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"Systems engineering Periodicals"
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Evaluating the efficacy of AI content detection tools in differentiating between human and AI-generated text
The proliferation of artificial intelligence (AI)-generated content, particularly from models like ChatGPT, presents potential challenges to academic integrity and raises concerns about plagiarism. This study investigates the capabilities of various AI content detection tools in discerning human and AI-authored content. Fifteen paragraphs each from ChatGPT Models 3.5 and 4 on the topic of cooling towers in the engineering process and five human-witten control responses were generated for evaluation. AI content detection tools developed by OpenAI, Writer, Copyleaks, GPTZero, and CrossPlag were used to evaluate these paragraphs. Findings reveal that the AI detection tools were more accurate in identifying content generated by GPT 3.5 than GPT 4. However, when applied to human-written control responses, the tools exhibited inconsistencies, producing false positives and uncertain classifications. This study underscores the need for further development and refinement of AI content detection tools as AI-generated content becomes more sophisticated and harder to distinguish from human-written text.
Journal Article
New insights from the biogas microbiome by comprehensive genome-resolved metagenomics of nearly 1600 species originating from multiple anaerobic digesters
Background Microorganisms in biogas reactors are essential for degradation of organic matter and methane production. However, a comprehensive genome-centric comparison, including relevant metadata for each sample, is still needed to identify the globally distributed biogas community members and serve as a reliable repository. Results Here, 134 publicly available metagenomes derived from different biogas reactors were used to recover 1635 metagenome-assembled genomes (MAGs) representing different biogas bacterial and archaeal species. All genomes were estimated to be > 50% complete and nearly half ≥ 90% complete with ≤ 5% contamination. In most samples, specialized microbial communities were established, while only a few taxa were widespread among the different reactor systems. Metabolic reconstruction of the MAGs enabled the prediction of functional traits related to biomass degradation and methane production from waste biomass. An extensive evaluation of the replication index provided an estimation of the growth dynamics for microbes involved in different steps of the food chain. Conclusions The outcome of this study highlights a high flexibility of the biogas microbiome, allowing it to modify its composition and to adapt to the environmental conditions, including temperatures and a wide range of substrates. Our findings enhance our mechanistic understanding of the AD microbiome and substantially extend the existing repository of genomes. The established database represents a relevant resource for future studies related to this engineered ecosystem.
Journal Article
Past, present, and future of smart learning: a topic-based bibliometric analysis
Innovative information and communication technologies have reformed higher education from the traditional way to smart learning. Smart learning applies technological and social developments and facilitates effective personalized learning with innovative technologies, especially smart devices and online technologies. Smart learning has attracted increasing research interest from the academia. This study aims to comprehensively review the research field of smart learning by conducting a topic modeling analysis of 555 smart learning publications collected from the Scopus database. In particular, it seeks answers to (1) what the major research topics concerning smart learning were, and (2) how these topics evolved. Results demonstrate several major research issues, for example, Interactive and multimedia learning, STEM (science, technology, engineering, and mathematics) education, Attendance and attention recognition, Blended learning for smart learning, and Affective and biometric computing. Furthermore, several emerging topics were identified, for example, Smart learning analytics, Software engineering for e-learning systems, IoT (Internet of things) and cloud computing, and STEM education. Additionally, potential inter-topic directions were highlighted, for instance, Attendance and attention recognition and IoT and cloud computing, Semantics and ontology and Mobile learning, Feedback and assessment and MOOCs (massive open online courses) and course content management, as well as Blended learning for smart learning and Ecosystem and ambient intelligence.
Journal Article
A variety of new rogue wave patterns for three coupled nonlinear Maccari’s models in complex form
Maccari’s system serves as a valuable tool in various mathematical disciplines, contributing to the understanding of complex dynamics, control theory, synchronization phenomena, and mathematical modeling. This study utilizes the truncated Painlevé approach (TPA) to investigate the three coupled nonlinear Maccari’s equations in complex form. By using this technique, the localized solutions have been found and expressed in terms of arbitrary functions. These solutions included multirogue waves, rogue wave doublets, and lump solutions. The dynamical behavior of these solutions is visualized by selecting arbitrary values for the control parameters. Moreover, the studied model undergoes analysis from multiple perspectives, including quasi-periodic, chaotic motion, and multistability. An external periodic perturbation is introduced to the system, allowing the utilization of various chaos detecting tools. Through these tools, we identify quasi-periodic and chaotic behavior, demonstrating the system’s deviation from regular patterns. It is worth noting that all calculations were verified using Maple for accuracy and reliability. The analysis in the given research will enhance our comprehension of the behavior of waves in high-dimensional Maccari systems.
Journal Article
Two decades of breakthroughs: charting the future of NeuroEngineering and Rehabilitation
The Journal of NeuroEngineering and Rehabilitation
(
JNER) has become a major actor for the dissemination of knowledge in the scientific community, bridging the gaps between innovative neuroengineering and rehabilitation. Major fields of innovations have emerged these last 25 years, such as machine learning and the ongoing AI revolution, wearable technologies, human machine interfaces, robotics, advanced prosthetics, functional electrical stimulation and various neuromodulation techniques. With the major burden of disorders impacting on the central/peripheral nervous system and the musculoskeletal system both in adults and in children, successful tailored neurorehabilitation has become a major objective for the research and clinical community at a world scale. JNER contributes to this challenging goal, publishing groundbreaking cutting-edge research using the open access model. The multidisciplinary approaches at the crossroads of biomedical engineering, neuroscience, physical medicine and rehabilitation make of the journal a unique growing platform welcoming breakthrough discoveries to reshape the field and restore function.
Journal Article
Painlevé analysis, auto-Bäcklund transformation and analytic solutions of a (2+1)-dimensional generalized Burgers system with the variable coefficients in a fluid
Burgers-type equations are used to describe certain phenomena in gas dynamics, traffic flow, plasma astrophysics and ocean dynamics. In this paper, a (2
+
1)-dimensional generalized Burgers system with the variable coefficients in a fluid is investigated. We obtain the Painlevé-integrable constraints of the system with respect to the variable coefficients. Based on the truncated Painlevé expansions, an auto-Bäcklund transformation is constructed, along with some soliton solutions. Via a truncated Painlevé expansions, certain multiple kink solutions are derived. Via a complex-conjugate transformation, some breather solutions, half-periodic kink solutions and hybrid solutions composed of the breathers and kink waves are seen.
Journal Article
Studies on certain bilinear form, N-soliton, higher-order breather, periodic-wave and hybrid solutions to a (3+1)-dimensional shallow water wave equation with time-dependent coefficients
Studies of the shallow water waves are active, possessing the applications in ocean engineering, marine environment, atmospheric science, etc. In this paper, we investigate a (3+1)-dimensional shallow water wave equation with time-dependent coefficients. Hirota method and symbolic computation help us work out (1) a bilinear form, (2)
N
-soliton solutions with
N
being a positive integer, (3) the higher-order breather solutions, (4) periodic-wave solutions and (5) hybrid solutions composed of one first-order breather and one soliton/two solitons. Moreover, we provide some nonlinear phenomena described by the associated solutions. All of the obtained results are determined via the time-dependent coefficients of that equation.
Journal Article
Wronskian, Gramian, Pfaffian and periodic-wave solutions for a (3+1)-dimensional generalized nonlinear evolution equation arising in the shallow water waves
Application of the shallow water waves in environmental engineering and hydraulic engineering is seen. In this paper, a (3+1)-dimensional generalized nonlinear evolution equation (gNLEE) for the shallow water waves is investigated. The
N
th-order Wronskian, Gramian and Pfaffian solutions are proved, where
N
is a positive integer. Soliton solutions are constructed from the
N
th-order Wronskian, Gramian and Pfaffian solutions. Moreover, we analyze the second-order solitons with the influence of the coefficients in the equation and illustrate them with graphs. Through the Hirota-Riemann method, one-periodic-wave solutions are derived. Relationship between the one-periodic-wave solutions and one-soliton solutions is investigated, which shows that the one-periodic-wave solutions can approach to the one-soliton solutions under certain conditions. We reduce the (3+1)-dimensional gNLEE to a two-dimensional planar dynamic system. Based on the qualitative analysis, we give the phase portraits of the dynamic system.
Journal Article
Review of guidance papers on regression modeling in statistical series of medical journals
Although regression models play a central role in the analysis of medical research projects, there still exist many misconceptions on various aspects of modeling leading to faulty analyses. Indeed, the rapidly developing statistical methodology and its recent advances in regression modeling do not seem to be adequately reflected in many medical publications. This problem of knowledge transfer from statistical research to application was identified by some medical journals, which have published series of statistical tutorials and (shorter) papers mainly addressing medical researchers. The aim of this review was to assess the current level of knowledge with regard to regression modeling contained in such statistical papers. We searched for target series by a request to international statistical experts. We identified 23 series including 57 topic-relevant articles. Within each article, two independent raters analyzed the content by investigating 44 predefined aspects on regression modeling. We assessed to what extent the aspects were explained and if examples, software advices, and recommendations for or against specific methods were given. Most series (21/23) included at least one article on multivariable regression. Logistic regression was the most frequently described regression type (19/23), followed by linear regression (18/23), Cox regression and survival models (12/23) and Poisson regression (3/23). Most general aspects on regression modeling, e.g. model assumptions, reporting and interpretation of regression results, were covered. We did not find many misconceptions or misleading recommendations, but we identified relevant gaps, in particular with respect to addressing nonlinear effects of continuous predictors, model specification and variable selection. Specific recommendations on software were rarely given. Statistical guidance should be developed for nonlinear effects, model specification and variable selection to better support medical researchers who perform or interpret regression analyses.
Journal Article