Miracle-dz/UniFAR-FTUs huggingface dataset:
Delft University of Technology Experimental Investigation on Frequency Characteristics of Plasma Synthetic Jets

The performance of a two–electrode plasma synthetic jet actuator (PSJA) is investigated for a wide range of dimensionless actuation frequencies (f*) using high-speed phase-locked Particle Imaging Velocimetry (PIV) measurements. The jet-induced velocity fields in the axisymmetric plane are measured during both transient and steady working stages of the PSJA. When f* increases, the jet duration time (Tjet) is reduced while the peak suction velocity (Us) increases consistently. Three integral parameters, including the total expelled gas mass, impulse and issued mechanical energy also decline considerably with increasing frequency, which is shown to relate to both the reduced cavity density and the decreasing jet duration. Theoretical analysis reveals that the mean cavity density decreases monotonically with the square root of discharge frequency. The decreasing rate is inversely proportional to a thermal cut-off frequency (fc, 210Hz for the current study), which scales with the convective heat transfer coefficient between the actuator cavity walls and the cavity gas, as well as the area of the cavity internal surface. In the time-averaged velocity fields, the jet centreline velocity ( c U ) exhibits a local maximum in the axial coordinate. The nondimensional maximum centreline velocity reduces with increasing frequency of operation. The jet spreading rate of the plasma synthetic jets (PSJ) decreases from 0.14 to 0.09 with increasing frequency. During the transient working stage of PSJ, the exit velocity trace elapses 20 successive actuation cycles to stabilize. In contrast to the exit velocity, approximately 130 cycles are needed for the mean cavity density/temperature to reach steady values.
The Cultural Production of Everyday Ethics in Two University STEM Labs

How do ethics show up in the everyday behaviors and conversations of researchers in a scientific laboratory? How does the microcosmic culture of the laboratory shape researchers’ understandings of scientific ethics? We, an interdisciplinary team representing anthropology, computer science, and rhetorical studies, investigated these questions in two university STEM labs. Similar to previous work mapping out the epistemic cultures, we sought to understand the ethical cultures of these research groups. We observed their lab meetings for several months and conducted interviews with members of the research laboratories. Ultimately, we recognized two distinct ethical cultures within the two laboratories: one focused on the relationship between science and social justice, and the other focused on clean data and accuracy as an ethical issue. These two distinct ethical cultures were discernable through ethnography, close reading of laboratory members’ language, as well as broad-scale topic modeling. Our project complements previous studies of ethics in science that have focused on codes of ethics or student curricula as ways in which scientists develop an understanding of scientific ethics. Our project demonstrates that everyday interactions between the members of scientific research labs additionally shape, at a decidedly local level, how scientists understand and ultimately approach ethical decision-making in the scientific research process.
Multiple imputation for nonresponse in surveys

Tables and Figures. Glossary. 1. Introduction. 1.1 Overview. 1.2 Examples of Surveys with Nonresponse. 1.3 Properly Handling Nonresponse. 1.4 Single Imputation. 1.5 Multiple Imputation. 1.6 Numerical Example Using Multiple Imputation. 1.7 Guidance for the Reader. 2. Statistical Background. 2.1 Introduction. 2.2 Variables in the Finite Population. 2.3 Probability Distributions and Related Calculations. 2.4 Probability Specifications for Indicator Variables. 2.5 Probability Specifications for (X,Y). 2.6 Bayesian Inference for a Population Quality. 2.7 Interval Estimation. 2.8 Bayesian Procedures for Constructing Interval Estimates, Including Significance Levels and Point Estimates. 2.9 Evaluating the Performance of Procedures. 2.10 Similarity of Bayesian and Randomization--Based Inferences in Many Practical Cases. 3. Underlying Bayesian Theory. 3.1 Introduction and Summary of Repeated--Imputation Inferences. 3.2 Key Results for Analysis When the Multiple Imputations are Repeated Draws from the Posterior Distribution of the Missing Values. 3.3 Inference for Scalar Estimands from a Modest Number of Repeated Completed--Data Means and Variances. 3.4 Significance Levels for Multicomponent Estimands from a Modest Number of Repeated Completed--Data Means and Variance--Covariance Matrices. 3.5 Significance Levels from Repeated Completed--Data Significance Levels. 3.6 Relating the Completed--Data and Completed--Data Posterior Distributions When the Sampling Mechanism is Ignorable. 4. Randomization--Based Evaluations. 4.1 Introduction. 4.2 General Conditions for the Randomization--Validity of Infinite--m Repeated--Imputation Inferences. 4.3Examples of Proper and Improper Imputation Methods in a Simple Case with Ignorable Nonresponse. 4.4 Further Discussion of Proper Imputation Methods. 4.5 The Asymptotic Distibution of (Qm,Um,Bm) for Proper Imputation Methods. 4.6 Evaluations of Finite--m Inferences with Scalar Estimands. 4.7 Evaluation of Significance Levels from the Moment--Based Statistics Dm and Dm with Multicomponent Estimands. 4.8 Evaluation of Significance Levels Based on Repeated Significance Levels. 5. Procedures with Ignorable Nonresponse. 5.1 Introduction. 5.2 Creating Imputed Values under an Explicit Model. 5.3 Some Explicit Imputation Models with Univariate YI and Covariates. 5.4 Monotone Patterns of Missingness in Multivariate YI. 5.5 Missing Social Security Benefits in the Current Population Survey. 5.6 Beyond Monotone Missingness. 6. Procedures with Nonignorable Nonresponse. 6.1 Introduction. 6.2 Nonignorable Nonresponse with Univariate YI and No XI. 6.3 Formal Tasks with Nonignorable Nonresponse. 6.4 Illustrating Mixture Modeling Using Educational Testing Service Data. 6.5 Illustrating Selection Modeling Using CPS Data. 6.6 Extensions to Surveys with Follow--Ups. 6.7 Follow--Up Response in a Survey of Drinking Behavior Among Men of Retirement Age. References. Author Index. Subject Index. Appendix I. Report Written for the Social Security Administration in 1977. Appendix II. Report Written for the Census Bureau in 1983.
Antibiotic Use for Febrile Children in a Tertiary Care Hospital’s Outpatient Department: A Cross-Sectional Study

Background Irrational prescription of antibiotics is contributing to the antimicrobial resistance crisis in low and middle-income countries. Antibiotic stewardship programs need to be implemented to rationalize the use of antibiotics, but data on antibiotic prescriptions in pediatric outpatient departments is minimal. This study aimed to determine the frequency of antibiotic prescriptions in febrile children attending the Paediatric Outpatient Department (OPD) at Combined Military Hospital, Lahore, and observe the factors affecting the decision to prescribe antibiotics. Methodology A cross-sectional, descriptive study with non-probability sampling in the Department of Paediatrics at the Combined Military Hospital (CMH), Lahore, was conducted over two years. The confidence limit was 95%, and the anticipated population proportion was 32%. The primary outcome was the proportion of children aged two months to 10 years presenting to the OPD with fever who received antibiotics. Further analysis included the effect of patient-level risk factors on antibiotic prescription, especially in children with respiratory tract infections (RTIs). Results Of the 225 children analyzed, 137 (61%) received antibiotics. Of these antibiotic prescriptions, 123 (90%) were second-line antibiotics. Older age (odds ratio (OR) = 2.3, 1.18-4.46), high fever (OR = 2.48, 1.37-4.5), presenting in autumn and winter seasons (OR = 2.85, 1.53-5.3), ill appearance (OR = 2.71, 1.12-6.55), tachycardia (OR = 4.28, 1.22-15.01), and tachypnea (OR = 4.01, 1.14-14.12) were associated with increased likelihood of antibiotic prescription. Antibiotic prescriptions in children with RTIs were associated with lower RTI (OR = 12.96, 3.49-48.08), probable bacterial infection (OR = 12.37, 4.77-30.05), tachycardia (OR = 10.88, 1.28-92.24), tachypnea (OR = 14.73, 3.14-68.99), and increased work of breathing (OR = 7.8, 2.05-29.56). Conclusions The evidence of the widespread inappropriate use of antibiotics in OPDs, particularly for upper RTIs, highlights the need for an antibiotic stewardship program. Antibiotic overprescription promotes antibiotic resistance, prolonging illness and increasing healthcare costs.
Influence of silicon doped biochar on germination and defense mechanisms of pea (Pisum sativum L.) under copper and salinity stresses

Abstract Soil pollution is an increasing environmental problem in all developing countries. Salinity and heavy metal stress increase the oxidative stress in plants and lead to the increased production of reactive oxygen species, decreases the production of anti-oxidant enzymes and decreases the rate of plant growth. In the current study, pea plants were grown in the botanical garden GCU, Lahore under stress of salinity and copper. In second stage, these plants were given the treatments of silicon nanoparticles and silicon nano-doped biochar. The salinity and copper effects were observed on different parameters of plant growth. Silicon nanoparticles and silicon-doped biochar proved to be the most effective in improving seedling fresh weight (70%) shoot length (68%), vitality index (82%), germination percentage (16%), seed vigor index (38%), and chlorophyll content (46%) under salinity and copper stress. Biochar, on the other hand, effectively improved root length (37%), total seedling length (55%), germination index (10%), and catalase (21%). Silicon nanoparticles and biochar proved to be most effective in decreasing total phenolics (11%) and total protein content (13%). Therefore, it is concluded that the application of Si-NPs and silicon-doped biochar can enhance plants resistance against saline-sodic and metal contaminated soil and can mitigate these stresses.
Consumer Behavior: Components of Purchase Intention Products E-Commerce Perspective Maqāṣid Al-Sharīʿah

Technological developments have led to changes in consumer shopping behavior from offline to online, leading to the emergence of various online marketplace platforms. The research discusses the influence of electronic of mouth (e-Wom), consumer rating, and reputation on product purchase intention in Shopee e-commerce. The population is Shopee customers, determining the sample with nonprobability techniques - purposive sampling with a sample size of 115 respondents. Analysis and hypothesis using the Structural Equation Model - Partial Least Square (SEM-PLS) method. The findings show that e-Wom, consumer rating, and reputation directly positively and significantly affect product purchase intention. The mediation test results prove that consumer rating and reputation partially mediate the effect of e-Wom on product purchase intention.
Dynamic Spatial Focus for Efficient Compressed Video Action Recognition

Recent years have witnessed a growing interest in compressed video action recognition due to the rapid growth of online videos. It remarkably reduces the storage by replacing raw videos with sparsely sampled RGB frames and other compressed motion cues (motion vectors and residuals). However, existing compressed video action recognition methods face two main issues: First, the inefficiency caused by the usage of coarse-level information under full resolution, and second, the disturbing due to the noisy dynamics in motion vectors. To address the two issues, this paper proposes a dynamic spatial focus method for efficient compressed video action recognition (CoViFocus). Specifically, we first use a light-weighted two-stream architecture to localize the task-relevant patches for both the RGB frames and motion vectors. Then the selected patch pair will be processed by a high-capacity two-stream deep model for the final prediction. Such a patch selection strategy crops out the irrelevant motion noise in motion vectors, as well as reduces the spatial redundancy of the inputs, leading to the high efficiency of our method in the compressed domain. Moreover, we found that the motion vectors can help our method to address the possibly happened static-issue, which means that the focus patches get stuck at some regions related to static objects rather than target actions, which further improves our method. Extensive results on both the HMDB-51 and UCF-101 datasets demonstrate the effectiveness and efficiency of our method in compressed video action recognition tasks.
Correlation of induced sputum eosinophil, absolute eosinophil count and serum IgE with clinical severity of bronchial asthma

Background: Asthma is a chronic inflammatory disorder of the airway. Eosinophil and Serum IgE being a marker of airway inflammation, can serve as a tool for assessing severity and response to treatment in asthma patients. The correlation of clinical assessment with various markers of airway inflammation in asthma is not well established in the Indian population. Present study correlates induced sputum eosinophil, blood eosinophil and Serum IgE count in assessing the clinical severity in bronchial asthma. Aims: To study the correlation of sputum eosinophil, absolute eosinophil count and Serum IgE in assessing the clinical severity of asthma. Methods: It was a cross sectional quantitative study, which was carried out between Feb 2020 to feb 2021. Total 70 asthmatics was selected which underwent history, examinations and spirometry, after written consent. Severity of asthma was assessed by clinical features and by FEV1 in spirometry. (as per GINA guidelines). After assessing the severity of Bronchial asthma all patient underwent Sputum examination for sputum eosinophil counts, blood sampling for Absolue eosinophil counts and Serum IgE levels. After that sputum eosinophil counts, absolute eosinophil counts and serum IgE levels were correlated with severity of Bronchial Asthma. Conclusion: Assessment of eosinophil count in sputum and blood, and serum IgE in blood are simple and inexpensive method that can show a direct measurement of airway inflammation. Thus it can help to identify specific phenotypes in asthmatic patients who are more responsive to steroids, which needs to be demonstrated in future studies. It could be the preferred method in routine practice in monitoring airway inflammation and guiding management.
Retarded stochastic differential equations with infinite delay driven by Rosenblatt process

ABSTRACT Hermite processes are self-similar processes with stationary increments, the Hermite process of order 1 is fractional Brownian motion and the Hermite process of order 2 is the Rosenblatt process. In this paper, we investigate a class of abstract functional second-order nonautonomous stochastic evolution equations driven by Rosenblatt process with index which is a special case of a self-similar process with long-range dependence. More precisely, a fixed point approach together with evolution operator is employed for achieving the required result. Global existence results concerning mild solutions are formulated and proved under various growth conditions. Also, the results obtained in this paper are new even for the autonomous case. Finally, stochastic partial differential equations arising in the modeling of wave phenomena are provided to illustrate the applicability of the obtained results.
Stochastic Analysis for Lagrangian Particles Simulation

This thesis broadly concerns colloidal particle simulation which plays an important role in understanding two-phase flows. More specifically, we track the particles inside a turbulent flow and model their dynamics as a stochastic process, their interactions as perfectly elastic collisions where the influence of the flow is modelled by a drift on the velocity term. By coupling each particle and considering their relative position and velocity, the perfectly elastic collision becomes a specular reflection condition. We put forward a time discretisation scheme for the resulting Lagrange system with specular boundary conditions and prove that the convergence rate of the weak error decreases at most linearly in the time discretisation step. The evidence is based on regularity results of the Feynman-Kac PDE and requires some regularity on the drift. We numerically experiment a series of conjectures, amongst which the weak error linearly decreasing for drifts that do not comply with the theorem conditions. We test the weak error convergence rate for a Richardson Romberg extrapolation and the effectiveness of the Multilevel Monte Carlo algorithm. We finally deal with Lagrangian/Brownian approximations by considering a Lagrangian system where the velocity component behaves as a fast process. We control the weak error between the position of the Lagrangian system and an appropriately chosen uniformly elliptic diffusion process and subsequently prove a similar control by introducing a specular reflecting boundary on the Lagrangian and an appropriate reflection on the elliptic diffusion.
Characterization of Finite Signals with Low-Rank Stft

The goal of this paper is characterize finite-length signals that have a low-rank short-time Fourier transform. By using the connection with Hankel matrices, we give a complete answer for maximal overlap, where the class of signals includes products of complex exponentials and polynomials. For the general case, we show that such signals are much more diverse.
Implementation of Project Based Learning Integrated TPACK in Improve Creative Thinking Skills Through Lesson Study

Facing 21st century learning, lecturers need to carry out student-centered learning that is able to improve creative thinking skills. This research aims to improve students' creative thinking skills by applying Project Based learning integrated TPAC through lesson study. This study used classroom action research through study lessons with three open classes with subjects totaling 32 students of the Hamzanwadi University, mathematics education study program. The data were analyzed using descriptive statistics. Student activity scores during the learning process from the first, second and third open classes were 73.34%, 77% and 87% there was an increase in average activity of 6.83%. Data on the percentage of students who scored the ability to think above 75 in the first open class was 78.13%, the second open class was 81.25% and the third open class was 93.75%, there was an average increase of 7.81%. The conclusion of this study is that the application of Project Based learning integrated TPACK through lesson study can improve students' creative thinking skill. Researchers hope that lecturers can apply TPACK integrated project-based learning to the courses taught.
CountShoots: Automatic Detection and Counting of Slash Pine New Shoots Using UAV Imagery

The density of new shoots on pine trees is an important indicator of their growth and photosynthetic capacity. However, traditional methods to monitor new shoot density rely on manual and destructive measurements, which are labor-intensive and have led to fewer studies on new shoot density. Therefore, in this study, we present user-friendly software called CountShoots, which extracts new shoot density in an easy and convenient way using unmanned aerial vehicles based on the YOLOX and Slash Pine Shoot Counting Network (SPSC-net) models. This software mainly consists of 2 steps. Firstly, we deployed a modified YOLOX model to identify the tree species and location from complex RGB background images, which yielded a high recognition accuracy of 99.15% and 95.47%. These results showed that our model produced higher detection accuracy compared to YOLOv5, Efficientnet, and Faster-RCNN models. Secondly, we constructed an SPSC-net. This methodology is based on the CCTrans network, which outperformed DM-Count, CSR-net, and MCNN models, with the lowest mean squared error and mean absolute error results among other models (i.e., 2.18 and 1.47, respectively). To our best knowledge, our work is the first research contribution to identify tree crowns and count new shoots automatically in slash pine. Our research outcome provides a highly efficient and rapid user-interactive pine tree new shoot detection and counting system for tree breeding and genetic use purposes.
Log-Mean Linear Parameterizations for Smooth Independence Models

In categorical data analysis the choice of suitable parameterizations is a relevant aspect for several reasons: (i) the parameter space is often involved, (ii) its dimension rapidly increases with the number of variables, (iii) tables are sparse for high dimensional data, (iv) models specified by non-linear constraints on joint probabilities can result in non-smooth models. There is, in particular, an interest in parameterizations defining smooth and interpretable models by means of linear constraints on the parameter space. These considerations motivate the increasing attention for novel parameterizations; see [5], [1] and [9]. We focus on the log-mean linear (LML) parameterization recently introduced by [9] for the binary case and then generalized by [8], which is suitable for models of marginal independence, also known as bi-directed graph or covariance graph models; see [3] and [4]. These models investigate the marginal independence structures of the variables and are very useful in high dimensional data analysis, where working in low-dimension sub-spaces is highly desirable.
Inequalities and limit theorems for weakly dependent sequences

These notes are a translation into Englsh of the preprint "Theoremes limites pour les suites de variables aleatoires faiblement dependantes", Prepublication 97-81 de l'Universite de Paris-Sud" which was published at the end of the year 1997. This course aims to treat the theory of summation of weakly dependent variables. The first eight chapters give extensions of the classical results for sums of independent random variables to strongly mixing or absolutely regular processes. Chapter 9 is devoted to applications to Markov chains. The potential reader is any researcher who is interested in sharp results for weakly dependent sequences.
Inner and outer layer turbulence over a superhydrophobic surface with low roughness level at low Reynolds number

The inner and outer layers of a turbulent channel flow over a superhydrophobic surface (SHS) are characterized using simultaneous long-range microscopic particle tracking velocimetry (micro-PTV) and particle image velocimetry, respectively. The channel flow is operated at a low Reynolds number of ReH = 4400 (based on full channel height and 0.174 m/s bulk velocity), equivalent to Reτ = 140 (based on half channel height and friction velocity). The SHS is produced by spray coating, and the root-mean-square of wall roughness normalized by wall-unit is k+rms = 0.11. The micro-PTV shows 0.023 m/s slip velocity over the SHS (about 13% of the bulk velocity), which corresponds to a slip-length of ∼200 μm. A drag reduction of ∼19% based on the slope of the linear viscous sublayer and 22% based on an analytical expression of Rastegari and Akhavan [J. Fluid Mech. 773, R4 (2015)] realized. The reduced Reτ over the SHS based on the corresponding friction velocity is ∼125, which is in the lower limit of a turbulence re.