Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship Between the Quality of Sustainability Reporting and Corporate Financial Performance: A Cross-Sectional and Longitudinal Study

PurposeThe purpose of this paper is to examine the relationship between the quality of sustainability reports (QSR) and corporate financial performance (CFP). Since the global reporting initiative (GRI) reporting guideline is widely adopted by organizations over the world, the reporting organizations that report their corporate social responsibility (CSR) information under GRI reporting guidelines. Design/methodology/approach-In this study total of 6,519 samples are obtained from the GRI report list in the reporting period from the year 2009 to 2013 for analysis. Findings-The results demonstrate higher QSR results in better profitability and CFP but QSR exceeding a certain level in return increase the utilization of the firm’s resources and this leads to a decrease in overall profitability. Besides, the study proved that continuing investment in sustainability reporting and the decrease in a firm’s profitability affect the overall profitability – Returns on asset (ROA) and Returns on sales (ROS) of the organization. Originality/value-Provides the empirical study on the relationship between QSR and CFP based on the GRI report list in the reporting period from 2009 to 2013. JEL: M41, Q01, Q56
Existence de «fonction-père» pour les ondelettes à support compact

On montre qu'une base d'ondelettes (ψ j,k ) de L 2 (R) avec une fonction-mere ψ holderienne a support compact provient necessairement d'une analyse multi-resolution. La fonction-pere φ a alors la meme regularite que φ et peut etre choisie a support compact
The Effect of Academic Adaptability on Learning Burnout Among College Students: The Mediating Effect of Self-Esteem and the Moderating Effect of Self-Efficacy

Background With the popularization of higher education, the problems of academic adaptability and learning burnout among college students have become increasingly prominent. The purpose of this study was to investigate the relationship between academic adaptability, learning burnout, self-esteem and self-efficacy of college students and their underlying mechanisms. Methods The study was conducted on 2110 college students using the College Student Learning Adjustment Scale, the Learning Burnout Undergraduates Scale, the Self-Esteem Scale, and the Self-Efficacy Scale to establish a mediating model of adjustment. SPSS 26.0 was used for descriptive statistics and Pearson correlation analysis. Model 4 and Model 14 in the process plug-in prepared by Hayes (2017) were used for mediating effects analysis and moderating mediator analysis respectively, and the significance of the mediating effects was tested using the bias-corrected percentile Bootstrap method. Results (1) academic adaptability significantly and positively predicted self-esteem; (2) self-esteem significantly and negatively predicted learning burnout; (3) academic adaptability significantly and negatively predicted learning burnout; (4) self-esteem partially mediated the effect of academic adaptability on learning burnout; and (5) self-efficacy moderated the latter half of the mediation process of academic adaptability-self-esteem-learning burnout. Conclusion These findings are useful for college educators and related researchers to better understand the mechanisms underlying the relationship between academic adaptability and learning burnout, thus providing practical and effective operational suggestions on the prevention and intervention of learning burnout in college students.
Teaching public administration historically

The American field of public administration and management has a history of neglecting history. As Gaus (1930) observed nearly a century ago, the story of how our field developed is “richer by far than we allow our students to see” (p. 138). Decades later, Durant (2014) asked: Why doesn’t the political economy that influences what and how we study interest us anymore? Why is our research largely “cross-sectional analyses and shorter-term longitudinal ones” rather than using history, context, and contingency to account for how and why things happen as they do (p. 10)? As we see the field today, it has made great strides in refining the use of the scientific method to demonstrate causal or quasi-causal relationships between and among important variables in administrative practice. But, as Gaus (1947) put it, we are not taking time seriously: “that part of science which describes and interprets why particular activities are undertaken by government and the problems of policy, organization, and management that result from such origins” (pp. 9–10). Perhaps it is time for another reminder of the importance of the historical context and capacity of public administration—of the political, economic, social, and cultural forces and trends in which public administration has been practiced and studied and by which it has been, and is still being, fundamentally shaped. And this reminder is twofold, one that refers not only to our need for historical context, and one that looks at why we need it: scholars, practitioners, and students alike.
Point Target Spectra Derived for Bistatic SAR Processing Based on Legendre Polynomial Expansion

The formulation of a point target spectrum is a key step in deriving synthetic aperture radar focusing algorithms,which exploits the processing efficiency of the frequency domain.However,the existence of a double-square-root (DSR) in the bistatic range equation makes it difficult to find an exact analytical solution for the 2-D spectrum.In this paper,according to the idea of function optimal approach,we derive a new 2-D point target spectrum on the basis of Legendre polynomial expansion,which is more exact than the existing spectrums during the synthetic aperture time.
An Analysis of Relationships between Menarche and Attained Body Size

The extent of contribution of body weight, height and age to the attainment at menarche was evaluated in a sample of 275 Japanese girls. The means of age, height and weight at menarche were 12.5 SD 0.89 years, 151.1 SD 5.73cm and 42.3 SD 5.75kg, respectively. According to the bivariate correlation analysis between age and height, and age and weight at menarche, height increased (r=0.406, slope=2.603) while weight did not increase significantly with an increase in menarcheal age (r=0.104). The increase of height does not support the invariance of mean height proposed by MATSUBAYASHI (1932), and the random distribution of weight does not support the particular value of weight on the menarcheal sttainment (FRISCH and REVELLE, 1971). However, our finding does not deny the role of weight on menarche, and the weight correlated with the menarcheal status (not attained, 0, versus attained, 1) at each chronological age. An existence of a threshold body size was suggested as one of possibilities to describe the observed relationship.
Linear Systems Analysis: Macrolevel Analysis with Microlevel Data

This paper introduces a method of linear systems analysis for examining the micro-to-macro relations between individual actions in social exchange and the consequences at the social system level. The techniqlue developed in the paper allows researchers to use individual-level data obtained from a sample of individluals in a system to study system-level relations. In the theoretical framework, there are two elements (actors and resources) and two relations (control and interest). Assuming rational action and assuming that all exchanges are made at equilibrium values, the value of the resources held by each actor after exchange equals the value of the resources held before exchange. Using this relation, we can estimate the value of each resource in the system. We present as examples an empirical study of student-teacher exchange using the High School and Beyond data and a study of labor mnarket exchange using the General Social Survey. In addition, assuming utility functions of the Cobb-Douglas form, we can estimate actors' interests. We extend the model to show estimation of interests.
Photonic Crystals as Valuable Technological Platform for Chemical and Biological Nanosensors

Registration of a bounded optical wave propagating along a surface under investigation is a widely used method among state-of-the-art optical chemical and biochemical sensor techniques [1,2]. Utilizing photonic crystals (PCs) permits to confine and concentrate an optical field in the desirable interaction area between light and (bio)sensing material and, therefore, to enhance the performance of the optochemical sensors. PCs are materials that possess a periodic modulation of their refraction indices (RIs) on the scale of the wavelength of light [3]. The multiple reflection from the periodic RI boundaries in such materials can lead to the destructive interference of the optical waves and to the formation of the bands where light propagation is forbidden. There are two main PC designs that may be utilized in optochemical sensors (see schematic illustration for 1D examples in Figure 12.1). In the first case, a high-index layer that is in contact with the external medium under study is nanostructured, and the periodic modulation of the RI takes places for the optical waves propagating along the layer. In the second case, the 1D PC structure is a simple periodic multilayer stack, and optical surface waves (SWs) are excited at the external flat layer, which may be a low-index layer (SiO2 layer, for example). The second case will be described in more detail in the present chapter, while the first case will be outlined in a basic way, for completeness and comparison. CONTENTS
Optical microflaring on the nearby flare star binary UV Ceti

We present extremely high time resolution observations of the visual flare star binary UV Cet obtained with the Optical Pulsar Timing Analyzer (OPTIMA) at the 1.3 m telescope at Skinakas Observatory (SKO) in Crete, Greece. OPTIMA is a fiber-fed optical instrument that uses Single Photon Avalanche Diodes to measure the arrival times of individual optical photons. The time resolution of the observations presented here was 4 μ s, allowing to resolve the typical millisecond variability time scales associated with stellar flares. We report the detection of very short impulsive bursts in the blue band with well resolved rise and decay time scales of about 2 s. The overall energetics put these flares at the lower end of the known flare distribution of UV Cet.
An Efficient Approach to Enumerate Cutsets Arising in Capacity Related Reliability Evaluation

Abstract This paper proposes an efficient approach to enumerate the subsets of cutsets group (SCG) of a communication network having heterogeneous link capacities to evaluate capacity related reliability (CRR) using minimal cutsets. The efficient methodologies in vogue use a priori information of either minimal pathsets or cutsets of the network, which can block or allow a required amount of flow through the network, termed as a first step in CRR evaluation. In the second step, the disjoint sets of the qualified cutsets or pathsets are obtained using an appropriate sum of disjoint product (SDP) approach. Efficient approaches do exist for the second step to obtain the mutually disjoint terms. In this paper, CRR evaluation uses minimal cutsets and an efficient technique to enumerate irredundant SCG. A comparison with respect to the number of subsets of cutsets generation, number of external/internal redundant subsets removal in obtaining irredundant SCG with recent algorithms have been made to show less computational efforts in using the proposed approach and thus a better performance than the existing approaches.
A Shuffled Frog Leaping Algorithm Using Greedy Search Strategy

A novel shuffled frog leaping algorithm is proposed to solve the problems of the primordial algorithm, such as non-uniform initial population, low search precision and slow convergence speed. In this algorithm, a newly designed greedy search strategy is applied to do local search, that is, both the worst individual frog and the best one in every sub-population are updated. The initial population is constructed on the basis of the good point set in the number theory. Furthermore, the pattern search method is introduced to improve the performance of the local best individuals. Experimental results show that the efficiency and convergence of the algorithm can be enhanced significantly.
A Newton-Euler Formulation for the Inverse Dynamics of the 6-PSS Parallel Mechanism

A formulation based on Newton-Euler equation was educed for the dynamic model of the 6-PSS parallel mechanism.The velocity and acceleration between platform and other poles were deduced.And Newton-Euler equations were presented for every poles and the platform.In order to contain the effect of the gravity and inertia force of all components,all of forces between poles and between platform and other pole were removed.As a result,closed-form equations for the inverse dynamics of the holistic parallel mechanism were cstablished.Finally,the emulational curves of each driving force are given,while the platform is moving with certain curves.Thus,the foundation is laid for the control based on dynamics.
Nonlinear noise reduction for electrocorticograms

Local projective nonlinear noise reduction method,which is based on locally linear fits to the nonlinear dynamics,is introduced to reduce the noise in electrocorticograms of Spragure-Dawley rats.Recurrence plots are used to estimate the size of local neighbours.In this way,the noise reduction is improved markedly.In order to show that the program for noise reduction is correct,a noise reduction process is implemented for x-axial time series of Lorenz equation contaminated by 50% gaussian white noise.And then,this noise reduction scheme is applied separately to electrocorticograms of anaesthetized rats and those of the onset of epilepsy induced by penicillin in anaesthetized rats.The analyses of a nonlinear prediction demonstrate the efficiency of noise reduction.
Fundamentals Of Statistical Processing Vol I Estimation Theory

Thank you for reading fundamentals of statistical processing vol i estimation theory. As you may know, people have search hundreds times for their chosen readings like this fundamentals of statistical processing vol i estimation theory, but end up in harmful downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they juggled with some harmful bugs inside their computer.
Ontarians’ Perceptions of Public Health Communications and Misinformation During the COVID-19 Pandemic: Survey Study

Background Clear, accurate, and transparent risk communication is critical to providing policy makers and the public with directions to effectively implement public health strategies during a health emergency. Objective We aimed to explore the public’s preferred sources of obtaining COVID-19 information, perceptions on the prevalence and drivers of misinformation during the pandemic, and suggestions to optimize health communications during future public health emergencies. Methods We administered a web-based survey that included Likert scale, multiple choice and open-ended response questions to residents of Ontario, Canada. We aimed to recruit a sample that reflected population diversity with respect to age and gender. Data were collected between June 10, 2020, and December 31, 2020, and were analyzed using descriptive statistics; open-ended data were analyzed using content analysis. Subgroup analyses to explore perceptions by age and gender were conducted using ordinal regression. Results A total of 1823 individuals participated in the survey (n=990, 54% women; n=703, 39% men; n=982, 54% aged 18-40 years; n=518, 28% aged 41-60 years; and n=215, 12% aged ≥61 years). Participants most commonly obtained COVID-19 information from local television news (n=1118, 61%) followed by social media (n=938, 51%), national or international television news (n=888, 49%), and friends and family (n=835, 46%). Approximately 55% (n=1010) of the participants believed they had encountered COVID-19–related misinformation; 70% (n=1284) of the participants reported high levels of trust in health authority websites and health care providers; 66% (n=1211) reported high levels of trust in health ministers or public health organizations. Sources perceived to be less trustworthy included friends and family, talk radio, social media, as well as blogs and opinion websites. Men were more likely to report encountering misinformation and to trust friends or family (odds ratio [OR] 1.49, 95% CI 1.24-1.79) and blogs or opinion websites (OR 1.24, 95% CI 1.03-1.50), compared to women. Compared to those aged 18-40 years, participants aged ≥41years were more likely to trust all assessed information sources, with the exception of web-based media sources, and less likely to report encountering misinformation. Of those surveyed, 58% (n=1053) had challenges identifying or appraising COVID-19 information. Conclusions Over half of our participants perceived that they had encountered COVID-19 misinformation, and 58% had challenges identifying or appraising COVID-19 information. Gender and age differences in perceptions of misinformation and trust in information sources were observed. Future research to confirm the validity of these perceptions and to explore information-seeking patterns by population subgroups may provide useful insights on how to optimize health communication during public health emergencies.
Nonlinear dynamics of milling processes

In this article, dynamics and stability of milling operations with cylindrical end mills are investigated. A unified–mechanics–based model, which allows for both regenerative effects and loss–of–contact effects, is presented for study of partial–immersion, high–immersion and slotting operations. Reduced–order models that can be used for certain milling operations such as full–immersion operations and finishing cuts are also presented. On the basis of these models, the loss of stability of periodic motions of the workpiece–tool system is assessed by using Poincare sections and the numerical predictions of stable and unstable motions are found to correlate well with the corresponding experimental observations. Bifurcations experienced by periodic motions of the workpiece–tool system with respect to quasi–static variation of parameters such as axial depth of cut are examined and discussed. For partial–immersion operations, consideration of both time–delay effects and loss–of–contact effects is shown to have a significant influence on the structure of the stability boundaries in the space of spindle speed and axial depth of cut. The sensitivity of system dynamics to multiple–regenerative effects, mode–coupling effects and feed rate is also discussed.
Analysis of QTL mapping for germination and seedling response to drought stress in sunflower (Helianthus annuus L.)

Sunflower is an important oilseed crop across the world. It is considered as a moderately drought tolerant plant, however, its yield is still negatively affected by drought stress. Improving drought tolerance is of the outmost important for breeding. Although several studies have documented the relationship between the sunflower phenotype and genotype under drought stress, but relatively few studies have simultaneously investigated the molecular mechanisms of drought tolerance in the sunflower at different growth stages. In this study, we conducted quantitative trait locus (QTL) analysis for different sunflower traits during the germination and seedling stages. Eighteen phenotypic traits were evaluated under well-watered and drought stress conditions. We determined that the germination rate, germination potential, germination index, and root-to-shoot ratio can be used as effective indexes for drought tolerance selection and breeding. A total of 33 QTLs were identified on eight chromosomes (PVE: 0.016%–10.712% with LOD: 2.017–7.439). Within the confidence interval of the QTL, we identified 60 putative drought-related genes. Four genes located on chromosome 13 may function in both germination and seedling stages for drought response. Genes LOC110898128, LOC110898092, LOC110898071, and LOC110898072 were annotated as aquaporin SIP1-2-like, cytochrome P450 94C1, GABA transporter 1-like, and GABA transporter 1-like isoform X2, respectively. These genes will be used for further functional validation. This study provides insight into the molecular mechanisms of the sunflower’s in response to drought stress. At the same time, it lays a foundation for sunflower drought tolerance breeding and genetic improvement.
Intelligent Deep Learning Estimators of a Lithium-Ion Battery State of Charge Design and MATLAB Implementation—A Case Study

The main objective of this research paper was to develop two intelligent state estimators using shallow neural network (SNN) and NARX architectures from a large class of deep learning models. This research developed a new modelling design approach, namely, an improved hybrid adaptive neural fuzzy inference system (ANFIS) battery model, which is simple, accurate, practical, and well suited for real-time implementations in HEV/EV applications, with this being one of the main contributions of this research. On the basis of this model, we built four state of charge (SOC) estimators of high accuracy, assessed by a percentage error of less than 0.5% in a steady state compared to the 2% reported in the literature in the field. Moreover, these estimators excelled by their robustness to changes in the model parameters values and the initial “guess value” of SOC from 80–90% to 30–40%, performing in the harsh and aggressive realistic conditions of the real world, simulated by three famous driving cycle procedure tests, namely, two European standards, WLTP and NEDC, and an EPA American standard, FTP-75. Furthermore, a mean square error (MSE) of 7.97 × 10−11 for the SOC estimation of the NARX SNN SOC estimator and 5.43 × 10−6 for voltage prediction outperformed the traditional SOC estimators. Their effectiveness was proven by the performance comparison with a traditional extended Kalman filter (EKF) and adaptive nonlinear observer (ANOE) state estimators through extensive MATLAB simulations that reveal a slight superiority of the supervised learning algorithms by accuracy, online real-time implementation capability, in order to solve an extensive palette of HEV/EV applications.
Irreducibility and strong Feller property for stochastic evolution equations in Banach spaces

The main goal of this paper is to generalize to Banach spaces the well-known results for diffusions on Hilbert spaces obtained in [Peszat, S. and Zabczyk, J. (1995). Strong Feller property and irreducibility for diffusions on Hilbert spaces. Ann. Probab. 23(1): 157-172. ]. More precisely, we are aiming to prove the strong Feller property and irreducibility of the solutions to a stochastic evolution equations (SEEs) in Banach spaces. We give sufficient conditions on the path space and the coefficients of the SEEs for these aforementioned properties to hold. We apply our result to investigate the long-time behavior of a stochastic nonlinear heat equations on $L^p$-space with $p>4$. Our result implies the uniqueness of the invariant measure, if it exists, for the stochastic nonlinear heat equations on $L^p$-space with $p>4$.
A new method for adding a parameter to a family of distributions with application to the exponential and Weibull families

SUMMARY A new way of introducing a parameter to expand a family of distributions is introduced and applied to yield a new two-parameter extension of the exponential distribution which may serve as a competitor to such commonly-used two-parameter families of life distributions as the Weibull, gamma and lognormal distributions. In addition, the general method is applied to yield a new three-parameter Weibull distribution. Families expanded using the method introduced here have the property that the minimum of a geometric number of independent random variables with common distribution in the family has a distribution again in the family. Bivariate versions are also considered.