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Found 6334 publications
Wild Blackberry Fruit (Rubus fruticosus L.) as Potential Functional Ingredient in Food: Ultrasound-Assisted Extraction Optimization, Ripening Period Evaluation, Application in Muffin, and Consumer Acceptance
Publication Name: Foods
Publication Date: 2024-03-01
Volume: 13
Issue: 5
Page Range: Unknown
Description:
The aim of the present study is to evaluate the antioxidant properties of wild blackberry fruits as well as their possible use in powdered form as a functional ingredient. For this, ultrasound-assisted extraction optimization, ripening stage evaluation, and wild blackberry powder incorporation into a real food matrix were applied. The optimum conditions for extraction were as follows: 60% MeOH, 20 min of extraction time, acidification with 0.5% HCl, and a 1:40 g/mL solid-to-solvent ratio, which allowed the following yields: total polyphenol content (TPC): 53.8 mg GAE/g; total flavonoid content (TFC): 5.78 mg QE/g; total monomer anthocyanin content (TMA): 11.2 mg CGE/g; 2,2-diphenyl-1-picrylhydrazyl radical scavenging activity (DPPH): 71.5 mg AAE/g; IC50 : 52.3 µg/mL. The study also highlighted that, during the ripening process, the TPC (41.4%), TFC (17.0%), and DPPH levels (66.4%) of the fruits decreased while the TMA yield increased. The incorporation of blackberry powder at different levels (5–20%) increased the TPC, TFC, TMA, and antioxidant properties of muffins. Although the muffins enriched with 20% wild blackberry powder had the best chemical properties (TPC: 3.15 mg GAE/g; TFC: 0.52 mg QE/g; TMA: 0.23 mg CGE/g; DPPH: 1.70 mg AAE/g; IC50 : 1.65 mg/mL), the sensory analysis showed that the addition of blackberry fruit at a concentration of 10% to the muffins resulted in the best consumer acceptability.
Open Access: Yes
AI in medical diagnosis: AI prediction & human judgment
Publication Name: Artificial Intelligence in Medicine
Publication Date: 2024-03-01
Volume: 149
Issue: Unknown
Page Range: Unknown
Description:
AI has long been regarded as a panacea for decision-making and many other aspects of knowledge work; as something that will help humans get rid of their shortcomings. We believe that AI can be a useful asset to support decision-makers, but not that it should replace decision-makers. Decision-making uses algorithmic analysis, but it is not solely algorithmic analysis; it also involves other factors, many of which are very human, such as creativity, intuition, emotions, feelings, and value judgments. We have conducted semi-structured open-ended research interviews with 17 dermatologists to understand what they expect from an AI application to deliver to medical diagnosis. We have found four aggregate dimensions along which the thinking of dermatologists can be described: the ways in which our participants chose to interact with AI, responsibility, ‘explainability’, and the new way of thinking (mindset) needed for working with AI. We believe that our findings will help physicians who might consider using AI in their diagnosis to understand how to use AI beneficially. It will also be useful for AI vendors in improving their understanding of how medics want to use AI in diagnosis. Further research will be needed to examine if our findings have relevance in the wider medical field and beyond.
Open Access: Yes
An Improved IEHO Super-Twisting Sliding Mode Control Algorithm for Trajectory Tracking of a Mobile Robot
Publication Name: Studies in Informatics and Control
Publication Date: 2024-03-01
Volume: 33
Issue: 1
Page Range: 49-60
Description:
In recent years, trajectory tracking of a mobile robot has been one of the most addressed problems in the specilized literature, as a mobile robot must have the ability to follow a trajectory, while also compensating various external and internal disturbances. This paper proposes an IEHO-STSM controller based on the super-twisting sliding mode for the path tracking of a mobile robot. First, a new improved IEHO algorithm has been developed and introduced, based on the EHO (Elephant Herding Optimization) metaheuristic algorithm. The developed algorithm consisted in improving the performance of the basic EHO such as convergence speed, exploration and exploitation capabilities. Then, based on a dynamic model of the mobile robot, a super-twisting sliding mode (STSM) controller was designed to guide the robot to the desired trajectory. Finally, the improved IEHO algorithm was applied for adjusting the parameters of the super-twisting sliding mode (STSM) controller. The analysis of the proposed IEHO algorithm has been done by comparing it with EHO, PSO (Particle Swarm Optimization) and GWO (Grey Wolf Optimizer) algorithms, by employing it in tuning the STSM. The simulation results show that the proposed IEHO-STSM can reach both high precision and high speed capability, by overcoming external and internal disturbances.
Open Access: Yes
Comparative Analysis of Ascaris suum and Macracanthorhynchus hirudinaceus Infections in Free-Ranging and Captive Wild Boars (Sus scrofa) in Hungary
Publication Name: Animals
Publication Date: 2024-03-01
Volume: 14
Issue: 6
Page Range: Unknown
Description:
Ascaris suum and Macracanthorhynchus hirudinaceus cause a large loss of yield in farm animals as well as in free-living and captive wild boar herds, thereby causing economic damage. This study compared A. suum and M. hirudinaceus infections in free-ranging and captive wild boars (Sus scrofa) in Hungary. The authors measured the A. suum and M. hirudinaceus infections of a 248-hectare wild boar garden and an 11,893-hectare free-living wild boar herd in the sample area. In all cases, samples were collected from shot wild boars. In total, 216 wild boars were examined from June 2015 to June 2023 in Hungary. Of the 173 dissected wild boars from the wild, 57 (32.9%) were infected with A. suum, while 30 (69.8%) of the 43 individuals from the captive area were infected. The prevalence of M. hirudinaceus in the free-living area population was 9.25% (16 wild boars), while that of the captive population was 34.89% (15 wild boars). In the case of the examined helminths, the captive herd was 36.9% more infected than the herd living in the open area.
Open Access: Yes
DOI: 10.3390/ani14060932
Discovering smart cities’ potential in Kazakhstan: A cluster analysis
Publication Name: Plos One
Publication Date: 2024-03-01
Volume: 19
Issue: 3 March
Page Range: Unknown
Description:
The potential for developing smart cities in Kazakhstan is evaluated using cluster analysis. Built on previous research focused on clustering the regions of Kazakhstan, this study applies the same method to the cities of the country. The analysis uses indicators related to human capital, infrastructure, education, information technology, production, and other factors to assess the potential of each city. The clustering is performed using Single Linkage, Complete Linkage, and Ward’s methods. The results show that Almaty and Astana are the cities with the highest potential for becoming smart cities. Aktobe is identified as a city with distinctive features that may help or hinder its development as a smart city. The remaining cities are clustered into two groups, with one group having the potential to catch up and maintain the trend of developing smart cities, while the other group is less suitable for starting smart city projects and may require more investment per capita. The study highlights the deep regional inequality affecting the potential to successfully develop and manage smart cities in Kazakhstan. The analysis also reveals some limitations and challenges in the data and variables used, including the lack of data for some variables and the difficulties in "translating" some factors and indicators into quantitative variables for clustering. The study concludes that future research should address these challenges and consider clustering inside certain regions to focus on their unique features. The study recommends launching pilot projects in small cities, with the most successful practices then scaled and implemented in the core smart cities and possibly Aktobe, if it manages to use its advantages to compensate for risks. Overall, this study provides insights into the potential of smart city development in Kazakhstan and can inform policymakers in their efforts to support smart city projects in the country.
Open Access: Yes
Investigation of the Effectiveness of the Robotic ReStore Soft Exoskeleton in the Development of Early Mobilization, Walking, and Coordination of Stroke Patients: A Randomized Clinical Trial
Publication Name: Robotics
Publication Date: 2024-03-01
Volume: 13
Issue: 3
Page Range: Unknown
Description:
Medical robotics nowadays can prevent, treat, or alleviate numerous severe conditions, including the dire consequences of stroke. Our objective was to determine the effect of employing a robotic soft exoskeleton in therapy on the development of the early mobilization, gait, and coordination in stroke patients. The ReStore™ Soft Exo-Suit, a wearable exosuit developed by a leading company with exoskeleton technology, was utilized. It is a powered, lightweight device intended for use in stroke rehabilitation for people with lower limb disability. We performed a randomized clinical intervention, using a before–after trial design in a university hospital setting. A total of 48 patients with a history of stroke were included, of whom 39 were randomized and 30 completed the study. Interventions: Barthel Index and modified Rankin scale (mRS) patients were randomly assigned to a non-physical intervention control (n = 9 of 39 completed, 30 withdrew before baseline testing), or to a high-intensity agility program (15 sessions, 5 weeks, n = 30 completed). The main focus of assessment was on the Modified Rankin Scale. Additionally, we evaluated secondary factors including daily life functionality, five dimensions of health-related quality of life, the Beck depression inventory, the 6 min walk test (6MWT), the Berg Balance Scale (BBS), and static balance (center of pressure). The Robot-Assisted Gait Therapy (ROB/RAGT) program led to significant improvements across various measures, including a 37% improvement in Barthel Index scores, a 56% increase in 10 m walking speed, and a 68% improvement in 6 min walking distance, as well as notable enhancements in balance and stability. Additionally, the intervention group demonstrated significant gains in all these aspects compared to the control group. In conclusion, the use of robotic therapy can be beneficial in stroke rehabilitation. These devices support the restoration and improvement of movement in various ways and contribute to restoring balance and stability.
Open Access: Yes
Experimental Investigation of the Soil-Water Characteristic Curves (SWCC) of Expansive Soil: Effects of Sand Content, Initial Saturation, and Initial Dry Unit Weight
Publication Name: Water Switzerland
Publication Date: 2024-03-01
Volume: 16
Issue: 5
Page Range: Unknown
Description:
Soil-water characteristic curve (SWCC) is an essential parameter in unsaturated soil mechanics, and it plays a significant role in geotechnical engineering to enhance theoretical analysis and numerical calculations. This study investigated the effects of key factors, such as the percentage of sand, initial degree of saturation, and initial dry unit weight, on the SWCC of expansive soil by measuring the matric suction using a pressure apparatus method. The empirical equation of SWCC was obtained using the Van Genuchten and Fredlung Xing models, and the processing of experimental data checks the fitting of the two empirical models. The findings revealed that the Fredlung Xing model fit the relationship between matric suction and volumetric water content of expansive soil better than the Van Genuchten model, indicating that the pressure apparatus approach’s experimental data are correct and acceptable. The study also found that the matric suction increased with decreasing percentage of added sand at the same volumetric moisture content, and the increase in initial dry unit weight increased the matric suction, with the water retention capacity decreasing significantly after adding 20% sand. Moreover, as the initial degree of saturation increased, the volumetric water content decreased, and the characteristic curves became identical when the initial saturation degree reached 90%. Finally, to minimize the water retention capacity of expansive soils, the study recommended adding a percentage of sand not less than 30% to the expansive clay sample.
Open Access: Yes
DOI: 10.3390/w16050627
Exploring the impact of ChatGPT on education: A web mining and machine learning approach
Publication Name: International Journal of Management Education
Publication Date: 2024-03-01
Volume: 22
Issue: 1
Page Range: Unknown
Description:
ChatGPT, an artificial intelligence model, has garnered significant interest within education. This study examined public sentiment regarding ChatGPT's influence on education by utilizing web mining and natural language processing (NLP) techniques. By adopting an empirical approach and leveraging machine learning models to process 2003 web articles, the study extracts valuable insights. The results indicate that ChatGPT has emerged as a crucial educational tool, offering advantages for both students and educators. Notably, the study emphasized ChatGPT's role in enhancing students' writing abilities and fostering dynamic, interactive learning environments. ChatGPT's capacity to address a broad spectrum of questions demonstrates its versatility and adaptability, contributing to more inclusive and personalized educational experiences. However, the study also uncovered challenges tied to academic integrity, such as plagiarism and cheating, which stem from incorporating AI-driven tools like ChatGPT into education. This raises concerns regarding ethical aspects, including responsible AI usage and data privacy, and highlights the need for institutions to develop guidelines and policies for AI tool implementation in education. This study's findings hold theoretical and practical implications for integrating ChatGPT into educational settings. It is the first to employ web mining and NLP techniques to analyze public opinions on ChatGPT's impact on education comprehensively.
Open Access: Yes
CHERRY PICKING—USING HYBRID LEARNING METHODS IN HEI’S MASS COURSES
Publication Name: Journal of Educators Online
Publication Date: 2024-03-01
Volume: 21
Issue: 2
Page Range: Unknown
Description:
Universities have a wealth of new digital tools and methodologies at their disposal for educational processes. It is difficult to know which of the many options to use, but it makes sense to combine methodologies to increase student satisfaction and, above all, to reduce drop-out rates. The study used a questionnaire survey in a mass course to see how satisfied students are with the technical services of Moodle, the quality of teaching, and its usability. The students’ learning habits and what content they use on the Moodle LMS (MLMS) platform of our own institution in Hungary is also examined. The use of MLMS as an educational tool, not only in distance learning but also in full-time education, is significant at our university, and its strengths have been successfully translated into benefits for students. The results confirmed our preliminary assumptions. The analysis suggests that the MLMS was a good choice as course outcomes improved, drop-out rates decreased, and student satisfaction increased.
Open Access: Yes
