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Rapid GUI prototyping has evolved into a widely applied technique in early stages of software development to facilitate the clarification and refinement of requirements. Especially high-fidelity GUI prototyping has shown to enable productive discussions with customers and mitigate potential misunderstandings, however, the benefits of applying high-fidelity GUI prototypes are accompanied by the disadvantage of being expensive and time-consuming in development and requiring experience to create. In this work, we show RaWi , a data-driven GUI prototyping approach that effectively retrieves GUIs for reuse from a large-scale semi-automatically created GUI repository for mobile apps on the basis of Natural Language (NL) searches to facilitate GUI prototyping and improve its productivity by leveraging the vast GUI prototyping knowledge embodied in the repository. Retrieved GUIs can directly be reused and adapted in the graphical editor of RaWi . Moreover, we present a comprehensive evaluation methodology to enable (i) the systematic evaluation of NL-based GUI ranking methods through a novel high-quality gold standard and conduct an in-depth evaluation of traditional IR and state-of-the-art BERT-based models for GUI ranking, and (ii) the assessment of GUI prototyping productivity accompanied by an extensive user study in a practical GUI prototyping environment.

Currently, the rapid growth of mobile apps requires automated testing technology to ensure their quality. Automated testing of mobile apps is usually closely related to the recognition and judgment of their graphical user interface (GUI), but there usually are numerous isomorphic GUIs with different styles and contents, and similar structure and function in mobile apps. In automatic testing, isomorphic GUI is easy to cause the issue of state space explosion, which leads to low efficiency or failure of testing. In view of the limitations of traditional automatic recognition of isomorphic GUI, this paper presents a GUI similarity judgment approach based on visual feature information. Firstly, the GUI component elements are identified by object detection, and then the GUI skeleton is abstracted. Secondly, the visual features of the GUI skeleton are extracted by a convolutional autoencoder. Finally, the isomorphic GUI judgment is completed by comparing the similarity of GUI visual features. The experimental results show that the proposed approach can effectively shield the influence of GUI style and content, complete the isomorphic GUI recognition more accurately and optimize the efficiency of automated mobile app testing. 当前快速增长的移动应用程序迫切需求自动化测试技术以保证其质量。移动应用的自动化测试与其图形用户界面(GUI)的识别与判断紧密相关, 但移动应用却通常存在大量的样式与内容有差异而结构与功能相类似的同构GUI。在自动化测试中, 同构GUI容易引发应用状态空间的爆炸问题, 进而导致测试的低效或失败。针对传统自动化识别同构GUI的局限性, 提出一种基于视觉特征信息的GUI相似度判断方法。通过目标检测技术识别GUI组件元素进而抽象出GUI结构框架; 采用卷积自编码器提取出GUI结构视觉特征; 对比GUI视觉特征的相似度完成同构GUI判断。经过实验验证, 所提方法能够屏蔽GUI的样式、内容等影响, 从而更精确地完成同构GUI识别, 优化自动化测试效率。

Background The molecular dynamics is an approach to obtain kinetic and thermodynamic characteristics of biomolecular structures. The molecular dynamics simulation softwares are very useful, however, most of them are used in command line form and continue with the same common implementation difficulties that plague researchers who are not computer specialists. Results Here, we have developed the VisualDynamics—a WEB tool developed to automate biological simulations performed in Gromacs using a graphical interface to make molecular dynamics simulation user-friendly task. In this new application the researcher can submit a simulation of the protein in the free form or complexed with a ligand. Can also download the graphics analysis and log files at the end of the simulation. Conclusions VisualDynamics is a tool that will accelerate implementations and learning in the area of molecular dynamics simulation. Freely available at https://visualdynamics.fiocruz.br/login , is supported by all major web browsers. VisualDynamics was developed with Flask, which is a Python-based free and open-source framework for web development. The code is freely available for download at GitHub https://github.com/LABIOQUIM/visualdynamics .

In this paper, a new reactive power market structure is studied and presented. Active power flow by itself causes active and reactive losses. Considering such losses after active power market clearing and in the reactive power market procedure without paying any costs is the main purpose of this paper. For this purpose, new methodologies for reactive power structure are proposed which the reactive losses are considered before market closing. Hence, this study tries to improve reactive power market and create fair competition in reactive power generation through improving the market structure. Also, in this work, the cost payment function of synchronous generators, which has an important influence on reactive power market, is modified. In order to stimulate and describe the proposed methods in the implementation of reactive power market, Cigre 32 bus test system is applied and the proposed methods. As will be shown, the total payment by ISO will be reduced by using the proposed methods.

Context Manual 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. Objective The 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. Method We 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. Results The 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. Conclusion This 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.

Measuring network performance is essential in computer networks, and benchmarking may not be effective for installation in peripheral devices, resulting in replacing those devices and thus increasing cost. In light of this, it is better to have a software system for the network to see its performance rather than the actual design. In this paper, we have developed negative network tomography techniques to infer correlation-level aberrations such as excessive loss rates and delays from path-level measurements. Our system involves placing packet probes in passive monitoring devices on strategic links within the network to learn about network performance with the identification of missing and transmitted packets, and to keep the cost of monitoring and communications infrastructure low. An intuitive graphical user interface(GUI) represents this work provided along with a variety of data, metrics, and statistics related to network results, and this work can be a useful guide for network researchers or other programmers to analyze their networks and understand how to calculate network performance.

Aim Regional disjunction in mountainous regions is ubiquitous and is closely associated with the evolution of mountain biodiversity. However, the mechanisms of maintaining regional disjunction are often ignored, especially regarding the role of ecological barriers. The aim of this study is to test whether an ecological barrier maintains the regional disjunction of Roscoea between the Himalayas (HIM) and the Hengduan Mountains/Yun‐Gui Plateau (HMY). Location The Himalayas and the Hengduan Mountains/Yun‐Gui Plateau, Asia. Taxon Monocot:Zingiberales:Zingiberaceae:Roscoea. Methods Occurrence data from Roscoea were collected from public databases and field investigations. Environmental niche modelling (ENM) was used to predict the potential distribution of Roscoea during the Last Interglacial (LIG), the Last Glacial Maximum (LGM), the present and the future. An environmental variable difference test, principal component analysis (PCA), discriminant function analysis (DFA) and niche identity test were employed to qualify and quantify the contributions of environmental factors to ecological divergence based on 7 and 26 environmental variables. Results Environmental niche modelling predicted an ecological gap of Roscoea between the HIM and the HMY from the LIG into the future, excluding the LGM. Statistically significant differences were detected in eight unique environmental variables across the Gap, which was mostly related to low temperatures and high moisture levels. The PCA, DFA and niche identity test suggested larger ecological separations among the Gap, the HIM and the HMY based on 26 environmental variables than based on seven variables. Main conclusions All clues point to an ecological barrier that has been maintaining the regional disjunction of Roscoea. This ecological barrier is predicted to be stable under future climate change and may reflect long‐term ecological divergence shaped by the adaptation of Roscoea to divergent habitats. Our study highlights that the effects of specific environmental variables, with possible interactions among multiple ecological factors, being closely related to the ecological barrier.

A Brain–Computer Interface (BCI) provides a novel non-muscular communication method via brain signals. A BCI-speller can be considered as one of the first published BCI applications and has opened the gate for many advances in the field. Although many BCI-spellers have been developed during the last few decades, to our knowledge, no reviews have described the different spellers proposed and studied in this vital field. The presented speller systems are categorized according to major BCI paradigms: P300, steady-state visual evoked potential (SSVEP), and motor imagery (MI). Different BCI paradigms require specific electroencephalogram (EEG) signal features and lead to the development of appropriate Graphical User Interfaces (GUIs). The purpose of this review is to consolidate the most successful BCI-spellers published since 2010, while mentioning some other older systems which were built explicitly for spelling purposes. We aim to assist researchers and concerned individuals in the field by illustrating the highlights of different spellers and presenting them in one review. It is almost impossible to carry out an objective comparison between different spellers, as each has its variables, parameters, and conditions. However, the gathered information and the provided taxonomy about different BCI-spellers can be helpful, as it could identify suitable systems for first-hand users, as well as opportunities of development and learning from previous studies for BCI researchers.

Accurate characterization of crystalline materials is critical for advancing low-carbon energy systems, pollution remediation, and sustainable infrastructure—applications where structural precision directly impacts environmental and economic sustainability. This study introduces a Python-based GUI tool that streamlines lattice parameter calculations by integrating the Cramer-Cohen algorithm, which applies Bragg’s law and crystallographic geometry to transform complex analyses into an efficient workflow. The interface enables users to select five crystal systems (cubic, tetragonal, hexagonal, orthorhombic, monoclinic), input X-ray diffraction angles (2θ) and Miller indices ( khl ), and automatically compute lattice parameters. Three-dimensional visualizations enhance interpretability of results, while open-source accessibility ensures broad applicability. Validated against reference data, the tool achieves errors ranging from 0.03% to 2.88%. By bridging advanced material characterization with sustainable development goals, this GUI democratizes crystallographic analysis for interdisciplinary teams, empowering researchers in energy harvesting, catalysis, and eco-friendly material design. Its computational efficiency and user-centric design support transdisciplinary innovation, reinforcing the role of accessible tools in accelerating sustainable technologies.

Vascular dementia (VaD) is the second most prevalent form of dementia, following Alzheimer's disease (AD), and severely impacts life quality of patients. Currently, effective strategies to alleviate symptoms and delay disease progression remain unavailable. Animal studies indicate that Dang Gui Shao Yao San (DGSYS) may enhance cognitive function in VaD models through mechanisms such as antioxidation and the enhancement of cerebral blood flow. However, a systematic review of its neuroprotective effects and a comprehensive assessment of its translational potential in preclinical models are still lacking. This study seeks to synthesize evidence on the intervention effects and underlying mechanisms of DGSYS in animal models of VaD through a systematic review and meta-analysis, so as to offer preclinical evidence to inform future research. A comprehensive literature search was performed across eight databases: China National Knowledge Infrastructure (CNKI), VIP Database for Chinese Technical Periodicals, Wanfang Data, SinoMed, Web of Science, Cochrane Library, PubMed, and EMBASE, to identify studies published from the inception to May 2025 on the effects of DGSYS in animal models of VaD. The primary outcomes were cognitive and behavioral assessments, histopathological alterations in brain tissue, and biomarkers of oxidative stress. The quality of the included studies was assessed using a 10-item checklist, and meta-analysis was conducted with RevMan 5.4 software. Seven studies involving 420 rats and mice were included. DGSYS notably enhanced cognitive and behavioral performance in the animal models. Specifically, DGSYS significantly improved spatial learning and memory performance, as assessed by the Morris water maze, and attenuated oxidative stress-related pathological changes. Current animal studies provide evidence for the multidimensional neuroprotective effects of DGSYS in VaD, with potential mechanisms involving antioxidative stress, inhibition of neuroinflammation, and enhancement of cerebral microcirculation. However, substantial heterogeneity across outcome measures and generally low methodological quality were observed. Overall, the available evidence suggests potential neuroprotective effects of DGSYS in preclinical models, warranting further standardized and rigorously designed studies before clinical translation can be considered. https://www.crd.york.ac.uk/PROSPERO/view/CRD420251058443, identifier CRD420251058443.