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Optimizing control strategies for DC-DC boost converters: Real-time application of an adaptive gain scheduled ISA-PI controller with hybrid state-space and linear parameter-varying modelling
No full textThis paper introduces an innovative sophisticated control scheme for a DC-DC boost converter (DCBC), employing an adaptive gain scheduled ISA-PI controller. Addressing the inherent non-minimum phase behaviour arising from a right-half plane zero and the complexities associated with nonlinear dynamics during continuous conduction mode (CCM), the proposed adaptive gain scheduled ISA-PI controller incorporates the distinct adjustable parameter within the controller structure. This parameter is instrumental in enhancing the adaptability of the controller to varied operating conditions. The adaptive ISA-PI controller seamlessly integrates the real-time duty cycle value, replacing traditional tuning variables with precision. The dynamic adjustment of this sole controllable parameter is facilitated through a carefully designed look-up table, employing the loop-shaping method. Verification of the proposed control system's effectiveness is conducted using MATLAB/Simulink, incorporating a comprehensive comparative analysis against single proportional integral (PI) controllers. The assessment centres on evaluating the system's precision in tracking desired signals and regulating plant process variables with optimal efficiency, minimizing delays and overshoot. Experimental validation is further undertaken using MATLAB/Simulink/Stateflow on a dSPACE Real-time-interface (RTI) 1007 processor, DS2004 High-Speed A/D, and CP4002 Timing and Digital I/O boards. The experimental results confirm the superior performance of the proposed adaptive gain schedule ISA-PI controller, which has a unique configurable parameter. This controller demonstrated a twofold improvement in tracking speed and significantly improved disturbance rejection, confirming its effectiveness.4063279
The Effect of Audio-Visual Methods on Preoperative Anxiety in Children: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
No full textBackground: Children presenting to hospitals during the preoperative period are often exposed to procedures that cause significant stress. Through preoperative interventions, nurses play an important role in relieving the anxiety of children and their parents. Objective: This study was conducted to determine the effect of audio-visual methods on preoperative anxiety levels in children. Methods: PubMed (including MEDLINE), Cochrane, EBSCOHost, Web of Science, YÖK National Thesis Center, and Google Scholar databases of randomized controlled studies published in the last 10 years were searched for this meta-analysis. 32 studies were included in the meta-analysis, and the total sample size was 2795. Results: Q According to the results of the meta-analysis using the random-effects model, audio-visual methods had a positive effect on reducing anxiety (SMD: -1.312, %95 CI -1,666-(0,958), Z=-7,260, p < 0,001, Q-value = 556,572 I2 = 94.519). The moderator analysis demonstrated that cartoons (SMD:-1.645, p < 0.001), games (SMD:-1.931, p = 0.001), music (SMD:-0.534, p < 0.001), video showings (SMD:-1.363, p = 0.001), and virtual reality (SMD:-1.782, p < 0.001) reduced preoperative anxiety in children. Conclusions: Audio-visual methods are effective in reducing preoperative anxiety in children. The results of this study may provide pediatric perioperative nurses with additional information to help them decrease anxiety for patients and their families. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024
Challenges of adopting artificial technology in human resource management practices
No full textIn this study, the challenges faced by organisations in integrating artificial intelligence (AI) into human resource management (HRM) practises are examined. For that, AI can bring significant benefits, includ¬ing increasing efficiency and decision-making in the HR processes, namely recruitment, performance evaluation and talent development. Its adoption, however, presents many challenges in technological infrastructure, data privacy, ethical, and organizational culture. This chapter investigates these barriers, particularly the importance of proper management changes and the trade-off between human element and AI's capabilities. The article discusses strategies for overcoming these challenges, the importance of practising ethical AI, data security and employee development. This study offers actionable insights for organisations attempting to leverage AI in HRM in a way that can succeed at both the operational and ethical dimensions. © 2025 by IGI Global Scientific Publishing. All rights reserved
Effect of heating rate on thermal inactivation kinetics of Escherichia coli O157:H7 in ground beef
No full textThe objective of this study was to investigate the effect of heating rate on thermal inactivation kinetics of microorganisms in food, testing the survival of Escherichia coli O157:H7 in ground beef during isothermal and dynamic heating. A 4-strain cocktail of E. coli O157:H7 was inoculated to irradiation-sterilized ground beef (10 % fat) and then subjected to isothermal heating (55-63 °C) and dynamic heating (20-63 °C). One-step analysis was used to determine the kinetic parameters. Different degrees of increased thermal resistance were observed in E. coli O157:H7 during dynamic heating. In comparison to isothermal heating, slight increase in the thermal resistance was found during fast heating (1.2-1.8 °C/min). However, slow heating (0.3-0.9 °C/min) led to significantly increased thermal resistance due to heat adaption at temperatures below 61.3 °C, but E. coli O157:H7 became more sensitive to heat above this temperature, suggesting that the increased resistance may diminish after reaching a critical temperature. To account for the increased heat resistance during dynamic heating, a unified kinetic model was developed and validated by applying one-step dynamic analysis, resulting in more accurate kinetic parameters to describe the survival curves of all heating rates. This study demonstrated that the kinetic parameters derived from isothermal conditions may not be applicable to dynamic conditions. It is necessary to consider the effect of heating rate and to determine the thermal inactivation kinetic parameters under dynamic conditions. It also demonstrated the advantage of using one-step dynamic analysis for evaluating thermal processes. The results of this study may be particularly useful for designing slow-heating processes to ensure proper cooking of products.4008630
Low Serum and Urine Fetuin-A Levels and High Composite Dietary Antioxidant Index as Risk Factors for Kidney Stone Formation
No full textBackground: Fetuin-A prevents the precipitation of hydroxyapatite in supersaturated solutions of calcium and phosphate; however, its relationship with nephrolithiasis has yet to be clarified. The aim of this study was to investigate the protective and predictive roles of serum and urine fetuin-A levels in nephrolithiasis and their relationships with the composite dietary antioxidant index (CDAI). Methods: This study involved 75 adult patients with kidney stone disease and 71 healthy adults without kidney stone disease in the control group. Participants had specific anthropometric measurements taken, and three-day food records were kept. The CDAI was calculated by summing six standard antioxidants, including vitamins A, C, and E, manganese, selenium, and zinc, representing participants' antioxidant profile. In addition to some analyzed serum and urine parameters of the participants, fetuin-A levels were measured using the enzyme-linked immunosorbent assay (ELISA) method. Results: In patients with kidney stones, both serum and urine fetuin-A levels (676.3 ± 160.14 ng/mL; 166.6 ± 128.13 ng/mL, respectively) were lower than in the control group (1455.6 ± 420.52 ng/mL; 2267.5 ± 1536.78 ng/mL, respectively) (p < 0.00001). In contrast, the CDAI was higher in patients with kidney stones compared to those without kidney stones (p < 0.001). Besides, several dietary parameters had significant positive correlations with serum and/or urinary fetuin-A. Conclusions: The present study suggests that serum and urinary fetuin-A levels may serve as protective factors against kidney stones and could potentially be used as predictive markers for the development of nephrolithiasis. Furthermore, our results suggest that the CDAI above a certain level may increase the risk of stone formation and that some dietary parameters may affect the levels of this biomarker in serum and urine.4009494
A comparative study of cognitive function and reaction time in obese and non-obese adults
No full textObjective: Obesity may negatively affect the physical health and cognitive functions of individuals and delay their reaction time to stimuli. However, the association among obesity, cognitive functions, and reaction times is yet to be fully elucidated. The aim of this study was to assess the effect of obesity on cognitive functions and visual and auditory reaction times in adults.
Methods: Data of 100 participants (50 obese and 50 normal) were analyzed in the study. Anthropometric parameters and 24-h dietary recall data were recorded. The Montreal Cognitive Assessment (MoCA) was used to evaluate the cognitive functions, Simple Reaction Time Task (SRTT)-Visual and SRTT-Auditory were used to assess visual and auditory reaction times of the participants, respectively.
Results: The mean MoCA score of the obese was significantly lower than normal (17.46 and 25.22, respectively; p < 0.001). In addition, the mean auditory (p < 0.001) and visual (p < 0.05) reaction times of obese were significantly longer than normal. Similarly, this condition was also observed for the fastest and lowest values of auditory and visual reaction times. Additionally, obesity caused a decrease in the MoCA score (β = -0.762; p < 0.001) and delayed visual (β = 0.423; p < 0.001) and auditory (β = 0.590; p < 0.001) reactions. The negative effect of obesity was maintained after controlling for potential factors (MoCA, β = -0.594; p < 0.001; SRTT-Auditory, β = 0.409; p < 0.01; SRTT-Visual, β = 0.330; p < 0.05).
Conclusion: Obese participants showed worse cognitive, auditory and visual performance. Additional research will be necessary in the future to shed light on the fundamental mechanisms involved.3990474
Snow cover detection using remote sensing techniques over different climate zones of Türkiye
No full textSnow-covered land surfaces can be easily mapped using remote sensing technologies. Accurate estimation of snow cover on the land surface allows for the construction of water resource management today. Using Landsat TM/ETM + satellite images, this study tried to assess how much snowfall covered the soil in Trabzon, Gümüşhane, and Bayburt provinces between 1999 and 2023. Satellite images were classified into three categories using the ERDAS 9.1 TM software. These classes are classified as snow-covered surfaces, other places, and data loss (cloud-shadow). When performing image analysis, it was important to verify that the cloudiness rate in the images was less than 15%. Images with cloudiness rates of more than 15% were not used. Seasonal and annual trend analysis of snow-covered areas (SCA) over three distinct regions (Trabzon, Gümüşhane, and Bayburt) were examined using the Mann-Kendall test. When three distinct study regions were examined together, Bayburt had the highest SCA rate, followed by Gümüşhane and Trabzon. In all three fields, the highest SCA was recorded in 2000, while the lowest SCA was recorded in 2017. The trends noticed that SCA on both annual and seasonal scales did not reach the statistical significance level of 0.05. Although snowfall in Trabzon, Gümüşhane, and Bayburt was beneficial in the autumn and spring seasons, no statistically significant association was found. The research concluded that the existing data are inadequate to make any statements on the impact of global warming in the area. However, the study figured out that satellite data may be effectively used to identify snowy places as a result of the study. Comparable investigations need to be undertaken in regions with varying climates, utilizing diverse remote sensing data and classification methodologies.4061559
Technological and nutritional aspects of fresh purslane (Portulaca oleracea L.) in ice cream production
No full textPurslane (Portulaca oleracea L.) is rich in ω-3 fatty acids, antioxidants, and minerals, and has notable neuroprotective, anti-inflammatory, antimicrobial, antidiabetic, antioxidant, anticancer, and antihypertensive properties. This research evaluated the effect of fresh purslane (FP) on the physicochemical and nutritional properties of ice cream, including α-linolenic acid (ALA; 18:3; ω-3), mineral content, and antioxidant properties, along with sensory characteristics. FP was added at 0, 5, 10, and 15% (w/w) levels. The addition of FP significantly increased the iron (Fe), calcium (Ca), copper (Cu), sodium (Na), oleic acid (OA), and ALA contents (P 0.05), but total phenolic content (TPC) and 2,2-diphenyl-1-picryl-hydrazyl (DPPH) radical scavenging activity significantly increased (P < 0.01). Thirty-one volatile compounds were identified, with increases in octadecane, dodecane, and 2-hexenal concentrations due to FP addition. Although the addition of FP improved the ALA content and antioxidant properties, sensory results showed that FP over 5% (w/w) lowered taste and general acceptability scores. Thus, using 5% of FP in ice cream is optimal for enhancing nutritional properties. © The authors
A novel equation synthesis for estimating resting energy expenditure in prostate cancer patients
No full textBackground: An accurate calculation of energy expenditure (REE) is necessary for estimating energy needs in malign prostate cancer. The purpose of this research was to evaluate the accuracy of the established novel equation for predicting REE in malign and benign prostate patients versus the accuracy of the previously used predictive equations based on REE measured by indirect calorimetry.
Methods: The study was conducted as a cross-sectional case-control study and between December 2020 and May 2021 with 40 individuals over the age of 40 who applied to the Urology Clinic of Gazi University Faculty of Medicine. Subjects with 41 malign prostate and 42 benign prostate patients were both over the age of 40 (65.3 ± 6.30 years) and recruited for the study. Cosmed-FitMate GS Indirect Calorimetry with Canopyhood (Rome, Italy) was used to measure REE. A full body composition analysis and anthropometric measurements were taken.
Clinical trial number: Not applicable.
Results: Malign prostate group PSA Total and measured REE values (4.93 ± 5.44 ng/ml, 1722.9 ± 272.69 kcal/d, respectively) were statistically significantly higher than benign group (1.76 ± 0.73 ng/ml, 1670.5 ± 266.76 kcal/d, respectively) (p = 0.022). Malign prostate group (MPG) and benign prostate group (BPG) have the highest percentage of the accurate prediction value of Eq. 80.9% (novel equation MPG) and 64.2% (novel equation BPG). The bias of the equations varied from - 36.5% (Barcellos II Equation) to 19.2% (Mifflin-St. Jeor equation) for the malign prostate group and varied from - 41.1% (Barcellos II Equation) to 17.7% (Mifflin-St. Jeor equation) in the benign prostate group. The smallest root mean squared error (RMSE) values in the malign and benign prostate groups were novel equation MPG (149 kcal/d) and novel equation BPG (202 kcal/d). The new specific equation for malign prostate cancer: REE = 3192,258+ (208,326* body weight (WT)) - (20,285* height (HT)) - (187,549* fat free mass (FFM)) - (203,214* fat mass (FM)) + (4,194* prostate specific antigen total (PSAT)). The new specific equation for the benign prostate group is REE = 615,922+ (13,094*WT). Bland-Altman plots reveal an equally random distribution of novel equations in the malign and benign prostate groups.
Conclusions: Previously established prediction equations for REE may be inconsistent. Utilising the PSAT parameter, we formulated novel energy prediction equations specific to prostate cancer. In any case, the novel predictive equations enable clinicians to estimate REE in people with malign and benign prostate groups with sufficient and most acceptable accuracy.4014881
[Grad-CAM yorumlanabilirliği ile hibrit CNN-Transformer modeller kullanılarak Alzheimer Hastalığının erken tanısı]
No full textDetecting Alzheimer's Disease (AD) at an early stage is vital because it enables prompt treatment and intervention, which can help slow disease progression and enhance patient prognosis. Given the increasing prevalence of AD globally, with an estimated 50 million people currently living with the condition and projected to triple by 2050, the development of accurate and efficient diagnostic tools is paramount. In this study, a novel architecture for the early diagnosis of AD by combining Convolutional Neural Networks (CNNs) or Vision Transformers (ViTs) with traditional Machine Learning (ML) algorithms was proposed. Utilizing MRI images as input, CNNs/ViTs serve as feature extractors, while demographic data is integrated to enhance diagnostic accuracy. Through extensive experimentation, our proposed model, which utilizes a CNN backbone optimized for MRI analysis as a feature extractor and LGBM as the classifier, achieved superior accuracy, reaching up to 96.83%. Statistical validation through confidence intervals and McNemar's test further demonstrated the robustness and significant performance improvements of the proposed model compared to baseline methods. This study employs eXplainable Al techniques to visualize critical regions in MRI images that influence the model's diagnostic decisions, promoting clinical transparency and trust in Al-assisted early diagnosis of AD. The novelty of this study lies in integrating deep feature extractors (CNNs/ViTs) with traditional ML classifiers, supported by interpretability through Grad-CAM and statistical validation, offering a transparent and accurate framework for early diagnosis of AD. © 2025, GUFBD/GUJS. All rights reserved.2-s2.0-10501871210