Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Rendering of Ocular Wavefront Aberrations using Tiled Point‐Spread Function Splatting

Visual aberrations are the imperfections in human vision, which play an important role in our everyday lives. Existing algorithms to simulate such conditions are either not suited for low‐latency workloads or limit the kinds of supported aberrations. In this paper, we present a new simulation method that supports arbitrary visual aberrations and runs at interactive, near real‐time performance on commodity hardware. Furthermore, our method only requires a single set of on‐axis phase aberration coefficients as input and handles the dynamic change of pupil size and focus distance at runtime. We first describe a custom parametric eye model and parameter estimation method to find the physical properties of the simulated eye. Next, we talk about our parameter sampling strategy which we use with the estimated eye model to establish a coarse point‐spread function (PSF) grid. We also propose a GPU‐based interpolation scheme for the kernel grid which we use at runtime to obtain the final vision simulation by extending an existing tile‐based convolution approach. We showcase the capabilities of our eye estimation and rendering processes using several different eye conditions and provide the corresponding performance metrics to demonstrate the applicability of our method for interactive environments.
Electric field sensing near the surface microstructure of an atom chip using cold Rydberg atoms

The electric fields near the heterogeneous metal/dielectric surface of an atom chip were measured using cold atoms. The atomic sensitivity to electric fields was enhanced by exciting the atoms to Rydberg states that are 10^8 times more polarizable than the ground state. We attribute the measured fields to charging of the insulators between the atom chip wires. Surprisingly, it is observed that these fields may be dramatically lowered with appropriate voltage biasing, suggesting configurations for the future development of hybrid quantum systems.
Predictive relationships between winter climate and hot season temperatures over India

Climate change has impacted the nature and the severity of extreme temperatures over India in the recent past. In this study, the characterization in nature and change of hot season (March–May) temperatures across India's various geographical regions have been analysed over the last 69 years. Using canonical correlation analysis (CCA), we elucidate the relationships between various meteorological parameters from the preceding Indian winter (December–February) and the following hot season. A combination of detrended and raw data for CCA has revealed the asynchronous winter parameter's effects on hot season temperatures. The raw data explained the evolution of the relationship between the variables in the warming climate. In contrast, detrended data explains the predictive relationship between hot season temperature and other predictive variables which are not influenced by the trend in the data. The evolving nature of the global and Indian ocean as well as, El‐Niño Southern Oscillation, zonal circulation, and pressure systems, are evident in effecting Indian hot season temperatures. The post‐1980s warming is also tangible from the increasing strength of El Niño in the last few decades. The cross‐validated and mean square skill scores are moderate except for a few regions having an average correlation of ~. 5 or more for the study periods. The minimum temperature has shown better skill than the maximum temperature, and the southern peninsular region has shown more predictability than the northern regions. Compared to raw data, detrended has a lesser prediction skill. The present study will help to predict the seasonal temperature along with the associated relationship and the warming effect post‐1980s.
Comparison of Different Types of Stylets with No-Stylet Technique for Intubation with C-MAC D-Blade® Videolaryngoscope in Simulated Difficult Airway: A Prospective Randomised Study

Abstract Objective: The angulated C-MAC D-Blade videolaryngoscope (VL) is designed for difficult intubation and may not be compatible with standard PVC endotracheal tubes (ETTs). This study was planned to compare efficacy of C-MAC, D-Blade VL using ETT with three different stylets versus no-stylet in patients undergoing tracheal intubation with simulated difficult airway. Methods: After obtaining written informed consent and IEC approval, a total of 144 adult patients were allocated to four groups of 36 each using no-stylet or different types of stylets. The four groups were as follows: Group NS: no-stylet; Group CS: C-MAC stylet; Group DS: D-Blade-type stylet; Group HS: hockey-stick shaped stylet. A rigid appropriate-sized Philadelphia cervical collar was placed around the neck to simulate difficult airway, and C-MAC D-Blade VL was used for intubation. The duration of each intubation stage and attempts were evaluated. Statistical analysis was performed using Statistical Package for the Social Sciences (SPSS) version 22.0 (IBM SPSS Corp.; Armonk, NY, USA), and appropriate tests for different variables were applied. Appropriately, Student’s t test, Chi-square test, Mann–Whitney U test, and one-way ANOVA test were applied. Results: Similar Cormack Lehane grade glottic view was observed in all groups. The number of attempts and duration of intubation were significantly greater using NS group than for other groups. Additional laryngeal manipulation was required in all cases in Group NS, compared to one, zero, and two cases in Groups CS, DS, and HS, respectively (P < .001). Conclusion: Use of Hockey stick shaped stylet, D-Blade-shaped stylet, and C-MAC stylet decreased the total intubation duration in patients with simulated difficult airway.
The role of statistics in the design and analysis of companion diagnostic (CDx) studies

Companion diagnostic tests are crucial in the development of precision medicine. These tests provide information that is essential for the safe and effective use of specific therapeutic products. Statistics plays a key role in the design and analysis of studies to demonstrate the safety and effectiveness of the companion diagnostics. This article can serve as an introduction to companion diagnostics for therapeutic statisticians and for diagnostic ones as well as a discussion of some of the statistical challenges. The topics include biomarker development, diagnostic performance, misclassification, prospective-retrospective validation, bridging studies, missing data, follow-on diagnostics and complex signatures.
An Investigation of Mediational Process in Social Learning During Online Language Learning

Online learning has become a new trend in the world. To teach online effectively, the instructors have to improvise their course content. Learners have mixed feelings over online learning, some of them prefer the face-to-face teaching; but some are comfortable with the online teaching mode. Previously, the success of language teaching has always depended on face-to-face interaction. However, language is taught online now. Therefore, this study was carried out to investigate the mediational process in social learning during online language learning. 111 diploma, bachelor degree and postgraduate students had participated in this quantitative study in a public university in Malaysia. The instrument used is a questionnaire with 29 items. This study examines the influence of online language learning on learner-to-learner, learner-to-instructor, learner-to-content interaction and mediational process. The results show there is a significant difference in education level. Findings in this study reveals that support from peers plays a crucial role as it prevents students from dropping out of the course. The students prefer teaching style that involves their active participation. The findings also indicate that students find it is important to get an overview of the content before the class begins. Lastly, learning motivation increases when instructor gives good comments during online lessons. Learners also need to learn to be more responsible to make sure their online learning time is filled with successful learning and interactions.
Numerical parametric study on the burner arrangement design for hydrogen production in a steam methane reformer

A numerical parametric study on the burner arrangement design for a steam methane reforming reactor was conducted under three burner configurations: a single co‐axial inside burner (SCIB), a single top burner (STB), and multiple top burners (MTB). The burner combustion gas inlet angle was changed to 25°, 45°, and 90° with respect to the horizontal plane. Moreover, the number of reformer tubes inside the reactor was changed to four, six, and eight tubes arrangements. Furthermore, the models were numerically evaluated for temperature distribution inside the combustion space and hydrogen mole fraction in the reactor by incorporating the Xu and Forment model using a user‐defined function (UDF). The results show that the STB configuration is preferable over the SCIB and MTB configuration due to the uniform temperature distribution inside the combustion space and efficient heating from the combustion gas. Furthermore, the standard deviation of the temperature inside the combustion space was found to be lower for the STB arrangement. Moreover, the STB configuration reported a maximum temperature uniformity index of 0.92 for the eight‐tubes reformer arrangement. The value of the average wall heat transfer coefficient and wall heat flux at the reformer tube surface for STB configuration was 396.6 W/(m2K) and 21.7 W/m2, respectively. The velocity inlet angle of the burner combustion gas also plays an important role in the methane steam reforming reaction. A burner combustion gas inlet angle of 45° was observed to have better hydrogen conversion than the 25° and 90° inlet angles due to the proper mixing, leading to more effective heat transfer to the reformer tubes.
A conceptual model-based sediment connectivity assessment for patchy agricultural catchments

Abstract. The accelerated sediment supply from agricultural soils to riverine and lacustrine environments leads to negative off-site consequences. In particular, the sediment connectivity from agricultural land to surface waters is strongly affected by landscape patchiness and the linear structures that separate field parcels (e.g. roads, tracks, hedges, and grass-buffer-strips). Understanding the feedbacks between these structures and sediment transfer is therefore crucial for minimising off-site erosion impacts. Although soil erosion models can be used to understand lateral sediment transport patterns, model-based connectivity assessments are hindered by the uncertainty in model structures and input data. In particular, the representation of linear landscape features in numerical soil redistribution models is often compromised by the spatial resolution of the input data and the quality of the process descriptions. Here we adapted the WaTEM/SEDEM model using high resolution spatial data (2 m × 2 m) to analyse the sediment connectivity in a very patchy mesoscale catchment (73 km2) of the Swiss Plateau. Specifically, we used a global sensitivity analysis to explore model structural assumptions about how linear landscape features (dis)connect the sediment cascade. Furthermore, we compared model simulations of hillslope sediment yields from five sub-catchments to tributary sediment loads, which were calculated with long-term water discharge and suspended sediment measurements. Our results showed that roads were the main regulators of sediment connectivity in the catchment. In particular, the sensitivity analysis revealed that the assumptions about how the road network (dis)connects the sediment transfer from field-blocks to water courses had a much higher impact on modelled sediment yields than the uncertainty in model parameters. Moreover, model simulations showed a higher agreement with tributary sediment loads when the road network was assumed to directly connect sediments from hillslopes to water courses. Our results ultimately illustrate how a high-density road network combined with an effective drainage system increase sediment connectivity from hillslopes to surface waters in this representative catchment of the Swiss Plateau. This further highlights the importance of considering linear structures in soil erosion and sediment connectivity models.
Wet milling of grain sorghum using a short steeping period

Commercial yellow grain sorghum was steeped in a vented container at 50-70°C for 2-10 hr with 1.5 parts (by weight) of water containing initially 0.1-0.5% sulfur dioxide (SO 2 ). During steeping, 75% of the SO 2 was lost through the vent. When grain sorghum and dent corn were steeped at 58°C with an initial concentration of 0.25% SO 2 , steepwater uptake by grain sorghum was faster during the first 4 hr, but leveled off at 4% below that of corn after 10 hr. In addition, the steepwater of grain sorghum became 25% more acidic than that of corn after 2-10 hr. The optimum recovery of starch from grain sorghum steeped 4 hr was 51% at 58°C with an initial concentration of 0.3% SO 2 . Decortication of the grain sorghum produced 70% recovery of pericarp-free, broken kernels, which gave a somewhat reduced recovery of milled starch with only a slight improvement in brightness. The hot paste characteristics of the starches from two sample of yellow grain sorghums matched those of a commercial corn starch.
The Journal of Asia TEFL

This study focused on analyzing how different interactions (face-to-face chatting and chatting with AI chatbots) may affect speaking skills. In order to examine whether using AI chatbots can be beneficial for improving speaking task performances, 110 participants were divided into three groups: a face-to-face chatting, AI text-chatting, and AI voice-chatting group. They were assigned three speaking tasks that involved describing a picture, responding to questions, and expressing an opinion, which they did both before and after the experiments. Based on the analysis of quantitative data, the findings of the study indicated that both AI groups improved their speaking performance after the experiment while there were mixed results from the face-to-face interactions. It was found that the participants in the face-to-face group improved significantly better in responding to questions and expressing an opinion while no significant differences were revealed in the describing a picture task. With respect to the effects of using AI chatbots, there were no significant differences in the two speaking tasks (describe a picture and respond to questions) between the three groups. However, the comparative analysis of the three different interaction modes suggested that the AI voice-chatting pairs outperformed in terms of their speaking performance task (expressing an opinion) compared with the face-to-face and AI text-chatting groups. Regarding students’ perspectives, descriptive statistics and selected student interviews were reported. Based on the findings of the current study, pedagogical implications and directions for future research are also suggested.
HUMAN RESOURCE MANAGEMENT PRACTICES AND THEIR INFLUENCE ON SERVICE DELIVERY AMONG THE STATE CORPORATIONS IN KENYA

The study focused on the utilization of human resource management practices in enhancing service delivery among state corporations in Kenya. Critique of existing literature on the human resource management practices revealed that only few studies have focused on the relationship between human resource management practices and service delivery. This study, therefore, was guided by two variables namely: reward and recognition programs and HR audits as human resource management practices and their influence on service delivery in State Corporations in Kenya. The study adopted a descriptive survey research design to gather data from the sampled respondents of the state corporations. Stratified random sampling was applied to select respondents from the state corporations to participate in the study. Information was gathered by use of questionnaires which were subjected to a pre-test to ensure both validity and reliability. Data analysis was done using both descriptive and inferential statistics with the aid of analysis tool; statistical package for social Sciences (SPSS). The study found that reward and recognition programs have a positive influence on service delivery among state corporations in Kenya. Further, HR audit practices were found to have a significant positive effect on service delivery. The implication is that adoption of these hrpractices can drive service delivery in state corporations.Itis, therefore, recommended that state corporations in Kenya put in place appropriate reward and recognition programs and periodically carry out HR audits since they
Big Five personality traits impact on entrepreneurial intention: the mediating role of entrepreneurial alertness

Purpose The purpose of this study is to investigate the impact of the Big Five personality traits on the entrepreneurial intentions of undergrad university students in Jordan. It further investigates the mediating role of entrepreneurial alertness. Design/methodology/approach A quantitative survey method was conducted with a convenience sample of Jordanian university students. A total of 323 valid questionnaires were received and analyzed. A structural equation modeling with partial least square (PLS) is used to analyze data. Findings Results revealed that conscientiousness, openness and alertness were associated with entrepreneurial intention. Extraversion and openness were associated with alertness, while agreeableness and neuroticism were unrelated to either outcome. Finally, alertness mediates the relationship between extraversion and openness with entrepreneurial intention. Originality/value There is a lack of previous studies investigating the relationship between the Big Five personality traits and students’ entrepreneurial intentions in Jordan, particularly the role of mediating variables in this relationship. This study is considered the first one that examined the mediating role of entrepreneurial alertness in the relationship between personality traits and entrepreneurial intentions.
Analytical modeling and optimization of new Ku‐band tunable square waveguide iris‐post polarizer

A novel design of the polarizer based on a square waveguide with four posts and four irises for Ku‐band 10.7–12.8 GHz is proposed. The main advantage of the developed polarizer design is the option to tune its polarization characteristics by variation of the posts height. The equivalent circuit of the polarizer has been obtained using scattering and transfer matrices technique. Using this model, the polarization and matching characteristics of the suggested polarizer were optimized simultaneously using the trust region method. This method is reliable and robust since it provides good convergence properties. The novelty of this study lies in the use of a new waveguide polarizer structure based on a combination of irises and posts. Posts enable fine‐tuning of the polarizer performance, while irises promote wide operating frequency band. The following simulated characteristics of the optimal polarizer design were obtained: VSWR for the main modes of horizontal and vertical polarization is less than 1.47, the differential phase shift is within 90° ± 2.6°, the axial is less than 0.46 dB, and the XPD is higher than 32 dB in the operating frequency range. A developed polarizer can be applied in antenna feeds for satellite communication and radar systems.
Conformational Analysis, Spectroscopic Insights, Chemical Descriptors, ELF, LOL and Molecular Docking Studies of Potential Pyrimidine Derivative with Biological Activities

Abstract The geometry, frontier molecular orbitals, chemical reactivity, vibrational, NBO analysis and molecular docking simulations of Ethyl −2-(4-propoxybenzylidene)-7-methyl-3-oxo-5-(4-benzyloxy phenyl)-2,3-dihydro-5H-[1, 3]thiazolo[3,2-a]pyrimidine-6-carboxylate (EBPC) have been extensively studied and discussed on DFT calculations. The stable structural conformational analysis has been achieved using potential energy scan for different rotable bonds. The lowest energy of the conformer was obtained from rotation along C2-C3-C26-O27. Electrostatic potential map, UV-Vis and chemical descriptors and drug-likeness properties are analyzed. Localization function and local orbital locator functions are also discussed. Charge delocalization patterns and second order perturbation energies of the most interacting natural bond orbitals have also been computed and predicted. Most of covalent region is in between blue circles around sulfur and few carbon, nitrogen atoms show that the electron depletion region. Docking binding affinities and the formation of a good number of hydrogen bonds suggests that the title compound appears to be a promising drug for the selected inhibitors.
The viability of analog-based accelerators for neuromorphic computing: a survey

Focus in deep neural network hardware research for reducing latencies of memory fetches has steered in the direction of analog-based artificial neural networks (ANN). The promise of decreased latencies, increased computational parallelism, and higher storage densities with crossbar non-volatile memory (NVM) based in-memory-computing/processing-in-memory techniques is not without its caveats. This paper surveys this rich landscape and highlights the advantages and challenges of emerging NVMs as multi-level synaptic emulators in various neural network types and applications. Current and potential methods for reliably programming these devices in a crossbar matrix are discussed, as well as techniques for reliably integrating and propagating matrix products to emulate the well-known MAC-like operations throughout the neural network. This paper complements previous surveys, but most importantly uncovers further areas of ongoing research relating to the viability of analog-based ANN implementations based on state-of-the-art NVM technologies in the context of hardware accelerators. While many previous reviews of analog-based ANN focus on device characteristics, this review presents the perspective of crossbar arrays, peripheral circuitry and the required architectural and system considerations for an emerging memory crossbar neural network.
Kinetics of nanocrystal synthesis in a microfluidic reactor: theory and experiment

The processes occurring during nanocrystal nucleation and growth are currently not well understood. Herein, we theoretically and experimentally investigate the growth kinetics in colloidal nanocrystal synthesis. Using a novel microfluidic reactor integrating independent modules for nucleation and growth, we demonstrate the controlled, direct synthesis of high quality nanocrystals in high yield. For CdSe nanocrystals, we find that size tuning solely by variation of the reaction time and temperature does not yield product populations of optimal size dispersion or yield. Instead, we present an improved method for the synthesis of bespoke nanocrystals that relies on the controlled addition of precise amounts of additional precursor subsequent to nucleation and fine tuning of the reaction time and temperature in the second stage. Real-time spectroscopic monitoring of the produced crystals in conjunction with kinetic simulations confirms the close correspondence between the model and the experiment and elegantly quantifies the effects of temperature, concentration, additives and surfactants on conversion, growth and diffusion rates within the model framework. We show that the conversion of the precursor to a monomer follows a first order rate law and that the growth rate has a stronger temperature dependence than the conversion rate. Moreover, the surfactant concentration retards the reaction by inhibiting diffusion to the growing crystals whilst maintaining a uniform conversion rate. Finally, we demonstrate that diphenylphosphine, a common additive in CdSe synthesis, enhances the reaction rate by accelerating precursor conversion.