Graphical User Interface Software Research Articles

Delta GUI change detection using inferred models

Recent software development methodologies emphasize iterative and incremental evolution to align with stakeholders’ needs. This perpetual and rapid software evolution demands ongoing research into verification practices and technologies that ensure swift responsiveness and effective management of software delta increments. Strategies such as code review have been widely adopted for development and verification, ensuring readability and consistency in the delta increments of software projects. However, the integration of techniques to detect and visually report delta changes within the Graphical User Interface (GUI) software applications remains an underutilized process. In this paper, we set out to achieve two objectives. First, we aim to conduct a comprehensive review of existing studies concerning GUI change detection in desktop, web, and mobile applications to recognize common practices. Second, we introduce a novel change detection tool capable of highlighting delta GUI changes for this diverse range of applications. To accomplish our first objective, we performed a systematic mapping of the literature using the Scopus database. To address the second objective, we designed and developed a GUI change detection tool. This tool simultaneously transits and compares state models inferred by a scriptless testing tool, enabling the detection and highlighting of GUI changes to detect the widgets or functionalities that have been added, removed, or modified. Our study reveals the existence of a multitude of techniques for change detection in specific GUI systems with different objectives. However, there is no widely adopted technique suitable for the diverse range of existing desktop, web, and mobile applications. Our tool and findings demonstrate the effectiveness of using inferred state models to highlight between 8 and 20 GUI changes in software delta increments containing a large number of changes over months and between 4 and 6 GUI changes in delta increments of small iterations performed over multiple weeks. Moreover, some of these changes were recognized by the software developers as GUI failures that required a fix. Finally, we expose the motivation for using this technique to help developers and testers analyze GUI changes to validate delta increments and detect potential GUI failures, thereby fostering knowledge dissemination and paving the way to standard practices.

Augmented testing to support manual GUI-based regression testing: An empirical study

ContextManual graphical user interface (GUI) software testing presents a substantial part of the overall practiced testing efforts, despite various research efforts to further increase test automation. Augmented Testing (AT), a novel approach for GUI testing, aims to aid manual GUI-based testing through a tool-supported approach where an intermediary visual layer is rendered between the system under test (SUT) and the tester, superimposing relevant test information.ObjectiveThe primary objective of this study is to gather empirical evidence regarding AT’s efficiency compared to manual GUI-based regression testing. Existing studies involving testing approaches under the AT definition primarily focus on exploratory GUI testing, leaving a gap in the context of regression testing. As a secondary objective, we investigate AT’s benefits, drawbacks, and usability issues when deployed with the demonstrator tool, Scout.MethodWe conducted an experiment involving 13 industry professionals, from six companies, comparing AT to manual GUI-based regression testing. These results were complemented by interviews and Bayesian data analysis (BDA) of the study’s quantitative results.ResultsThe results of the Bayesian data analysis revealed that the use of AT shortens test durations in 70% of the cases on average, concluding that AT is more efficient. When comparing the means of the total duration to perform all tests, AT reduced the test duration by 36% in total. Participant interviews highlighted nine benefits and eleven drawbacks of AT, while observations revealed four usability issues.ConclusionThis study presents empirical evidence of improved efficiency using AT in the context of manual GUI-based regression testing. We further report AT’s benefits, drawbacks, and usability issues. The majority of identified usability issues and drawbacks can be attributed to the tool implementation of AT and, thus, can serve as valuable input for future tool development.

Directed self-assembly software for single cell deposition.

Laser direct-write (LDW) bioprinting methods offer a diverse set of tools to design experiments, fabricate tissue constructs and to cellular microenvironments all in a CAD/CAM manner. To date, we have just scratched the surface of the system’s potential and for LDW to be utilized to its fullest, there are many distinct hardware and software components that must be integrated and communicate seamlessly. In this perspective article, we detail the development of novel graphical user interface (GUI) software to improve LDW capability and functionality. The main modules in the control software correspond to cell transfer, microbead fabrication, and micromachining. The modules make the control of each of these features, and the management of printing programs that utilize one or more features, to be facile. The software also addresses problems related to construct scale-up, print speed, experimental conditions, and management of sensor data. The control software and possibilities for integrated sensor data are presented.

The daughter–parent plot: a tool for analyzing thermochronological data

Abstract. Data plots of daughter against parent concentration (D–P plots) are a potential tool for analyzing low-temperature thermochronology, similar to isochron plots in radioisotopic geochronology. Their purposes are to visualize the main term of the radiometric age equation – the daughter–parent ratio – and to inspect the daughter–parent relationship for anomalies indicating influences of geological processes or analytical bias. The main advantages of the D–P plot over other data analysis tools are (1) its ability to detect systematic offsets in D and P concentrations, (2) its unambiguous representation of radiation-damage-dependent daughter retention, and (3) the possibility to analyze potential age outliers. Despite these benefits, the D–P plot is currently not used for analyzing low-temperature thermochronology data, e.g., from fission-track, (U–Th) / He, or zircon Raman dating. We present a simple, decision-tree-based classification for daughter–parent relationships based on the D–P plot that places a dataset into one of seven classes: linear relationship with zero intercept, cluster, linear relationship with systematic offset, nonlinear relationship, several age populations, scattered data, and inverse relationship. Assigning a class to a dataset enables choosing further data analysis steps and how to report a sample age, e.g., as a pooled, central, or isochron age or a range of ages. This classification scheme aims at facilitating thermochronological data analysis and making decisions more transparent. We demonstrate the proposed procedure by analyzing published datasets from a variety of geological settings and thermochronometers and introduce Incaplot, which is graphical user interface software that we developed to facilitate D–P plotting of thermochronology data.

From SARS-CoV-2 to Global Preparedness: A Graphical Interface for Standardised High-Throughput Bioinformatics Analysis in Pandemic Scenarios and Surveillance of Drug Resistance.

The COVID-19 pandemic highlighted the need for a rapid, convenient, and scalable diagnostic method for detecting a novel pathogen amidst a global pandemic. While command-line interface tools offer automation for SARS-CoV-2 Oxford Nanopore Technology sequencing data analysis, they are inapplicable to users with limited programming skills. A solution is to establish such automated workflows within a graphical user interface software. We developed two workflows in the software Geneious Prime 2022.1.1, adapted for data obtained from the Midnight and Artic's nCoV-2019 sequencing protocols. Both workflows perform trimming, read mapping, consensus generation, and annotation on SARS-CoV-2 Nanopore sequencing data. Additionally, one workflow includes phylogenetic assignment using the bioinformatic tools pangolin and Nextclade as plugins. The basic workflow was validated in 2020, adhering to the requirements of the European Centre for Disease Prevention and Control for SARS-CoV-2 sequencing and analysis. The enhanced workflow, providing phylogenetic assignment, underwent validation at Uppsala University Hospital by analysing 96 clinical samples. It provided accurate diagnoses matching the original results of the basic workflow while also reducing manual clicks and analysis time. These bioinformatic workflows streamline SARS-CoV-2 Nanopore data analysis in Geneious Prime, saving time and manual work for operators lacking programming knowledge.

Design and Implementation of a Cost‐Effective, Portable Impedance Analyzer Device with AD5941

This study proposes a cost‐effective, small‐size, and portable impedance analyzer using the AD5941 Analog Front End (AFE) that makes frequency sweep measurement for various applications. The design utilizes a microcontroller and an AD5941 circuit for impedance measurement. The AD541 is a high precision impedance converter system that consists of a 16‐bit, 1.6 MSPS, analog to digital converter (ADC), an integrated waveform generator, and a digital signal processing (DSP) block. The AD5941 has many advantages over the AD5933 which was used in numerous studies in the past decade. Also, the device implements the four‐wire impedance method which is an impedance measuring technique that reduces the effect of electrodes to achieve higher accuracy. A supporting Graphic User Interface (GUI) software is employed to control the Impedance Analyzer device and to visualize the measurement. This impedance analyzer achieves a frequency resolution of 0.015 Hz and can generate sinusoid up to 200 kHz. In frequency range from 10 kHz to 150 kHz, the device can measure impedance in the range of 10 Ω–100 kΩ with less than 4.3% of error in comparison with benchtop impedance analyzer, Microtest 6632. Moreover, our impedance measurement device has undergone testing involving human calf measurements and electrochemical quantification, particularly for estimating Sodium Chlorite. The experimental outcomes demonstrate that our design not only fulfills the criteria of an impedance analyzer device but also performs effectively across diverse applications. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Machine learning-based prediction and experimental validation of heavy metal adsorption capacity of bentonite

As a natural adsorbent material, bentonite is widely used in the field of heavy metal adsorption. The heavy metal adsorption capacity of bentonite varies significantly in studies due to the differences in the properties of bentonite, solution, and heavy metal. To achieve accurate predictions of bentonite's heavy metal adsorption capacity, this study employed six machine learning (ML) regression algorithms to investigate the adsorption characteristics of bentonite. Finally, an eXtreme Gradient Boosting Regression (XGB) model with outstanding predictive performance was constructed. Explanation analysis of the XGB model further reveal the importance and influence manner of each input feature in predicting the heavy metal adsorption capacity of bentonite. The feature categories influencing heavy metal adsorption capacity were ranked in order of importance as adsorption conditions > bentonite properties > heavy metal properties. Furthermore, a web-based graphical user interface (GUI) software was developed, facilitating researchers and engineers to conveniently use the XGB model for predicting the heavy metal adsorption capacity of bentonite. This study provides new insights into the adsorption behaviors of bentonite for heavy metals, offering guidance and support for enhancing its application efficiency and addressing heavy metal pollution remediation.

An improved approach for early diagnosis of Parkinson’s disease using advanced DL models and image alignment

An innovative approach to enhance image alignment through affine transformation, allowing images to be rotated from 0 to 135 degrees. This transformation is a crucial step in improving the diagnostic process, as image misalignment can lead to inaccurate results. The accurate alignment sets the stage for a robust U-Net model, which excels in image segmentation. Precise segmentation is vital for isolating affected brain regions, aiding in the identification of PD-related anomalies. Finally, we introduce the DenseNet architecture model for disease classification, distinguishing between PD and non-PD cases. The combination of these DL models outperforms existing diagnostic approaches in terms of acceptance precision (99.45%), accuracy (99.95%), sensitivity (99.67%), and F1-score (99.84%). In addition, we have developed user-friendly graphical interface software that enables efficient and reasonably accurate class detection via Magnetic Resonance Imaging (MRI). This software exhibits superior efficiency contrasted to current cutting-edges technique, presenting an encouraging opportunity for early disease detection. In summary, our research tackles the problem of low accuracy in existing PD diagnostic models and addresses the critical need for more precise and timely PD diagnoses. By enhancing image alignment and employing advanced DL models, we have achieved substantial improvements in diagnostic accuracy and provided a valuable tool for early PD detection.

HormoneBayes: A novel Bayesian framework for the analysis of pulsatile hormone dynamics.

The hypothalamus is the central regulator of reproductive hormone secretion. Pulsatile secretion of gonadotropin releasing hormone (GnRH) is fundamental to physiological stimulation of the pituitary gland to release luteinizing hormone (LH) and follicle stimulating hormone (FSH). Furthermore, GnRH pulsatility is altered in common reproductive disorders such as polycystic ovary syndrome (PCOS) and hypothalamic amenorrhea (HA). LH is measured routinely in clinical practice using an automated chemiluminescent immunoassay method and is the gold standard surrogate marker of GnRH. LH can be measured at frequent intervals (e.g., 10 minutely) to assess GnRH/LH pulsatility. However, this is rarely done in clinical practice because it is resource intensive, and there is no open-access, graphical interface software for computational analysis of the LH data available to clinicians. Here we present hormoneBayes, a novel open-access Bayesian framework that can be easily applied to reliably analyze serial LH measurements to assess LH pulsatility. The framework utilizes parsimonious models to simulate hypothalamic signals that drive LH dynamics, together with state-of-the-art (sequential) Monte-Carlo methods to infer key parameters and latent hypothalamic dynamics. We show that this method provides estimates for key pulse parameters including inter-pulse interval, secretion and clearance rates and identifies LH pulses in line with the widely used deconvolution method. We show that these parameters can distinguish LH pulsatility in different clinical contexts including in reproductive health and disease in men and women (e.g., healthy men, healthy women before and after menopause, women with HA or PCOS). A further advantage of hormoneBayes is that our mathematical approach provides a quantified estimation of uncertainty. Our framework will complement methods enabling real-time in-vivo hormone monitoring and therefore has the potential to assist translation of personalized, data-driven, clinical care of patients presenting with conditions of reproductive hormone dysfunction.

Multi-channel magnetic resonance spectroscopy graphical user interface (McMRSGUI).

This work introduces an open-sourced graphical user interface (GUI) software enabling the combination of multi-channel magnetic resonance spectroscopy data with different literature-based methods for the improvement of the quality and reliability of combined spectra. The multi-channel magnetic resonance spectroscopy graphical user interface (McMRSGUI) is a MATLAB-based spectroscopy processing GUI equipped to load multi-channel MRS data, pre-process, combine, and export combined data for evaluation with open-source quantification software (jMRUI). A literature-based, decision-tree process was incorporated into the combination type selection to serve as a guide to minimize spectral distortion in selecting between weighting methods. Multi-channel, simulated spectra were combined with the different combination techniques and evaluated for spectral distortion to validate the code. The incorporation of the combination methods into a single processing software enables multi-channel magnetic resonance spectroscopy (MRS) data to be combined and compared for improved spectral quality with little user knowledge of combination techniques. Through the spectral peak distortion simulation of the combination methods, combined signal-to-noise ratio (SNR) values from the literature were verified. The spectral peak distortion simulation provides a secondary tool for researchers to estimate the spectral SNR levels when spectral distortion could occur and use this knowledge to further guide the selection of their combination technique. The McMRSGUI provides a software toolkit for evaluating multi-channel MRS data and their combination. Simulations evaluating spectral distortion at different noise levels were performed for each combination method to validate the GUI and demonstrate a method for researchers to assess the combined SNR levels at which they could be introducing spectral distortion.

NeuroClick: software for mimicking click reaction to generate drug-like molecules permeating the blood-brain barrier.

Background: Traditional methods for chemical library generation in virtual screening often impose limitations on the accessible chemical space or produce synthetically irrelevant structures. Incorporating common chemical reactions into generative algorithms could offer significant benefits. Materials & methods: In this study, we developed NeuroClick, a graphical user interface software designed to perform in silico azide-alkyne cycloaddition, a widely utilized synthetic approach in modern medicinal chemistry. Results & conclusion: NeuroClick facilitates the generation and filtering of large combinatorial libraries at a remarkable rate of 10,000 molecules per minute. Moreover, the generated products can be filtered to identify subsets of pharmaceutically relevant compounds based on Lipinski's rule of five and blood-brain barrier permeability prediction. We demonstrate the utility of NeuroClick by generating and filtering several thousand molecules for dopamine D3 receptor ligand screening.

TreeViewer: Flexible, modular software to visualise and manipulate phylogenetic trees.

Phylogenetic trees illustrate evolutionary relationships between taxa or genes. Tree figures are crucial when presenting results and data, and by creating clear and effective plots, researchers can describe many kinds of evolutionary patterns. However, producing tree plots can be a time-consuming task, especially as multiple different programs are often needed to adjust and illustrate all data associated with a tree. We present TreeViewer, a new software to draw phylogenetic trees. TreeViewer is flexible, modular, and user-friendly. Plots are produced as the result of a user-defined pipeline, which can be finely customised and easily applied to different trees. Every feature of the program is documented and easily accessible, either in the online manual or within the program's interface. We show how TreeViewer can be used to produce publication-ready figures, saving time by not requiring additional graphical post-processing tools. TreeViewer is freely available for Windows, macOS, and Linux operating systems and distributed under an AGPLv3 licence from https://treeviewer.org. It has a graphical user interface (GUI), as well as a command-line interface, which is useful to work with very large trees and for automated pipelines. A detailed user manual with examples and tutorials is also available. TreeViewer is mainly aimed at users wishing to produce highly customised, publication-quality tree figures using a single GUI software tool. Compared to other GUI tools, TreeViewer offers a richer feature set and a finer degree of customisation. Compared to command-line-based tools and software libraries, TreeViewer's graphical interface is more accessible. The flexibility of TreeViewer's approach to phylogenetic tree plotting enables the program to produce a wide variety of publication-ready figures. Users are encouraged to create their own custom modules to expand the functionalities of the program. This sets the scene for an ever-expanding and ever-adapting software framework that can easily adjust to respond to new challenges.

Thermotopes-COH—A software for carbon isotope modeling and speciation of COH fluids

Carbon-bearing fluids and condensed carbon are common on and inside planetary bodies. Understanding the mechanisms capable of transferring carbon from fluids into solids and vice-versa is central in many fundamental and applied research targets within the Earth and Planetary Sciences. A broad range of applications can benefit from the thermodynamic properties of carbon-oxygen-hydrogen (COH) systems. As an example, the precipitation of natural graphite or diamond can be modeled within the COH thermodynamic systems. Because the evolution of COH fluids implies isotopic fractionation among different species, carbon stable isotopes can be used in conjunction with thermodynamic calculations to reconstruct graphite or diamond formation mechanisms, or the evolution of fluid species such as carbon dioxide or methane.Thermotopes-COH is a Python-based graphical user interface (GUI) software for computation of thermodynamic and carbon isotopic modeling in the C–O–H system within the 0.1–5 GPa and 300–900 °C range. The software allows generic and process-oriented thermodynamic and carbon stable isotope calculations including fluid mixing, fluid-graphite/diamond interactions with changing pressure or temperature, and fluid desiccation. This versatile numerical tool is designed to model processes of dissolution/precipitation of graphite or diamond. Along with a description of the software functions, this contribution also provides practical examples.

Operational strategy of reconfigurable membrane process for bio-based amino acid production

Reconfigurable manufacturing systems can rapidly and economically transform production facilities, allowing for the simultaneous realization of diverse customized product manufacturing and high productivity. In this study, the concept of reconfigurable manufacturing systems was introduced to the counter-current diafiltration membrane process for bio-based amino acid production. A superstructure model adaptable to any counter-current diafiltration cascade configuration was developed. This superstructure model optimizes the objective cost function, minimizing fluctuation costs associated with yield and utility. Case studies such as the production of L-lysine, L-arginine, and L-tryptophan were considered. Sensitivity analysis indicated that when membrane capacity becomes limited due to increased overall feed flow rates and decreased permeate flux, the role of the counter-current diafiltration step grows in importance. Circumstances caused by diverse product manufacturing, natural disturbance in bioprocesses, and shifts in productivity and cost priorities based on market dynamics indicate the promising economic potential of reconfigurable membrane systems. Since scalability, diagnosability, customization, modularity, and integrability are high, the reconfigurable membrane system has proven its capability to flexibly adapt to continuously changing conditions. All superstructure modeling and simulations in this study were executed using in-house graphical user interface software.

On the Optimization of the Protocol for Automated Radiosyntheses of [68Ga]Ga-Pentixafor, [68Ga]Ga-FAPI-4 and [68Ga]Ga-DOTATATE in a Modular-Lab Standard.

The present work describes the automated radiochemical synthesis of different PET tracers like [68Ga]Ga-Pentixafor, [68Ga]Ga-FAPI-4 and [68Ga]Ga-DOTATATE using optimized single protocol in the non-cassette based Eckert & Ziegler (EZ) Modular Lab (fixed tubing system) without any modification in the inbuilt human machine interface (HMI) software. Recently, PET agents viz. [68Ga]Ga-Pentixafor and [68Ga]Ga-FAPI-4 are gaining prominence for the diagnosis of overexpressed Chemokine Receptor-4 (CXCR4) and Fibroblast Activation Protein (FAP) receptor, respectively, in the microenvironment of numerous cancer types. The promising results observed with the clinical usage of [68Ga]Ga-DOTATATE produced using the automated protocol, provided impetus for the clinical translation of [68Ga]Ga-Pentixafor and [68Ga]Ga-FAPI-4 using the in-house developed automated radiolabeling protocol. Herein we report a single radiolabeling protocol for the automated preparation of [68Ga]Ga-Pentixafor and [68Ga]Ga-FAPI-4 in the non-cassette based EZ Modular-Lab Standard radiochemistry module, without any changes in schematic, graphical user interface (GUI) software and time list, from that used for routine production of [68Ga]Ga-DOTATATE in our centre, since 2015. Physico-chemical quality control and in-vitro stability analyses were carried out using radio-TLC and radio-HPLC. The automated protocol yielded reliable and consistent non-decay corrected (ndc) radiochemical yield (RCY) of (84.4%±0.9%) and (85.5%±1.4%) respectively, for [68Ga]Ga-Pentixafor and [68Ga]Ga-FAPI-4, with RCP>98%, which are comparable to the RCY of (84.4%±1.2%) and RCP (99.1%±0.3%) for [68Ga]Ga-DOTATATE. The biological quality control studies confirmed the formulations to be of ready-to-use pharmaceutical grade. The consistent and reliable RCY and RCP of multiple 68Ga-labeled PET tracers by single automated radiochemistry protocol exhibits the versatility of the EZ Modular Lab.

Projection mapping system for laser speckle contrast image: feasibility study for clinical application.

Laser speckle contrast images (LSCIs) have been utilized to monitor blood flow perfusion. However, they have conventionally been observed on monitor screens, resulting in potential spatial mismatching between the imaging region of interest (IROI) and monitor screen. This study proposes a projection mapping (PM) system for LSCIs (PMS_LSCI) that projects LSCIs to directly observe the blood flow perfusion in the IROI. The PMS_LSCI consists of a camera, imaging optics, a laser projector, and graphic user interface software. The spatial matching in the regions of interest was performed by adjusting the software screen of the LSCI in the IROI and evaluated by conducting in-vitro and in-vivo studies. An additional in-vivo study was performed to investigate the feasibility of real-time PM of the LSCI. The spatial mismatching in the regions of interest was ranged from 2.74% to 6.47% depending on the surface curvature. The PMS_LSCI could enable real-time PM of LSCI at four different blood flow states depending on blood pressure. The PMS_LSCI projects the LSCI in the IROI by interacting with a projector instead of the monitor screen. The PMS_LSCI presented clinical feasibility in the in-vitro and in-vivo studies.

An Analytical Model for Weak Avalanche Induced Kink Effect of PDSOI nMOSFETs

Silicon-on-insulator (SOI) devices and circuits are widely used in semiconductor industry for its superior natures on integration density, isolations degree. Inefficient body contact of partially-depleted SOI (PDSOI) devices cannot evacuate excess carriers which transported from the weak avalanche multiplication of pinch-off region at high drain voltage bias. These accumulated carriers elevate the internal body potential and trigger electrical effects namely the body bias effect of threshold voltage and the turn-on of parasitic bipolar junction transistor (BJT). A comprehensive analytical model which include all these mechanisms are proposed to describe this kink effect. This model is constructed by an equivalent circuit and five strong nonlinearly coupled equations to describe the electrical behaviors. To solve these equations, a C <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$++$</tex-math> </inline-formula> Qt-based graphical interface software is developed for the parameter extraction of the model. The fixed point iteration algorithm are adopted for the solution of equations. The effectiveness and accuracy of this model are verified by the T-gate shaped PDSOI nMOSFETs of 130 nm manufacturing process node. It can predict the electrical behaviors of kink effect. This is meaningful for the circuit simulation of PDSOI platform.

Design, Development and Testing of a Monitoring System for the Study of Proton Exchange Fuel Cells and Stacks.

This article is about the design, development and validation of a new monitoring architecture for individual cells and stacks to facilitate the study of proton exchange fuel cells. The system consists of four main elements: input signals, signal processing boards, analogue-to-digital converters (ADCs) and a master terminal unit (MTU). The latter integrates a high-level graphic user interface (GUI) software developed by National Instruments LABVIEW, while the ADCs are based on three digital acquisition units (DAQs). Graphs showing the temperature, currents and voltages in individual cells as well as stacks are integrated for ease of reference. The system validation was carried out both in static and dynamic modes of operation using a Ballard Nexa 1.2 kW fuel cell fed by a hydrogen cylinder, with a Prodigit 32612 electronic load at the output. The system was able to measure the voltage distributions of individual cells, and temperatures at different equidistant points of the stack both with and without an external load, validating its use as an indispensable tool for the study and characterization of these systems.

Development of Graphical Interface Software for Solar Flare Monitoring System

Solar activity such as solar flares causes increased X-ray and ultraviolet ray flux. This event will cause sudden ionospheric disturbances (SID) and disrupts the communication systems as well as the space-based equipment on Earth. Public awareness especially to school students on the effects of solar activities towards humans on Earth is very important as the dependency of human daily life on space technology is increasing. The awareness has been conducted by the Space Science Center, Institute of Climate Change, UKM using UKM-SID™ system. Based on the program, it was found that school student experienced constraints in the process of analyzing data due to the absence of computers in schools. Therefore, UKM-SID™ system, with portable kit equipped with an interactive software to produce an easy-to-understand figure, was proposed. An algorithm was also developed to transfer the observed data onto the server in near real time. The developed Graphical Interface software showed a visualized sunrise and sunset patterns which is in agreement with the previous study. A solar flare was detected on 1 December 2020. The observed data is also successfully uploaded onto the server in near real time. Result shows that this new UKM-SID™ system is able to capture the solar flare occurrence. This new system is also at an optimal and sophisticated level compared to the technology that has been used. Hence, the researchers believe the UKM-SID™ is able to help educators, students and the general public in the learning of space science more effectively.

Device for Dual Ultrasound and Dry Needling Trigger Points Treatment.

Ultrasound is a well-known tool to produce thermal and non-thermal effects on cells and tissues. These effects require an appropriate application of ultrasound in terms of localization and acoustic energy delivered. This article describes a new device that combines ultrasound and dry needling treatments. The non-thermal effects of ultrasound should locally amplify the needle's effects. The ultrasound transducer can mechanically rotate in 3D space to align itself in the direction of the needle. The transducer electronically focuses the acoustic pressure automatically on the needle tip and its surroundings. A computer, using graphical interface software, controls the angulation of the array and the focus position.