Minimum Value Research Articles

A fuzzy-PID controller for load frequency control of a two-area power system using a hybrid algorithm

This paper presents the use of a new hybrid optimization approach known as particle swarm optimization and grey wolf optimizer (PSO-GWO) for improving frequency stability load frequency control (LFC) in tow-area power systems. The approach consists in optimizing the fuzzy proportional-integral-derivative (fuzzy-PID) controller parameters with meta-heuristic hybrid algorithm: PSO-GWO. This technique allows to have dynamic responses with the least possible frequency deviation in very short response times. The approach proposes to controls the tie-line power and the frequency deviation in the considered two-area power systems under variable perturbation in load and changing of system parameters in order to evaluate its effectiveness. The suggested hybrid algorithm-based fuzzy-PID controller is compared with various widely used control methods in the literature such as PID controller and algorithms such as PSO and GWO in order to evaluate its effectiveness and its robustness. Through the simulations carried out on MATLAB/Simulink, the proposed PSO-GWO fuzzy-PID and the objective function exhibit improved performance, achieving minimal objective values. The proposed technique proved to be quite powerful tool in the resolution of problems related to electrical power systems, particularly in load frequency control.

Inverse distance weight-assisted particle swarm optimized indoor localization

Indoor localization using wireless fidelity (WiFi) fingerprint has attracted considerable attention due to its extensive deployment and low cost. Most indoor fingerprint localization methods could be computationally inefficient and behave with unsatisfactory positioning accuracy. Therefore, an inverse distance weight (IDW) assisted particle swarm optimized (PSO) indoor localization (IDWPSOInLoc) algorithm is proposed. It is an optimized positioning process in the online stage rather than an offline optimization approach. The main idea is to find the optimal particle with the most similar generated fingerprint to the real-time testing one in the online stage. K nearest neighbors and boundary constraints are combined to initialize particles’ positions. The generated fingerprint of each particle is interpolated based on the IDW algorithm and nearby reference points within a specified range. A new fitness function, the sum of standard deviations between the generated and real-time testing fingerprints, is proposed to find the optimal particle. The position of the optimal particle with the minimal fitness value is taken as the estimated coordinate through iterations updating the particles’ velocities, positions, and generated fingerprints. IDWPSOInLoc achieves a mean positioning accuracy of 2.477 meters in the local environment experimental test and that of about 6 meters using selected floor in the UJIIndoorLoc dataset. Compared with state-of-the-art algorithms, positioning error is decreased by at least 11.9%. In addition, IDWPSOInLoc has the characteristic of low computational complexity. Experimental results show that the proposed IDWPSOInLoc outperforms the considered WiFi indoor positioning algorithms.

Crypto-influencers

AbstractThis study examines the investment value of information provided by crypto-influencers, that is, social media influencers covering crypto assets on Twitter. We examine the returns associated with approximately 36,000 tweets issued by 180 of the most prominent crypto social media influencers covering over 1,600 crypto assets for the two years spanning through December 2022. Our primary results indicate that crypto-influencers’ tweets are initially associated with positive returns. However, these tweets are followed by significant negative longer-horizon returns, suggesting they generate minimal long-term investment value. These effects are most pronounced for tweets issued by crypto-influencers proclaiming to be crypto experts, for smaller cap crypto asset securities and for self-described experts with many Twitter followers. In an additional analysis, we use machine-learning methods to classify tweets and find that this pattern of results strengthens when the tweets have a more positive sentiment or relate to buy recommendations.

Pilot study: Measurement of first phase ejection fraction in a sample of Egyptian people

Abstract Background Left ventricular dysfunction (LVD) constitutes the final common pathway for a number of cardiac disorders. Ischemic heart disease (IHD) is the dominant cause of heart failure (HF). The remaining etiologies include cardiomyopathy, hypertension (HTN), valvular heart diseases (VHD) and myocarditis. Data from the Framingham heart study shows that it develops in approximately 16% of men and 18% of women who had diabetes; 12% of men and 8% of women who had HTN; and 30% of both sexes who had myocardial infarction (MI). Aim of the Work to measure the first phase ejection fraction (EF1) in a sample of Egyptian population and to determine its normal value and to assess its reliability in assessment of systolic function. Patients and Methods This study is a prospective and observational clinical that was conducted at El- Mokattam health insurance & Ain Shams University hospitals from October 2019 to March 2022. Results we found that mean EF1 was 35.41 ± 4.16 %, its minimal value was 26.9% and its maximal value was 43.4%. We found that EF1 was reliable and reproducible as there was no statistically significant intra observer nor inter observer variabilities (p-value was 0.547 & 0.602 respectively). We found that there was no significant statistical correlation between EF1 and gender or heart rate or other demographic or clinical data. Conclusion EF1 is a simple and reproducible measurement of LV systolic function that is easily measured by transthoracic echocardiography and is considered comparable to other indices that measure LV systolic function.

Differential Serum Phosphate Levels in Pediatric Febrile Syndromes and Their Clinical Significance.

The potential of hypophosphatemia (HP) to differentiate between febrile syndromes and its clinical significance in children without sepsis were not previously described. Data were retrospectively collected of febrile children aged 3 months to 18 years, hospitalized at general pediatric wards during 2010-2019. Phosphate levels were compared between bacterial infection (BI), viral infection (VI), and Kawasaki disease (KD). Regression analyses were used to evaluate the relationship between HP and outcome. Of 3963 febrile children, 559 had BI, 3271 had VI, and 133 had KD. In BI compared to VI and KD, HP was more prevalent (49.2%, 19.7%, and 31.6%, respectively; P<0.001) and more severe [median (interquartile range) phosphate standard deviation score: -1.85 (2.08), -0.56 (2.08), and -1.20 (2.28), respectively; P<0.001]. In the BI group, Pi-SDS level was lower among patients with than without bacteremia (-2.33 ± 1.8 vs. -0.79 ± 1.68; P<0.001). Phosphate levels displayed discriminatory potential between bacterial and viral etiologies, with an area under the curve of 0.719 (95% CI, 0.697-0.742). Minimal phosphate standard deviation score values had a negative weak correlation with the maximal C-reactive protein levels and white blood cell count. Univariate and multivariate analyses showed an association of HP with a more severe disease course, manifested by longer hospital stay [+2.10 (95% CI, 0.75-3.46) days; P=0.003] and a higher rate of intensive care unit admission [odds ratio, 2.63 (95% CI, 1.94-3.56); P<0.001). Hypophosphatemia rates were highest in bacterial etiology, intermediate in KD, and lowest in viral etiology and were associated with poorer outcomes. Phosphate level may serve as a marker for ruling out a bacterial etiology.

Immuno-informatics study identifies conserved T cell epitopes in non-structural proteins of Bluetongue virus serotypes: formulation of a computationally optimized next-generation broad-spectrum multi-epitope vaccine.

Bluetongue (BT) poses a significant threat to the livestock industry, affecting various animal species and resulting in substantial economic losses. The existence of numerous BT virus (BTV) serotypes has hindered control efforts, highlighting the need for broad-spectrum vaccines. In this study, we evaluated the conserved amino acid sequences within key non-structural (NS) proteins of BTV and identified numerous highly conserved murine- and bovine-specific MHC class I-restricted (MHC-I) CD8+ and MHC-II-restricted CD4+ epitopes. We then screened these conserved epitopes for antigenicity, allergenicity, toxicity, and solubility. Using these epitopes, we developed in silico-based broad-spectrum multiepitope vaccines with Toll-like receptor (TLR-4) agonists. The predicted proinflammatory cytokine response was assessed in silico using the C-IMMSIM server. Structural modeling and refinement were achieved using Robetta and GalaxyWEB servers. Finally, we assessed the stability of the docking complexes through extensive 100-nanosecond molecular dynamics simulations before considering the vaccines for codon optimization and in silico cloning. We found many epitopes that meet these criteria within NS1 and NS2 proteins and developed in silico broad-spectrum vaccines. The immune simulation studies revealed that these vaccines induce high levels of IFN-γ and IL-2 in the vaccinated groups. Protein-protein docking analysis demonstrated promising epitopes with strong binding affinities to TLR-4. The docked complexes were stable, with minimal Root Mean Square Deviation and Root Mean Square Fluctuation values. Finally, the in silico-cloned plasmids have high % of GC content with > 0.8 codon adaptation index, suggesting they are suitable for expressing the protein vaccines in prokaryotic system. These next-generation vaccine designs are promising and warrant further investigation in wet lab experiments to assess their immunogenicity, safety, and efficacy for practical application in livestock. Our findings offer a robust framework for developing a comprehensive, broad-spectrum vaccine, potentially revolutionizing BT control and prevention strategies in the livestock industry.

Implementing fuzzy SMRGT, ANN, and ANFIS for flow coefficient estimation in Antalya River Basin

The estimation of the flow coefficient is a vital hydrological procedure that holds considerable importance in flood prediction, water resource management, and flood mitigation. The precise estimation of the flow coefficient is imperative in mitigating flood-related damages, administering flood alert mechanisms, and regulating water discharge. It is hard to accurately determine the flow coefficient without a good understanding of the river basin’s hydrology, climate, topography, and soil characteristics. A range of methodologies have been documented in the most recent body of literaturefor flow coefficient modeling. The majority of these methods, however, depend on opaque techniques that lack generalizability. Therefore, this research employed three distinct methodologies—specifically, the Adaptive Neural Fuzzy Inference System (ANFIS), the Simple Membership Function, and the Fuzzy Rules Generation Technique (SMRGT) are all examples of fuzzy inference systems, and Artificial Neural Network (ANN), to achieve its objectives. The Aksu River Basin in Antalya, Turkey, was chosen as the study area. The models underwent multiple permutations of precipitation (P), temperature (T), relative humidity (Rh), wind speed (Ws), land use (LU), and soil properties (Sp) data that were tailored to the particular study region. The study analyzed the results using various performance metrics of the model such as mean absolute error (MAE), Nash–Sutcliffe efficiency coefficient (NSE), root mean square error (RMSE), and correlation coefficient (R2). The results indicate that the SMRGT method resulted in a remarkable degree of accuracy in forecasting the flow coefficient, as demonstrated with the minimal RMSE and MAE values and high correlation coefficient values. The study’s findings suggest that the SMRGT method was applied effectively in hydrological analysis to estimate the flow coefficient, contributing to more accurate flood prediction, water resource management, and flood mitigation strategies.

Hyperreflective focuses as a biomarker of multiple sclerosis progression

Purpose: to identify the intraretinal hyperreflective foci (HRF), their specific characteristics, localization features and correlations with the duration of the disease, type of course and previous episodes of optic neuritis (ON) in multiple sclerosis (MS) patients using a high-resolution OCT scanning protocol. Materials and methods. The study included 160 patients (318 eyes) divided into 8 groups, i.e. Group 1: 44 eyes (13.84 %) — MS onset without a history of ON; Group 2: 30 eyes (9.43 %) — debut of MS with ON; Group 3: 56 eyes (17.61 %) — relapsing-remitting MS (RRMS) lasting ≤ 10 years without ON; Group 4: 38 eyes (11.95 %) — RRMS lasting ≤ 10 years with ON; Group 5: 49 eyes (15.41 %) — RRMS lasting ˃ 10 years without ON; Group 6: 37 eyes (11.63 %) — RRMS lasting ˃ 10 years with ON; Group 7: 34 eyes (10.69 %) — secondary progressive MS (SPMS) without ON; Group 8: 30 eyes (9.43 %) — SPMS with ON. Results. HRF were identified in all groups, at the levels of both the outer nuclear layer (ONL) and the inner nuclear layer (INL). Their number increased depending on the duration, type of course, and the presence of ON history. The thickness of the inner layers of the retina corresponded to the average normative indicators in the group with the onset of MS without ON. In the SPMS group after ON, a decrease in the total thickness of ganglions retinal cells layer (GCL) and the inner plexiform layer (IPL) was noted, showing minimal values of both avGCL + IPL (65.83 ± 8.27 μm) and avRNFL (76.37 ± 6.94 μm). High inverse correlations were revealed between avGCL + IPL and the amount of GRF at the levels of ONL and INL (-0.82 and -0.85, respectively, p = 0.01). Conclusions. The presence and quantity of HRF can be considered as a prognostic non-invasive biomarker associated with the duration of MS and the history of ON, allowing one to visualize the penetration of microglia activated by immune cells into the unmyelinated part of the central nervous system, helpful in elucidating their role in the pathogenesis and progression of the disease.

Xenon Antiaggregant Effects.

In in vitro model of short-term therapeutic inhalation of Xe/O2 mixture, xenon in millimolar concentrations led to a pronounced decrease in induced platelet aggregation in the platelet-enriched blood plasma. The maximum and statistically significant decrease occurred in response to induction by collagen (by ≈30%, p≤0.01) and ADP (by ≈25%, p≤0.01). A slightly weaker but statistically significant reduction in aggregation appeared in response to ristocetin (by ≈12%, p≤0.01) and epinephrine (by ≈9%, p≤0.01). It should be noted that the spontaneous aggregation exceeded the reference values in the control group. Nevertheless, even at minimal absolute values, spontaneous platelet aggregation decreased by 2 times in response to xenon (p≤0.01). The reasons for the decrease of spontaneous and induced aggregation are xenon accumulation in the lipid bilayer of the membrane with subsequent nonspecific (mechanical) disassociation of membrane platelet structures and specific block of its distinct from neuronal NMDA receptor.

A new intervention to prevent social isolation in people with complex communication needs

While implementing communication interventions, practitioners follow diverse theoretical models. Different conceptual orientations influence the way professionals embrace the subject of communication and its disorders. This research project explores the co-creation and validation of a new model and intervention program to analyze and improve communication between persons with Complex Communication Needs and their caregivers. The methodology incorporated a comprehensive narrative review, as foundation for the new model and intervention proposal. Succeeding this stage, the team implemented an online Delphi Panel to improve and validate these results, involving 17 international renowned experts. Following the Appropriateness Method, 25 indications were subject to scrutiny and rated as appropriate with minimal values of disagreement among the evaluators. Qualitative feedback was used to improve the research products. Quality assurance measures were taken to ensure quality and transparency of the results. A new conceptual framework of atypical interpersonal communication and intervention program result from the investigation. The new model is inspired by the Transactional model and principles of Dialogism. The intervention consists of consultations with caregivers, using video analysis and a dialogical methodology to enhance communication. The next research phase is to pilot-test the intervention program with clinicians supporting persons with disability at risk of social isolation.

Supportive psychotherapeutic intervention and video directing observed therapy to increase family adherence

To determine the effect of supportive psychotherapy and video-directing observed therapy interventions on family compliance in assisting patients with mental disorders in the working area of the Kabila Health Center, Bone Bolango District, Gorontalo City. Research design quasi-experimental design with a one group pre- and post-test design, where the variables to be measured are family adherence in providing treatment assistance, which are included in the dependent variable. The independent variables in this study were supportive psychotherapy and video-directed observation therapy. The sampling technique used was a total sampling technique with a sample size of 39 respondents. Data analysis was performed using univariate analysis, namely descriptive analysis (frequency, percentage, median, minimum value, and maximum value) and bivariate analysis (Wilcoxon test), with a significance level of &amp;lt;0.05, which was performed using SPSS version 25 software. Supportive psychotherapy and video-directing observed therapy increased family compliance accompanying the treatment of patients with mental disorders (p-value of x1=0.020, x2=0.000, p&amp;lt;0.05). Supportive psychotherapy interventions and video-directed observed therapy have been proven to increase family compliance in treatment assistance, which can improve the quality of life of patients with mental disorders.

Dynamic ant colony optimization algorithm for parameter estimation of PEM fuel cell

Proton Exchange Membrane Fuel Cells (PEMFCs) provide a reliable, pollution-free, sustainable, and stable power generating alternative to non-renewable resources, and they do not self-discharge. Proton exchange membrane fuel cells (PEMFCs) necessitate correct parameter estimates for effective investigation, modelling and designing effective fuel cells, highlighting the importance of exact modelling for successful use in many industries. The present research aims to determine the approximate parameters estimation of PEMFC using a modified algorithm derived from the Ant Colony Optimization (ACO) meta-heuristic algorithm. In order to provide justification for the algorithm, it is initially benchmarked against 10 functions. The study compares the outcomes of PEMFC parameter estimation through the Dynamic Ant Colony Optimisation (DACO) algorithm including some additional metaheuristic algorithms such as Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO), Artificial Bee Colony (ABC), Differential Evolution (DE) algorithm, and an algorithm known as Grey Wolf Optimisation - Cuckoo Search (GWOCS) which is hybrid in nature. The suggested algorithm’s performance evaluation is based on minimising the Square Error (SSE). The modified proposed optimization algorithm exhibits superior performance compared to other alternative meta-heuristic algorithms due to its minimal SSE value. The effectiveness and efficiency of the modified method based on the Ballard Mark V datasheet were evaluated using statistical error analysis and non-parametric testing. The convergence curves of DACO demonstrate a faster convergence compared to the other optimization algorithms.

Unveiling the Anti-Candida albicans activity of bioactive fractions of mining soil-dwelling Streptomyces sp. DS104

Due to an increase in the incidence of Candida albicans infection and its growing resistance to currently used antifungal drugs, further development of more potent antimicrobials is needed. This study sought to assess the antifungal properties of Streptomyces sp. DS104, isolated from a mining soil, against C. albicans and identify the bioactive substances that are produced by this strain. Ethyl acetate supernatant's crude extract showed a high inhibition against C. albicans, with a minimal inhibitory concentration (MIC) value as low as 4 µg/mL. Two bioactive fractions (F5 and F6) have been isolated using silica gel column chromatography, demonstrating zones of inhibition against C. albicans measuring 28.33 ± 01.52 to 29.00 ± 02.64 mm. The GC-MS analysis was carried out on the purified fractions and allowed the identification of 21 compounds predominantly consisting of carboxylic acids and pyrrolopyrazine derivatives. In Fraction F5, the major compounds detected are pentadecanoic and hexadecanoic acids, constituting the highest area percentages of 41.99% and 33.77%, respectively. As for fraction F6, the predominant compounds include pyrrolo[1,2-a]pyrazine-1,4-dione, hexahydro-3-(2-methylpropyl) and pyrrolo[1,2-a]pyrazine-1,4-dione, hexahydro-3-(methylphenyl), accounting for area percentages of 20.18% and 12.16%, respectively. Various other bioactive compounds, such as isocoumarins, and phenolic compounds, had previously been identified as components with antifungal activity, were also detected. It's worth highlighting that three compounds specifically, 2-hydrazino-8-hydroxy-4-phenylquinoline, hydroxyphenylacetic acid, and 3-carboxaldehyde-1H-indole have been reported for the first time to be detected within the Streptomyces genus. These results suggested that Streptomyces sp. DS104 is a promising strain and thus appears to be a potential candidate for the development of antifungal drugs.

Geoelectric Modelling Based on Bessel Functions Integral and Damped Least-Square Inversion for Layered Earth Models

Apparent resistivity formulations of a geoelectric method for layered Earth have been obtained analytically in the Bessel functions integral. This formulation is obtained through the application of two boundary conditions. First, the current density is zero at the Earth's surface. Second, current density and electric potential are continuous at the boundary between the layers. Geoelectric modelling can be done using several model parameters through this formulation. The modelling results show that apparent resistivity formulations based on Bessel function integrals can simulate apparent resistivity curves for layered earth models. The inversion process uses the apparent resistivity formulation based on Bessel function integrals. In this study, the inversion process uses a dumped Least-squared inversion method. The first step begins by testing the inversion program using synthetic data. After that, the inversion program is used in field data. The inversion results using field data from geoelectric data in Mount Pandan, East Java, show that the program was well done, with a minimal error value of 1.24%.

Quality Assessment of Developed Cumin Cookies

Abstract: Cookies are good carrier of nutrients like carbohydrate and fat which can be enriched with protein. Refined Flour is the finest type of wheat flour containing high calorie content but minimal nutritional value that is used to make pizza, bread, samosa, kachoris, puri, cakes and biscuits.by partially replacing refined wheat flour with wheat flour up to an acceptable level. It is a fast and quick recipe for cookies made with Refined wheat flour, wheat flour and cumin seeds. The special characteristic of these cookies is that, as opposed to other cookie recipes, they do not contain plain flour, sugar or even jaggery. It is an excellent snack or coffee snack for munching and is enjoyed by all age groups, including children and adults because of its rich nutrients.

Linear support for the prime number sequence and the first and second Hardy-Littlewood conjectures

Servais and Grün used results about linear support for the prime number sequence to obtain upper bounds on the smallest prime in odd perfect numbers. This was extended by Cohen and Hendy who proved that for every $n \in \mathbb {N}$ there exists an integer $b_n$ such that $p_i \ge p_1 + ni - b_n$ for any sequence $(p_i)$ of odd primes, and found minimal values of $b_n$ for $3 \le n \le 5$, and conjectured minimal values for $6 \le n \le 10$. We give a new proof of the existence of $b_n$ and the values for $3 \le n \le 5$. We also show that if we assume that the second Hardy-Littlewood conjecture, $\pi (a+b) \le \pi (a) + \pi (b)$ for $a, b \ge 2$, is true, then we can in a finite number of steps determine numbers, $T_n$, that give quite close bounds for the values of $b_n$, namely $T_n \le b_n \le T_n + n - 2$, and determine the values of $T_n$ for $6 \le n \le 20$. We also consider the question of whether the values of $b_n$ can be replaced by smaller numbers if we assume that $p_1 &gt; 3$. We will show that if we assume that the first Hardy-Littlewood conjecture is true, then we can determine the minimum such values, $a_n$, for $3 \le n \le 5$. We also determine some lower bounds for $a_n$ for $n \ge 6$. It is well-known that the two Hardy-Littlewood conjectures are mutually exclusive, but we never use both conjectures simultaneously. These results give us the upper bound $p_1&lt;\frac {n}{2^n-1}t+b_n$ on the smallest prime in odd perfect numbers, where $t$ is the number of distinct primes dividing the odd perfect number. This bound was also found by Cohen and Hendy, but we improve the constants $b_n$.

Пыльцевой анализ линий селекционно-генетической коллекции подсолнечника

We studied pollen productivity and its morphological heterogeneity in the lines of the breeding and genetic sunflower collection. The research was carried out at the V.S. Pustovoit All-Russian Research Institute of Oil Crops, Krasnodar, in 2022–2023. Collection lines VK934, VK1-klp, VK678, VK876, In Krupnyak, VK195, MVG-8, VK416, L2138, K1587, KG49 and RIL200 were used. To assess the quality of pollen, we used the parameter of morphological heterogeneity of pollen grains, i.e. the proportion of atypical grains. The pollen productivity was assessed by two parameters: pollen weight and the number of pollen grains. A Biolab TS-2000 LCD MS 20 microscope was used at a magnification of 40×. A line L2138 was characterized by a maximum weight of 1.17 mg/anther and a number of pollen grains of 45,239 pieces/anther. A line VK876 had the minimal values of these traits – 0.25 mg/anther and 16448 pcs/anther, respectively. A high positive correlation of r = 0.90 was noted between these traits. In 2022, the average diameter of pollen grains in 12 studied lines varied from 30 to 32 µm, with an average value of 31 µm. In 2023, the minimal diameter of pollen grains was lower than in 2022 and amounted to 27 µm, the maximum was at the level of 2022 – 32 µm with an average value of 30 µm. Over two years of research, a line KG49 showed significant morphological heterogeneity of pollen, which was expressed in a high proportion of defective pollen grains (58%). A line VK195 was characterized by low morphological heterogeneity with a proportion of defective pollen grains of 5%.

Recommendations for Additional Imaging on Head and Neck Imaging Examinations: Interradiologist Variation and Associated Factors.

BACKGROUND. A paucity of relevant guidelines may lead to pronounced variation among radiologists in issuing recommendations for additional imaging (RAI) for head and neck imaging. OBJECTIVE. The purpose of this article was to explore associations of RAI for head and neck imaging examinations with examination, patient, and radiologist factors and to assess the role of individual radiologist-specific behavior in issuing such RAI. METHODS. This retrospective study included 39,200 patients (median age, 58 years; 21,855 women, 17,315 men, 30 with missing sex information) who underwent 39,200 head and neck CT or MRI examinations, interpreted by 61 radiologists, from June 1, 2021, through May 31, 2022. A natural language processing (NLP) tool with manual review of NLP results was used to identify RAI in report impressions. Interradiologist variation in RAI rates was assessed. A generalized mixed-effects model was used to assess associations between RAI and examination, patient, and radiologist factors. RESULTS. A total of 2943 (7.5%) reports contained RAI. Individual radiologist RAI rates ranged from 0.8% to 22.0% (median, 7.1%; IQR, 5.2-10.2%), representing a 27.5-fold difference between minimum and a maximum values and 1.8-fold difference between 25th and 75th percentiles. In multivariable analysis, RAI likelihood was higher for CTA than for CT examinations (OR, 1.32), for examinations that included a trainee in report generation (OR, 1.23), and for patients with self-identified race of Black or African American versus White (OR, 1.25); was lower for male than female patients (OR, 0.90); and was associated with increasing patient age (OR, 1.09 per decade) and inversely associated with radiologist years since training (OR, 0.90 per 5 years). The model accounted for 10.9% of the likelihood of RAI. Of explainable likelihood of RAI, 25.7% was attributable to examination, patient, and radiologist factors; 74.3% was attributable to radiologist-specific behavior. CONCLUSION. Interradiologist variation in RAI rates for head and neck imaging was substantial. RAI appear to be more substantially associated with individual radiologist-specific behavior than with measurable systemic factors. CLINICAL IMPACT. Quality improvement initiatives, incorporating best practices for incidental findings management, may help reduce radiologist preference-sensitive decision-making in issuing RAI for head and neck imaging and associated care variation.

Type-3 fuzzy dynamic adaptation of Bee colony optimization applied to mathematical functions

In this article, an Interval Type-3 Fuzzy Logic System (IT3FLS) for enhancing the performance in Bee Colony Optimization (BCO) is outlined. The efficiency of the IT3FLS approach is verified with results on a set of benchmark mathematical functions. The IT3FLS provides an approach that helps to identify the optimal values in α and β parameters that allows to improve the performance in the original BCO. The IT3FLS approach exhibits advantages in the optimization of the benchmark functions. It can be noted that a IT3FLS exhibits better results in the minimal values of the set of mathematical functions. The experimentation demostrates that the implementation of the IT3FLS approach enhances the performance of BCO when compared with respect to the variants utilizing Generalized Type-2 FLS (GT2FLS), Interval Type-2 FLS (IT2FLS) and Type-1 FLS (T1FLS).

Insignificance of the Act in Criminal and Administrative Tort Law: Nature and Content

The study develops an idea of the criminal legal nature of the insignificance of the act. The author arguments in favor of the fact that such nature is due to the differentiated approach of the federal legislator to assessing the level of public danger of actions and inaction provided for by criminal law. At the same time, the high role of the law enforcement officer in determining the scale of the threat posed by a specific offense for the object of criminal law protection is stated. Studying the mitigating and aggravating circumstances of the act, the personal characteristics of the offender and the line of their behavior, the court decides on the degree of public danger of the relevant act. Its minimal value becomes the reason for raising the question of recognizing the committed action or inaction as insignificant. The paper considers issues on categories of crimes that the offense formally falls under and thus can be assessed on the grounds of insignificance. It is argued against a well-known judgment that the insignificance of the act containing structural elements of the corpus delicti serves as the basis for evaluating what was done according to the norms and provisions of another branch of Russian legislation. A mechanism for developing the insignificance category potential at the level of an individual criminal wrong, known as a criminal offense, is proposed. The study offers a set of arguments proving the inconsistency of the position of the legislator and law enforcement officer on the issue of the possibility of recognizing an administrative offense as insignificant. Their essence boils down to the fact that the formal essence of administrative offenses excludes their differentiation into groups according to the level of harmfulness. This implies the inexpediency of using the category of insignificance in the legislation on administrative offenses.