Miracle-dz/UniFAR-FTUs huggingface dataset:
23.2: Q‐Tensor Based Numerical Modeling of Blue‐Phase LCDs

We have developed a novel numerical modeling software for calculation of the molecular orientation within layers of liquid crystal material in the blue phase and for the optical properties of blue phase LCDs including additional optical components like polarizers and retarder sheets. The calculation of the molecular orientation within the blue phase layer is based on the Q‐tensor approach. Equilibrium and time dependent states are obtained with a relaxation method that minimizes the total energy of the system. Mutual coupling of the electrostatic potential and molecular orientation is taken into account. The geometry is mapped onto a 3d‐grid, periodic boundary conditions are assigned to the faces of the bounding box. The grid is extended on top and bottom side of the bounding box to apply suitable boundary conditions for the electric potential. The finite difference time domain method is applied to calculate reflectance and transmittance of blue‐phase LCDs with uniaxial perfectly matched layers on top and bottom sides of the bounding box to mitigate spurious reflections from the grid boundaries. The grid used for the Q‐tensor calculation is also chosen for the optics calculation.
Robust classification of sector-scan sonar image sequences

The paper reports the development of a system for the automated identification of sonar targets. It uses a novel set of feature measures, derived from sequences of sonar scans, to characterise the behaviour of targets over time. Previous research used grey-scale and shape descriptors derived from images of single sonar scans. However, problems were experienced with targets whose return varied significantly over time (such as divers, ROVs, and ships' wakes). Hence a novel set of temporal feature measures have been developed, to provide a quantitative description of a sonar target's behaviour over several sonar scans. The research showed that the classification accuracy was significantly improved by the use of these new features. While the use of "static" feature measures (derived from a single scan) gave classification errors between 20% and 40% for certain targets, the use of temporal measures reduced this error rate to zero in some cases. <<ETX>>
The influence of exogenous gibberellic acid (GA3) and 24-epibrassinolide (24-EpiBL) on seed germination and the expression of genes involved in GA and BR synthesis/signalling in pepper (Capsicum annuum L.)

Gibberellins (GAs) and brassinosteroids (BRs) are the plant hormones involved in various physiological processes including seed germination. In this study, the effects of exogenous gibberellic acid (GA3) and 24-epibrassinolide (24-EpiBL) treatments on the expression of key genes involved in GA and BR syntheis/signalling during seed germination were investigated in pepper (Capsicum annuum L). The expressions of BES1 and BRI1 involved in BR synthesis/signalling pathway as well as GA3OX1 and GA20OX1 associated with gibberellic acid biosynthesis in plants were determined. Exogenous GA3 treatments increased BES1 expression and the highest increase was determined with 10⁻⁸ M BR + 100 µM GA3 (P<0.05). On the contrary, the expression of BRI1 gene was significantly decreased by 10-8 M BR + 100 µM GA3 (P<0.05). The expression of GA3OX1 gene was induced with BR and GA3 treatments (P<0.05). GA20OX1 gene expression was generally higher compared to the expression of GA3OX1 and significantly increased by the GA3 treatments. Our findings are expected to bring an insight to the influence of BRs during seed germination together with the expression of associated genes.
Learning through computer science unplugged on team assisted individualization on the computational thinking ability

Technical facilities are an element that can support educational and learning activities, especially for professional students in the fields of technology and information. Computational thinking is also one of the supportive skills that every student must have. This is consistent with the preliminary research conducted by the researchers. The teacher said that when students learned basic programming materials, they found it difficult and slowed down because of the limited media they used and the non-optimal methods. This research is aimed to determine the effect of unplugged media based on team assisted individualization on the computational thinking skills of vocational high school students in basic programming subjects. The method used in this research is Quasi-experiment using pretest and posttest control group design. The results of the survey are as follows. 1) Learning media was declared available by media professionals at a rate of 94.23%, including the "very good" category. (2) The designed learning media can improve students' mathematical thinking skills with an average profit value of 0.49, and the standard of effectiveness is "medium". (3) Student response to the use of learning media shows a 97.87% percentage value in the "Very Good" category.
A Requirements-Based CNS/ATM Architecture

This paper identifies an approach to the definition of a National Airspace System (NAS) architecture which will support the future development of the U.S. air transportation system, consistent with long-range needs of the various users of the NAS. The approach outlined identifies the development of an FAA preliminary design methodology, with supporting tools and processes to provide the basis for NAS modernization. This approach begins with the quantification of the primary long-range objectives of the NAS, which the system architecture must support over its design life. These objectives are the basis of the mission analysis and requirements development, which, in turn, are used for technology tradeoff studies and the baselining of an architecture for evaluation.
An integrative review of Indigenous informal caregiving in the context of dementia care.

AIMS To appraise the empirical literature on the needs of Indigenous informal caregivers caring for people living with dementia in Indigenous communities. DESIGN Whittemore and Knafl's updated approach to integrative reviews, PRISMA guidelines, and CASP checklists for narrative analysis were followed. DATA SOURCES A systematic search of published empirical literature from January 2010 to August 2020 was undertaken in six databases. REVIEW METHODS Fifty-one studies met the research question and the inclusion criteria. RESULTS Five themes describe the findings: Decolonizing Western perspectives on dementia, the centrality of cultural safety, caregivers' experiences, pre-dementia community education and family and community-centred care emerged from the thematic analysis. Most of the studies used quantitative methodologies, and few studies were conducted using community-based approaches. CONCLUSION This review shows that Indigenous caregiving represents an emerging field in nursing and health sciences in a context of a global crisis. Researchers need to focus on Indigenous values and voices to adapt care and support informal caregivers. Our review emphasizes that working with Indigenous communities will likely translate into new care delivery models, policies and practices to support Indigenous informal caregivers and address the specific social determinants impacting caregivers' roles and tasks. IMPACT This review highlights the necessity of having community and family-based discussions on enhancing the delivery of dementia care for Indigenous peoples in Canada and worldwide. Decolonizing Western perspectives of dementia translate into culturally safe approaches that aim to integrate Indigenous cultural perspectives of holism, reciprocity, wisdom, respect of older people and relationality into nursing practice. The support of Indigenous informal caregivers requires future studies to address the stigmatizing Western views of dementia.
Automated Drawing Tube (Camera Lucida) Method in Light Microscopy Images Analysis Can Comes True

Background: In a light microscope, image acquisition with different component depths is difficult, and there are various approaches for solving this problem. One of the common approaches is Camera Lucida (CL). This method has some disadvantages such as time-consuming, handed problems in painting, causing user boring, and produce gray scale output images. Aims and Objectives: In this study, we purposed a novel-combined hardware and software method. In this article, we try to present an automated method for our designed microscope. Materials and Methods: We have done a project with designed code number 377,694 to design and implement an upgraded light microscope. That project was about automatic movement of a stage with closed-looped control of a servomotor. Furthermore, automated camera catches images in predefined positions. That project has acceptable results in different parts, which encourage us to work on this study. This study help specialist have good fixative of all components in a sample. It is about trying to have useful Lucida Camera (drawing tube) in an automated scheme. Results: This method is an acceptable usual way for microscopic specialists, but with some disadvantages. It is time-consuming and boring that effect on the accuracy of results. Hence, how can be good if automated similar method could be implemented is exciting and affective. This studies idea comes from the basis of manual drawing tube (CL) method. In this experimental study, we have taken 400 handed an image of microorganisms. Captured images are from its whole body or various organs. They have been captured in different z-axis positions of stage, and hence components with different depths could be focused. Each patch checked for its edge strength to choose highest resolutions sub image and reconstruct focused image like a puzzle. This process has been continued for all areas to merge and complete reconstructed image as output. Conclusion: Comparing edge strength with other images and mean square error with manual focused on confirm our method with pleasure outcomes. Furthermore, independent focusing of an internal component in a sample body has been surveyed. It helps to have better resolution in internal selected component for more analysis and replace in its primitive image. This article presents efficient consequences with good accuracy and saving time in process period, which could be useful in different microscopes types and various samples type.
Symptom reduction in DBT-informed partial hospital, intensive outpatient, and step-down programs: Mindfulness matters

Abstract Objective Preliminary evidence suggests the efficacy of Dialectical Behavior Therapy (DBT) to reduce clinical symptoms in Partial Hospital (PH) programs. However, less is known about DBT in Intensive Outpatient (IOP) programs, or in PH to IOP step-down models. The current study examined changes in depression, anxiety, stress, hopelessness, and mindfulness skills acquisition, from intake and discharge data of clients at a southeastern behavioral health clinic in the United States. Method The sample included 146 clients, 65.75% female (ages M = 33.88, SD = 12.34), who attended either a DBT-PH, -IOP, or -PH to IOP step-down program. Participants completed the Depression, Anxiety, Stress Scale (DASS-21), Beck Hopelessness Scale (BHS), and Five Facets of Mindfulness Questionnaire Short Form (FFMQ-SF). Results Depression, anxiety, and hopelessness decreased from intake to discharge in the PH program, while all symptoms decreased in the IOP and step-down programs. Mindfulness total scores, and most subscales, increased in each program. Mindfulness skills acquisition predicted decreases in depression and stress in the IOP group, and decreases in depression and hopelessness in the step-down group. Conclusion Overall, clinical symptoms and mindfulness skills acquisition improved over the course of the DBT-PH and—IOP programs.
Clogging of Recharge Wells by Suspended Solids

Field conditions have been reproduced in the laboratory in order to investigate the fundamentals governing the mechanism of clogging of recharge wells. Dosing with water of controlled quality and temperature, containing different types of added suspended solids of know size, with concentration in the range 0.5–250 mg/L was carried out in 45° segmental perspex models simulating confined aquifer conditions. Both filter packed and nonfilter packed wells were tested. It was found that, the lower the concentration of the suspended solids in the recharge water the greater the weight of solids required to clog the well. The filter pack has been clearly established as a major factor in controlling the clogging speed.
Delay and Energy Consumption Optimization Oriented Multi-service Cloud Edge Collaborative Computing Mechanism in IoT

The rapid development of the Internet of Things has put forward higher requirements for the processing capacity of the network. The adoption of cloud edge collaboration technology can make full use of computing resources and improve the processing capacity of the network. However, in the cloud edge collaboration technology, how to design a collaborative assignment strategy among different devices to minimize the system cost is still a challenging work. In this paper, a task collaborative assignment algorithm based on genetic algorithm and simulated annealing algorithm is proposed. Firstly, the task collaborative assignment framework of cloud edge collaboration is constructed. Secondly, the problem of task assignment strategy was transformed into a function optimization problem with the objective of minimizing the time delay and energy consumption cost. To solve this problem, a task assignment algorithm combining the improved genetic algorithm and simulated annealing algorithm was proposed, and the optimal task assignment strategy was obtained. Finally, the simulation results show that compared with the traditional cloud computing, the proposed method can improve the system efficiency by more than 25%.
2D Omni-Directional Wireless Power Transfer Modeling for Unmanned Aerial Vehicles with Noncollaborative Charging System Control

Wireless power transfer (WPT) has been extensively studied from various aspects such as far field and near field, operating frequency, coil design, matched capacitance values, misaligned locations of transmitting and receiving coils, distance variance between them, target loads in the specific locations, environment, and operating conditions. This is due to the usefulness of WPT technology in many applications, including the revolutionary method of auto-recharging of unmanned aerial vehicles (UAVs). This paper presents analytical modeling of a WPT-link with two orthogonal transmitting coils arranged to produce an omnidirectional magnetic field suitable for charging a moving rotating load, maximizing energy transfer without any feedback from the receiving end. To achieve a suitable 2D WPT simulation system, as well as an accurate control design, the mutual coupling values in terms of receiver angular rotation are simulated using Ansys software. Power transfer is maximized by using extremum seeking control (ESC), making use of the input power as an objective function with specific parameter values that represent the WPT model to obtain the results. The results shown are those of the input power transmitted by the transmitting-end coils to a load of an orbiting mobile UAV. Based on the simulation results, the controller can achieve maximum power transfer in 100 µs of duration when the speed of the UAV is close to 314 rad/s.
An Enhanced Deep Network for Recognizing the Coronavirus Disease Using X-ray Images

The spreading of Coronavirus (covid-19) is pushing the healthcare organizations under exceptional strain over the universe and increasing pressure concurring to the World Health Organization (WHO). With advancement of Artificial Intelligence, the discovery of this type of infection during the initial stage offers assistance in quick recuperation and in discharging the pressure on healthcare organizations. This paper presents the deep convolution network to detect the coronavirus in chest x-ray images. Due to the lack of benchmark datasets for covid-19 specifically in chest x-ray images, this work presents the framework that adopts the Generative Adversarial Network of Deep Convolution (DC-GAN). The proposed model of DC-GAN can generate a maximum of 30 different patterns for a single image and thus increases the size of dataset. It also offers assistance in overwhelming the overfitting issue and building the proposed framework more robust. The proposed model implements the transfer learning updated by the loss function using the ImageNet to attain the finest parameters from the pre-trained model. The publically available dataset is utilized to validate the proposed work. This work is validated by conducting the various experiments in various perspectives and also its performances are recorded using the measures namely accuracy, recall, precision and, F1score. These recorded results compared with the various existing methods.
Theoretical Investigation on the Impact of Two HDR Dampers on First Modal Damping Ratio of Stay Cable

Stay cables are one of the vital components of a cable-stayed bridge. Due to their flexible nature, stay cables are vulnerable to external excitation and often vibrate with large amplitude under wind action which leads to the fatigue failure of the cables. To suppress such kind of large amplitude vibration by improving the damping ratio of the cable various dampers such as magnetorheological damper, friction damper; oil damper; or high damping rubber (HDR) damper are utilized and gained popularity over time. This paper focuses on improving the damping ratio of stay cables using a combination of two HDR dampers. First, the theoretical model is formulated considering cable bending stiffness to evaluate the damping effect of cable-HDR dampers system. Then, the impact of various design parameters of HDR dampers on cable damping considering the cable stiffness is performed. The comparative analysis of results shows that the considered parameters such as loss factor, spring factor, and installation location of dampers have much effect on the stay cables damping ratio. Finally, the optimal parameters of the two HDR dampers are proposed for damper design.
Automated Micro-PIV measurement in Lab-on-a-Chip systems

Flow rate and wall shear stress are important parameters for perfused cell culture systems and should be monitored. An easy and non-invasive method is the particle image velocimetry (PIV). In this work PIV was used to characterize a cell culture system with included peristaltic pump. The time-dependent flow profile was measured on several points of the chip for different pumping speeds to figure out which forces are applied to dissolved and adherent cells. The results can be used to improve the developed pump in respect to its layout, the excitation and the position within the chip.
Forecasting SQL Query Cost at Twitter

With the advent of the Big Data era, it is usually computationally expensive to calculate the resource usages of a SQL query with traditional DBMS approaches. Can we estimate the cost of each query more efficiently without any computation in a SQL engine kernel? Can machine learning techniques help to estimate SQL query resource utilization? The answers are yes. We propose a SQL query cost predictor service, which employs machine learning techniques to train models from historical query request logs and rapidly forecasts the CPU and memory resource usages of online queries without any computation in a SQL engine. At Twitter, infrastructure engineers are maintaining a large-scale SQL federation system across on-premises and cloud data centers for serving ad-hoc queries. The proposed service can help to improve query scheduling by relieving the issue of imbalanced online analytical processing (OLAP) workloads in the SQL engine clusters. It can also assist in enabling preemptive scaling. Additionally, the proposed approach uses plain SQL statements for the model training and online prediction, indicating it is both hardware and software-agnostic. The method can be generalized to broader SQL systems and heterogeneous environments. The models can achieve 97.9% accuracy for CPU usage prediction and 97% accuracy for memory usage prediction.
Complex Valued and Layer Based Categorization of Synthetic Aperture Radar Patches

This paper presents a comparison between a complex valued layer based sparse coding and complex valued convolutional neural network for Synthetic Aperture Radar (SAR) patch categorization. Recent progress in convolutional neural networks made a classification and categorization of SAR patches very attractive. Layered sparse coding is based on an optimal dual based l1 analysis that can be applied to the problems of SAR image patch classification. In this paper a sparse coding approach is designed in multi layered architecture. This this paper proposes a layered based sparse coding using approaches introduced within deep learning architecture, therefore, we incorporated spatial pooling layer, normalization layer, map reduction layer and a classification layer into the process of sparse coding. In this paper a layer based convolutional neural network consisted of convolutional, drop out, Relu, fully connected, soft max and classification layers were combined to achieve the best classification accuracy. Experimental results showed that the CNN based classification achieved better results compared to the layered based sparse classification.
Evaluation of Optical and Acoustical Properties of Ba1−xSrxTiO3 Thin Film Material Library via Conjugation of Picosecond Laser Ultrasonics with X-ray Diffraction, Energy Dispersive Spectroscopy, Electron Probe Micro Analysis, Scanning Electron and Atomic Force Microscopies

Wide-range continuous spatial variation of the film composition in lateral compositionally graded epitaxial films requires the development of high throughput measurement techniques for their local and non-destructive characterization with the highest possible spatial resolution. Here we report on the first application of the picosecond laser ultrasonics (PLU) technique for the evaluation of acoustical and optical parameters of lateral compositionally graded film, the Ba1−xSrxTiO3 (0 ≤ x ≤ 1) material library. The film was not dedicatedly prepared for its opto-acousto-optic evaluation by PLU, exhibiting significant lateral variations in thickness and surface roughness. Therefore, the achieved measurements of the sound velocity and of the optical refractive index, and characterization of the surface roughness confirm the robustness of the PLU technique for thin film evaluation. We hope that the first measurements of the acoustical and optical properties of epitaxial grown Ba1−xSrxTiO3 (0 ≤ x ≤ 1) by PLU technique accomplished here provide the parameters required for more extended predictive design of the phononic, photonic and phoxonic mirrors and cavities with superior properties/functionalities for novel multifunctional nanodevices.