The purpose of this study is to analyze the relationship between industrial digital strategy in the area of transformational technopreneurship development and analyze the relationship between human creativity in the area of transformational technopreneurship development. This study uses a quantitative approach with an explanatory research design, which aims to examine the influence of integrity, organizational commitment, and motivation on sustainable employee performance with job satisfaction as a mediating variable. The population consists of all employees of SME organizations, totaling 765 employees. The sampling technique applied is simple random sampling. The research instrument is a questionnaire using a 5-point Likert scale. The research variables are: Digital Work Environment (X1), Job Satisfaction (X2), Organizational Culture (X3) and Employee Work Productivity (Y). Data were analyzed using Partial Least Square – Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The analysis consists of two stages: Outer Model (Measurement Model): Convergent validity, discriminant validity, and reliability testing. Inner Model (Structural Model): Testing path coefficients, R² values, and direct and indirect influences between variables. The results of the study show that the Industrial digital strategy variable has a positive relationship with the transformational development area of technopreneurship, human creativity has a positive relationship with the transformational development area of technopreneurship.

The purpose of this study is to analyze the relationship between e-CRM (Electronic Customer Relationship Management) variables on e-Loyalty of online shop customers, e-WOM (electronic word-of-mouth) on e-Loyalty of online shop customers, and e-service quality on e-Loyalty of online shop customers. This study uses a quantitative approach. The population consists of all online shop consumers, and the sample of this study is 765 online shop consumers. The sampling technique used is simple random sampling. The research instrument is a questionnaire with a 7-point Likert scale. The research variables include e-CRM (Electronic Customer Relationship Management), e-WOM (electronic word-of-mouth), e-service quality, and e-Loyalty. Data were analyzed using Partial Least Square – Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The analysis consists of two stages: Outer Model (Measurement Model): Testing convergent validity, discriminant validity, and reliability. Inner Model (Structural Model): Testing path coefficients, R² values, and direct effects or hypothesis testing. The results of this study are E-CRM (Electronic Customer Relationship Management) has a positive relationship on e-Loyalty of online shop Customers, e-WOM (electronic word-of-mouth) has a positive relationship on e-Loyalty of online shop Customers, E-service quality has a positive relationship on e-Loyalty of online shop Customers. Optimal implementation of E-CRM, e-WOM and E-service quality through applications or websites can improve the overall user experience, which will ultimately encourage e-loyalty.

This paper proposes Social-only Particle Swarm Optimization-based Iterative Learning Control (SO-PSO-ILC) to address the limitations of conventional Iterative Learning Control (ILC) in model dependency and manual parameter tuning. The proposed method autonomously optimizes the learning gain using a social-only PSO variant. Comparative results on four distinct trajectories demonstrate superior performance: SO-PSO-ILC achieved a final RMSE of 0.0008 m in the linear path test and a precision 4.6 times higher than the baseline in the waveform path test. It also exhibits the fastest convergence rate, outperforming PSO-ILC in tracking accuracy and computational complexity while avoiding the convergence issues observed in WSA-ILC. The simulation results validate that swarm-optimized ILC provides a robust framework for repetitive tasks requiring high accuracy.

Digital microfluidic biochips (DMFBs) find extensive applications in biochemical experiments, medical diagnostics, and safety-critical domains, with their reliability dependent on efficient online testing technologies. However, traditional random search algorithms suffer from slow convergence and susceptibility to local optima under complex fluidic constraints. This paper proposes a hybrid optimization method based on priority strategy and an improved sparrow search algorithm for DMFB online test path planning. At the algorithmic level, the improved sparrow search algorithm incorporates three main components: tent chaotic mapping for population initialization, cosine adaptive weights together with Elite Opposition-based Learning (EOBL) to balance global exploration and local exploitation, and a Gaussian perturbation mechanism for fine-grained refinement of promising solutions. Concurrently, this paper proposes an intelligent rescue strategy that integrates global graph-theoretic pathfinding, local greedy heuristics, and space–time constraint verification to establish a closed-loop decision-making system. The experimental results show that the proposed algorithm is efficient. On the standard 7 × 7–15 × 15 DMFB benchmark chips, the shortest offline test path length obtained by the algorithm is equal to the length of the Euler path, indicating that, for these regular layouts, the shortest test path has reached the known optimal value. In both offline and online testing, the shortest paths found by the proposed method are better than or equal to those of existing mainstream algorithms. In particular, for the 15 × 15 chip under online testing, the proposed method reduces the path length from 543 and 471 to 446 compared with the IPSO and IACA algorithms, respectively, and reduces the standard deviation by 53.14% and 39.4% compared with IGWO in offline and online testing.

Purpose: This study develops a beginner-oriented roadmap for applying PLS-SEM in SmartPLS, addressing the gaps between theory and practical application. Methods: Using an instructional design-based approach, simulated datasets with six latent constructs were analysed in SmartPLS 4 to demonstrate key steps in measurement validation, structural path testing and model evaluation. Results: The demonstrations shows both acceptable and problematic validity outcomes, highlighting how reliability, discriminant validity and model fit can be refined. The results are pedagogical, not statistically generalizable and shows methodological learning rather than empirical findings. Conclusion: This study provides novice researchers’ and educators with a structured, practice-oriented guide that transforms common PLS-SEM pitfalls into learning opportunities, enhancing methodological literacy.

Evidence on homologous recombination repair (HRR) mutation prevalence in prostate cancer (PC) patients and the diagnostic testing path to guide treatment remains limited outside of clinical trials. The objective of this study was to investigate the DNA source, type of tumor tissue, timing for testing in the patient's disease course, and rate of conclusive results in a real-world population. This was an observational, cohort study, involving 20 Italian cancer centers. The study population included consecutive PC patients undergoing germline, tumor, and/or plasma circulating tumor DNA (ctDNA) to profile HRR genes between January 1, 2020 and January 31, 2025. Among 1400 PC patients included, 248 (17.7%) showed (likely)pathogenic variants (PVs) in the HRR genes. Most HRR testing was conducted during the metastatic castration-resistant PC (mCRPC)(779, 62.8%). The rate of conclusive results was 89.7% and varied widely according to the type of tumor tissue. The prevalence of HRR alterations was 18.1% in the mCRPC and 13.8% in the hormone-sensitive PC (P = .06). The concordance between tumor testing and ctDNA was 83.9%. Interestingly, 4.6% reported ctDNA testing positive but tumor testing negative, leading to important therapeutic implications. The prevalence of positive ctDNA testing was 47.4% vs 10.5%, for testing within 1 month or over 3 months, respectively, from the initiation of a new line of therapy. This large real-world study, through the workflow adopted by clinicians for HRR genomic testing, provides novel insights into the variables influencing the success rate of genomic testing.

Introduction We study whether gravity-like kinematics (bending, time-delay, redshift-like shifts, capture/orbits) can arise as media analogs from a deterministic scalar-field propagation model without invoking mass or spacetime curvature. Methods We evolve a real scalar field under a spatially varying symmetric positive-definite transport tensor R(x) and non-negative damping field Λ(x) ; with source off ( S≡0 ). Thirteen simulations quantify deflection, transit delay with escape thresholds, collapse/trapping and orbital containment, anisotropy-induced drift, repulsion under curvature inversion, and interference. We monitor energy budgets (Rayleigh loss + boundary flux) and check spectral safety and robustness. Results Observables are reproducible on 256 × 256 grids with 512 × 512 confirmations for key cases. Bending scales with ∥∇R∥ and flips sign under gradient reversal; transit delay increases monotonically with ∫Λdx and can prevent exit; bounded orbits satisfy a/p ≤1.15 over a finite capture band; radial drift in 1/ r 2 profiles follows | r ̇ |∝ r^(-α) with a ≈2; transverse drift sign matches sign( R xy ); interference visibility follows a cosine in relative phase. Discussion Results constitute operational gravitational analogs—transport and loss in structured media—rather than statements about spacetime curvature. We release code/configs/outputs for full reproducibility and outline laboratory test paths.

This study aims to examine the extent to which Sharia-based financing—comprising murabahah, musyarakah, mudharabah, qard, istishna, and ijarah contracts—affects the profitability of Islamic Commercial Banks in Indonesia, with non-performing financing (NPF) serving as a mediating variable.Data were collected from annual reports, the official websites of the OJK, IDX, and sample companies during the period 2020–2024, then analyzed using multiple linear regression and path analysis. The regression results indicate that all types of financing significantly influence profitability, with the largest contribution coming from istishna (β = 96.277; p < 0.001), followed by musyarakah (β = 71.895; p < 0.001), and mudharabah (β = 39.244; p < 0.001). Conversely, ijarah shows a negative effect on profitability (β = –2.598; p = 0.034). Regression analysis of NPF indicates that mudharabah, istishna, and ijarah have a significant positive effect on NPF, while murabahah, musyarakah, and qard have no significant effect. Path testing reveals that there is no mediation of NPF in the relationship between murabahah and profitability. However, significant mediation by NPF was found in the relationship between musyarakah, mudharabah, qard, istishna, and ijarah on profitability. These findings confirm that the effectiveness of Islamic financing in improving profitability is not only determined by the type of contract used but also highly dependent on the quality of financing risk management reflected in the NPF level.

Scheme design of cable insulation path testing system based on CPCI bus

This study addresses the inefficiency and error-prone nature of manual counseling and student violation point recording processes in schools, which often result in delays and inaccuracies. To overcome these challenges, we propose the development of a digital guidance and counseling service system designed to improve data management and enhance service accessibility for school administrators and counselors. The innovation lies in the creation of an integrated, browser-accessible application built using the MERN (MongoDB, Express.js, React, Node.js) stack, which ensures robust functionality and scalability. By applying modern development and testing methodologies, the system is designed to be both reliable and user-friendly. The core objective of this system is to streamline processes such as counseling appointment scheduling, alumni tracking, certificate submission, and student behavior reporting. It was developed using the Extreme Programming (XP) methodology, which encourages flexibility and iterative planning through close collaboration with end users. White Box Testing techniques, including cyclomatic complexity analysis and independent path testing, were employed to validate the system's internal logic. The system’s usability was assessed using the System Usability Scale (SUS), achieving an excellent score of 93.25, indicating high user satisfaction. Furthermore, the Lighthouse performance test yielded a perfect score of 100, confirming the system's high responsiveness. These results demonstrate that the developed system significantly enhances the efficiency, accuracy, and accessibility of guidance services, reduces administrative burdens, and enables better monitoring of student development, making it ideal for deployment in real-world school environments.

This study examines the mediation path of motivation in linking self-efficacy and non-physical work environment to the performance of the State Civil Apparatus. The research was conducted using a quantitative approach. The population was 90 employees of AK-Tekstil Solo with stratified sampling from the population resulting in a sample of 61 respondents. Data were collected through questionnaires, analysed with a structural equation modeling (SEM) approach assisted by the SmartPLS version 3 application. The results show that self-efficacy has a positive and significant effect, both on motivation and performance. Non-physical work environment has a positive and significant effect on motivation, but not on performance. Motivation affects performance positively and significantly. Path testing revealed that motivation failed to mediate self-efficacy on performance, whereas motivation showed a perfect mediating effect between non-physical work environment and performance. The fact that self-efficacy has a direct effect on performance without the need for mediation and the non-physical work environment only impacts performance indirectly through increased motivation implies that strengthening self-efficacy and creating a work environment that supports motivation are important strategies to maximize performance.

In this paper, RF sub-modules with millimeter-wave functionality are considered and verified for designing an ultra-wideband receiver (18–40 GHz) required in the electronic support measure (ESM) field. The pre-design of an ultra-wideband super heterodyne receiver (SHR) requires a front-end module (FEM) with four units in the system. Each FEM has four channels with the same path, while the quadrature millimeter down-converter (QMDC) needs to have a converting function that uses a broadband mixer. The FEM includes the ability to provide built-in test (BIT) path functionality to the antenna ports prior to system field installation. Each path of the QMDC requires the consideration of several factors, such as down-converting, broadband gain flatness, and high isolation. As this is an RF module requiring high frequency and wideband characteristics, it is necessary to identify risk factors in advance within a predictable range. Accordingly, the blind-mate A (BMA) connector connection method, the phase-alignment test method in the down-conversion structure, and the LO signal, IF path inflow-blocking method were analyzed and designed.

Ambient monitoring in chemical laboratories and industrial sites that use toxic, hazardous, or flammable materials is essential to protect the lives of workers, material resources, and infrastructure at these sites. In this research paper, we present an innovative approach for developing a low-cost and portable sensor node that detects and warns of hazardous chemical gas and vapor leaks. The system also enables leak location tracking using an indoor tracking and positioning system operating in ultra-wideband (UWB) technology. An array of sensors is used to detect gases, vapors, and airborne particles, while the leak location is identified through a UWB unit integrated with an Internet of Things (IoT) processor. This processor transmits real-time location data and sensor readings via wireless fidelity (Wi-Fi). The real-time indoor positioning system (IPS) can automatically select a tracking area based on the distances measured from the three nearest anchors of the movable sensor node. The environmental sensor data and distances between the node and the anchors are transmitted to the cloud in JSON format via the user datagram protocol (UDP), which allows the fastest possible data rate. A monitoring server was developed in Python to track the movement of the portable sensor node and display live measurements of the environment. The system was tested by selecting different paths between several adjacent areas with a chemical leakage of different volatile organic compounds (VOCs) in the test path. The experimental tests demonstrated good accuracy in both hazardous gas detection and location tracking. The system successfully issued a leak warning for all tested material samples with volumes up to 500 microliters and achieved a positional accuracy of approximately 50 cm under conditions without major obstacles obstructing the UWB signal between the active system units.

In software development, similar apps often encounter similar bugs due to shared functionalities and implementation methods. However, current automated GUI testing methods mainly focus on generating test scripts to cover more pages by analyzing the internal structure of the app, without targeted exploration of paths that may trigger bugs, resulting in low efficiency in bug discovery. Considering that a large number of bug reports on open source platforms can provide external knowledge for testing, this paper proposes BugHunter, a novel bug-aware automated GUI testing approach that generates exploration paths guided by bug reports from similar apps, utilizing a combination of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). Instead of focusing solely on coverage, BugHunter dynamically adapts the testing process to target bug paths, thereby increasing bug detection efficiency. BugHunter first builds a high-quality bug knowledge base from historical bug reports. Then it retrieves relevant reports from this large bug knowledge base using a two-stage retrieval process, and generates test paths based on similar apps’ bug reports. BugHunter also introduces a local and global path-planning mechanism to handle differences in functionality and UI design across apps, and the ambiguous behavior or missing steps in the online bug reports. We evaluate BugHunter on 121 bugs across 71 apps and compare its performance against 16 state-of-the-art baselines. BugHunter achieves 60% improvement in bug detection over the best baseline, with comparable or higher coverage against the baselines. Furthermore, BugHunter successfully detects 49 new crash bugs in real-world apps from Google Play, with 33 bugs fixed, 9 confirmed, and 7 pending feedback.

Based on the data, increasing customers within the company is not only related to the problem of scheduling work and skills in completing marketing, but also regarding how the atmosphere or how to promote products and pay attention to prices and relationships with customers at PT. Smartfren Telecom Tbk. Metro City Branch certainly needs a good promotion and strategy to attract customers so they can compete with other providers. The number of product sales depends on how the company promotes and develops the product brand itself. This study has a goal, namely to whether there is a direct effect on brand image and price on customer loyalty and customer satisfaction. The sample of this research is the customers of PT.Smartfren Telecom Tbk. Metro City branch as many as 36 people. Data collection used a questionnaire, and data analysis used a Validity Test, Reliability Test, Normality Test, Homogeneity Test, Linearity Test and Regression Significance and Path 2 Substructural Analysis with the program (SPSS 20). The results showed that there was a direct effect of Brand Image and Work Environment on Customer Loyalty, there was a direct effect of Brand Image and Work Environment on Customer Satisfaction, and there was a direct effect of Customer Satisfaction on Customer Loyalty.

Exploring the distribution and transmission mechanism of ARGs in crab aquaculture ponds and ditches using metagenomics.

Driver assessment recommendation system to conduct assessment and recommendations of national public transportation driver competency and behavior. To ensure the reliability and stability of the program logic in this system, testing is carried out using the White Box Testing approach, especially the Path Testing method. This method tests each execution path in the program control structure to identify potential logic errors and ensure that each condition has been thoroughly tested. Testing is carried out by calculating cyclomatic complexity, describing the program flowchart, and identifying and tracing independent paths. The test results show that all logic paths have run as expected without any functional defects. This indicates that the system has a strong logic structure and is ready to be integrated into a national-scale operational environment. Thus, Path Testing has proven effective in ensuring system quality in terms of internal structure.

Test case design is a critical task in software testing. Manual test case generation is time-consuming and challenging to maintain. To address these issues, this paper proposes a method for automatically generating test cases based on user interface and flowchart analysis. Firstly, YOLOv8 object detection and EasyOCR text recognition are used to identify control information within the interface. Secondly, the Faker library is utilized to generate corresponding test data. Finally, a text generation program is employed to transform control information and test data into a set of interface test cases. Additionally, a circular traversal algorithm is applied to traverse the flowchart, generating test paths that are combined with interface test cases to form a complete set of test cases. To validate the effectiveness of the method, corresponding tools were developed, and 209 test cases were generated for three systems using this approach. Experimental results demonstrate that our proposed method performs well in terms of test case generation efficiency, defect discovery, and maintainability.

Financial literacy and digital financial inclusion play an important role in SME performance, with financial resilience as a moderating variable. This study aims to evaluate the effect of financial literacy and financial inclusion on entrepreneurial performance. Using a quantitative approach, primary data were collected from 203 SME owners in Sidoarjo and Surabaya through questionnaires. The results of this study indicate that financial literacy has a significant positive impact on digital financial inclusion. Furthermore, digital financial inclusion is proven to significantly influence the improvement of SME entrepreneurial performance. Interestingly, although financial resilience was initially hypothesized to strengthen the relationship between digital financial inclusion and SME performance, the results of the path test showed that its role as a moderating variable was not statistically significant on entrepreneurial performance. This finding emphasizes the importance of efforts to improve financial literacy and expand access to digital financial services in supporting sustainable SME business growth and performance. However, this study also highlights the urgency to continue strengthening SME financial resilience so that they are better able to face various economic challenges and achieve long-term stability The practical implications of this research are recommendations to help SMEs face economic challenges and achieve sustainable growth.

To strengthen the control of key points of projects, enhance management capabilities, effectively guide project planning and operation, and promote the implementation and sustainable development of metro commercial development projects, a structural equation theoretical model of the success of metro commercial development projects was established, with four latent variables: government governance, market governance, social governance, and project cooperation process, and 19 observed variables. Through a questionnaire survey of the “Metro e-Station” project in Tianjin and using the AMOS software for validity, reliability analysis, and path testing, it was found after model revision that social governance has the greatest impact on the success of metro commercial development projects, followed by market governance and government governance, while the direct impact of the project cooperation process is not significant. Analysis of the observed variables revealed that supervision and evaluation, operation management, and supervision and review are more prominent factors affecting the success of metro commercial development projects.