Software Platform Research Articles

ForzaETH Race Stack—Scaled Autonomous Head‐to‐Head Racing on Fully Commercial Off‐the‐Shelf Hardware

ABSTRACTAutonomous racing in robotics combines high‐speed dynamics with the necessity for reliability and real‐time decision‐making. While such racing pushes software and hardware to their limits, many existing full‐system solutions necessitate complex, custom hardware and software, and usually focus on Time‐TrIals rather than full unrestricted Head‐to‐head racing, due to financial and safety constraints. This limits their reproducibility, making advancements and replication feasible mostly for well‐resourced laboratories with comprehensive expertise in mechanical, electrical, and robotics fields. Researchers interested in the autonomy domain but with only partial experience in one of these fields, need to spend significant time with familiarization and integration. The ForzaETH Race Stack addresses this gap by providing an autonomous racing software platform designed for F1TENTH, a 1:10 scaled Head‐to‐Head autonomous racing competition, which simplifies replication by using commercial off‐the‐shelf hardware. This approach enhances the competitive aspect of autonomous racing and provides an accessible platform for research and development in the field. The ForzaETH Race Stack is designed with modularity and operational ease of use in mind, allowing customization and adaptability to various environmental conditions, such as track friction and layout, which is exemplified by the various modularly implemented state estimation and control systems. Capable of handling both Time‐Trials and Head‐to‐Head racing, the stack has demonstrated its effectiveness, robustness, and adaptability in the field by winning the official F1TENTH international competition multiple times. Furthermore, the stack demonstrated its reliability and performance at unprecedented scales, up to over on tracks up to 150 m in length.

Gait pathology presented with developmental dysplasia of the hip: a control case study

A well-known and long-term complication of developmental dysplasia of the hip (DDH) is improper gait pattern, early regressive joint disorder, and permanent pain. It can affect the family's psychological, social, and functional parts. This study planned to resolve foot posture and gait analysis across patients with developmental hip dysplasia and correlate it with the control group. Case-control studies determine the main results. We correlated the gait analysis results on the Zebris FDM platform. The case included candidates with DDH under conservative treatment with an abduction brace and a control group with healthy participants. This study was conducted at King Abdullah Specialized Children Hospital, Riyadh, in the Kingdom of Saudi Arabia. This research enclosed 445 outcomes with DDH and 168 for the control category. The Sign test presented a significant diversity in Zebris FDM outcomes between DDH and the control group, especially in left foot external rotation with a p-value of 0.01 (left hip mean of 4.53, n=445, SD 8.78). A significant variation was present in step width, stance phase on both legs, single support, load response, swing phase, pre-swing, and a double support p-value of 0.00 (p<0.05). W-sitting was preferred in 256 (n=445, 58%) of the DDH results and by 61 (n=168, 36%) from the control group. This study's outcomes presented a greater risk of pronation on the left foot and gait alteration on the right lower limb. The gait investigation presented a clear description of its patterns in paediatrics with DDH. Analyzing the gait among the DDH and the control group demonstrated a variation in each gait outcome from Zebris FDM platform software. DDH has a negative response on the gait pattern and foot posture, this is a great consequence presented in connection with Saudi applicants. Keywords: FDM, DDH, gait, control group, Kingdom of Saudi Arabia

Targets and Mechanisms of Resveratrol against Endothelial-Mesenchymal Transition in Atherosclerosis: A Network Pharmacology Analysis Combined with In vivo Experiments

Background: Atherosclerosis (AS) is a chronic inflammatory disease characterized by plaque formation and endothelial dysfunction. Under pro-inflammatory conditions, the endothelial-mesenchymal transition (EndMT) plays an important role in the pathogenesis of AS. Resveratrol (RES) is a natural polyphenol in traditional Chinese medicines, which has been proven to possess anti-AS effects. However, the mechanism of RES treating AS through EndMT is not clear at present. Methods: RES targets were screened using databases such as SwissTargetPrediction and TargetNet, and AS and EndMT targets were searched using databases such as OMIM and DisGeNET. With the help of Venny 2.1, the key targets were selected by intersection. Next, the protein-protein interaction (PPI) network was constructed through the STRING 11.0 platform and Cytoscape software; gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotations were performed using DAVID. Further, Cytoscape was used to construct a drug-component-gene target-pathway network diagram to identify the core components and genes. Subsequently, an AS rat model was established. The blood lipid level of rats was detected by an automatic biochemical analyzer, and the expression level of the target protein was measured by western blotting. Results: Through network pharmacology analysis, 37 potential targets for RES treating AS and EndMT were identified, and the core targets for RES treating AS consisted of AKT1, TNF, MIMP9, and PPARG. GO enrichment analysis indicated that the treatment of AS with RES mainly involved the migration and proliferation of epithelial and endothelial cells. The KEGG pathway enrichment analysis revealed that the enrichment of TNF and Rap1 signaling pathways was most significant. Besides, RES effectively reduced the levels of total cholesterol (TC), triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C) in the serum of AS rats, increased the level of high-density lipoprotein cholesterol (HDL-C), and significantly cut down the atherosclerosis index (AI). Twist1, calponin, α-SMA and VE-cadherin were considered as EndMT indexes. The results of the western blot demonstrated that the protein levels of Twist1, calponin and α-SMA were significantly decreased, while the protein expression level of VE-cadherin was notably increased in rats treated with RES. Moreover, RES could also reduce the expression levels of Rap1 and Epac1 proteins. Conclusion: RES is an effective anti-AS drug. Briefly, RES can effectively improve the blood lipid level of AS patients, regulate the expression of EndMT-related proteins, and alleviate the dysfunction of endothelial cells. Notably, the functions of RES are closely associated with the EPAC1-Rap1 pathway.

Automation of Computations in Designing an Integrated Energy System Based on Its Digital Twin

The construction of integrated energy systems (IESs) based on traditional energy systems operating separately provides higher efficiency and reliability of energy supply to consumers. However, IESs are complex structures to design. A digital twin is a tool that allows you to combine all the tools necessary for design in a single information space. Software tools that implement the digital twin of IESs require high computational flexibility, which is due to the need to simulate a variety of equipment and involve a wide range of methods and mathematical models. Automating the construction process of a computing subsystem is a highly efficient solution for overcoming the challenges mentioned above. This paper proposes a methodological approach to automating the construction of the computing subsystem of the digital twin of an IES. The proposed approach involves using modern metaprogramming tools on a software platform to perform automated construction. During construction, the Model-Driven Engineering concept is implemented and knowledge formalized in the form of ontologies is used. The digital twin, obtained as a result of the practical application of the proposed methodological approach, enables computer and mathematical modeling of an IES in virtual space, with exploration of various configurations of its construction.

Concept of flexible no-code automation for complex sample preparation procedures

Driven by demographic changes and dwindling Science Technology Engineering Mathematics enrolments, our research introduces no-code automation as a strategic response, aimed at mitigating labor shortages while enhancing productivity and safety in the laboratory environment. Employing a user-friendly, no-code software platform, we automated a complex HPTLC assay, enabling laboratory personnel to configure and modify workflows without requiring specialized programming skills. The manuscript outlines the deployment of a collaborative robot (cobot), a programmable logic controller (PLC), and the utilization of self-developed open-source hardware components to establish automated stations for sample handling, incubation, spraying, detection, and storage within the assay process. The research addresses challenges such as the handling of fragile HPTLC plates and the seamless integration of automated stations, solved through innovative design solutions and adaptive programming methods. This investigation demonstrates the feasibility and efficiency of no-code automation in overcoming skilled labor deficits.

Turbulence effects in the topology optimization of compressible subsonic flow

AbstractTurbulence significantly influences fluid flow topology optimization, and this has already been verified under the incompressible flow regime. However, the same cannot be said about the compressible flow regime, in which the density field now affects and couples all of the fluid flow and turbulence equations and makes obtaining the adjoint model, which is necessary for topology optimization, extremely difficult. Up to now, the turbulence phenomenon has still not been considered in compressible flow topology optimization, which is what is being proposed and analyzed here. Rather than being based in the Reynolds‐Averaged Navier–Stokes (RANS) equations which are defined only for incompressible flow, the equations are now based on the Favre‐Averaged Navier–Stokes (FANS) equations, which are the counterpart of the RANS equations for compressible flow and feature different dependencies and terms. The compressible turbulence model being considered is the compressible version of the Spalart–Allmaras model, which differs from the usual Spalart–Allmaras model, since now there are some new spatially varying density and specific heat terms that depend on the primal variables and that act over some of the turbulence terms of the overall model. The adjoint equations are obtained by using an automatic differentiation scheme through a coupled software platform. The optimization algorithm is IPOPT, and some examples are presented to show the effect of turbulence in the compressible flow topology optimization.

Investigating the Evolution of Technological Integration on Teaching Effectiveness and Staff Development

Technology Integration (TI) has been incorporated into education and how it has affected both the efficacy of coaching and the development of teams. The research used a blended-techniques approach, integrating qualitative interviews, consciousness businesses, and quantitative surveys to provide a comprehensive understanding of the role that generations play in schooling. As part of the inquiry, 150 educators and administrators participated in awareness seminars and surveys. The findings demonstrate significant gains in instructional efficacy due to technology-enabled tools like interactive software and digital platforms that provide individualized instruction and instant feedback. Employees report higher levels of involvement and improved accessibility awareness.Staff readiness for TI is likewise evaluated, revealing that, while many educators are assured and prompted, there remains a need for continuing help and education. Statistical analysis, the usage of Cronbach's Alpha, confirms high internal consistency across the examinee’s constructs, inclusive of cronbach's Alpha values across the Technological Integration (TI)(0.81), Teaching Effectiveness (TE) (0.87), and Staff Development (SD)(0.80).There is generally positive emotion toward the role that technology plays in career advancement, despite the persistence of some challenging circumstances. Overall, the findings underscore the transformative ability of generation in education while emphasizing the need for strategic assistance and assets to maximize its benefits.

Why Did You Stop? Reasons for Stopping Faking Orgasms and Its Association with Sexual, Relationship, and Life Satisfaction in Denmark, Finland, France, Norway, Sweden, and the UK

ABSTRACT The current study investigated the phenomenon of faking orgasms, including the reasons why people stop faking orgasms, sociodemographic predictors of faking orgasms, its association with sex toy use, and its association with sexual, relationship, and life satisfaction. A cross-country convenience sample of 11,541 respondents from six European countries (Denmark, Finland, France, Norway, Sweden, and the UK) was collected in May and June 2022 through respondent panels by Cint, a market research software platform. Participants completed an online self-report survey. The study’s main findings showed that around 51% of men and women in the study had never faked orgasms, around 28% had faked orgasms but stopped faking and around 13% currently faked orgasms. Further, the reasons for men and women to stop faking orgasms included becoming more comfortable with not having an orgasm, improving sexual communication with their sexual partner, and the partner paying more attention to the respondents’ desires and preferences. Finally, it was shown that faking orgasms was associated with lower sexual, relationship, and life satisfaction. The current study represents one of the few research projects focusing on the phenomenon of stopping faking orgasms and reasons for it, with the added strength of including a large male sample.

VOLCANBOX: A software platform for volcanic hazard assessment

Volcanic eruptions have an intrinsic multi-hazard nature, in which a variety of volcanic products (lava flows, fallout, lahars, and pyroclastic flows) and associated hazards (seismic shocks, landslides, tsunamis, or floods) may interact and impact sequentially. Volcanic hazard assessment relies on probabilistic approaches based on the past eruptive history, from which scientists identify eruptive scenarios and their expected recurrence. However, not enough attempts have yet been made to address volcanic hazard assessment in a systematic way, based on principles that may be equally applicable to different volcanoes and volcanic zones regardless of their particular nature. Hence, we present VOLCANBOX, a new multiplatform (GNU/Linux, MacOS, Windows) system designed to conduct long-and short-term volcanic hazard assessment and risk analysis in a systematic and rational manner, aimed at reducing volcanic risk by anticipating future eruptions. VOLCANBOX includes several sets of software tools designed to evaluate long and short-term volcanic hazards, to conduct vulnerability analysis, and to assist decision-makers during the management of a volcanic crisis. VOLCANBOX can be implemented before an emergency, in order to identify optimum mitigating actions and how these may have to be adapted as new information is obtained. VOLCANBOX is aimed at experts in volcanic hazard and risk assessment and management and is designed to facilitate the interaction and cooperation between scientists, policy makers and civil protection agencies to anticipate volcanic disasters in a timely manner, by quantifying volcanic hazards, understanding volcanic unrest, forecasting volcanic eruptions, and identifying the most probable scenarios in a simple and clear manner.

Measured harmonics modelling and study of their impact on the transient stability of electrical networks using MATLAB software platform

Measured harmonics modelling and study of their impact on the transient stability of electrical networks using MATLAB software platform

Immersive Photorealistic Three-Dimensional Neurosurgical Anatomy of the Cerebral Arteries: A Photogrammetry-Based Anatomic Study.

Neurosurgeons need a profound knowledge of the surgical anatomy of the cerebral arteries to safely treat patients. This is a challenge because of numerous branches, segments, and tortuosity of the main blood vessels that supply the brain. The objective of this study was to create high-quality three-dimensional (3D) anatomic photorealistic models based on dissections of the brain arterial anatomy and to incorporate this data into a virtual reality (VR) environment. Two formaldehyde-fixed heads were used. The vessels were injected with radiopaque material and colored silicone and latex. Before the dissections, the specimens were computed tomography scanned. Stratigraphical anatomic dissection of the neck and brain was performed to present the relevant vascular anatomy. A simplified surface scanning method using a mobile phone-based photogrammetry application was used, and the data were incorporated into a VR 3D modeling software for post-processing and presentation. Fifteen detailed layered photorealistic and two computed tomography angiography-based 3D models were generated. The models allow manipulation in VR environment with sufficient photographic detail to present the structures of interest. Topographical relevant anatomic structures and landmarks were annotated and uploaded for web-viewing and in VR. Despite that the VR application is a dedicated 3D modeling platform, it provided all necessary tools to be suitable for self-VR study and multiplayer scenarios with several participants in one immersive environment. Cerebral vascular anatomy presented with photogrammetry surface scanning method allows sufficient detail to present individual vessel's course and even small perforating arteries in photorealistic 3D models. These features, including VR visualization, provide new teaching prospects. The whole study was done with simplified algorithms and free or open-source software platforms allowing creation of 3D databases especially useful in cases with limited body donor-based dissection training availability.

Large scale massively parallel numerical simulation for blast effects on structures

An efficient large-scale parallel computing program for blast effects on structures is developed based on software platform mode, which adopts component-based three-layer software architecture to achieve disciplinary hierarchy. The parallel layer encapsulates high-performance data structures and shields large-scale parallel computing technology, enabling efficient mesh adaptivity. The common numerical algorithm layer encapsulates fluid, structural, and coupling algorithm processes providing standardized interfaces for extending numerical schemes. The physical model layer provides extension interfaces for state equations, source terms, initial boundary values, etc, to facilitate quick customization of large-scale parallel software for blast effects on structures. Typical examples verify the correctness, effectiveness and high precision of the proposed program in fluid-structure coupling problems. The parallel efficiency of 300,000 processor cores with hundreds of millions of grids reach 60.84% for the shock wave transmission. Finally, the dynamic behavior of multi-storey buildings under blast waves is simulated to reveal the damage model of the overall collapse. These results show that the software has a broad application prospect in the field of explosion. The results suggest that the software holds significant potential for application in the field of explosion, particularly in intricate and large-scale scenarios.

Innovative Approach for Serious Educational Games with Creative Visualization in Selected Eco-context

This paper presents a new research approach for technological solutions in the ProNature project to create an innovative software platform for serious educational games with creative visualization to build competence on natural ecosystems, responsible management of natural resources and environmental protection. With the built software platform and based on created educational game scenarios, demonstration serious educational games with creative visualization will be developed in a selected eco-context.

Third Information Day: Research Infrastructure Services in the Humanities and Social Sciences

The main results of the work of the team of the Institute of Mathematics and Informatics at the Bulgarian Academy of Sciences on the research projects CLaDA-BG – the Bulgarian National Interdisciplinary Research e-Infrastructure for Resources and Technologies in Favor of the Bulgarian Language and Cultural Heritage, Part of the EU Infrastructures CLARIN and DARIAH and No KP-06-N50/4 30.11.2020 “Fourteenth Century South Slavonic Scribes and Scriptoria (Palaeographical Attribution and Online Repertorium)”, will be presented during the Information Day within the DiPP2024 conference. The main emphasis will be placed on developments and implementations of CultIS – a webbased software platform for intelligent digital management and presentation of large data sets and knowledge from the fields of culture, humanities, and social sciences.

Rethinking the Smart City as an Intelligent City Archway

Urban intelligence is the ability to understand and navigate the physical and digital dimensions of “connected complex urban places”. For example, new infrastructures (e.g., sensors, Internet of Things {IoT} devices like smart lamp posts) are needed to capture and represent places in software platforms and on the Internet. New spatial skills and spatial thinking are needed to navigate these new interfaces and networks of places. This paper aims at understanding urban intelligence by exploring variations in how smart cities have been conceptualized; how citizens have been placed within the smart city; and how Canada’s smart cities initiative has placed on urban (and highly spatial) problems over digital technologies. The metaphor of the Roman arch is used to describe the interdependency of the building blocks of smart cities. Components (building blocks) of the smart city, be they openness, resilience or inclusion, must all be present, and build towards what we argue is the keystone of urban intelligence. We discuss how these components lead to a new consideration of the smart city, the Intelligent City.

Machine Learning Platform for Disease Diagnosis with Contrast CT Scans

Machine learning has gained significant recognition as a powerful approach for medical diagnosis using medical images. Among various medical imaging modalities, contrast-enhanced CT (CECT) is utilized to obtain additional diagnostic information that improves visualization and evaluation of certain abnormalities in the human body, as well as to observe temporal changes in lesions and tumors across different time phases. However, developing such medical diagnostic systems presents two significant challenges: high technical complexity and substantial development effort. This paper presents a software platform that effectively addresses these challenges. Specifically, we propose a unified software process that fully automates contrast-enhanced CT (CECT)-specific disease diagnosis, with key tasks performed by leveraging task-specific machine learning models to enhance accuracy. The platform incorporates a suite of specialized machine learning models into the diagnostic process, enabling precise diagnosis of lesions, malignancies, tumors, tumor characteristics, and temporal changes over phases. Moreover, the platform has been designed according to the Open–Closed Principle, allowing it to be applicable to a wide range of CECT-based diagnostic systems. The platform has been implemented in Python using the Scikit-learn and TensorFlow libraries. To validate its applicability and reusability, a hepatocellular carcinoma (HCC) diagnosis system has been implemented.

Simulation Model of a Steelmaking-Continuous Casting Process Based on Dynamic-Operation Rules.

The steelmaking-continuous casting process (SCCP) is a complex manufacturing process which exhibits the distinct features of process manufacturing. The SCCP involves a variety of production elements, such as multiple process routes, a wide array of smelting and auxiliary devices, and a variety of raw and auxiliary materials. The production-simulation of SCCP holds a natural advantage in being able to accurately depict the intricate production behavior involved, and this serves as a crucial tool for optimizing the production operation of the SCCP. This paper thoroughly considers the various production elements involved in the SCCP, such as the fluctuation of the converter smelting cycle, fluctuation of heat weight, and ladle operation. Based on the Plant Simulation software platform, a dynamic simulation model of the SCCP is established and detailed descriptions are provided regarding the design of an SCCP using dynamic-operation rules. Additionally, a dynamic operational control program for the SCCP is developed using the SimTalk language, one which ensures the continuous operation of the caster in the SCCP, using the discrete simulation platform. The effectiveness of the proposed dynamic simulation model is verified by the total completion time of the production plan, the transfer time of the heat among the different processes, and the frequency of ladle turnover. The simulation's results indicate that the dynamic simulation model has a satisfactory effect in simulating the actual production process. On this basis, the application effects of different schedules are compared and analyzed. Compared with a heuristic schedule, the optimized schedule based on the "furnace-machine coordinating" mode reduces the weighted value of total completion time by 8.7 min, reduces the weighted value of transfer waiting time by 45.5 min, and the number of rescheduling times is also reduced, demonstrating a better application effect and verifying the optimizing effect of the "furnace-machine coordinating" mode on the schedule.

USING THE ARDUINO PLATFORM IN THE RESEARCH OF INTERNAL COMBUSTION ENGINES

Modern measuring systems used in the study of internal combustion engines require significant investments. The universal Arduino platform offers ready-made powerful hardware modules for data collection (shields) and control, which work in a wide range of frequencies and signal amplitudes, provide their analysis and processing, allow to implement equipment management, and have a relatively low cost and free software with standard libraries. These facts testify to the high relevance of the use of the Arduino platform in the study of internal combustion engines. The purpose of this work is to determine the possibilities and features of using the Arduino hardware and software platform in the study of processes occurring in energy power plants with internal combustion engines, early prototyping of their control and diagnostic systems. The paper considers the possibility of hardware and software connection of sensors for measuring basic physical quantities to the Arduino platform: crankshaft rotation frequency (based on induction sensors and Hall sensors), pressure, air and fuel flow, temperatures (resistance sensors and thermocouples). In addition, the characteristics (dependence of the measurement parameter on the output value) of some popular sensors used in the study of internal combustion engines are given. It is important to consider that the equipment used for the study of processes in the ICE must meet the certification requirements. In the case of Arduino, this certification may not be available. However, the recommendations for the use of various sensors, shields and Arduino boards can be applied if the measured quantity is not the determining factor. It is important to consider these limitations and use Arduino with an understanding of the capabilities and limitations of the platform. The use of Arduino in the educational process in the training of specialists in the field of power engineering and in the research of energy installations of vehicles will allow students to apply the knowledge, skills and abilities acquired in the learning process at the hardware and software levels, which will create additional motivation for further study devices and principles of operation of automated and automatic vehicle control systems.

Impacts of Big Data Analytics for Agriculture tools and techniques

The present paper deals with “Impacts of Big Data Analytics for Agriculture tools and techniques.” A random sample 30 Various software platforms are developed to give information to farmers about new tools and techniques related to agriculture: (MySmartFarm, Awhere weather, Phenone, Farmlog, Datafloq, Farmeron) has been used by secondary source from Agriculture depart in the state of Bihar. The traditional tools and techniques (Big data) analysis massive amount of data. To store and analyze this type of data parallel computing and analyze paradigm is required. Big data analytic is used to weather changes and its impacts of agriculture in Bihar. From the big data analytic Agriculture framework is developed that identify disease based on symptoms similarity and recommend a solution based on high similarity and achieve their tools has been used. Then cleansing of data is done that is important information is extracted from unstructured redundant data and were normalization is done that is features are extracted from cleaned data. The data was used to analyze the agricultural tools and technique. It finds out disease name based on weather changes and its impacts of agriculture has been taken on past data. Result has been shows that data analytic in weather changes past 2018-2023 years that was.

Infliximab in Inflammatory Bowel Disease: Leveraging Physiologically Based Pharmacokinetic Modeling in the Clinical Context.

In this study, a physiologically based pharmacokinetic (PBPK) modeling framework was employed to explore infliximab exposure following intravenous (5 mg/kg) and subcutaneous administration (encompassing the approved 120 mg flat-fixed dose as a switching option) in virtual adult and pediatric patients with inflammatory bowel disease (IBD). The PBPK model and corresponding simulations were conducted using the PK-Sim® software platform. The PBPK simulation indicated that a 120 mg subcutaneous flat-fixed dose might not be optimal for heavier adults with IBD, suggesting the need for infliximab dose escalation. For an older virtual pediatric patient (14 years old), subcutaneous administration of a 120 mg flat-fixed dose appears to be a feasible IBD treatment option. In the final exploration scenario, the model was extended to predict hypothetical subcutaneous infliximab doses in a virtual pediatric population (6-18 years old), stratified into three weight bands (20-30 kg, 30-45 kg, and 45-70 kg), that would yield post-switch trough concentrations of infliximab comparable to those seen in adults with the 120 mg flat-fixed subcutaneous dose. The PBPK-model-informed dose suggestions were 40 mg for the 20-30 kg band, 80 mg for the 30-45 kg band, and 120 mg for the 45-70 kg band. As demonstrated in this paper, the PBPK modeling framework can serve as a versatile tool in clinical pharmacology to investigate various clinical scenarios, such as exploring alternative dosing regimens and routes of administration, ultimately advancing IBD treatment across diverse (sub)populations of clinical interest.