Miracle-dz/UniFAR-FTUs huggingface dataset:
3-D-Printed Dual-Mode Filter Using an Ellipsoidal Cavity With Asymmetric Responses

A new structure based on an ellipsoidal cavity that operates with the fundamental mode and its degenerate in a transverse routing scheme is presented in this letter. This configuration yields asymmetric filtering functions with two poles and one transmission zero, the position of which can be easily controlled by the rotation of the input and output. For validation purposes, a two-pole filter has been designed and manufactured using 3-D printing techniques. Measured results demonstrate the feasibility of the proposed filter with good agreement between simulation and measurement.
AHP-BASED SOFTWARE FOR STUDENTS' SELF-ASSESSMENT OF CRITICAL THINKING CAPACITY

Students’ capacity for eliciting valid and accurate assessment is crucial for their self-assessment skill. Despite the central role that self-assessment plays in current conceptions of formative and classroom assessment, little attention has been paid for measuring the students’ ability for carrying out valid and accurate assessment. This ability, connected with critical thinking, can be evaluated by comparing a students’ assessment to performance on tests. Recently, the consistency index has been proposed as a metric for measuring students’ critical thinking capacity, affording the observation of poor performance in the judgment capacity of a sample of 23 civil engineering students. This stresses the need of improving this aspect of students’ education, which is required not only as a transversal competence, but also for the attainment of effective self-assessment capacity. In our study, we present an educational software that implements the Analytic Hierarchy Process (AHP) method for providing students with self-assessment of their ability to issue consistent judgment, as well as for training their critical thinking capacity. This way we aim at making students aware of eventual lacks in their skill for valid and consistent assessment, as well as at giving them the opportunity of improving this aspect through self-assessment. The educational software embodies a three-step process, in which the self-assessment takes place in the last stage: first, the student is asked to carry out a conventional teacher assessment based on a set of criteria, which are then weighted by him/her through AHP without consistency control. Second, students are asked to turn on the software’s consistency index control, which will reveal eventual inconsistencies, and accordingly revise his/her judgments until they are acceptable. Finally, the student is invited to self-assess his/her capacity to issue consistent judgment by analysing differences between their assessment with (step 2) and without (step 1) the aid of the consistency control, to reflect upon the differences between consistent and inconsistent assessment, and to think of potential causes driving to inconsistent judgment. The whole process can be performed by the students in the presented software, which serves as a platform for effective self-feedback and training of their assessment accuracy and critical thinking capacity.
APPLICATION OF PROBLEM-BASED LEARNING (PBL) IN THE COURSE "INDUSTRIAL CHEMICAL TECHNOLOGY" OF THE MASTER'S DEGREE IN INDUSTRIAL ENGINEERING

This paper describes the application of Problem-Based Learning (PBL) in the subject "Industrial Chemical Technology" of the Master's Degree in Industrial Engineering from the Universitat Politécnica de València (UPV). This course includes contents related to the Basic Operations of Chemical Engineering, not previously studied by most students. This fact, together with the difficulties associated with the management of 300 students have conditioned the type of methodologies that can be applied and, therefore, the level of depth at which the contents can be developed. Therefore, the main methodology applied so far has been the participative masterclass, with problem solving in the classroom. Although the results in terms of percentage of students who pass the course are very satisfactory, the approach to learning is superficial in some aspects and teachers believe that it should be adapted to master's level. To achieve deeper learning of students in the contents of the course, it has been decided to partially modify the methodology, integrating Problem-Based Learning (ABP). This new methodology will consist of grouped resolution of problems integrated into the same real industrial process, which will allow students to also acquire a more global view of the contents covered in the course. The level of the problems will be increased compared to those solved in the classroom and students will be required to search, select and justify additional data and information to solve the problems that will also be multidisciplinary. All this innovation is part of an Innovation and Educational Improvement Project granted and funded by the “Vicerrectorado de Estudios, Calidad y Acreditación (VECA)” of the UPV. This work describes how the PBL has been defined for implementation in the course and analyses the results achieved to date, identifying the aspects to be improved for the continuation of the methodology in the following academic years.
Large third-order optical Kerr nonlinearity in 2D PdSe2 dichalcogenide films for nonlinear photonic devices

As a novel layered noble metal dichalcogenide material, palladium diselenide (PdSe2) has attracted wide interest due to its excellent optical and electronic properties. In this work, a strong third-order nonlinear optical response of 2D PdSe2 films is reported. We conduct both open-aperture (OA) and closed-aperture (CA) Z-scan measurements with a femtosecond pulsed laser at 800 nm to investigate the nonlinear absorption and nonlinear refraction, respectively. In the OA experiment, we observe optical limiting behaviour originating from large two photo absorption (TPA) in the PdSe2 film of β = 3.26 ×10-8 m/W. In the CA experiment, we measure a peak-valley response corresponding to a large and negative Kerr nonlinearity of n2 = -1.33×10-15 m2/W – two orders of magnitude larger than bulk silicon. In addition, the variation of n2 as a function of laser intensity is also characterized, with n2 decreasing in magnitude when increasing incident laser intensity, becoming saturated at n2 = -9.96×10-16 m2/W at high intensities. Our results show that the extraordinary third- order nonlinear optical properties of PdSe2 have strong potential for high-performance nonlinear photonic devices.
Performance Improvement of Circular Micro-Strip Patch Antenna for WCS

The proposed a circular micro-strip antenna (CMSA) with a circular slot in this paper, that solves the current narrow bandwidth dilemma. The parametric analysis reveals that only with the right choice of parameters would wideband features be achieved with a smaller antenna. The proposed antenna is built at 27.5GHz with wider bandwidth and tremendous return failure. This antenna can also be used extensively for embedded applications with a large data rate. This antenna can be physically implemented with embedded devices that enable it to function in a broader variety of applications.
A case report: insights into reducing plastic waste in a microbiology laboratory

Single-use plastics have often replaced more sustainable materials in microbiology laboratories. Keeping in mind that one of the objectives of the United Nations Sustainable Development Goals is responsible consumption and production, we wanted to document how many single-use plastic items could be saved by taking reduction and reuse approaches in a microbiology laboratory. After taking 4 weeks to document the baseline levels of single-use plastic waste being generated in our laboratory and identifying ways to reduce our reliance on them, we implemented various reduction and reuse approaches and then documented our plastic use over a 7-week period. Reduction approaches included moving to sustainable materials, such as reusable wooden sticks for patch plating and metal loops for inoculation. Reuse approaches focused on reusing plastic tubes via a chemical decontamination station and autoclaving, facilitating the reduction of single-use plastics and a decrease in the amount of waste generated. By utilizing reduction and reuse strategies, which could be implemented in other microbiology laboratories, substantial single-use plastic savings were achieved. These savings had an impact on the amount of biohazard waste being autoclaved and incinerated, as well as generating substantial cost savings for the research institute. The reductions in waste documented in this study could act as a benchmark for others wanting to implement the changes described.
Effect of birth type, gender on psychological resilience

Introduction: Every human being has experienced different stressful situations or hardships sometime in their life. For babies born via C-section this hardship can start at the time of birth. Over the last 10 years there has been an increase in the Cesarean birth type from 8.5% in 2005-06 to 17.5% in 2015-16. Past research has shown the difference in physiological development, increased risk of obesity and asthma, behavioral difficulties in children and adults born via cesarean birth type. Method: The present study aims to study whether there are any birth types and gender differences in Psychological resilience among adults. Online and in-person survey method was used to collect the data of 220 participants through snowball sampling. Resilience Scale (RS) by Wagnild and Young (1993) was used to measure Psychological resilience. Results: 173 participants reported that they were born with Vaginal Birth (78.63%) and 47 with Caesarean Section Birth (21.36%). There were 75% female (N = 165) participants and 25% male (N = 55) participants in this study. The Skewness and Kurtosis were calculated through SPSS 23rd version, which revealed the data was normally distributed. Thus, hypotheses were tested though Univariate Analysis of Variance. The mean difference between Vaginal Delivery (139.01) and Cesarean Section (136.82) was 2.37. The mean difference between female (137.82) and male (140.64) scores in Resilience Scale is 2.82. The test results of One way ANOVA revealed that there no significant differences in Psychological resilience of the participants based on their birth type (F (1,218) = . 65, ns) and gender (F (1, 218) = 1.28, ns). Conclusion: 1) There was no difference in Psychological resilience among Indian adults born with Vaginal Delivery and Cesarean Section delivery. 2) Male and female didn’t differ in their Psychological resilience.
The COVID-19 Crisis and Complexity in the United States

The main objective of this research is to present a transdisciplinary research process which identifies thecomplexity of the issues surrounding COVID-19 using collective intelligence through transdisciplinarycollaborative e ort. Interpretive Structural Modeling (ISM), a methodology for dealing with complexsystem design and development has been the key component of this research. Building collective intelligenceto understand how factors affecting COVID-19 transmission and fatality and their relationships wereinvestigated. The complexity measure of the COVID-19 was investigated by using cyclomatic complexity.The results showed that the complexity of the COVID-19 is dicult to understand and handle.
Fitting the space line of high repeatability to noisy point cloud data

The spatial line fitting algorithm with high repeatability for noise point cloud data is challenging and it is of great significance for high-precision measurement, visual guidance of robotics and CNC machining, but little study has been done at this topic. In this paper, a new algorithm is proposed to fit the spatial line with high repeatability to adapt to the point cloud data with noises. This method combines the idea of repeated residuals and the least square algorithm to filter out the noises and then solve the problem. The algorithm can successfully filter the noises. Four popular straight lines fitting algorithms are implemented as benchmarks. A large number of experimental results show that this algorithm can obtain highly repeatable and accurate straight lines.
A new method for quantification of retinal blood vessel characteristics

Uniform and quantitative grading of retinal vessel characteristics are replacing subjective and qualitative schemes. However clinically accurate blood vessel extraction is very important. The tortuosity of these vessels is an important metric to study the curvature variations in normal and diseased eyes. In this study we provide a new unsupervised and fully automated approach for studying curvature variation of the blood vessels. We then pro- vide tortuosity quantification of these extracted vessels. In this study we used optical coherence tomography angiographic fundus images of dimensions 420x420 pixels corresponding to 6mm x 6mm were used in this study. We focused on the central circular 210x210 pixel region around the foveal avascular zone (FAZ) for tortuosity quantification. Our segmentation approach starts with a 3mm x 3mm central circular region extraction surrounding the FAZ. We then use a multi-scale, multi-span line detection filter to smoothen out the high noise in the background and at the same time increase the intensity of target vessels. This is followed by a K-means procedure to filter out the noise and target vessels into two categories. Next steps are morphological closing and noise removal and iterative erosion of pixels to skeletonize the vessels. The final extracted vessels are of the form of single pixel piecewise continuous fragments. These are finer than human annotations and at the same time free of noise. We then provide accurate standard tortuosity measures - Distance Measure, Inflection Points, Turning Points, etc. for these OCTA images using the extracted vessels through mathematical modelling.
Ensemble Flower-Pollination Algorithm for Automatic Breast Cancer Classification using Haar Features

Breast cancer is a deadly disease which reports a higher mortality rate, every year. This type of cancer is more common in women of developed countries while compared with the incident rate in developing countries. The objective of this work is to propose a methodology to increase earlier breast cancer detection. The methodology makes use of ensemble-based classifiers namely histogram-based Gradient Boosting Machine (hbGBM), Gradient Boosting with Light GBM (lGBM), and Gradient Boosting with CatBoost (GBCB) algorithms. The paper adopts the Mammogram Image Analysis Society (MIAS) database for testing the effectiveness of the algorithms. Haar wavelet transform is used for feature extraction and Flower-Pollination Algorithm (FPA) is employed for selecting the best features. Thus, a flower-pollination based haar wavelet feature with three different ensemble-based classifiers is proposed for the automatic mammogram classification. The performance results are then compared briefly by using some benchmark metrics such as specificity, sensitivity, precision, accuracy, and precision, F1 score, and Matthews Correlation Coefficient (MCC) analysis. The result reveals that the highest classification accuracy is obtained for ensemble GBCB based FPA algorithm i.e., 91% when comparing with other existing models.
Expanding the property profile of Bayfol HX® film towards NIR recording and ultra-high index modulation

Bayfol HX photopolymer films prove themselves as easy-to-process recording materials for volume holographic optical elements (vHOEs) and are available at industrial scale. Their full-color (RGB) recording and replay capabilities are two of their major advantages. Bayfol HX is compatible to plastic processing techniques like thermoforming, film insert molding and casting. Therefore, Bayfol HX made its way in applications in the field of augmented reality such as Head-up-Displays (HUD) and Head-mounted-Displays (HMD), in free-space combiners, in plastic optical waveguides, and in transparent screens. Bayfol HX can be adopted for a variety of applications. To offer access to more applications, we address the sensitization into the Near Infrared Region (NIR) and increase the achievable index modulation Δn1 beyond 0.06. In this paper, we will report on our latest developments in these fields.
Asymmetric PEDOT:PSS Trilayers as Actuating and Sensing Linear Artificial Muscles

Soft ionic actuators and sensors have been intensively studied over the last 20 years. The bending trilayer configuration has been considered a standard architecture, allowing the development of new materials and their optimization. However, bending deformation remains low in force output and presents limited integration capabilities in fast emerging fields like humanoid robotics and actuating textiles. A generalizable architecture of asymmetric supercapacitor‐like trilayers is presented to develop open‐air linear artificial muscles that actuate and sense. First, tuning of electromechanical properties of asymmetric electrodes is performed separately by combining poly(3,4‐ethyl‐enedioxythiophene):poly(styrene sulfonate) with a polyethylene oxide network and 1‐ethyl‐3methylimidazolium bis(trifluoromethanesulfonyl)imide as additives. By varying their content, electronic conductivity can be tuned between 20 and 457 S cm−1, Young's modulus from 1.5 to 0.27 GPa, and volumetric charge density increased by 36%. Asymmetric trilayers are then fabricated using a simple layer stacking process by selecting the optimal combination of materials according to an electromechanical model. Linear strain of 0.5% is obtained in 30 s under ±2 V with 70% of the deformation within 5 s and blocking stress as high as 0.3 MPa. When mechanically stimulated, these asymmetric trilayers demonstrate linear sensing as well, with a sensitivity of 0.38 mV %−1.
Detailed investigation of MOCVD-grown β-Ga2O3 through quantitative defect spectroscopies

Ultra-wide bandgap (~ 4.8 eV) beta phase gallium oxide (β-Ga2O3) grown by metal organic chemical vapor deposition (MOCVD) has demonstrated promising electronic transport properties with room temperature electron mobilities reaching 194 cm2/V-s and background doping as low as 9×1014 cm-3 [Zeng et al, Appl. Phys. Lett. 114, 250601 (2019)]. Commensurate with these values is a total trap concentration that is ~10x lower, with a different distribution of states throughout the bandgap than what has been observed for β-Ga2O3 grown by other methods [Zhang et al., Appl. Phys. Lett. 108, 052105 (2016), Farzana et al, Appl. Phys. Lett. 123, 161410 (2018)]. Given the promise of MOCVD-grown β-Ga2O3, a deeper understanding of the nature of defects in this material is of interest. This work provides a comprehensive picture of the current state of knowledge regarding deep levels in MOCVD-grown β-Ga2O3, including trapping properties, energy and concentration distributions in the bandgap, potential physical sources, and comparisons with other growth methods. By applying a suite of complementary defect spectroscopy methods-deep level optical spectroscopy, deep level transient spectroscopy, and admittance spectroscopy, quantitative characterization of defect states within the ~ 4.8 eV bandgap is possible. We find that, through systematically varying growth conditions, differing trends in concentrations for individual states are observed, implying that growth optimization is possible. Combined with observations made after high energy particle irradiation, we can differentiate between states of intrinsic and extrinsic origin.
Information, Communications and Media Technologies for Sustainability: Constructing Data-Driven Policy Narratives

This paper introduces the idea of data-driven narratives to examine how the use of information, communications, and media technologies (ICMTs) impacts the sustainable growth of economies. While ICMTs have regularly been advocated as a policy tool for growth and development, there is a research gap in empirical studies validating how such policies may be effective. This analysis is based on historical panel data from 39 economies across the developed North (19) and developing South (20). The industry-standard Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology was applied to construct narratives that weave extant theories with empirical data. The art of developing data-driven narratives is rarely addressed in previous research articles. In the narrative approach, prior research on how ICMTs and sustainable growth are quantitatively scored and measured is reviewed. Panel data from authoritative sources such as the United Nations, World Economic Forum, and Sustainable Society Index were collected, cleansed, and conglomerated for data analytics. This was followed by evidence-based reasoning to examine any possible relationships between ICMT development and the sustainable growth of economies across the “North” and “South”. The findings reveal that there are differentiated outcomes in sustainable growth in high- and low-income economies. This poses legitimate questions as to whether low-income economies will be able to meet the UN’s Sustainable Development Goals by 2030 through the intermediation of ICMTs. It is the intended contribution of this paper to exemplify how data-driven narratives using CRISP may construct rich stories about ICMT for sustainability for the purposes of sharing good practice as well as lessons learned.
A conditional gradient algorithm for distributed online optimization in networks

This paper addresses a network of computing nodes aiming to solve an online convex optimisation problem in a distributed manner, that is, by means of the local estimation and communication, without any central coordinator. An online distributed conditional gradient algorithm based on the conditional gradient is developed, which can effectively tackle the problem of high time complexity of the distributed online optimisation. The proposed algorithm allows the global objective function to be decomposed into the sum of the local objective functions, and nodes collectively minimise the sum of local time-varying objective functions while the communication pattern among nodes is captured as a connected undirected graph. By adding a regularisation term to the local objective function of each node, the proposed algorithm constructs a new time-varying objective function. The proposed algorithm also utilises the local linear optimisation oracle to replace the projection operation such that the regret bound of the algorithm can be effectively improved. By introducing the nominal regret and the global regret, the convergence properties of the proposed algorithm are also theoretically analysed. It is shown that, if the objective function of each agent is strongly convex and smooth, these two types of regrets grow sublin-early with the order of O (log T ), where T is the time horizon. Numerical experiments also demonstrate the advantages of the proposed algorithm over existing distributed optimisation algorithms.
Green synthesis of nickel‐manganese/polyaniline‐based ternary composites for high‐performance supercapattery devices

The study divulges formation of nickel‐manganese phosphate and polyaniline (NiMn(PO4)2‐PANI)‐based ternary composites at different aspect ratios, synthesized via facile sonochemical method. The composite is utilized for high‐performance energy storage applications. The composite with 30 wt% PANI depicts the best electrochemical performance with maximum specific capacity (Qs) of 847 C g−1 at 0.5 A g−1 in three‐electrode assembly. The supercapattery device is assembled by utilizing NiMn(PO4)2‐PANI and activated carbon. The supercapattery demonstrates outstanding performance by delivering a remarkable specific energy of 71.3 Wh kg−1, and the maximum specific power is 12 686 W kg−1 and capacity retention of 97.6% after 5000 GCD series. Furthermore, the diffusive and capacitive mechanism is evaluated by applying Dunn's model. The b values are calculated to confirm the hybrid nature of the device. The study depicts the potentials of reported ternary composites as self‐supported electrode materials in the development of cost‐effective and efficient energy storage system.