1-5 level is made, and the transparent part is O level. The observer compares the smoke target with the gray gradient block through the left eyepiece of the telescope to determine the standard grade of smoke blackness. Smoke is divided into sampling part and measuring part. In the sampling part, the sampling cylinder extracts a certain volume of smoke from the exhaust pipe so that it passes through a certain area of white filter paper, so the particulate matter in the exhaust gas adheres to the filter paper and makes the filter paper black. Then, the smoke traces on the filter paper are measured by photoelectric detection device to evaluate the exhaust smoke of diesel engine. The above method can measure the smoke level of diesel vehicle exhaust to a certain extent, but it has great application limitations in practice, or cannot be applied in practice. For example, (I) Although the level of diesel vehicle exhaust smoke can be measured with the Lingman blackness telescope, it cannot record the level of diesel vehicle exhaust smoke and the relevant information of the vehicle; (2) The Lingman blackness telescope must be measured manually. It is time-consuming and laborious, and it is impossible for traffic police to observe every vehicle 24 hours with Lingman blackness telescope; (3) Smokemeter can only measure static diesel vehicles, but cannot measure driving vehicles. In view of the above problems, this paper introduces digital image processing technology, through the analysis of digital image of diesel vehicle exhaust, realizes the dynamic detection of diesel vehicle exhaust.
Dynamic Target Tracking of Autonomous Underwater Vehicle Based on Deep Reinforcement Learning

Due to the unknown motion model and the complexity of the environment, the problem of target tracking for autonomous underwater vehicles (AUVs) became one of the major difficulties in model-based controllers. Therefore, the target tracking task of AUV is modeled as a Markov decision process (MDP) with unknown state transition probabilities. Based on actor–critic framework and experience replay technique, a model-free reinforcement learning algorithm is proposed to realize the dynamic target tracking of AUVs. In order to improve the performance of the algorithm, an adaptive experience replay scheme is further proposed. Specifically, the proposed algorithm utilizes the experience replay buffer to store and disrupt the samples, so that the time series samples can be used for training the neural network. Then, the sample priority is arranged according to the temporal difference error, while the adaptive parameters are introduced in the sample priority calculation, thus improving the experience replay rules. The results confirm the quick and stable learning of the proposed algorithm, when tracking the dynamic targets in various motion states. Additionally, the results also demonstrate good control performance regarding both stability and computational complexity, thus indicating the effectiveness of the proposed algorithm in target tracking tasks.
Development and validation of radiomics machine learning model based on contrast-enhanced computed tomography to predict axillary lymph node metastasis in breast cancer

Preoperative identification of axillary lymph node metastasis can play an important role in treatment selection strategy and prognosis evaluation. This study aimed to establish a clinical nomogram based on lymph node images to predict lymph node metastasis in breast cancer patients. A total of 193 patients with non-specific invasive breast cancer were divided into training (n ═ 135) and validation set (n ═ 58). Radiomics features were extracted from lymph node images instead of tumor region, and the least absolute shrinkage and selection operator logistic algorithm was used to select the extracted features and generate radiomics score. Then, the important clinical factors and radiomics score were integrated into a nomogram. A receiver operating characteristic curve was used to evaluate the nomogram, and the clinical benefit of using the nomogram was evaluated by decision curve analysis. We found that clinical N stage and radiomics score were independent clinical predictors. Besides, the nomogram accurately predicted axillary lymph node metastasis, yielding an area under the receiver operating characteristic curve of 0.95 (95% confidence interval 0.93–0.98) in the validation set, indicating satisfactory calibration. Decision curve analysis confirmed that the nomogram had higher clinical utility than clinical N stage or radiomics score alone. Overall, the nomogram based on radiomics features and clinical factors can help radiologists to predict axillary lymph node metastasis preoperatively and provide valuable information for individual treatment.
Relationships between Plasma Concentrations of Testosterone and Dihydrotestosterone and Geriatric Depression Scale Scores in Men and Women Aged 60–65 Years—A Multivariate Approach with the Use of Quade’s Test

The potential role of testosterone and dihydrotestosterone in the pathogenesis of depression in older subjects is poorly recognized and understood. The current study examines the symptoms of depression in males and females at the age of 60–65 using a short version (15 questions) of the Geriatric Depression Scale (GDS) questionnaire. Blood plasma levels of androgens were estimated by LC/MS/MS. Total GDS score calculated for males were not found to be significantly associated with plasma levels of testosterone or dihydrotestosterone. Older men with higher plasma testosteronemia were more likely to report being in good spirits most of the time, but more willing to stay at home than undertake outside activities. The men with higher plasma levels of dihydrotestosterone also perceived themselves as being in good spirits most of the time. Older men with higher testosterone were more likely to report having more problems with their memory than others. No significant associations were found between plasma levels of androgens and GDS scores in older women; however, some tendencies suggest that testosterone and dihydrotestosterone may act as antidepressants in older women.
Fundamentals of Nonlinear Digital Filtering

Nonlinear Signal Processing Signal Processing Model Signal and Noise Models Fundamental Problems in Noise Removal Algorithms Statistical Preliminaries Random Variables and Distributions Signal and Noise Models Estimation Some Useful Distributions 1001 Solutions Trimmed Mean Filters Other Trimmed Mean Filters L-Filters C-Filters (Ll-Filters) Weighted Median Filters Ranked-Order and Weighted Order Statistic Filters Multistage Median Filters Median Hybrid Filters Edge-Enhancing Selective Filters Rank Selection Filters M-Filters R-Filters Weighted Majority with Minimum Range Filters Nonlinear Mean Filters Stack Filters Generalizations of Stack Filters Morphological Filters Soft Morphological Filters Polynomial Filters Data-Dependent Filters Decision-Based Filters Iterative, Cascaded, and Recursive Filters Some Numerical Measures of Nonlinear Filters Discussion Statistical Analysis and Optimization of Nonlinear Filters Methods Based on Order Statistics Stack Filters Multistage and Hybrid Filters Discussion Exercises Bibliography Index
A POPULATION OF NON-RECYCLED PULSARS ORIGINATING IN GLOBULAR CLUSTERS

We explore the enigmatic population of long-period, apparently non-recycled pulsars in globular clusters, building on recent work by Boyles et al. This population is difficult to explain if it formed through typical core-collapse supernovae, leading many authors to invoke electron capture supernovae. While Boyles et al. dealt only with non-recycled pulsars in clusters, we focus on the pulsars that originated in clusters but then escaped into the field of the Galaxy due to the kicks they receive at birth. The magnitude of the kick induced by electron capture supernovae is not well known, so we explore various models for the kick velocity distribution and size of the population. The most realistic models are those where the kick velocity is ≲ 10 km s−1 and where the number of pulsars scales with the luminosity of the cluster (as a proxy for cluster mass). This is in good agreement with other estimates of the electron capture supernovae kick velocity. We simulate a number of large-area pulsar surveys to determine if a population of pulsars originating in clusters could be identified as being separate from normal disk pulsars. We find that the spatial and kinematical properties of the population could be used, but only if large numbers of pulsars are detected. In fact, even the most optimistic surveys carried out with the future Square Kilometer Array are likely to detect <10% of the total population, so the prospects for identifying these as a separate group of pulsars are presently poor.
Challenges facing interventions to promote equity in the early years: exploring the ‘impact’, legacy and lessons learned from a national evaluation of Children’s Centres in England

ABSTRACT This paper discusses the challenges facing a national evaluation of an early years intervention programme, Sure Start Children’s Centres (SSCCs), that was implemented across England in the first decade of the 21st century. The paper describes the rationale for the evaluation’s mixed methods research design and the ecological theoretical approach adopted. It investigates the SSCC policy aim of combatting the ‘impact’ of multiple disadvantage on outcomes for families, parents and children. Based on a clustered sample (2,600 families) it provides evidence of statistical effects for different user groups, including non-users. It points to the complexities in evaluation in non-experimental interventions where there was an emphasis on services to meet local needs and where families could choose which services to access and change patterns of service use over time. The paper synthesises findings and considers how complex, volatile and uncertain environments affected SSCC provision, particularly linked to a change of government and austerity policies after 2010. The paper identifies lessons learned, explores implications for future early years interventions in uncertain times, and proposes alternative approaches to evaluation (a realist approach based on mixed methods and theoretically driven models) where randomised experimental designs are inappropriate for the evaluation of certain complex policies.
Quantum weak coin flipping with arbitrarily small bias

“God does not play dice. He flips coins instead. ” And though for some reason He has denied us quantum bit commitment. And though for some reason he has even denied us strong coin flipping. He has, in His infinite mercy, granted us quantum weak coin flipping so that we too may flip coins. Instructions for the flipping of coins are contained herein. But be warned! Only those who have mastered Kitaev’s formalism relating coin flipping and operator monotone functions may succeed. For those foolhardy enough to even try, a complete tutorial is included.
RELATIONS BETWEEN CENTRAL BLACK HOLE MASS AND TOTAL GALAXY STELLAR MASS IN THE LOCAL UNIVERSE

Scaling relations between central black hole (BH) mass and host galaxy properties are of fundamental importance to studies of BH and galaxy evolution throughout cosmic time. Here we investigate the relationship between BH mass and host galaxy total stellar mass using a sample of 262 broad-line active galactic nuclei (AGNs) in the nearby universe (z < 0.055), as well as 79 galaxies with dynamical BH masses. The vast majority of our AGN sample is constructed using Sloan Digital Sky Survey spectroscopy and searching for Seyfert-like narrow-line ratios and broad Hα emission. BH masses are estimated using standard virial techniques. We also include a small number of dwarf galaxies with total stellar masses Mstellar ≲ 109.5 M⊙ and a subsample of the reverberation-mapped AGNs. Total stellar masses of all 341 galaxies are calculated in the most consistent manner feasible using color-dependent mass-to-light ratios. We find a clear correlation between BH mass and total stellar mass for the AGN host galaxies, with MBH ∝ Mstellar, similar to that of early-type galaxies with dynamically detected BHs. However, the relation defined by the AGNs has a normalization that is lower by more than an order of magnitude, with a BH-to-total stellar mass fraction of MBH/Mstellar ∼ 0.025% across the stellar mass range 108 ≤ Mstellar/M⊙ ≤ 1012. This result has significant implications for studies at high redshift and cosmological simulations in which stellar bulges cannot be resolved.
From constructive field theory to fractional stochastic calculus. (I) The Lévy area of fractional Brownian motion with Hurst index $\alpha\in (1/8,1/4)$

Let $B=(B_1(t),\ldots,B_d(t))$ be a $d$-dimensional fractional Brownian motion with Hurst index $\alpha<1/4$. Defining properly iterated integrals of $B$ is a difficult task because of the low Holder regularity index of its paths. Yet rough path theory shows it is the key to the construction of a stochastic calculus with respect to $B$, or to solving differential equations driven by $B$. We show in this paper how to obtain second-order iterated integrals as the limit when the ultra-violet cut-off goes to infinity of iterated integrals of weakly interacting fields defined using the tools of constructive field theory, in particular, cluster expansion and renormalization. The construction extends to a large class of Gaussian fields with the same short-distance behaviour, called multi-scale Gaussian fields. Previous constructions \cite{Unt-Holder,Unt-fBm} were of algebraic nature and did not provide such a limiting procedure.
Land Use and Land Cover Mapping in the Era of Big Data

We are currently living in the era of big data. The volume of collected or archived geospatial data for land use and land cover (LULC) mapping including remotely sensed satellite imagery and auxiliary geospatial datasets is increasing. Innovative machine learning, deep learning algorithms, and cutting-edge cloud computing have also recently been developed. While new opportunities are provided by these geospatial big data and advanced computer technologies for LULC mapping, challenges also emerge for LULC mapping from using these geospatial big data. This article summarizes the review studies and research progress in remote sensing, machine learning, deep learning, and geospatial big data for LULC mapping since 2015. We identified the opportunities, challenges, and future directions of using geospatial big data for LULC mapping. More research needs to be performed for improved LULC mapping at large scales.
Sex difference in the association between pathological albuminuria and subclinical atherosclerosis: insights from the I-Lan longitudinal aging study

Background: Pathological albuminuria (PAU) (urinary albumin creatinine ratio [UACR] ≥30 mg/g) is an independent risk factor of cardiovascular disease. PAU is more prevalent in men than women. We aimed to compare the association of PAU and the early phase of subclinical atherosclerosis (SA) between sexes. Methods: 1228 subjects aged 50–90 years were stratified by sex and UACR (normal or PAU). SA was defined as mean carotid intima-media thickness ≥75th percentile of the cohort. Demographics and SA prevalence were compared between groups. Multivariate logistic regression was performed to assess the relationship between PAU and SA. Results: Both men and women with PAU had increased prevalence of hypertension, anti-hypertensive therapy, and metabolic syndrome than controls. Men with PAU were older and had greater waist circumference and total body fat percentage. Sex disparity was observed in associations between waist-to-height ratio, total body fat, and UACR. After adjusting for traditional risk factors, multivariate logistic regression disclosed that PAU was independently associated with SA in men (adjusted odds ratio 1.867, 95% CI 1.066–3.210) but not in women. Conclusion: The relationship of PAU and SA differed between sexes. This result may highlight the need for sex-specific risk management strategies to prevent atherosclerosis.
Targeted approaches to improve tomato fruit taste

Abstract Tomato (Solanum lycopersicum) is the most valuable fruit and horticultural crop species worldwide. Compared with the fruits of their progenitors, those of modern tomato cultivars are, however, often described as having unsatisfactory taste or lacking flavor. The flavor of a tomato fruit arises from a complex mix of tastes and volatile metabolites, including sugars, acids, amino acids, and various volatiles. However, considerable differences in fruit flavor occur among tomato varieties, resulting in mixed consumer experiences. While tomato breeding has traditionally been driven by the desire for continual increases in yield and the introduction of traits that provide a long shelf-life, consumers are prepared to pay a reasonable premium for taste. Therefore, it is necessary to characterize preferences of tomato flavor and to define its underlying genetic basis. Here, we review recent conceptual and technological advances that have rendered this more feasible, including multi-omics-based QTL and association analyses, along with the use of trained testing panels, and machine learning approaches. This review proposes how the comprehensive datasets compiled to date could allow a precise rational design of tomato germplasm resources with improved organoleptic quality for the future.
Energy dependence of normal branch oscillations in Scorpius X-1

We report the energy dependence of normal branch oscillations (NBOs) in Scorpius X-1, a low-mass X-ray binary Z-source. Three characteristic quantities (centroid frequency, quality factor, and fractional root-mean-squared (rms) amplitude) of a quasi-periodic oscillation signal as functions of photon energy are investigated. We found that, although it is not yet statistically well established, there is a signature indicating that the NBO centroid frequency decreases with increasing photon energy when it is below 6− 8k eV, which turns out to be positively correlated with the photon energy at the higher energy side. In addition, the rms amplitude increases significantly with the photon energy below 13 keV and then decreases in the energy band of 13−20 keV. There is no clear dependence on photon energy for the quality factor. Based on these results, we suggest that the NBO originates mainly in the transition layer.
EtWExplorer: Multi-Priority Scheduling Path Exploration Technology Based on Abstract Syntax Tree Analysis

Symbolic execution is well known as a dynamic vulnerability discovery technique. Its greatest advantage is the capability to analyze the execution information of the program and to explore the path in the program deterministically. This is a more accurate way to determine if there are vulnerabilities in a program than randomized testing by fuzzing. In addition, symbolic execution does not suffer from the problem of decreasing the capability to discover new paths as more paths are discovered, similar to that caused by random-based fuzzing. However, the reason why symbolic execution is not widely used in vulnerability discovery is mainly due to the state space explosion in the program. The state space explosion severely affects the applicability of symbolic execution. To further improve the applicability of symbolic execution, this paper proposes a path exploration technology based on abstract syntax tree analysis. With the distance between the expression generated by the symbolic execution of the repeat location and the “unsatisfiable” condition of the “unsat” state, we can perform multi-priority scheduling for the repeat location state, thus mitigating the impact of the state space explosion on path exploration. We proposed and implemented EtWExplorer, a multi-priority scheduling technique based on abstract syntax tree analysis. With this technique, we can significantly improve the capability of symbolic execution to discover unknown paths even in state space exploration. Experiments show that EtWExplorer introduces a performance overhead of 72% in the worst case and can improve performance by 294% in the best case. EtWExplorer has a 95% improvement in state space explosion mitigation capability and a 199% to 983% improvement in the path exploration capability of block coverage and a 181% to 1047% improvement in the path exploration capability of edge coverage when facing programs that cause a state space explosion.
Influence of Vegetable Oils on In Vitro Performance of Lutein-Loaded Lipid Carriers for Skin Delivery: Nanostructured Lipid Carriers vs. Nanoemulsions

Nanostructured lipid carriers (NLC) were prepared from solid lipid (glyceryl monostearate, GMS) and vegetable oils, including palm oil (PO), rice bran oil (RBO) or virgin coconut oil (VCO), at different ratios (95:5, 90:10 and 80:20), while nanoemulsions (NE) were prepared with sole vegetable oils. After production, the particle size of the lutein-free NLC and NE was found to be between 100 and 150 nm and increased after loading with lutein. An increase in oil loading in NLC reduced the particle size and resulted in a less ordered lipid matrix and an increase in % entrapment efficiency. From the stability study, it was observed that the types of oils and oil content in the lipid matrix had an impact on the chemical stability of lutein. Regarding the release study, lutein-loaded NE showed higher release than lutein-loaded NLC. Both NLC and NE prepared from VCO exhibited higher release than those prepared from PO and RBO, respectively (p < 0.05). In contrast, among the formulations of NLC and NE, both lutein-loaded NLC and NE prepared from RBO showed the highest permeation through the human epidermis due to the skin enhancement effect of RBO. Based on all the results, the lipid nanocarriers composed of RBO could effectively enhance the chemical stability of lutein and promote drug penetration into the skin.
Statistical Analysis and the OPEA Model of the White-Light Flares Occurring on Krüger 60B (DO Cep)

Abstract In this study, new observations and some results of statistical analyses are presented. The largest flare data set of DO Cep in the literature has been obtained with 89 flares detected in 67.61 hours of U-band flare patrol. First of all, the observations demonstrated that the star is one of the most active flare stars in respect to the computed flare frequency. Secondly, using the independent samples t-test, the detected flares were classified into two subtypes, and then they were modelled. Analysing the models demonstrated that the fast and slow flares occurring on the star can be separated with a critical value of the ratio of their decay time to rise time. The critical value was computed as 3.40. According to this value, the fast flare rate is 20.22%, while the slow flare rate is 79.78%. Besides, there is a 39.282 times difference between the energies of these two types of flares. However, the flare equivalent durations versus the flare rise times increase in similar ways for both groups. In addition, all the flares were modelled with the one-phase exponential association function. Analysing this model, the plateau value was found to be 2.810. Moreover, the half-life value was computed as 433.1 s from the model. The maximum flare rise time was found to be 1164 s, while the maximum flare total duration was found to be 3472 s. The results of the flare timescales indicate that the geometry of the flaring loop on the surface of the star might be similar to those seen on analogues of DO Cep. Consequently, considering both the half-life value and flare timescales, the flares detected on the surface of DO Cep get maximum energy in longer times, while the geometries of the flaring loops or areas get smaller.