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Nonlinear fractional-order differential equations have an important role in various branches of applied science and fractional engineering. This research paper shows the practical application of three such fractional mathematical models, which are the time-fractional Klein–Gordon equation (KGE), the time-fractional Sharma–Tasso–Olever equation (STOE), and the time-fractional Clannish Random Walker's Parabolic equation (CRWPE). These models were investigated by using an expansion method for extracting new soliton solutions. Two types of results were found: one was trigonometric and the other one was an exponential form. For a profound explanation of the physical phenomena of the studied fractional models, some results were graphed in 2D, 3D, and contour plots by imposing the distinctive results for some parameters under the oblige conditions. From the numerical investigation, it was noticed that the obtained results referred smooth kink-shaped soliton, ant-kink-shaped soliton, bright kink-shaped soliton, singular periodic solution, and multiple singular periodic solutions. The results also showed that the amplitude of the wave augmented with the pulsation in time, which derived the order of time fractional coefficient, remarkably enhanced the wave propagation, and influenced the nonlinearity impacts. [ABSTRACT FROM AUTHOR]

Background: Abdominal aortic aneurysms (AAAs) present a formidable public health concern due to their propensity for localized, anomalous expansion of the abdominal aorta. These insidious dilations, often in their early stages, mask the life-threatening potential for rupture, which carries a grave prognosis. Understanding the hemodynamic intricacies governing AAAs is paramount for predicting aneurysmal growth and the imminent risk of rupture. Objective: Our extensive investigation delves into this complex hemodynamic environment intrinsic to AAAs, utilizing comprehensive numerical analyses of the physiological pulsatile blood flow and realistic boundary conditions to explore the multifaceted dynamics influencing aneurysm rupture risk. Our study introduces novel elements by integrating these parameters into the overall context of aneurysm pathophysiology, thus advancing our understanding of the intricate mechanics governing their evolution and rupture. Methods: Conservation of mass and momentum equations are used to model the blood flow in an AAAs, and these equations are solved using a finite volume-based ANSYS Fluent solver. Resistance pressure outlets following a three-element Windkessel model were imposed at each outlet to accurately model the blood flow and the AAAs' shear stress. Results: Our results uncover elevated blood flow velocities within an aneurysm, suggesting an augmented risk of future rupture due to increased stress in the aneurysm wall. During the systole phase, high wall shear stress (WSS) was observed, typically associated with a lower risk of rupture, while a low oscillatory shear index (OSI) was noted, correlating with a decreased risk of aneurysm expansion. Conversely, during the diastole phase, low WSS and a high OSI were identified, potentially weakening the aneurysm wall, thereby promoting expansion and rupture. Conclusion: Our study underscores the indispensable role of computational fluid dynamic (CFD) techniques in the diagnostic, therapeutic, and monitoring realms of AAAs. This body of research significantly advances our understanding of aneurysm pathophysiology, thus offering pivotal insights into the intricate mechanics underpinning their progression and rupture, informing clinical interventions and enhancing patient care. [ABSTRACT FROM AUTHOR]

Skin cancer poses a significant healthcare challenge, requiring precise and prompt diagnosis for effective treatment. While recent advances in deep learning have dramatically improved medical image analysis, including skin cancer classification, ensemble methods offer a pathway for further enhancing diagnostic accuracy. This study introduces a cutting-edge approach employing the Max Voting Ensemble Technique for robust skin cancer classification on ISIC 2018: Task 1-2 dataset. We incorporate a range of cutting-edge, pre-trained deep neural networks, including MobileNetV2, AlexNet, VGG16, ResNet50, DenseNet201, DenseNet121, InceptionV3, ResNet50V2, InceptionResNetV2, and Xception. These models have been extensively trained on skin cancer datasets, achieving individual accuracies ranging from 77.20% to 91.90%. Our method leverages the synergistic capabilities of these models by combining their complementary features to elevate classification performance further. In our approach, input images undergo preprocessing for model compatibility. The ensemble integrates the pre-trained models with their architectures and weights preserved. For each skin lesion image under examination, every model produces a prediction. These are subsequently aggregated using the max voting ensemble technique to yield the final classification, with the majority-voted class serving as the conclusive prediction. Through comprehensive testing on a diverse dataset, our ensemble outperformed individual models, attaining an accuracy of 93.18% and an AUC score of 0.9320, thus demonstrating superior diagnostic reliability and accuracy. We evaluated the effectiveness of our proposed method on the HAM10000 dataset to ensure its generalizability. Our ensemble method delivers a robust, reliable, and effective tool for the classification of skin cancer. By utilizing the power of advanced deep neural networks, we aim to assist healthcare professionals in achieving timely and accurate diagnoses, ultimately reducing mortality rates and enhancing patient outcomes. [ABSTRACT FROM AUTHOR]

This article reports an investigation of the Soret and Dufour effects on the double-diffusive natural convection of A l 2 O 3 - H 2 O nanofluids in a U-shaped porous enclosure. Numerical problems were resolved using the multiple-relaxation-time (MRT) lattice Boltzmann method (LBM). The indented part of the U-shape was cold, and the right and left walls were heated, while the bottom and upper walls were adiabatic. The experimental data-based temperature and nanoparticle size-dependent correlations for the A l 2 O 3 -water nanofluids are used here. The benchmark results thoroughly validate the graphics process unit (GPU) based in-house compute unified device architecture (CUDA) C/C++ code. Numeral simulations were performed for a variety of dimensionless variables, including the Rayleigh number, ( R a = 10 4 , 10 5 , 10 6 ), the Darcy number, ( D a = 10 − 2 , 10 − 3 , 10 − 4 ), the Soret number, ( S r = 0.0 , 0.1 , 0.2 ), the Dufour number, ( D f = 0.0 , 0.1 , 0.2 ), the buoyancy ratio, ( − 2 ≤ B r ≤ 2 ), the Lewis number, ( L e = 1 , 3 , 5 ), the volume fraction, ( 0 ≤ ϕ ≤ 0.04 ), and the porosity, ϵ = ( 0.2 − 0.8 ), and the Prandtl number, P r = 6.2 (water) is fixed to represent the base fluid. The numerical results are presented in terms of streamlines, isotherms, isoconcentrations, temperature, velocity, mean Nusselt number, mean Sherwood number, entropy generation, and statistical analysis using a response surface methodology (RSM). The investigation found that fluid mobility was enhanced as the R a number and buoyancy force increased. The isoconcentrations and isotherm density close to the heated wall increased when the buoyancy force shifted from a negative magnitude to a positive one. The local N u increased as the Rayleigh number increased but reduced as the volume fraction augmented. Furthermore, the mean N u ( N u ¯ ) decreased by 3.12 % and 6.81 % and the S h ¯ increased by 83.17 % and 117.91 % with rising Lewis number for ( R a = 10 5 and D a = 10 − 3 ) and ( R a = 10 6 and D a = 10 − 4 ), respectively. Finally, the B r and S r demonstrated positive sensitivity, and the R a and ϕ showed negative sensitivity only for higher values of ϕ based on the RSM. [ABSTRACT FROM AUTHOR]

Diabetes is one of the fatal diseases that play a vital role in the growth of other diseases in the human body. From a clinical perspective, the most significant approach to mitigating the effects of diabetes is early-stage control and management, with the aim of a potential cure. However, lack of awareness and expensive clinical tests are the primary reasons why clinical diagnosis and preventive measures are neglected in lower-income countries like Bangladesh, Pakistan, and India. From this perspective, this study aims to build an automated machine learning (ML) model, which will predict diabetes at an early stage using socio-demographic characteristics rather than clinical attributes, due to the fact that clinical features are not always accessible to all people from lower-income countries. To find the best fit of the supervised ML classifier of the model, we applied six classification algorithms and found that RF outperformed with an accuracy of 99.36%. In addition, the most significant risk factors were found based on the SHAP value by all the applied classifiers. This study reveals that polyuria, polydipsia, and delayed healing are the most significant risk factors for developing diabetes. The findings indicate that the proposed model is highly capable of predicting diabetes in the early stages. [ABSTRACT FROM AUTHOR]

Mental health is a major concern for all classes of people, but especially physicians in the present world. A challenging task is to identify the significant risk factors that are responsible for depression among physicians. To address this issue, the study aimed to build a machine learning-based predictive model that will be capable of predicting depression levels and finding associated risk factors. A raw dataset was collected to conduct this study and preprocessed as necessary. Then, the dataset was divided into 10 sub-datasets to determine the best possible set of attributes to predict depression. Seven different classification algorithms, KNN, DT, LGBM, GB, RF, ETC, and StackDPP, were applied to all the sub-datasets. StackDPP is a stacking-based ensemble classifier, which is proposed in this study. It was found that StackDPP outperformed on all the datasets. The findings indicate that the StackDPP with the sub-dataset with all the attributes gained the highest accuracy (0.962581), and the top 20 attributes were enough to gain 0.96129 accuracy by StackDPP, which was close to the performance of the dataset with all the attributes. In addition, risk factors were analyzed in this study to reveal the most significant risk factors that are responsible for depression among physicians. The findings of the study indicate that the proposed model is highly capable of predicting the level of depression, along with finding the most significant risk factors. The study will enable mental health professionals and psychiatrists to decide on treatment and therapy for physicians by analyzing the depression level and finding the most significant risk factors. [ABSTRACT FROM AUTHOR]

The numerical investigation of magneto-hydrodynamic (MHD) mixed convection flow and entropy formation of non-Newtonian Bingham fluid in a lid-driven wavy square cavity filled with nanofluid was investigated by the finite volume method (FVM). The numerical data-based temperature and nanoparticle size-dependent correlations for the Al 2 O 3 -water nanofluids are used here. The physical model is a two-dimensional wavy square cavity with thermally adiabatic horizontal boundaries, while the right and left vertical walls maintain a temperature of T C and T H , respectively. The top wall has a steady speed of u = u 0 . Pertinent non-dimensional parameters such as Reynolds number ( R e = 10 , 100 , 200 , 400 ), Hartmann number ( H a = 0 , 10 , 20 ), Bingham number ( B n = 0 , 2 , 5 , 10 , 50 , 100 , 200 ), nanoparticle volume fraction ( ϕ = 0 , 0.02 , 0.04 ), and Prandtl number ( P r = 6.2 ) have been simulated numerically. The Richardson number R i is calculated by combining the values of R e with a fixed value of G r , which is the governing factor for the mixed convective flow. Using the Response Surface Methodology (RSM) method, the correlation equations are obtained using the input parameters for the average Nusselt number ( N u ¯ ), total entropy generation ( E s ) t , and Bejan number ( B e a v g ). The interactive effects of the pertinent parameters on the heat transfer rate are presented by plotting the response surfaces and the contours obtained from the RSM. The sensitivity of the output response to the input parameters is also tested. According to the findings, the mean Nusselt numbers ( N u ¯ ) drop when H a and B n are increased and grow when R e and ϕ are augmented. It is found that (E s) t is reduced by raising H a , but (E s) t rises with the augmentation of ϕ and R e . It is also found that the ϕ and R e numbers have a positive sensitivity to the N u ¯ , while the sensitivity of the H a and B n numbers is negative. [ABSTRACT FROM AUTHOR]

Huntingtin-associated protein 1 (HAP1) is a determinant marker for the stigmoid body (STB), a neurocytoplasmic physiological inclusion. STB/HAP1 enriched areas in the brain/spinal cord are usually protected from neurodegenerative diseases, whereas the regions with tiny amounts or no STB/HAP1 are affected. In addition to the brain/spinal cord, HAP1 is highly expressed in the myenteric/submucosal plexuses of the enteric nervous system in the gastrointestinal tract. The tongue is attached to the pharynx by the hyoid bone as an extension of the gastrointestinal system. To date, the immunohistochemical distribution and neurochemical characterization of HAP1 have not been elucidated in the lingual ganglia. Using immunohistochemistry and light microscopy, our current study demonstrates the expression and immunohistochemical phenotype of HAP1 in the lingual ganglia of adult mice. We showed that HAP1 was profoundly distributed in the intralingual ganglion (ILG) and the ganglia near the root of the tongue (which we coined as "lingual root ganglion"; LRG). Neurons in ILG and LRG exhibited high coexpression of HAP1 with NOS or ChAT. Furthermore, most HAP1-immunoreactive neurons contained SP, CGRP, and VIP immunoreactivity in both ILG and LRG. The current results might serve as an essential base for future studies to elucidate the pathological/physiological functions of HAP1 in the lingual ganglia. [ABSTRACT FROM AUTHOR]

This study aims to consider lattice Boltzmann method (LBM)–magnetohydrodynamics (MHD) data to develop equations to predict the average rate of heat transfer quantitatively. The present approach considers a 2D rectangular cavity with adiabatic side walls, and the bottom wall is heated while the top wall is kept cold. Rayleigh–Bénard (RB) convection was considered a heat-transfer phenomenon within the cavity. The Hartmann ( H a ) number, by varying the inclination angle (θ), was considered in developing the equations by considering the input parameters, namely, the Rayleigh ( R a ) numbers, Darcy ( D a ) numbers, and porosity (ϵ) of the cavity in different segments. Each segment considers a data-driven approach to calibrate the Levenberg–Marquardt (LM) algorithm, which is highly linked with the artificial neural network (ANN) machine learning method. Separate validations have been conducted in corresponding sections to showcase the accuracy of the equations. Overall, coefficients of determination ( R 2 ) were found to be within 0.85 to 0.99. The significant findings of this study present mathematical equations to predict the average Nusselt number ( N u ¯ ). The equations can be used to quantitatively predict the heat transfer without directly simulating LBM. In other words, the equations can be considered validations methods for any LBM-MHD model, which considers RB convection within the range of the parameters in each equation. [ABSTRACT FROM AUTHOR]

The present study aims to investigate the impact of air pollutants dispersion from traffic emission under the influence of wind velocity and direction considering the seasonal cycle in two major areas of Dhaka city: namely, Tejgaon and Gazipur. Carbon monoxide (CO) mass fraction has been considered as a representative element of traffic-exhausted pollutants, and the distribution of pollutants has been investigated in five different street geometries: namely, single regular and irregular, double regular and irregular, and finally, multiple irregular streets. After the grid independence test confirmation as well as numerical validation, a series of case studies has been presented to analyze the air pollutants dispersion, which mostly exists due to the traffic emission. The popular Reynolds-averaged Navier–Stokes (RANS) approach has been considered, and the finite volume method (FVM) has been applied by ANSYS FluentTM. The k − ϵ turbulence model has been integrated from the RANS approach. It was found that the wind velocity as well as wind direction and the fluid flow fields can play a potential role on pollution dispersion in the Dhaka city street canyons and suburbs. Inhabitants residing near the single regular streets are exposed to more traffic emission than those of single irregular streets due to fewer obstacles being created by the buildings. Double regular streets have been found to be a better solution to disperse pollutants, but city dwellers in the east region of double irregular streets are exposed to a greater concentration of pollutants due to the change of wind directions and seasonal cycles. Multiple irregular streets limit the mobility of the pollutants due to the increased number of buildings, yet the inhabitants near the multi-irregular streets are likely to experience approximately 11.25 % more pollutants than other dwellers living far from the main street. The key findings of this study will provide insights on improving the urbanization plan where different geometries of streets are present and city dwellers could have less exposure to traffic-exhausted pollutants. The case studies will also provide a template layout to map pollutant exposure to identify the alarming zone and stop incessant building construction within those regions by creating real-time air quality monitoring to safeguard public safety. [ABSTRACT FROM AUTHOR]

Technological advancement leads researchers to develop multifunctional materials. Considering such trends, this study aimed to conjugate dual functionality in a single material to satisfy aesthetic and functional necessities. We investigated the potentiality of polysorbate 20 to perform as an effective ultraviolet absorber to develop UV-protective fabric. Coumarin derivative (Benzoxazolyl type) disperse dyes are well-known as fluorescent colors. On the other hand, luminescence materials are conspicuous and viable for fashion trends. Deliberate utilization of this inherent property of the dye and incorporation of polysorbate fulfilled the need for dual functionality. In addition, the knitted fabric structure enhanced wearing comfort as well. The effect of polysorbate consolidated the PET fabric as an excellent UV absorber, exhibiting an ultraviolet protection factor (UPF) of 53.71 and a blocking percentage of more than 95% for both UVA and UVB. Surface morphology was studied by scanning electron microscope (SEM). Fourier transform infrared spectroscopy (FTIR) with attenuated mode was used to investigate chemical modification. Moreover, X-ray diffraction (XRD) investigated the crystallography of the surface. Reflectance spectrophotometric analysis unveiled the color strength (K/S) of the dyed polyester fabrics. Finally, light fastness assessment revealed that the developed samples could resist a certain amount of photo fading under a controlled testing environment with the increment of ratings towards betterment. [ABSTRACT FROM AUTHOR]

The atmospheric flow and dispersion of traffic exhaust were numerically studied in this work while considering a model street canyon intersection of a city. The finite volume method (FVM)-based large-eddy simulation (LES) technique in line with ANSYS Fluent have been used for flow and pollutant dispersion modelling through the consideration of the atmospheric boundary layer (ABL). Hexahedral elements are considered for computational domain discretization in order to numerically solve problems using FVM-LES. The turbulence parameters were superimposed through a spectral synthesizer in the existing LES model through ANSYS Fluent as part of 'damage control' due to the unsteady k − ϵ simulation. Initially, the code is validated with an experimental study of an urban street canyon where the width and height ratio is in unity. After validation, a model urban street canyon intersection was investigated in this work. The model shows a high pollutant concentration in the intersecting corner areas of the buildings. Additionally, the study of this model intersection shows a high level of pollutant concentration at the leeward wall of downwind building in the case of increased height of an upwind building. Most importantly, it was realized from the street intersection design that three-dimensional interconnection between the dominating canyon vortices and roof level flow plays a pivotal role in pollutant concentration level on the windward walls. The three-dimensional extent of corner eddies and their interconnections with dominating vortices were found to be extremely important as they facilitate enhanced ventilation. Corner eddies only form for the streets towards the freeway and not for the streets towards the intersection. The results and key findings of this work offer qualitative and quantitative data for the estimation, planning, and implementation of exposure mitigation in an urban environment. [ABSTRACT FROM AUTHOR]

Infections and persistent immunological activation are linked to increased kynurenine (KYN) and the KYN-to-Tryptophan (TRP) or KT ratio and may be critical factors in undernutrition. We sought to determine the association between the KT ratio and adult malnutrition, as well as investigate if nutritional supplementation had any influence on the decrease of the KT ratio. A total of 525 undernourished adults aged 18–45 years were recruited and provided a nutrition intervention for 60 feeding days. TRP and KYN concentrations were determined from plasma samples using LC-MS/MS. At baseline, the median (interquartile range (IQR)) TRP, KYN and KT ratios were 24.1 (17.6, 34.3) µmol/L, 0.76 (0.53, 1.18) µmol/L and 30.9 (24.5, 41.7), respectively. Following intervention, the median (IQR) KYN and KT ratios were significantly reduced to 0.713 (0.46, 1.12) µmol/L and 27.5 (21.3, 35.8). The KT ratio was found to be inversely linked with adult BMI (coefficient: −0.09; 95% CI: −0.18, 0.004; p-value = 0.06) but not statistically significant. Additionally, Plasma CRP was correlated positively, while LRP1 was inversely correlated with the KT ratio. Our data suggest that in Bangladeshi adults, the KT ratio is not related to the pathophysiology of malnutrition but correlated with inflammatory and anti-inflammatory biomarkers, and the ratio can be reduced by a nutrition intervention. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate the effects of temperature-dependent viscosity on the natural convection flow from a vertical permeable circular cone with uniform heat flux. As part of numerical computation, the governing boundary layer equations are transformed into a non-dimensional form. The resulting nonlinear system of partial differential equations is then reduced to local non-similarity equations which are solved computationally by three different solution methodologies, namely, (i) perturbation solution for small transpiration parameter (ξ), (ii) asymptotic solution for large ξ, and (iii) the implicit finite difference method together with a Keller box scheme for all ξ. The numerical results of the velocity and viscosity profiles of the fluid are displayed graphically with heat transfer characteristics. The shearing stress in terms of the local skin-friction coefficient and the rate of heat transfer in terms of the local Nusselt number (Nu) are given in tabular form for the viscosity parameter (ε) and the Prandtl number (Pr). The viscosity is a linear function of temperature which is valid for small Prandtl numbers (Pr). The three-fold solutions were compared as part of the validations with various ranges of Pr numbers. Overall, good agreements were established. The major finding of the research provides a better demonstration of how temperature-dependent viscosity affects the natural convective flow. It was found that increasing Pr, ξ, and ε decrease the local skin-friction coefficient, but ξ has more influence on increasing the rate of heat transfer, as the effect of ε was erratic at small and large ξ. Furthermore, at the variable Pr, a large ξ increased the local maxima of viscosity at large extents, particularly at low Pr, but the effect on temperature distribution was found to be less significant under the same condition. However, at variable ε and fixed Pr, the temperature distribution was observed to be more influenced by ε at small ξ, whereas large ξ dominated this scheme significantly regardless of the variation in ε. The validations through three-fold solutions act as evidence of the accuracy and versatility of the current approach. [ABSTRACT FROM AUTHOR]

The hydro-distilled essential oil of hog plum peel may be used for enhancing the flavor and taste of food products as well as for hiding the unpleasant odor of drugs. Thus, the waste peels of Spondias mombin appear to have economic importance. To find out the chemical composition and anti-microbial properties of hog plum peel oil, the samples were collected from different regions of Bangladesh for extraction and identification of volatile compounds by GC-MS, where dichloromethane was used as an extraction solvent. The required standard analytical methods were used to assay the anti-microbial properties of hog plums. In this study, pentenyl-3-thy-met-4-alpha-methyl-alpha-ethanol-oxiranen (29.04%), (3,3.1,1)-4-dimethylethyl-1,1-phenol (8.00%), cycohexanol-3 (10.85%), 4-hydroxy-penzeneethanamine (7.09%), hydroxylamine (4.63%), dibutyl phthalate (6.85%), etc., were majorly determined. Consequently, the highest content of 75.81% volatile compounds was found in the Dinajpur district, where the lowest content of 35.00% was found in the Rajshahi district. In contrast, 33 volatile compounds were identified in hog plum peels collected from the Barishal district, whereas 22 compounds were detected in the peel samples collected from the Dinajpur district. In addition, the antimicrobial activity of the oil was analyzed by the disk diffusion method, and the results revealed that the highest Ciprocin content was recorded in the hog plums of Barishal (22.0–23.0 mm), while the lowest was recorded in the Mymensingh sample (20.67–21.63 mm), which was on par with Rajshahi sample (20.70–21.50 mm). The results of the anti-fungal activities of the peel oil showed the highest zone of inhibition against the Aspergillus niger (11.63 ± 0.0003 mm) and Penicillium oxalicum (13.67 ± 1.97 mm) content of the Rajshahi and Pabna district samples, respectively. [ABSTRACT FROM AUTHOR]

In this article, we construct the exact dynamical wave solutions to the Date–Jimbo–Kashiwara–Miwa equation with conformable derivative by using an efficient and well-established approach, namely: the two-variable G ' / G ,     1 / G -expansion method. The solutions of the Date–Jimbo–Kashiwara–Miwa equation with conformable derivative play a vital role in many scientific occurrences. The regular dynamical wave solutions of the abovementioned equation imply three different fundamental functions, which are the trigonometric function, the hyperbolic function, and the rational function. These solutions are classified graphically into three categories, such as singular periodic solitary, kink soliton, and anti-kink soliton wave solutions. Furthermore, the effect of the fractional parameter on these solutions is discussed through 2D plots. [ABSTRACT FROM AUTHOR]

From a residential point of view, home energy management (HEM) is an essential requirement in order to diminish peak demand and utility tariffs. The integration of renewable energy sources (RESs) together with battery energy storage systems (BESSs) and central battery storage system (CBSS) may promote energy and cost minimization. However, proper home appliance scheduling along with energy storage options is essential to significantly decrease the energy consumption profile and overall expenditure in real-time operation. This paper proposes a cost-effective HEM scheme in the microgrid framework to promote curtailing of energy usage and relevant utility tariff considering both energy storage and renewable sources integration. Usually, the household appliances have different runtime preferences and duration of operation based on user demand. This work considers a simulator designed in the C++ platform to address the domestic customer's HEM issue based on usages priorities. The positive aspects of merging RESs, BESSs, and CBSSs with the proposed optimal power sharing algorithm (OPSA) are evaluated by considering three distinct case scenarios. Comprehensive analysis of each scenario considering the real-time scheduling of home appliances is conducted to substantiate the efficacy of the outlined energy and cost mitigation schemes. The results obtained demonstrate the effectiveness of the proposed algorithm to enable energy and cost savings up to 37.5% and 45% in comparison to the prevailing methodology. [ABSTRACT FROM AUTHOR]

The high-level penetration of renewable energy sources (RESs) is the main reason for shifting the conventional centralized power system control paradigm into distributed power system control. This massive integration of RESs faces two main problems: complex controller structure and reduced inertia. Since the system frequency stability is directly linked to the system's total inertia, the renewable integrated system frequency control is badly affected. Thus, a fractional order controller (FOC)-based superconducting magnetic energy storage (SMES) is proposed in this work. The detailed modeling of SMES, FOC, wind, and solar systems, along with the power network, is introduced to facilitate analysis. The FOC-based SMES virtually augments the inertia to stabilize the system frequency in generation and load mismatches. Since the tuning of FOC and SMES controller parameters is challenging due to nonlinearities, the whale optimization algorithm (WOA) is used to optimize the parameters. The optimized FOC-based SMES is tested under fluctuating wind and solar powers. The extensive simulations are carried out using MATLAB Simulink environment considering different scenarios, such as light and high load profile variations, multiple load profile variations, and reduced system inertia. It is observed that the proposed FOC-based SMES improves several performance indices, such as settling time, overshoot, undershoot compared to the conventional technique. [ABSTRACT FROM AUTHOR]

Adolescence is the critical postnatal stage for the action of androgen in multiple brain regions. Androgens can regulate the learning/memory functions in the brain. It is known that the inhibitory avoidance test can evaluate emotional memory and is believed to be dependent largely on the amygdala and hippocampus. However, the effects of androgen on inhibitory avoidance memory have never been reported in adolescent male rats. In the present study, the effects of androgen on inhibitory avoidance memory and on androgen receptor (AR)-immunoreactivity in the amygdala and hippocampus were studied using behavioral analysis, Western blotting and immunohistochemistry in sham-operated, orchiectomized, orchiectomized + testosterone or orchiectomized + dihydrotestosterone-administered male adolescent rats. Orchiectomized rats showed significantly reduced time spent in the illuminated box after 30 min (test 1) or 24 h (test 2) of electrical foot-shock (training) and reduced AR-immunoreactivity in amygdala/hippocampal cornu Ammonis (CA1) in comparison to those in sham-operated rats. Treatment of orchiectomized rats with either non-aromatizable dihydrotestosterone or aromatizable testosterone were successfully reinstated these effects. Application of flutamide (AR-antagonist) in intact adolescent rats exhibited identical changes to those in orchiectomized rats. These suggest that androgens enhance the inhibitory avoidance memory plausibly by binding with AR in the amygdala and hippocampus. [ABSTRACT FROM AUTHOR]

The steady increase in energy demand for residential consumers requires an efficient energy management scheme. Utility organizations encourage household applicants to engage in residential energy management (REM) system. The utility's primary goal is to reduce system peak load demand while consumer intends to reduce electricity bills. The benefits of REM can be enhanced with renewable energy sources (RESs), backup battery storage system (BBSS), and optimal power-sharing strategies. This paper aims to reduce energy usages and monetary cost for smart grid communities with an efficient home energy management scheme (HEMS). Normally, the residential consumer deals with numerous smart home appliances that have various operating time priorities depending on consumer preferences. In this paper, a cost-efficient power-sharing technique is developed which works based on priorities of appliances' operating time. The home appliances are sorted on priority basis and the BBSS are charged and discharged based on the energy availability within the smart grid communities and real time energy pricing. The benefits of optimal power-sharing techniques with the RESs and BBSS are analyzed by taking three different scenarios which are simulated by C++ software package. Extensive case studies are carried out to validate the effectiveness of the proposed energy management scheme. It is demonstrated that the proposed method can save energy and reduce electricity cost up to 35% and 45% compared to the existing methods. [ABSTRACT FROM AUTHOR]

Several efforts have been taken to promote clean energy towards a sustainable and green economy. Existing sources of electricity present some complications concerning consumers, utility owners, and the environment. Utility operators encourage household applicants to employ residential energy management (REM) systems. Renewable energy sources (RESs), energy storage systems (ESS), and optimal energy allocation strategies are used to resolve these difficulties. In this paper, the development of a cluster-based energy management scheme for residential consumers of a smart grid community is proposed to reduce energy use and monetary cost. Normally, residential consumers deal with household appliances with various operating time slots depending on consumer preferences. A simulator is designed and developed using C++ software to resolve the residential consumer's REM problem. The benefits of the RESs, ESS, and optimal energy allocation techniques are analyzed by taking in account three different scenarios. Extensive case studies are carried out to validate the effectiveness of the proposed cluster-based energy management scheme. It is demonstrated that the proposed method can save energy and costs up to 45% and 56% compared to the existing methods. [ABSTRACT FROM AUTHOR]

A modified power-law (MPL) viscosity model of non-Newtonian fluid flow has been used for the multiple-relaxation-time (MRT) lattice Boltzmann methods (LBM) and then validated with the benchmark problems using the graphics process unit (GPU) parallel computing via Compute Unified Device Architecture (CUDA) C platform. The MPL model for characterizing the non-Newtonian behavior is an empirical correlation that considers the Newtonian behavior of a non-Newtonian fluid at a very low and high shear rate. A new time unit parameter (λ) governing the flow has been identified, and this parameter is the consequence of the induced length scale introduced by the power law. The MPL model is free from any singularities due to the very low or even zero shear-rate. The proposed MPL model was first validated for the benchmark study of the lid-driven cavity and channel flows. The model was then applied for shear-thinning and shear-thickening fluid flows through a backward-facing step with relatively low Reynolds numbers, R e = 100–400. In the case of shear-thinning fluids ( n = 0.5 ), laminar to transitional flow arises while R e ≥ 300 , and the large vortex breaks into several small vortices. The numerical results are presented regarding the velocity distribution, streamlines, and the lengths of the reattachment points. [ABSTRACT FROM AUTHOR]