This study delves into the dynamic behavior and thermal effects on isolated protein microtubules. Microtubules, pivotal as bio-beam structures, form an essential component of the cytoskeleton in eukaryotic cells. Modeling microtubules as beam elements is crucial for accurately capturing their dynamic characteristics. To this end, the equation of motion is formulated, accompanied by parametric analyses to examine the influences of shear deformation, thermal effects, and the length scale coefficient. The findings are then juxtaposed with classical systems and existing literature, demonstrating that the approach adopted in this research yields results that are not only more precise but also align more closely with experimental data, underscoring the superiority of the proposed system in capturing the nuanced behavior of microtubules.

In this research, the dynamic behavior, along with the thermal impacts using isolated protein microtubules, is investigated. Microtubules are one of the bio-beam structures, which is a significant part of the cytoskeleton in eukaryotic posses and cells. A significant role in the dynamic characteristics is to model the microtubules consistent with a beam element. The equation of motion is constructed along with the parametric investigations to scrutinize the impacts of shear deformation, thermal effect, and coefficient of length scale. The obtained form of the results is compared with the classical systems along with the literature results designating the system provided in this study as more precise than other systems in better agreement using the experimental data.

This paper presents an analytical investigation of wave propagation in a rotating, isotropic, transversely magneto-piezoelectric thermoelastic solid bar submerged in an inviscid fluid. Using the principles of linearized elasticity theory, the study explores displacement potential functions and derives an analytical solution to the governing motion equations with Bessel functions. A numerical analysis is conducted to examine the interaction between the rotating bar and the surrounding fluid under specific boundary conditions. The numerical results, shown as dispersion curves, reveal the impact of various parameters on the system. This research has significant applications in improving livestock environments, particularly in water treatment for cattle farming, enhancing filtration efficiency, and developing advanced membrane materials for water purification and air filtration systems. Additionally, it offers potential for optimizing the quality of water and air in livestock settings, contributing to better animal health and environmental conditions.

The leadership feature can activate organizational citizenship behavior and organizational identification by making them visible and ensuring their continuity. In this context, the research aimed to examine the effects of ethical leadership and responsible leadership behaviors on organizational identification and organizational citizenship behaviors through moral awareness. For this purpose, with the help of scales whose validity and reliability have been previously approved in the literature, data collection was conducted on healthcare professionals working in healthcare institutions and administrative institutions providing clinical and polyclinic services under the Provincial Health Directorate on the European side of Istanbul. Data was obtained from 639 healthcare professionals. To collect data, surveys were applied through face-to-face interviews, one of the field research methods. For the purpose of the study, fit indices were first checked with confirmatory factor analysis, and the suitability of the data for normal distribution was evaluated with histogram, Q-Q graphs and Shapiro-Wilk test. The homogeneity of variance was evaluated with the Levene test. In comparisons between groups, an independent two-sample t-test was applied for quantitative variables. One-way analysis of variance was used for comparisons between more than two groups. Tukey and Tamhane's tests were applied for multiple comparisons. The relationship between quantitative data was evaluated with Pearson correlation analysis. Then, correlation and hierarchical regression analyses were conducted to evaluate the hypotheses established for the working model. The mediator effect between the scales was investigated. Data analysis was conducted in R 4.3.2 (www.r-project.org) software. The significance level was accepted as p<0.05. As a result of the analysis, it was determined that ethical leadership and responsible leadership behaviours in healthcare businesses positively affected organizational citizenship behaviour and organizational identification. Additionally, moral awareness has been found to play a mediating role.

In recent years, Algeria has been introducing English as a subject in intermediate schools, with instruction intensifying in high schools before students move on to university. Some Algerian universities and higher institutes already use English instead of French or Arabic as the language of instruction. The country is currently reforming its education system in line with the government’s continual efforts. English is crucial for key science majors like mathematics, chemistry, and computing education In fact, as the majority of world knowledge is written in English, respective teachers should be educated to teach these areas using English as the means of instruction. This study describes Algerian university teachers’ attitudes and perceptions about their preparation for learning to teach scientific modules using English as a means of instruction with their students. An openended questionnaire gathered data from 50 teachers at the Intensive Language Teaching Centre (CILT), who received training in general English for future use in teaching. These teachers indicated that English was of paramount need for their concept development in science education. The present work discusses these and other findings, offering insights into practices that could improve both science education and English language acquisition.

This research article investigates the impact of rotation and gravity on the deformation of a fiber-reinforced elastic medium subjected to a magnetic field, considering the presence of initial hydrostatic stress. The study delves into the theory of generalized surface waves and applies it to analyze specific cases. An analytical solution to the Equations of motion for the fiber-reinforced elastic medium, considering specific boundary conditions, is derived. The dispersion curves for displacement components and normal and shear stress components are examined, taking into account the influence of rotation, initial stress, magnetic field, and gravity field. The numerical results are presented and visually depicted for each variable of interest. Lastly, comprehensive comparisons are conducted between scenarios with and without initial hydrostatic stress, rotation, gravity field, and magnetic field, facilitating a thorough understanding of their combined effects.

This study develops a computational framework using a Levenberg-Marquardt backpropagation neural network (LMBNN) to solve the fractional-order Buruli ulcer (BU) and cholera model, integrating key aspects of microbial genetics and disease dynamics. The fractional-order model accounts for ten distinct categories, reflecting the nonlinear dynamics of infection, pathogen evolution, and host-pathogen interactions. Numerical solutions are derived using the stochastic LMBNN approach, supported by a dataset optimized with the Adam scheme. The data is partitioned into 76% for training and 12% each for validation and testing to minimize the Mean Square Error (MSE). The neural network employs a single layer with twelve neurons and a log-sigmoid activation function, offering precise approximations of disease dynamics. Validation against reference solutions shows negligible absolute error, confirming the solver's reliability. Statistical analyses further validate the model's robustness, making it a valuable tool for studying genetic resistance, microbial evolution, and the dynamics of infectious diseases.

This study investigates the combined effects of fractional order heat conduction and variable thermal conductivity on the propagation of thermal, acoustic, and optical waves in a rotating hydro-semiconductor medium. The novelty of this work lies in incorporating both fractional heat transfer theory and variable thermal conductivity within a hydrodynamic semiconductor model subjected to rotational effects, which has not been thoroughly explored in previous studies. The governing equations are formulated based on photo-thermoelasticity and fractional calculus, introducing a fractional heat conduction model to account for nonlocal and memory-dependent thermal responses. The normal mode analysis technique is applied. Numerical solutions are obtained and graphically represented to analyze the influence of fractional order parameters, variable thermal conductivity, and rotational effects. The results highlight significant deviations in wave propagation behavior when fractional heat transfer and thermal conductivity variations are included compared to classical heat conduction models.

This study is an attempt to analyze and determine impact of CPEC investment on Pakistan and its environment. In recent years, air pollution and global climate change issues caused by greenhouse gases have become the focus of international attention. However, analysts are of the view that CPEC investment shall be having far-reaching effects not only for Pakistan but for the region as well. The expected impact of CPEC project on transportation and infrastructure will cause future GHG projections to hike up. Due to dependency of transporters to rely upon fossil fuels, CO2 from vehicular emission is expected to elevate immensely. In order to mitigate its negative impact, this paper presents strategies that need to be designed to successfully manage consumption of fuel and emission of hazardous gases. Hence, a model of Green ICT based ITS technologies is presented to mitigate the risk of environmental degradation in Pakistan on CPEC transportation route. However, it will take a length of time to accept such a transition for complete replacement and incorporation of dynamic measures in ITS infrastructure.

The effect of drought stress on 11durum wheat (Triticum durum Desf.) cultivars at the germination stage was determined. Cultivars were screened to select for drought-tolerance. Six osmotic stress levels (0, -0.47, -1.48, -3.02, -5.11 and -7.73 bars) were assessed by using different concentrations of polyethylene glycol (PEG-8000). Analysis of variance showed significant differences between treatments for all seedling characteristics (p<0.05, p<0.001) except for mean day germination (MDG). All seedling traits also differed significantly (p<0.001) among all cultivars. In general, osmotic stress decreased seed germination percentage, germination rate (GR), coleoptile length (CL), shoot length (SL), root length (RL), root/shoot (R/S) length ratio and root number (RN). Averaged over all osmotic stress levels, Mahmoudi had high MDG (0.55), GR (1.88), CL (4.20 cm), SL (10.45 cm), and RL (9.93 cm), suggesting it was highly tolerant to drought stress. There were high correlation coefficients between different characteristics: SL had a positive and significant (p<0.01) correlation with CL (r = 0.83) and RL (r = 0.74), R/S length ratio (r = 0.67). This study showed that, based on morphological traits, preliminary screening at an early stage for drought stress using PEG-8000 may improve efforts to choose an adequate cultivar for growth under water stress conditions.

Providing users with interesting and surprising knowledge is one aim of Data mining. But it is also important that the discovered knowledge be accurate especially in medical domains. Classification rules are comprehensible form of knowledge and are most sought out by users. It is important that the classifier is less complex and understandable to the user. In the current study a Multi Objective Cultural Algorithm (MOCA) is applied to a data set to find rules with desired user defined properties. Along with accuracy metrics novelty metrics like interest and surprise are introduced to prune the evolved classifier so as to make the rule set more understandable and thus useful to the users for decision making. Preliminary experimental results on a bench mark medical data set is encouraging in that that the algorithm is promising in producing rules which are accurate, interesting and compact as well.

Background: The aim of this study was investigate the usefulness of preprocedural serum GGT levels in predicting the in stent restenosis (ISR) in patients with angina pectoris.\n\nMethods: 552 consecutive patients who had undergone bare-metal stent implantation and additional control coronary angiography for stable or unstable angina pectoris were analyzed.\n\nResults: Preprocedural GGT was significantly higher in patients with ISR than those without restenosis (33,7+21,4 vs. 23,7+12,8, P < 0.001).On receiver-operating characteristics curve analysis GGT level >21.5 U/L had 71% sensitivity and 61% specificity (area under the curve 0.677, p <0.001)) in predicting ISR. \n\nConclusions: Our results indicate that higher preprocedural GGT is a powerful and independent predictor of BMS restenosis in patients with angina pectoris.

Background/Aims. Inflammatory bowel disease (IBD) is a chronic disorder developed by inflammation of the gastrointestinal tract. Some studies have showed abnormalities such as first degree, wenckebach and complete atrio-ventricular block in patients with IBD. We aimed to evaluate the Tp-e interval and Tp-e/QT ratio in patients with IBD.\nMethods. Hundred patients with IBD (51 patients had CD and 49 patients had UC) and 100 age matched controls were enrolled in our study. Tp-e interval, Tp-e/QT and Tp-e/QTc ratio were obtained from the electrocardiography.\nResults. Tp-e interval (p<0.001), Tp-e/QT ratio (p=0.001) and Tp-e/QTc ratio (p=0.001) were higher in patients with CD than control subjects and it was significant. Also, Tp-e interval (p<0.001), QT interval (p=0.009), Tp-e/QT ratio (p<0.001) and Tp-e/QTc ratio (p<0.001) were significantly higher in patients with UC than control subjects. Tp-e/QTc ratio was no different between the CD and UC groups (p=0.130). However, Tp-e/QTc ratio was positively correlated with sedimentation rate (r= 0.209, p=0.003).\nConclusion. This study demonstrated that QT dispersion parameters were elevated in patients with IBD.

Background: Atrial fibrillation (AF) is the most common arrhythmia in clinical practice, is associated with an increased incidence of stroke, congestive heart failure, and higher mortality. Pulmonary embolism severity index (PESI) is the accepted score to predict short term mortality. In this study, we tried to find the relation between PESI score and new onset Lone-AF in patients with APE. \n Methods: Between May 2012 and December 2015, 869 patients\' data were evaluated. Patients were diagnosed with APE by pulmonary CT angiography or V/Q sintigraphy. We aimed to include a population with lone AF after APE. The following conditions were excluded, including hypertension, structural heart disease, hepatic or renal dysfunction, chronic obstructive pulmonary disease, thyroid dysfunction, diabetes mellitus or sleep apnea. In addition, none of the participants had any history of inflammatory or infection disease or recent (within the last 4 weeks) trauma or surgery; none was under treatment with nonsteroidal anti‑inflammatory or corticosteroids drugs. After exclusion period, 42 lone-AF and 107 non-AF patients were included. PESI score was calculated for every patient. \n Results: In patients with lone AF, the mean age was 62,79± 4,05 years, and 54.8% were male, in Non-AF group the mean age was 59,45±12,34 years, and 51,4% were male. No significant differences were observed between two groups with age, gender, their systolic and diastolic blood pressure, heart rate, fasting glucose, and serum creatinin (p > 0.05).Uric acid, CRP and erythrocyte sedimentation rate levels were higher in Lone-AF patients, this difference was not statistically significant(p>0,05 ). Lone-AF patients showed a larger LVEDD and LAD(p<0.05).There was no statistically significant difference between two groups in LV ejection fraction, TAPSE and SPAB(p>0.05).PESI scores were higher in Lone-AF group, this difference was statistically significant(p<0.05).In the univariate regression analysis, LVEDD, LAD, uric acid levels and PESI scores were univariate predictors of Lone-AF.\n Conclusion: Our study demonstrated that lone AF patients have a higher level of PESI score compared to age and gender‑matched Non-AF control patients. PESI score were positively correlated and associated with lone-AF. PESI score is helpful in the short time prognostic assessment of patients with acute PE and according to our study result; PESI score can be useful to predict lone-AF in patients with APE.

With the development of 3D printing, weapons are easily printed without any restriction from the original providers. Therefore, anti-weapon detection is necessary issue in safe 3D printing to prevent the printing of 3D weapon models. In this paper, we would like to propose an anti-weapon detection algorithm to prevent the printing of 3D weapon models for safe 3D printing based on the D2 shape distribution and the convolutional neural networks (CNNs). The purpose of the proposed algorithm is to detect anti-3D weapon models when they are used in 3D printing. The D2 shape distribution is computed from random points on the surface of a 3D weapon model and their geometric features in order to construct a D2 vector. The D2 vector is then trained by a CNNs. The CNNs is used to detect anti-3D weapon models for safe 3D printing by training D2 vectors which have been constructed from the D2 shape distribution of 3D weapon models. Experimental results show that the histogram of the D2 shape distribution of 3D weapon models in the same class is similar. Training and testing results also show that the accuracy of the proposed algorithm is higher than the conventional works. The proposed algorithm is applied in small application, and it could detect anti-3D weapon models for safe 3D printing.