Miracle-dz/UniFAR-FTUs huggingface dataset:
Teaching Humanoid Robots to Assist Humans for Collaborative Tasks

As technology has advanced, society has witnessed and participated in the creation of robots that can walk, talk, and recognize speech. To facilitate communication and collaboration between humans and humanoid robots, we develop a teaching-learning framework for human beings to teach humanoid robots to complete object identification and operation tasks. The robots learn from their human partners based on the transfer learning approach and can assist humans using their learned knowledge. Experimental results and evaluations suggest the success and efficiency of the developed approach in smart service contexts for human-robot partnerships. The future work of this study is also discussed.
Photocatalytic Performance of Sol-Gel Prepared TiO2 Thin Films Annealed at Various Temperatures

Titanium dioxide (TiO2) in the form of thin films has attracted enormous attention for photocatalysis. It combines the fundamental properties of TiO2 as a large bandgap semiconductor with the advantage of thin films, making it competitive with TiO2 powders for recycling and maintenance in photocatalytic applications. There are many aspects affecting the photocatalytic performance of thin film structures, such as the nanocrystalline size, surface morphology, and phase composition. However, the quantification of each influencing aspect needs to be better studied and correlated. Here, we prepared a series of TiO2 thin films using a sol-gel process and spin-coated on p-type, (100)-oriented silicon substrates with a native oxide layer. The as-deposited TiO2 thin films were then annealed at different temperatures from 400 °C to 800 °C for 3 h in an ambient atmosphere. This sample synthesis provided systemic parameter variation regarding the aspects mentioned above. To characterize thin films, several techniques were used. Spectroscopic ellipsometry (SE) was employed for the investigation of the film thickness and the optical properties. The results revealed that an increasing annealing temperature reduced the film thickness with an increase in the refractive index. Atomic force microscopy (AFM) was utilized to examine the surface morphology, revealing an increased surface roughness and grain sizes. X-ray diffractometry (XRD) and UV-Raman spectroscopy were used to study the phase composition and crystallite size. The annealing process initially led to the formation of pure anatase, followed by a transformation from anatase to rutile as the annealing temperature increased. An overall enhancement in crystallinity was also observed. The photocatalytic properties of the thin films were tested using the photocatalytic decomposition of acetone gas in a home-built solid (photocatalyst)–gas (reactant) reactor. The composition of the gas mixture in the reaction chamber was monitored using in situ Fourier transform infrared spectroscopy. Finally, all of the structural and spectroscopic characteristics of the TiO2 thin films were quantified and correlated with their photocatalytic properties using a correlation matrix. This provided a good overview of which film properties affect the photocatalytic efficiency the most.
Extending Wireless Power Transfer Range for Self-Powered Micro Devices with mm-size Antenna

Extending the wireless power transfer range in miniaturized remotely powered micro-devices is a big challenge due to the very small effective area and low gain of the mm-sized antenna utilized in the micro-devices, which limits the harvested RF energy. This paper presents a method for increasing the separation distance between an external energy source antenna as a transmitter (TX) and micro device antenna as a receiver (RX) beyond 10 cm by utilizing various TX antennas, including a conventional loop antenna, multiple patch antennas, and a rectangular cavity antenna, and a 2-turn double-sided square loop RX antenna, sized 1.2mm x 1.2mm on FR4 substrate, which can be mounted on top of a CMOS SoC. The performance of the wireless power transfer system is evaluated and compared in different scenarios. At the 434 MHz ISM band, the results indicate that the highest peak power transfer efficiency of -20 dB and the highest harvested DC voltage of 4 V through an 8-stage Dickson RF-DC converter are obtained inside the rectangular hollow cavity sized 49.6cm x 49.6cm x 30.4cm, as TX, with an input TX power of 20 dBm. Furthermore, the multiple patch antennas have a power transfer efficiency of -39 dB and a harvested DC voltage of 2.5 V at a distance of 10 cm with an input TX power of 37 dBm. The specific absorption rate of both cases stays below the limits established by IEEE.
GenSim: Unsupervised Generic Garment Simulator

In this paper, we propose a novel generic garment simulator to drape a template 3D garment of arbitrary type, size, and topology onto an arbitrary 3D body shape and pose. Existing learning-based methods for 3D garment simulation methods train a single model for each garment type, with a fixed topology. Most of them use supervised learning, which requires huge training data that is expensive to acquire. Our method circumvents the above-mentioned limitations by proposing GenSim, a generic unsupervised method for garment simulation, that can generalize to garments of different sizes, topologies, body shapes, and poses, using a single trained model. Our proposed GenSim consists of (1) a novel body-motion-aware as-rigid-as-possible (ARAP) garment deformation module that initially deforms the template garment considering the underlying body as an obstacle and (2) a Physics Enforcing Network (PEN) that adds the corrections to the ARAP deformed garment to make it physically plausible. PEN uses multiple types of garments of arbitrary topology for training using physics-aware unsupervised losses. Experimental results show that our method significantly outperforms the existing state-of-the-art methods on the challenging CLOTH3D [4] dataset and the VTO [23] dataset. Unlike the unsupervised method PBNS [5], GenSim generalizes well on unseen garments with varying shapes, sizes, types, and topologies draped on different body shapes and poses.
A Comparative Study of PID Controller and Artificial Neural Network for Load Frequency Control in Hydro Power Plant

This paper explores the utilization of an artificial neural network (ANN) controller based on neural networks to replace the conventional PID controller in load frequency control of a power plant. The ANN controller performs exceptionally well in minimizing steady-state error, maximum overshoot, rise time, and settling time. The proposed control scheme includes a layered artificial neural network controller for a single-area isolated power system that contains a hydro turbine. The power system's performance is evaluated individually for both the conventional integral controller and the ANN controller [1]. The results indicate that the ANN controller outperforms the conventional controller. This study showcases the potential of ANN in industrial process control and can serve as a reference for future research in this field.
Stabilizing Adaptive Feedback Controller Design for a Helicopter Gun Turret System

This study proposes a stabilizing controller design for a helicopter gun turret system using adaptive backstepping control. A two-degree-of-freedom manipulator dynamics is employed to model the gun turret system, enabling accurate control of the weapon pointing system. The proposed controller design utilizes an adaptive backstepping control strategy to ensure system stability and robustness against disturbances such as firing and operational conditions. Simulation results demonstrate the efficacy of the controller, achieving stable and precise control of the gun turret system. The study offers a simplified model to enhance the performance of helicopter gun turret systems, with potential applications in military ground and naval vehicles. The proposed controller design is a promising solution to improve the precision and stability of the gun turret system, contributing to safer and more efficient defense systems.
Genotypic Difference in Growth and Physiological Indices of Grain Amaranth Species under Salinity Stress

The present experiment was conducted during October to February of year 2019−20, to investigate the effect of salinity on morpho-physiological traits and identify the genotype have higher salt tolerance among ten genotypes belongs to three grain Amaranth species. Plant growth traits viz., plant height, shoot and root dry weight decreases with increase in the salinity stress level (EC of 5 and 10 dS m-1) in all the genotypes, however significant (p<0.01) genotypic difference were present among genotypes and GA-5 maintained the maximum growth under salinity. Percent decrease in SDW and RDW was lowest (10.61−23.86 and 10.37 and 26.59) in A. hypochondriachus while in A. cruentus (15.10-29.55 and 12.78-33.09) and A. caudatus (15.15−28.84 and 16.62-34.90). Salinity significantly (p<0.01) decreases the membrane stability, relative water content and leaf potassium content while, leave sodium content increases. As compared to other genotype GA-5 have maximum membrane stability (53.30), relative water content (85.40%), K+ accumulation and minimum Na+ accumulation in leaves.Morpho-physiological traits of grain Amaranthus species are significantly positively correlated with dry shoot biomass (0.649), MSI (0.770), RWC (0.768), chlorophyll (0.908), carotenoid (0.883) and leaf potassium (0.883). It might be concluded that among studied genotypes GA-5 maintained the growth and have higher physiological efficiency results into maximum salt tolerance index also morpho-physiological traits like dry weight, RWC, MSI, Chlorophyll, Carotenoid and leaf potassium content might be utilised for selection of salt tolerant Amaranth genotypes.
Certification Compliant Performance Analysis and Requirements Management of an Electrically Powered General Aviation Aircraft

This paper presents an implementation of a requirements validation toolchain for certification compliant aircraft performance analysis of an electrically powered general aviation aircraft. As part of the dtec.bw project ELAPSED, a novel electric propulsion system approach for a CS-22 class aircraft is being developed. In order to comply with CS-22 certification rules, pre-defined aircraft requirements must be fulfilled by the design, such as a maximum take-off distance of 500 m. To validate the feasibility of aircraft and system requirements and their accordance with the certification standards, a toolchain providing bidirectional traceability from requirements to test results has been set up. This toolchain is comprised of Polarion PLM for requirements management and MATLAB/Simulink providing mission evaluation capabilities using a nonlinear simulation model of the specific aircraft. Two inhouse tools named SimPol and Tico provide connectivity and round-tripping between Polarion and Simulink. Application of this toolchain is presented along a test run of 3 requirements.
A Time-Domain Charge-Balancing Method for Neuromodulators

Closed-loop neuromodulation systems, featuring neurostimulation adapted to simultaneously recorded biomarkers, have shown tremendous potential in the treatment of neural disorders. When periodic stimulation is applied, considerations regarding patient and electrode safety are of utmost importance: Unbalanced stimulation can lead to residual charge, which can accumulate and lead to irreversible reactions, associated with electrode damage and cytotoxic byproducts. Current-controlled stimulation has improved control over the introduced charge, and biphasic stimulation allows for a first-order cancellation. However, unavoidable mismatches in the anodic and cathodic current branch will nevertheless result in imperfect symmetry and hence in residual charge on the electrode post-stimulation. Active or passive charge balancing methods have been explored; while passive discharge has large and uncontrollable initial current density, active cancellation requires significant hardware effort. In this paper, we propose to explore the availability of a neural recorder and employ an iterative method of altering the duration of the compensation pulse in biphasic stimulation in order to achieve excess charge minimization in the time domain with fine (μs) granularity. No excess hardware is required, as the neural recorder is utilized as a sensing path for charge imbalance via the triggered artifact. By relying only on the sign of the initial threshold crossing of the artifact voltage response, a robust implementation with minimal signal processing is achieved. The method requires no prior knowledge or model of the mismatch or the electrode-tissue interface and is verified via wet-electrode measurements.
A Fully Integrated SCC DC-DC Converter with Novel FMC Controller for Fast Transient Response

In this paper, a fully integrated switched capacitor (SC) DC-DC converter with a novel closed-loop control method has been analyzed in comparison to frequency modulation control (FMC) towards the current starved voltage controlled ring oscillator input voltage $(V_{ctrl})$ and the output voltage $(V_{out})$ transient response. The power converter and control circuits of the SC converter (SCC) are designed using CMOS 0.18 $\mu \mathrm{m}$ technology and simulated in Cadence specter. The output of the SCC is regulated at 1.8 V from 3.3 V input voltage, with 2/3 of the no-load voltage conversion ratio (G). The load current $(I_{o})$ and switching frequency $(f_{sw})$ vary from 100 mA to 200 mA and 20 MHz to 100 MHz, respectively, with the allowable output voltage ripple $(\triangle V_{out})$ of less than 0.12% and maximum efficiency of 72.12% at 100 mA of load current.
Expansion of bovine skeletal muscle stem cells from spinner flasks to benchtop stirred-tank bioreactors for up to 38 days

Introduction Successful long-term expansion of skeletal muscle satellite cells (MuSCs) on a large scale is fundamental for cultivating animal cells for protein production. Prerequisites for efficient cell expansion include maintaining essential native cell activities such as cell adhesion, migration, proliferation, and differentiation while ensuring consistent reproducibility. Method This study investigated the growth of bovine MuSC culture using low-volume spinner flasks and a benchtop stirred-tank bioreactor (STR). Results and discussion Our results showed for the first time the expansion of primary MuSCs for 38 days in a bench-top STR run with low initial seeding density and FBS reduction, supported by increased expression of the satellite cell marker PAX7 and reduced expression of differentiation-inducing genes like MYOG, even without adding p38-MAPK inhibitors. Moreover, the cells retained their ability to proliferate, migrate, and differentiate after enzymatic dissociation from the microcarriers. We also showed reproducible results in a separate biological benchtop STR run.
Nonlinear Optics of Skin: Enhancement of Autofluorescence and Second Harmonic Generation Signals by Immersion Optical Clearing

Multiphoton microscopy and especially two-photon microscopy are actively used in dermatology for the diagnosis and analysis of skin diseases. The typical skin probing depth for these methods is limited to 150–200 µm due to the strong scattering properties of skin. The application of the optical clearing method to biological tissues makes it possible to control their optical properties, namely light scattering, by matching the refractive indices of the structural components of tissues. Reducing the scattering of the upper layers of tissue increases the depth of probing for any method of optical imaging by increasing the intensity of the optical signal recorded from the depth up to 6.6 times. This paper presents a brief review of the methods of nonlinear optics used to assess the condition of the skin, discusses the possibility of improving the efficiency of diagnosing skin diseases through the use of the optical clearing method. In particular, this paper discusses the enhancement of the intensity of autofluorescence and second harmonic generation signals during two-photon microscopy of the skin. © 2023 Journal of Biomedical Photonics & Engineering.
Status of the Muon g − 2 experiment at Fermilab

The aim of the Muon g − 2 Experiment at Fermilab (E989) is to measure the muon anomalous magnetic moment ( a µ ) with a relative precision of 140 parts-per-billion (ppb). This precision, which is a factor of four improvement from the current experimental result, will allow for a much more stringent test of the Standard Model. This paper present the current status of the experimental measurement of a µ after the ﬁrst physics run.
The Effect of Injector Geometry on Performance of a Lab-Scale Hybrid Rocket Motor

This study includes the investigation of the effect of injector geometry on the performance of a 200 Newton class laboratory hybrid rocket motor using a paraffin wax/gaseous oxygen propellant pair. The diameter, number, and geometrical placement of orifices on the injector plate are examined to define the best shower-head injector geometry. The mass flow rate and total orifice area are calculated analytically for the motor to reach the desired thrust value according to the design parameters. The final injector geometries are determined by Computational Fluid Dynamics analysis. As a result of numerical studies, three injectors configured with 8, 15 and 33 orifices are defined as the closest value. These injectors have been produced and also examined experimentally to validate the numerical results. According to the experimental studies, the thrust variation of each motor are obtained as a function of time. This study aims to study the effect of changes in injector geometry on the overall performance of the hybrid rocket motor.
A Novel Spatial–Spectral Pyramid Network for Hyperspectral Image Classification

As the research on deep learning methods gradually progresses, more and more classification models are applied in the classification of hyperspectral image (HSI). High-dimensional and low-resolution characteristics of HSI, however, make it difficult for conventional models to process its data effectively. In this article, a novel HSI classification model, namely, spatial–spectral pyramid network (SSPN), is designed by combining a 3-D convolutional neural network (3D CNN) with feature pyramid structure. SSPN taking advantage of 3-D convolution coupled with multiscale convolutional extraction is used to obtain a large set of diverse spatial–spectral features. Multiscale interfusion is also applied in SSPN to enrich the features contained in a single feature map and to improve the sensitivity on HSI spatial–spectral information, allowing it to better learn spatial–spectral features. Moreover, the losses of each combination based on multiscale interfusion are calculated via weighted average, which enables SSPN to avoid the excessive influence of single combination in the updating of model parameters. Four HSI public datasets and several comparison models are employed to validate the classification effect of SSPN. Experimental results show that SSPN achieves the highest overall accuracy (OA) in all datasets compared with other classification models, with 100%, 98.8%, 99.8%, and 98.7% on the datasets of Chikusei, Pavia University, Botswana, and Houston 2013, respectively. SSPN is demonstrated to possess higher classification accuracy and better generalization performance on HSI.
Effect of Non-Genetic Factors on Seminal Traits of Indigenous and Crossbred Bulls under Semi-arid Climatic Conditions

The study was conducted at Post Graduate Institute of Veterinary Education and Research (PGIVER), Jaipur, Rajasthan, India during July–December 2020 to evaluate the effects of non-genetic factors on semen characteristics of bulls. The data of 4608 ejaculates during the period of 2017–2020 from Tharparkar and its cross with Holstein, Jersey and its cross with Sahiwal cows was maintained at Frozen Semen Bank (FSB), India. The Semen characteristics were recorded and stored in Information Network for Animal Productivity & Health (INAPH) application maintained at FSB and National Dairy Development Board (NDDB). The average semen volumes were estimated as 4.18±0.02 ml. Non-genetic factors viz. season, period, breed, ejaculation order and age of bulls showed significant effects on various semen parameters. Higher estimates of semen concentration, motility, Total Ejaculation Volume (TEV) and Post-thaw Motility (PTM) were recorded in Jersey Sahiwal crossbred bull whereas semen motility was observed as higher for Tharparkar bull. Seasonal analysis revealed that winter and autumn were favorable seasons for higher quantity and quality semen production. Age wise analysis presented significantly increased values with the increasing age except semen motility. Non-genetic factors under semi-arid climatic conditions revealed significant effects on semen characteristics of exotic, crossbred and indigenous genotypes and need to be accounted for quality semen production in a semen production centre. Present findings indicate that Jersey Sahiwal cross bulls were found better for quality semen production under semi-arid climatic condition than exotic and other crossbreed bulls.
Sustainable consumer behaviour in clothes disposal in the Sri Lankan context

Purpose: Interest in sustainability has developed in recent decades and individuals are being encouraged to shift toward consumption that is more socially and environmentally sustainable. Sustainable consumption encompasses the acquisition, use, and disposal of goods as a subset of general consumption. The phrase "disposal" in the context of apparel consumption refers to whether a garment is merely discarded, resold, reused, or recycled. This study investigates how consumers can be persuaded to adopt sustainable practices when disposing of clothes. Design/methodology/approach: The study has been conducted by using 366 respondents in Sri Lanka as a quantitative study. This study used the Fogg Behavior Model to investigate what would stimulate consumers to include sustainability criteria. There are three independent variables of the study namely; motivation- sensation anticipation, motivation-social evaluation, and ability which have tested the influence on the dependent variable sustainable clothing disposing behavior while investigating the moderation effect from the trigger. Findings: The results of the study indicated that variables motivation- sensation anticipation, motivation- social evaluation, and ability have a significant positive impact on sustainable clothing disposing behaviour. Furthermore, the trigger has no moderation impact on the relationship between motivation- sensation anticipation, motivation- social evaluation, ability and sustainable clothing disposing behaviour. Originality: Even though clothing disposal has become a significant area for marketing research, especially in post-consumption behaviour, no research has been found on how consumers sustainably dispose of clothing in the Sri Lankan context. Implications: This research provides recommendations, suggestions, and insights for marketers and fashion retailers to design their strategies when introducing a novel approach like sustainable clothing disposal. Keywords: Clothing Disposal, Fashion, Post Consumption, Sustainable Consumption