Analysis Approach Research Articles

Inertial active Ornstein–Uhlenbeck particle in a non-linear velocity dependent friction

We explore the self-propulsion of an active Ornstein–Uhlenbeck particle with a non-linear velocity dependent friction. Using analytical approach and numerical simulation, we have exactly investigated the dynamical behaviour of the particle in terms of particle trajectory, position and velocity distribution functions in both underdamped as well as overdamped regimes of the dynamics. Analyzing the distribution functions, we observe that for a confined harmonic particle, with an increase in duration of self-propulsion, the inertial particle prefers to accumulate near the boundary of the confinement rather than the mean position, reflecting an activity induced bistability in the presence of nonlinear friction. On the other hand, in the overdamped or highly viscous regime, where the inertial influence is negligible, the sharp peak structure in the distribution across the mean position of the well reveals as usual trapping of the particle with increase in the persistent duration of activity. Moreover, for a free particle, using perturbation method, we have analytically computed the velocity distribution function in the vanishing limit of noise. The distribution interestingly shows the similar attributes as in case of a harmonic well, thus providing an additional effective confining mechanism that can be explained as a decreasing function of effective temperature. In this limit, the analytically computed distribution agrees well with the simulation results.

Diffraction of Magnetoelastic Plane Waves through a Rigid Strip in an Orthotropic Medium: An Analytical Approach

Diffraction of Magnetoelastic Plane Waves through a Rigid Strip in an Orthotropic Medium: An Analytical Approach

A simple and effective non-invasive method for the analysis of volatile organic compounds in exhaled air

Breath analysis is a cutting-edge technique that collects significant medical information by analyzing the substances found in exhaled breath. Fluctuations in the levels of chemicals such as acetone can serve as indicators of medical ailments or contact with hazardous substances such as occupational exposure. In order to detect acetone in exhaled air, techniques such as needle trap coupled with gas chromatography have been devised. This procedure involves the use of a nanocomposite called Mil101(Fe)@Fe3O4@SiO2.The nanocomposite is synthesized using a chemical hydrothermal method. In order to examine the properties of the Mil101(Fe)@Fe3O4@SiO2 nanocomposite, researchers utilized a range of analytical techniques including scanning electron microscopy (SEM), thermal analysis (TGA), x-ray analysis (EDX), Brunauer-Emmett-Teller (BET) method, and Fourier Transform Infrared Spectroscopy (FT-IR). The efficiency of the NTD-GC-FID method depends on several parameters, such as temperature, desorption time, fracture passage volume, sampling time, sample temperature, and sampling flow rate. These parameters have been studied using the simplex method to optimize the process. The optimal conditions yielded a limit of detection (LODs) of 0.4 µg/L and a limit of quantification (LOQs) of 1.1 µg/L. The calibration curve for the NTD-GC-FID method ranged from 0.011 to 10 mgl−1 with an acceptable error range. Moreover, the method demonstrated good repeatability and reproducibility, with calculated values of 3.9 and 4.6 %, respectively. The proposed method was successfully employed in this study to identify and measure acetone in the exhaled air of individuals with diabetes, yielding satisfactory results. The needle trap tool was used over 100 times without any decline in its efficiency for adsorbing acetone. In summary, this research presents a new analytical approach, namely the NTD-GC-FID method, to detect and measure acetone in exhaled air. Compared to the other methods for analyzing acetone, the application of Mil101(Fe)@Fe3O4@SiO2 nanocomposite demonstrated promising results in detection of diabetes.

Featuring the aspects with temperature dependent viscosity of inclined MHD Williamson fluid along with heat source/sink, Soret and Dufour effects: A predictor-corrector approach

The boundary layer flow analysis of Williamson fluid moving on the stretched cylinder has applications in the polymer processing, drug delivery system, cooling systems, rheology of food products, dyeing, and finishing. The numerical solutions of governing Navier-Stokes equations at different scenarios of thermal and solutal aspects have lots of practical implications, including biomedical engineering, cooling and heating processes, chemical reactors, aerodynamics, environmental science, and thermal storage systems. From these practical applications, the authors were motivated to conduct a study in which the numerical behavior is examined by applying the Adams-Bashforth predictor and corrector approach of numerical analysis for the Williamson fluid model in the presence of varying viscosity, natural convection, and the inclined magnetic field. Furthermore, Joule heating, thermal radiation, and heat source/sink effects are included in the thermal aspects because these are the important concepts in thermal management and engineering and have applications in solar thermal energy systems, combustion engines, heat exchangers, nuclear reactors, thermal imaging, and safety. Apart from thermal aspects, the analysis of mass transfer focuses on the influence of chemical reactions and Soret-Dufour effects. The similarity transformations are adopted to convert partial differential equations into ordinary differential equations. Specifically, the well-known predictor and corrector numerical method named the Adams-Bashforth method in combination with the Runge-Kutta 4th order scheme is used to achieve the numerical solutions. The temperature, concentration, and velocity regions are displayed on the graphical and numerical conducts. A comparison is also made between the results obtained by the shooting method and the numerical findings of skin friction, Nusselt number, and Sherwood number determined by the Adams-Bashforth method. The determining results concluded that the restrictions in the flow of Williamson fluid are caused by variations in the inclination magnetic field, the surface curvature, and the Williamson parameter, whereas the motion of the fluid increases due to convection, which occurs due to thermal phenomena. The determined results indicate that the temperature distribution is enhanced due to the addition of thermal radiation, Eckert number, and magnetic field. The surface curvature, Soret number, and reaction coefficient marks the decrease impact on the concentration region. The temperature-dependent viscosity increases the drag force and friction coefficient. The Nusselt number is amplified by applying thermal radiation to the surface of the cylinder. The chemical reaction is the source of the increment in the Sherwood number.

Design of Experiment and green analytical chemistry principles for developing a robust and sustainable Stability-Indicating HPLC method for Bempedoic acid impurity profiling

Bempedoic acid (BEM), a drug used to lower cholesterol levels in patients with atherosclerosis. Controlling its process-related impurities is crucial due to their potential toxicity. This study details the development of a RP-HPLC method for the analysis of four process-related substances in BEM. To ensure robust chromatographic performance meeting six sigma quality standards, the method was optimized using a combined approach of response surface methodology (specifically, an I-optimal design) and tolerance analysis, integrating predefined specifications for critical method attributes such as resolution, tailing factor, and number of theoretical plates into the developmental process. Chromatographic separation was achieved using a C18 column. The mobile phase consisted of 0.1 % phosphoric acid in water and acetonitrile, utilizing a stepped gradient elution profile. The flow rate was maintained at 0.9 mL/min, with UV detection performed at 210 nm. The column temperature was set to 20 °C. The method demonstrated linearity for BEM process related impurities in the range of LOQ to 30 μg mL−1. The method ability to differentiate the drug substance from its degradation products was confirmed through forced degradation study. The environmental sustainability of the developed method was assessed using multiple Green Analytical Chemistry (GAC) tools. The National Environmental Methods Index (NEMI) showed two green-shaded quadrants, and the Green Certificate modified Eco-scale awarded a score of 70. The Complementary Green Analytical Procedure Index (Complex GAPI) confirmed the method environmentally friendly profile. Additionally, The AGREE tool generated a score of 0.77, indicating strong overall greenness, while the AGREEprep tool, focused on sample preparation, yielded a score of 0.54. Other tools such as the Sample Preparation Metric of Sustainability (SPMS) and the HPLC Environmental Assessment Tool (HPLC-EAT) scored 8.42 and 569, respectively, further demonstrating the method green credentials. This robust and environmentally conscious analytical framework offers significant potential for application in quality control of BEM.

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection.

Time series are the primary data type used to record dynamic system measurements and generated in great volume by both physical sensors and online processes (virtual sensors). Time series analytics is therefore crucial to unlocking the wealth of information implicit in available data. With the recent advancements in graph neural networks (GNNs), there has been a surge in GNN-based approaches for time series analysis. These approaches can explicitly model inter-temporal and inter-variable relationships, which traditional and other deep neural network-based methods struggle to do. In this survey, we provide a comprehensive review of graph neural networks for time series analysis (GNN4TS), encompassing four fundamental dimensions: forecasting, classification, anomaly detection, and imputation. Our aim is to guide designers and practitioners to understand, build applications, and advance research of GNN4TS. At first, we provide a comprehensive task-oriented taxonomy of GNN4TS. Then, we present and discuss representative research works and introduce mainstream applications of GNN4TS. A comprehensive discussion of potential future research directions completes the survey. This survey, for the first time, brings together a vast array of knowledge on GNN-based time series research, highlighting foundations, practical applications, and opportunities of graph neural networks for time series analysis.

Microwave-aided sensitive and eco-friendly HPTLC method for estimation of mirabegron using NBD-Cl as bio-sensing fluorescent probe by Integration of principal component Analysis, response surface modelling and white analytical chemistry approach

A large number of analytical methods have been used in in-vivo pharmacokinetic investigations and assays of mirabegron, which is used to treat overactive bladder. Because mirabegron does not give fluorescence, there is no known chromatographic method that uses this property in conjunction with environmentally safe solvents. In order to develop and assess analytical procedures that are precise, sensitive, environmentally friendly, economical, and easy to use, white analytical chemistry was recently presented. Hence, a microwave-aided HPTLC method with fluorescence detection was developed and applied for mirabegron quantification; this method is both sensitive and environmentally acceptable, and it makes use of NBD-Cl, a bio-sensing fluorescent-probe. The analytical-QbD approach, which includes chemometric and response-surface modeling concepts, was used to design this targeted chromatographic method. Critical method variables and performance parameters were identified and optimized using principal component analysis and Box-Behnken design. The targeted method was used to estimate mirabegron through the development of method operable design range navigation and control strategy. A mobile phase consisting of ethyl-acetate and ethanol (8.0 + 2.0, v/v) was used to develop the chromatogram of NBD-Cl derivatised-mirabegron into 8.0 mm bands on a TLC-plate that was supported with aluminum and precoated with silica-gel G60 F254. In a mirabegron concentration range of 50–250 ng/band, the suggested method exhibited linearity. Results showed that the suggested method has a recovery rate of 98 % to 102 %. When estimating mirabegron, the %RSD for the precision and robustness study was determined to be less than 2.0. The mirabegron %assay in the commercially available formulations was determined to be between 98 % and 102 % of the labelled claimed value. Mirabegron had a limit of detection of 10 pg/band and a limit of quantification of 50 pg/band. Marketed tablet formulations of mirabegron had a maximum plasma concentration of 71.58 ng/mL in rats. Using metrics from green analytical chemistry and the RGB model scoring system, we compared the whiteness and greenness profiles of the published and suggested methods. The suggested method was found to be sensitive, eco-friendly, quick, cost-effective, and easy to use for estimation of mirabegron.

Experimental characterization of the in-plane shear strength of unreinforced masonry walls with damp-proof course and thermal break layer

Due to the highly demanding energy standards in Europe and challenging weather conditions, thermal break elements, such as aerated autoclaved concrete (AAC), have become increasingly popular in modern day residential buildings made of masonry cavity walls. Furthermore, a damp-proof course (DPC) layer is also used on top of the thermal break element to prevent water seeping and eventual entrapment due to capillary action. The presence of an AAC layer and of a DPC can have an adverse effect on the in-plane shear strength of a masonry wall, although information on this is barely available in the existing literature. This study aims at filling that knowledge gap through experimental investigations on traditional masonry walls and composite masonry walls, i.e. with an AAC and a DPC layer. The in-plane shear behaviour is compared between both types of wall specimens on the base of load-displacement curves and observation of failure modes. The capacity of analytical design approaches in predicting the test results has also been assessed. For the tested configurations, it can be concluded that the presence of AAC and DPC makes the failure mode switch from diagonal shear sliding combined with flexural toe crushing to horizontal shear sliding with crushing localized in the AAC layer, associated to a drop of the resistance by 6 to 9% depending on the type of clay units and mortar. The proposed analytical method, derived from EN 1996-1-1, is providing a safe estimate of the test results with a similar level of accuracy for traditional and composite configurations (predicted values in the range of 75 to 86% of the measured values). Finally, the influence of the definition of the compressed length and of the shear span ratio are shortly discussed.

3D and 2D-QSAR Studies on Natural Flavonoids for Nitric Oxide Production Inhibitory Activity

Background: Nitric oxide (NO), an important second messenger molecule, regulates numerous physiological responses, while excessive NO generates negative effects on the circulatory, nervous and immune systems. Recently, some natural flavonoids were reported to possess the capability of inhibiting LPS-induced NO production. To fully understand the nature of their own NO inhibitory activity, it is necessary to address the structural requirements of flavonoids as NO inhibitors. Objective: The objective of this work was to develop efficient QSAR models for predicting the NOinhibitory activity of new flavonoids and improving insights into the critical properties of the chemical structures that were required for the ideal NO production inhibitory activities. Methods: To provide insights into the structural basis of flavonoids as NO inhibitors, 3D quantitative structure-activity relationship (3D-QSAR) and 2D-QSAR models were developed on a dataset of 55 flavonoids using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and hologram quantitative structure-activity relationship (HQSAR) approaches. Results: The statistically significant models for CoMFA, CoMSIA and HQSAR resulted in crossvalidated coefficient (q2) values of 0.523, 0.572 and 0.639, non-cross-validated coefficient (r2) values of 0.793, 0.828 and 0.852, respectively. The robustness of these models was further affirmed using a test set of 18 compounds, which resulted in predictive correlation coefficients (r2 pred) of 0.968, 0.954 and 0.906. Furthermore, the models-derived contour maps were appraised for activity trends for the molecules analyzed. Conclusion: The 3D and 2D-QSAR models constructed in this paper were efficient in estimating the NO inhibitory activities of flavonoids and facilitating the design of flavonoid-derived NO production inhibitors.

Assessing the Implications of Deforestation and Climate Change on Rural Livelihood in Ghana: a Multidimensional Analysis and Solution-Based Approach.

The Ashanti region in Ghana, abundant in natural resources such as forests and vegetation biomes, significantly supports the livelihoods of a significant portion of the population. The sustainable management of forest resources remains a significant challenge to achieving environmental and economic growth and poverty alleviation. The study aims to identify the drivers of deforestation and assess its impact on the livelihoods of the poor and vulnerable communities in the Ashanti region. The study utilized qualitative and space-based data to examine the patterns of vegetation cover and deforestation from 2000 to 2020. The results revealed moderate to sparse vegetation in Ashanti from 2002, 2005, 2011, 2015, 2017, and 2018, with no vegetation in the northcentral part, attributed to climate change, agricultural practices, government policies, and deforestation-related disasters. The study found a significant correlation (R² = 0.8197) between years and deforestation areas, especially in 2018 at around 16,000 Sqkm, indicating an exponential increase with severe implications for sustainable livelihoods. Much of these changes were reflected in 2020 with a high peak of deforestation towards the southeastern parts of the region. Additionally, the results show that the poor groups are not passive actors but are actively involved in identifying systems and processes through which to build their adaptive capacity and resilience to environmental and climate change-induced changes. The findings provide evidence-based and all-inclusive approaches that would encourage vulnerable and marginalized groups to participate in the co-production and co-creation of policies and strategies. This outcome is geared towards transformative and sustainable communities while ensuring efficient and effective response and recovery capacities of deforested lands.

Bicycle parking allocation and its equity implications: The case of Bogota, Colombia

Bicycles are a sustainable alternative for urban mobility; however, their usage depends mainly on safety, convenience, and infrastructure availability, which have been widely studied. However, most studies have overlooked the importance of bicycle parking facilities in the network-planning process. In this work we aim to draw attention to the importance of including bicycle parking (BP) facilities in a well-thought-out bicycle infrastructure planning process highlighting the detrimental effects of not doing so for transportation equity, using Bogotá, Colombia, as a case study, where bicycle trips have multiplied in the last few years, reaching a 6.6 % modal share in 2019. To this end, we present a geospatial analysis and machine learning approach to assess the network coverage of bicycle parking spots. Additionally, we compared the city's bicycle trip patterns and applied a survey to know the perception of users (n = 397). The results show that the current distribution of bicycle parking in the city does not favour equity, given that it is not in line with the origin and destination of bicycle trips. This could widen socio-territorial inequity by affecting accessibility to bicycle use for daily commutes. To the best of our knowledge, this study presents the first assessment of the impact of parking distribution on the planning of bicycle infrastructure in the Global South.

Adherence to melanoma screening and surveillance skin check schedules tailored to personal risk.

Population-wide skin cancer screening is not currently recommended in most countries. Instead, most clinical guidelines incorporate risk-based recommendations for skin checks, despite limited evidence around implementation and adherence to recommendations in practice. We aimed to determine adherence to personal risk-tailored melanoma skin check schedules and explore reasons influencing adherence. Patients (with/without a previous melanoma) attending tertiary dermatology clinics at the Melanoma Institute Australia, Sydney, Australia, were invited to complete a melanoma risk assessment questionnaire via iPad and provided with personal risk information alongside a risk-tailored skin check schedule. Data were collected from the risk tool, clinician-recorded data on schedule deviations, and appointment booking system. Post-consultation, we conducted semi-structured interviews with patients and clinic staff. We used a convergent segregated mixed methods approach for analysis. Interviews were audio recorded, transcribed and data were analysed thematically. Participant data were analysed from clinic records (n = 247) and interviews (n = 29 patients, 11 staff). Overall, there was 62% adherence to risk-tailored skin check schedules. In cases of non-adherence, skin checks tended to occur more frequently than recommended. Decisions to deviate were similarly influenced by patients (44%) and clinicians (56%). Themes driving non-adherence among patients included anxiety and wanting autonomy around decision-making, and among clinicians included concerns around specific lesions and risk estimate accuracy. There was moderate adherence to a clinical service program of personal risk-tailored skin check recommendations. Further adherence may be gained by incorporating strategies to identify and assist patients with high levels of anxiety and supporting clinicians to communicate risk-based recommendations with patients.

Temporal dynamics of implicit moral evaluation: from empathy for pain to mentalizing processes

To understand how we evaluate harm to others, it is crucial to consider the offender’s intent and the victim’s suffering. Previous research investigating event-related potentials (ERPs) during moral evaluation has been limited by small sample sizes and a priori selection of electrodes and time windows that may bias the results. To overcome these limitations, we examined ERPs in 66 healthy human adults using a data-driven analytic approach involving cluster-based permutation tests. Participants performed an implicit moral evaluation task requiring to observe scenarios depicting intentional harm (IHS), accidental harm (AHS), and neutral actions (NAS) while judging whether each scenario was set indoors or outdoors. Our results revealed two distinct clusters, peaking at ∼170 and ∼250 ms, showing differences between harm scenarios (IHS and AHS) and NAS, suggesting rapid processing of the victim’s physical outcome. The difference between IHS and AHS scenarios emerged later, at ∼400 ms, potentially reflecting subsequent evaluation of the agent’s intentions. Source analysis showed that brain regions associated with empathy for pain were associated with the earlier peaks at ∼170 and ∼250 ms, while the modulation of the activity of the mentalizing network was presented at ∼250 and ∼400 ms. These findings advance our understanding of the neural mechanisms underlying implicit moral evaluation. Notably, they provide electrocortical new insights for models of implicit moral evaluation, suggesting an early neural response linked to empathy for pain, with subsequent integration of empathy response with mentalizing processes, followed by later cognitive evaluations, likely reflecting the assessment of the agent’s moral responsibility.

Optimizing Grid-Dependent and Islanded Network Operations through Synergic Active-Reactive Power Integration

DG integration improves distribution network performance and also enables microgrid (MG) formation for islanded operation. However, existing studies assume an isolated operation approach for islanded mode, which is unrealistic and increases overall system costs while adding complexity to the grid. This paper presents a dual-stage methodology for the efficient operation of distributed generation (DG) and shunt capacitor banks (SCBs) in radial distribution networks (RDNs) for both grid-integrated and islanded modes. The first stage proposes an improved Jaya algorithm (IJaya) to optimize DG and SCB allocation during grid-connected operation, aiming to reduce power loss and improve voltage profiles. IJaya employs a dynamic weight-based grid search to address premature convergence. The second stage formulates a multiobjective function for the islanded operation to minimize power loss and underutilization of DG-SCB capacity. Case studies on IEEE 33- and 69-bus RDNs show IJaya reduces power loss by 38.84% and improves voltage by 3.26% in grid-connected networks compared to existing methods. The proposed analytical approach for islanded operation tunes the source power factor, reducing DG-SCB underutilization by up to 15.83% for power factors between 0.8 and 0.93. The results demonstrate that operating distributed resources near optimal capacities meets a larger portion of the island network's energy needs.

Sustainable liquid-liquid microextraction and determination of inorganic arsenic species in nut-based beverages using hydrophobic natural deep eutectic solvents

Arsenic (As) is a carcinogenic, mutagenic, and toxic element, making its determination in food and beverages essential for assessing its impact on human health. Since the total As content alone does not provide adequate information on toxicity and bioavailability, it is crucial to develop methods for the speciation of As(III) and As(V). The aim of this work was to develop an efficient and selective method for the determination of inorganic As (iAs) species in complex samples such as nut-based beverages. This method involves the application of a hydrophobic natural deep eutectic solvent (HNADES) in the vortex-assisted liquid-liquid microextraction (VA-LLME) technique based on the solidification of floating droplets. The As(III) species was complexed with ammonium pyrrolidinedithiocarbamate (APDC) and extracted using 50μL of HNADES capric acid:lauric acid (CAP:LAU) (2:1). Then, As(III) species was determined by hydride generation atomic fluorescence spectrometry (HG-AFS). Optimization of the sample volume, HNADES volume, vortex stirring time, and cooling time was performed using a multivariate study. The method contributes to the development of a more environmentally friendly analytical approach and offers several advantages, including 100% As(III) extraction efficiency, low limits of detection (0.11μgL⁻¹ for As(III) and 0.30μgL⁻¹ for As(V)), and excellent selectivity.

Baseline-dependent improvement in CF studies, plausibility of bias

Background:It has been commonly reported that therapeutic treatments in cystic fibrosis (CF) have ceiling effects, such that their efficacy is diminished for persons with high pre-treatment health (Montgomery et al., 2012 and Newsome et al., 2019). Floor effects have also been reported where decline is of lower magnitude in those with below-average pre-treatment health (Harun et al., 2016; Konstan et al., 2012 and Szczesniak et al., 2017). When measurement error is present, the statistical literature has warned of exaggerated or spurious associations between pre-treatment measures and subsequent change (Chambless and Davis, 2003 and Yanez et al., 1998). Measurement error, equivalently described as day-to-day variation, has been described to occur in CF outcome measurements such as forced expiratory volume in 1 s taken by spirometry (FEV1pp) (Magaret et al., 2024; Stanojevic et al., 2020 and Thornton et al., 2023). Methods:We conducted a simulation study to assess the potential for spurious floor or ceiling effects in studies of CF therapeutics. We considered uncontrolled or single-arm studies, and evaluated estimated association between pre-treatment FEV1pp and treatment-induced change: post- versus pre-treatment. Results:When day-to-day variation was present in FEV1pp, at levels equivalent to those reported in large studies measuring spirometry both at home and in clinic, naive analytic approaches found spurious associations of change with baseline (Paynter et al., 2022 and Saiman et al., 2003). Type I error ranged from 31.9% to 98.3% for day-to-day variation as high as 3% to 15% relative to biological variation. Incorporating known day-to-day variation, the regression calibration approach corrected bias and controlled type I error (Chambless and Davis, 2003). Conclusion:Exaggerated ceiling effects are possible. Further studies could provide meaningful confirmation of ceiling effects in CF, perhaps reducing day-to-day variation by incorporating multiple pre- and post-treatment measurements.

Perspectives on Constrained Forecasting

This expository paper discusses Bayesian decision analysis perspectives on problems of constrained forecasting. Foundational and pedagogic discussion contrasts decision analytic approaches with the traditional, but typically inappropriate, inferential approach. Illustrative examples include development of novel constrained point forecasting and entropic tilting methodology to explore consistency of a predictive distribution with an imposed or hypothesized constraint. Linear, aggregate constraints define illuminating examples that relate to broadly important problems involving aggregate and hierarchical constraints in commercial and economic forecasting. Discussion explores the impact of different loss functions, questions of how constrained forecasting is impacted by dependencies among outcomes being predicted, and promotes the broader use of decision analysis including routine evaluation of predictive distributions of loss under chosen forecasts/decisions. Extensions to more general constrained forecasting problems, connections with broader interests in forecast reconciliation and other considerations are noted.

+Analytical Approach for Predicting the Moment-Curvature Response of Structural Lightweight Reinforced Concrete Beams

With the switch towards performance-based design procedures, the prediction of the flexural behavior of lightweight reinforced concrete, LWRC, members using advanced and reliable analytical tools has been of great interest to researchers. This paper proposes nonlinear analytical and numerical procedures based on sectional analysis and finite element methods for predicting the moment-curvature and load-deflection responses of structural LWRC beams subjected to pure bending. The proposed analytical and numerical models were validated experimentally by casting and testing a series of eight full-scale LWRC beams under four-points bending configuration. The effects of different compressive strengths of concrete and tensile reinforcement ratios on the flexural behavior of LWRC were examined. The analytical and numerical predictions of the load-deflection behavior and the moment-curvature and load-deflection responses of the LWRC beams investigated, compared very well with the corresponding responses measured from experiments, and test results of previous studies existing in the literature. Among the parameters evaluated using sensitivity analysis, the compressive strength had a significant influence on the flexural strength and stiffness of LWRC beams, whereas the compressive reinforcement ratio was the most important factors affecting the energy absorption and curvature ductility. Moreover, the theoretical models developed could serve as viable tools for simplifying the design process of structural lightweight reinforced concrete members and enhance their applications.

Parallel (competitive) reactions of micelle formation and cyclodextrin–surfactant inclusion complex formation in aqueous solution: A consequence of the Gibbs–Duhem equation—invariance of the mass action law and the possibility of determining the equilibrium constant of the inclusion complex

The Gibbs–Duhem equation results in the independence between the standard Gibbs free energy of micelle formation and the standard Gibbs free energy of monocomponent surfactant’s and cyclodextrin’s (CD’s) inclusion complex formation in aqueous solution. The experimental data show that the surfactant’s critical micellar concentration increases in the presence of CD. At a constant temperature, the standard Gibbs free energy of micelle formation remains constant, irrespective of the presence of parallel competitive processes such as inclusion complex formation. This indicates that the critical micellar concentration remains unchanged at the corresponding concentration scale. As a result, the equilibrium constant for surfactant–CD inclusion complex formation can be determined by changing the critical micellar concentration in the presence and absence of CD. A graphical method for determining the equilibrium constant of the inclusion complex is also presented. An analytical approach for analyzing the influence of the formation of the inclusion complex with CD on the formation of the binary mixed micellar pseudophase is presented. Suppose that different values exist for the equilibrium constants of the formation of the inclusion complex for two surfactants from their binary mixture. In this case, there is a change in the initial mole fraction from the initial mixture of surfactants, which should be considered when applying the regular solution theory protocol when determining the parameters of a binary mixed micelle in the presence of CD.

Reliability study of battery lives: A functional degradation analysis approach

Reliability study of battery lives: A functional degradation analysis approach