Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic machine learning Framework for Forest fire forecasting

Based on the automatic machine learning framework, combined with the characteristics of forest fire meteorological data and the adaptive requirements of forest fire prediction, this paper optimizes the data preprocessing, parameter learning, loss function and other links of auto-sklearn, builds a forest fire risk prediction framework with regional adaptive characteristics. Based on the forest meteorological fire risk data, a forest fire risk prediction model with regional characteristics and self-learning characteristics is constructed to solve the problems of low compatibility of the existing machine learning methods with binary unbalanced forest fire data, improve the accuracy of forest fire prediction and provide decision-making basis for forestry risk management. The comparative analysis results show that the prediction accuracy of the improved framework in different test sets is improved by 13% on average. Compared with the existing machine learning model for forest fire prediction, the prediction accuracy of the framework proposed in this paper is comprehensively better than the existing methods in terms of real forest fire data.
Research and design of activation function hardware implementation methods

Activation function is an important part of neural network. Many artificial intelligence accelerators specially design hardware component supporting for activation function. In this article, we analyze normal activation functions, study kinds of activation function hardware implementation methods, and propose a parallel look-up table based piecewise linear fitting method. In many-core AI processor, we determine the table precision by memory size, and propose the basic algorithm and detailed structural design scheme. After the design is completed, we verify its correctness and evaluate its performance. The result shows that proposed method meets the need of correctness, and can finish the parallel computation of sixteen activation function fitting results within thirteen cycles. It greatly improves the efficiency of activation function hardware design.
Enhanced Canny edge detection for Covid-19 and pneumonia X-Ray images

In image processing, one of the most fundamental technique is edge detection. It is a process to detect edges from images by identifying discontinuities in brightness. In this research, we present an enhanced Canny edge detection technique. This method integrates local morphological contrast enhancement and Canny edge detection. Furthermore, the proposed edge detection technique was also applied for pneumonia and COVID-19 detection in digital x-ray images by utilising convolutional neural networks. Results show that this enhanced Canny edge detection technique is better than the traditional Canny technique. Also, we were able to produce classifiers that can classify edge x-ray images into COVID-19, normal, and pneumonia classes with high accuracy, sensitivity, and specificity.
On an SEIR Epidemic Model with Vaccination of Newborns and Periodic Impulsive Vaccination with Eventual On-Line Adapted Vaccination Strategies to the Varying Levels of the Susceptible Subpopulation

This paper investigates a susceptible-exposed-infectious-recovered (SEIR) epidemic model with demography under two vaccination effort strategies Firstly, the model is investigated under vaccination of newborns, which is fact in a direct action on the recruitment level of the model Secondly, it is investigated under a periodic impulsive vaccination on the susceptible in the sense that the vaccination impulses are concentrated in practice in very short time intervals around a set of impulsive time instants subject to constant inter-vaccination periods Both strategies can be adapted, if desired, to the time-varying levels of susceptible in the sense that the control efforts be increased as those susceptible levels increase The model is discussed in terms of suitable properties like the positivity of the solutions, the existence and allocation of equilibrium points, and stability concerns related to the values of the basic reproduction number It is proven that the basic reproduction number lies below unity, so that the disease-free equilibrium point is asymptotically stable for larger values of the disease transmission rates under vaccination controls compared to the case of absence of vaccination It is also proven that the endemic equilibrium point is not reachable if the disease-free one is stable and that the disease-free equilibrium point is unstable if the reproduction number exceeds unity while the endemic equilibrium point is stable Several numerical results are investigated for both vaccination rules with the option of adapting through ime the corresponding efforts to the levels of susceptibility Such simulation examples are performed under parameterizations related to the current SARS-COVID 19 pandemic
INTERDIFFUSION OF GASES IN A LOW-PERMEABILITY GRAPHITE. II. INFLUENCE OF PRESSURE GRADIENTS

A previous experimental investigation of the interdiffusion behavior of two unlike gases within a porous medium at uniform pressure has been extended. The extended studies were focused on interdiffusion under the influence of pressure gradients which, in turn, give rise to both viscous and diffusive components of the experimentally determined fluxes. The fact that the diffusion processes investigated occurred within the region bounded by the normal and Knudsen regimes (the transition region), constituted one of the most important features of these studies. The experimentally observed flux phenomena could be readily explained within the framework of a ``dust‐gas'' model. The flux equations exhibited only one major weakness and this involved the absence of viscous flow contributions resulting from the pressure gradients. However, it was possible to use these and related equations and, with associated parameters, to reconstruct the experimental curves via computations. It was found that the range of applicab.
EFFICIENT RESOURCE ALLOCATION OF A MIMO- OFDM SYSTEM USING CONVEX OPTIMIZATION

For higher order Multiple Input Multiple Output (MIMO) networks with and without Zero Forcing (ZF) technique, we consider the problem of sum rate maximization. The aim is to maximize the achievable communication sum rate by formulating the user dependent MIMO channel matrix. To obtain a quality to the existing non-convex problem, we devise a method based on convex optimization by applying the negative sum rate of the non-convex optimization. Furthermore, to obtain the optimal power allocation channel coefficients, the KKT condition is applied. Simulations are performed for 4 × 4, 8 × 8, 16 × 16, 32 × 32, 64 × 64, 128 × 128 and 256 × 256 MIMO systems. Simulation results prove that ZF technique performs better at higher power levels.
On the isothermal-isobaric ensemble partition function

We briefly review the isothermal-isobaric ensemble partition function correctly derived by Corti and Soto-Campos [J. Chem. Phys. 108, 7959 (1998)] from the view point of usual simulations in which the external bath of a system is appropriately approximated. We show that, for the homogeneous system, the partition function can be reduced to the result of Attard [J. Chem. Phys. 103, 9884 (1995)] which was criticized by Corti and Soto-Campos. We conclude that the volume scale cannot be defined in general but in some particular cases and the recently controverted volume scales are those of the cases. We also confirm the validity of Brown’s [Mol. Phys. 1, 68 (1958)] partition function which has never been used in simulations before, by demonstrating that it is equivalent to the one of Corti and Soto-Campos.
Multi-scale Feature Fusion for 3D Saliency Detection

3D saliency detection aims to take advantage of the disparity map, depth map and color information to automatically detect informative objects from natural scenes. Although studies have concentrated on this issue in recent years, there are challenges such as how to leverage disparity map or depth map effectively to compute depth-induced saliency, and how to fuse optimally multiple visual features and cues. A novel 3D saliency detection approach is proposed, which fuses local contrast, region contrast, texture feature, depth cue, and location cue into a unified saliency computation framework. Results show that the proposed approach achieves significant and consistent improvements on other advanced methods in the RGBD1000 datasets.
n-Beam lattice images. II. Methods of calculation

The calculation of amplitudes and phases of beams of electrons diffracted from thin (≤ 100 nm) crystals of W4Nb26O77 is described. These diffraction data are used to compute 11-beam 00l electron microscope lattice images and the effects of instrument aberrations are considered. Several approximations are compared with a more exact 435-beam, two-dimensional computation, and with experimental diffraction data and lattice images. Finally, the projected charge density approximation to image contrast is evaluated.
Developing functional relationships between temperature and cover crop species vegetative growth and development

Funding information National Institute of Food and Agriculture, Grant/Award Numbers: 2019-34263-30552:, MIS 043050; USDA Agricultural Research Service, Grant/Award Number: 58-6064-9007 Abstract Cover crops planted in the offseason are subjected to uncontrollable weather variables that limit agro-ecological services through modifications in growth and development. The growth of five cover crop species was investigated in response to an array of day/night temperatures, 17/9, 22/14, 27/19, 32/24, and 37/29 ̊C. Shoot and root parameters were measured 33 d after planting. Quadratic functions best described most of the root and shoot dynamics in response to increasing temperatures except for a linear response of plant height in crimson clover (Trifolium incarnatum) and mustard (Brassica juncea). Temperature minimum (Tmin), maximum (Tmax), and optimum (Topt) for shoot traits varied from 9.8 to 10.6, 37.5 to 43.2, and 23.9 to 26.5 ̊C, respectively. The Tmin for root traits varied significantly, ranging from 8.5 to 10.8 ̊C. Topt and Tmax ranged from 22 to 25.7 and 35.2 to 40.6 ̊C, respectively. On average, the Topt for root traits was significantly lower than shoot traits in four of five species. Regardless of temperatures, cover crop species recorded higher biomass partitioning to shoot (62%) than to root, with a maximum proportion of biomass partitioned to shoot in crimson clover and Mighty Mustard Pacific Gold (80%) than other species (64–70%). The results of this study will help growers choose mixes of cover crops with the same temperature range to plant in the same climatic conditions during fallow periods. The cardinal temperatures and functional algorithms for growth and developmental traits could be used to develop models for cover crops under different temperature conditions.
Electronic conduction in : the dependence on the oxygen stoichiometry

We report a systematic study of the electronic transport properties of the metallic perovskite oxide as a function of the oxygen stoichiometry . The electrical resistivity, magnetoresistance, susceptibility, Hall effect and thermopower have been studied. All of the transport coefficients are dependent on the value of . The resistivity increases almost exponentially as increases. We relate this increase in to the creation of with square-planar coordination. We find that there is a distinct -contribution to the resistivity over the whole temperature range. The thermopower is negative, as expected for systems with electrons as the carrier, but the Hall coefficient is positive. We have given a qualitative and quantitative explanation for the different quantities observed and their systematic variation with the stoichiometry .
Combating Deactivation in Methane Non-Oxidative Dehydrocyclization via Hydrogen Feed Pulsing

The non-oxidative dehydrocyclization of methane was carried out over RuMo/HZSM-5 catalyst in a fixed-bed catalytic reactor between 873 and 973 K. The catalyst, prepared by incipient wetness co-impregnation, was highly selective towards benzene production. The formation and deposition of low-H/C carbonaceous species was found to be more important at high temperatures and high methane space velocities. Intermittent hydrogenation of the catalyst by periodically switching from CH4 stream to pure hydrogen in the feedstream contributed significantly to the regeneration of active sites through hydrogenation of the carbonaceous species. Coke removal from the catalyst during H2 exposure was confirmed through temperature programmed oxidation and mass spectrometry analyses of spent catalyst. Alternating sequences of dehydrocyclization and hydrogenation under moderate and high feed flow rates resulted in improving catalyst stability due to efficient reduction of coke formation. These results might suggest an option for maintaining relatively high catalyst activity towards benzene production for prolonged reaction times.
Epidemiological associations among lung cancer, radon exposure and elevation above sea level--a reassessment of Cohen's county level radon study.

Abstract—Inhalation of radon (222Rn) decay products by persons living in homes has been associated with increased risk of lung cancer. Some epidemiological studies have shown a positive association between radon exposure and lung cancer rates. However, a large U.S.-wide ecological study (Cohen 1995)
Quantifying energetic and fitness consequences of seasonal heterothermy in an Arctic ungulate

Abstract Animals have adapted behavioral and physiological strategies to conserve energy during periods of adverse conditions. Heterothermy is one such adaptation used by endotherms. While heterothermy—fluctuations in body temperature and metabolic rate—has been shown in large vertebrates, little is known of the costs and benefits of this strategy, both in terms of energy and in terms of fitness. Hence, our objective was to model the energetics of seasonal heterothermy in the largest Arctic ungulate, the muskox (Ovibos moschatus), using an individual‐based energy budget model of metabolic physiology. We found that the empirically based drop in body temperature (winter max ~−0.8°C) overwinter in adult females resulted in substantial fitness benefits in terms of reduced daily energy expenditure and body mass loss. Body mass and energy reserves were 8.98% and 14.46% greater in modeled heterotherms compared to normotherms by end of winter. Based on environmental simulations, we show that seasonal heterothermy can, to some extent, buffer the negative consequences of poor prewinter body condition or reduced winter food accessibility, leading to greater winter survival (+20%–30%) and spring energy reserves (+10%–30%), and thus increased probability of future reproductive success. These results indicate substantial adaptive short‐term benefits of seasonal heterothermy at the individual level, with potential implications for long‐term population dynamics in highly seasonal environments.
Experimental Analysis of the Dynamic Stiffness in Industrial Robots

Industrial robots are regularly being employed for machining tasks. As a key machining parameter, dynamic stiffness has a significant influence on robotic machining performance. This paper examines two experimental approaches for obtaining the dynamic stiffness of an industrial robot. One approach is based on experimental modal analysis. The other approach is a direct calculation with the acquisition of excitation forces and vibration displacement. Different excitation frequencies are planned to stimulate an industrial robot. The dynamic stiffnesses obtained by the two approaches are thoroughly evaluated. Large deviation appears between the dynamic stiffness measured by two approaches. The factors that result in variations in the measurements are discussed.
SEC23A Regulated by Splicing Factor EIF3A may be Involved in the Development of Cervical Squamous Cell Cancer via Adherens Junction Pathway

Background: Cervical squamous cell cancer is a common malignancy in women globally. Increasing studies have indicated that there was an indivisible association between alternative splicing and cancer. However, comprehensive analysis of alternative splicing is scarce in cervical squamous cell cancer. Methods: Alternative mRNA splicing events data and clinical information of 216 cervical squamous cell cancer patients were downloaded from TCGA SpliceSeq database and TCGA website. We used identified survival-associated splicing events to construct prognostic signatures. Kaplan-Meier survival analysis and receiver operating characteristic curve were performed to evaluate the clinical value of prognostic signatures. A nomogram was carried out to quantitatively predict individuals’ survival probability. Regulatory network between splicing factors and survival-associated splicing events was analyzed. Additionally, we performed Pearson’s correlation analysis between survival-associated splicing events and pathways to explore potential downstream pathways. In order to verify the relationships between EIF3A and cell proliferation and migration, CCK8 and wound healing assays were conducted.Results: After sorting out survival-associated splicing events, multivariable regression analysis was used to acquire 70 survival-associated splicing events that could be independent prognostic factors for overall survival in cervical squamous cell cancer. A nomogram was constructed with a concordance index of 0.82. EIF3A positively regulated SEC23A-27346-AP with highest correlation coefficient (P＜0.001, R=0.69). The most significant KEGG pathways was adherens junction pathway (P=0.02, R=0.65). Cell proliferation and wound healing assays showed that EIF3A knockdown decreases cell proliferation and cell migration. Conclusion: Prognostic signatures of survival-associated splicing events were independent prognostic factors for overall survival among cervical squamous cell cancer patients. A nomogram could quantitatively predict individuals’ survival probability by integrating multiple risk factors. Moreover, SEC23A positively regulated by EIF3A may contribute to cervical squamous cell cancer via adherens junction pathway. This study may offer new direction for subsequent experimental research in cervical squamous cell cancer.
Effects Of β-adrenergic Stimulation On TheVentricular Action Potential: A Simulation Study

Cathecholamines increase heart rate and contraction force. This effect is mainly mediated by their interaction with the β-adrenergic receptor (β-AR) and its downstream ability to modulate Ca cycling and fluxes of a number of ions through specific channels across the cell membrane. The complex nature and broad cellular influence of the β-AR signaling cascade suggests that an integrative modelling approach is appropriate to size the relative weight of each of the single mechanisms by which β-adrenergic inputs modulate whole-cell action potential (AP) and Ca handling in cardiac myocytes. The ventricular AP was simulated by using the Luo-Rudy model. The transmural heterogeneity of the AP (epicardial, mid-myocardial and endocardial cells) was reproduced by considering three different levels of expression of the transient outward current (ITo) and three different ratios of the slow vs. the rapid component of the delayed rectifier K current (IKs / IKr). The β-AR stimulation was modelled by incorporating its effects on L-type Ca current, phospholamban, IKr, IKs, Na-K pump and Na/Ca exchanger. Simulation of β-AR stimulation showed significant changes in the AP and in Ca handling, depending on the cell type and on the levels of ion fluxes alterations due to β-adrenergic inputs. Notably, the occurrence of earlyand delayed-after-depolarizations (EADs and DADs respectively) was also reproduced. In the present analysis, EADs and DADs are suggested as mechanisms responsible for the arrhythmogenic effect of the adrenergic stimulation.
Observation of Quill Effect induced by Distortion of Spatial Beam Profile

Femtosecond laser modification was carried out for silica substrates using spatially distorted pulses. Modified lines were inscribed in the alternative scanning directions. Etching of the sample revealed significant difference in etching rate, representing Quill effect. Also, the etching rates were affected by the distortion of the spatial beam profile. These results suggest the possibility to control the characteristics of the modified region by controlling the beam profile.
THE RELATIONSHIP BETWEEN ECONOMIC GROWTH AND AGRICULTURAL LAND-USE INTENSITY

This study aims to investigate the relationship between economic growth and agricultural land-use intensity for 86 countries over the period 1990-2017. Specifically, this study analyzes the relationship between economic growth and fertilizer use intensity, pesticide use intensity, cropping frequency, production value of crops per area, GHG emissions per area. The results suggest the existence of an inverted-U-shaped relationship between economic growth and each of the agricultural land-use intensity indicators, which is consistent with the Environmental Kuznets Curve (EKC) hypothesis. This implies that in the early stages of economic growth, agricultural land-use intensity rises steadily as per capita income grows, and then begins to decline as per capita income continues to grow after reaching the turning point. A mediation analysis is conducted to test the potential causes behind the relationship.
A Comprehensive Evaluation Method of Intelligent Embedded Platform

With the continuous development of intelligent electronic technology, the intelligent embedded devices become more and more popular. While there is no unified standard for the quantitative evaluation of effectiveness of the intelligent embedded platform. For this problem, this paper proposes a comprehensive evaluation method. The evaluation factors are designed for build the evaluation model, including the hardware efficiency factors and the software efficiency factors. Then the weight of each evaluation factor are calculated through AHP algorithm and CRITIC algorithm. The experiment results show that, the method this paper proposed is more stable and suitable for the efficiency evaluation problems.
INVESTOR HERD BEHAVIOUR IN AFRICA’S EMERGING AND FRONTIER MARKETS

Daily returns of 224 stocks traded on three distinctively classified markets (stand-alone, frontier, and emerging) within a developing continent context are used, employing the Chang, Chen and Khorana (2000) measure. We provide evidence of the presence of investor herding in Africa’s emerging and frontier markets. Evidence of asymmetric herding activities during various market conditions is further provided. The paper also shows that the 2007-2009 global financial crisis did not intensify herding in African markets. The findings suggest that Africa’s leading markets are still fairly inefficient, allowing for potential excess returns for investment strategies that seek to explore market anomalies.
3D scenes semantic segmentation using deep learning based Survey

Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the power and popular tool for data and image processing in computer vision, used for many applications like “image recognition”, “object detection”, “semantic segmentation”, In this research paper, provide survey a background for many techniques designed to 3 Dimensions point cloud semantic segmentation in different domains on many several available free datasets and also making a comparison between these methods.