Fitting Parameters Research Articles

Activity coefficients of 3-amino-1-propanol and 2-amino-1-propanol in aqueous solutions from surface tension data

Surface tension of 3-amino-1-propanol and (RS)-2-Amino-1-propanol in aqueous solution were measured in the temperature range from 293.15 to 308.15 K at intervals of 5 K over the whole concentration range. The concentration dependence of surface tension for both amino alcohols aqueous solution shows a similar behavior to that observed for other polar solutes in water. The surface tension data of 3-amino-1-propanol and 2-amino-1-propanol at the selected temperatures were accurately described using the integral Gibbs adsorption equation, the virial equation, and the Langmuir-Gibbs equation of state. The activity coefficients γ for both solutes were determined using the virial equation and found to be unitary within the experimental uncertainty, which was confirmed by the accurate representation of the experimental data by the Langmuir Gibbs Equation of State (LGSEOS). The standard adsorption energy calculated for both solutes from the fitting parameters of LGSEOS to the experimental data indicates that (RS)-2-amino-1-propanol has a higher hydrophobic character and a greater tendency to migrate to the surface than 3-amino-1-propanol as shown by the more negative ΔGads0 values for this solute than for 3-amino-1-propanol.

Measurements of F1‐ Region Ionosphere State Variables at Arecibo Through Quasi Height‐Independent Exhaustive Fittings of the Incoherent Scatter Ion‐Line Spectra

AbstractWe discuss an exhaustive search approach to fit the incoherent scatter spectrum (ISS) in the F1‐region for molecular ion fraction (fm), ion temperature (Ti), and electron temperature (Te). The commonly used “full profile” approach for F1‐region measurements parameterizes the molecular ion fraction as a function of altitude and fits all the related heights for the state variables. In our approach, we fit the ISS at each height for fm, Ti, Te, and ion velocity (Vi) independently. Our exhaustive search method finds all the major local minima at each altitude. Although a parameterized function is used to guide the algorithm in finding the best solution, the fitting parameters retain their local characteristics. Despite that fitting fm, Ti, and Te without constraints requires Doppler shift to be accurately determined and the ISS signal‐to‐noise ratio higher than the full‐profile method, simulations show that Ti, Te, and fm can be recovered within a few percent accuracy with a moderate signal‐to‐noise ratio. We apply the exhaustive search approach to the Arecibo high‐resolution incoherent scatter radar data taken on 13 September 2014. The derived ion and electron temperatures are sensitive enough to reveal thermosphere gravity waves commonly seen in the electron density previously. Our method is more robust than previous height‐independent fitting methods. Comparison with another Arecibo program indicates our results are likely more accurate. Simultaneous high‐resolution measurements of Ti, Te, fm, Vi, and electron concentration (Ne) in our approach open new opportunities for synergistic studies of the F1‐region dynamics and chemistry.

Analytical and numerical models for impedance of a button SOFC anode

We report a physics–based model for the impedance of a button–type anode–supported SOFC. The model includes ion and electron charge conservation equations and a Fick’s diffusion transport equation for hydrogen in the anode support layer. In the limit of small overpotentials, an analytical solution for the anode impedance is derived. For typical SOFC anode parameters, this solution is valid from open–circuit voltage (OCV) up to the cell current density of about 5 mA cm−2. Fast least–squares fitting of the model impedance to an experimental spectrum measured at OCV is demonstrated and the resulting fitting parameters are compared with literature data. A high–current numerical version of the model is also suitable for fast fitting of experimental impedance spectra.

Home-Based HIFT Altered Quality of Life and Health Related Fitness Parameters in Women

The effects of high intensity functional training (HIFT) on health related components of fitness and quality of life were studied in the gym environment, but there has not been any study on examining the effects of HIFT by using bodyweight exercises at home environment on health related components of fitness and quality of life in women. The goal of this research is to examine the effects of home-based bodyweight HIFT on health related components of physical fitness and quality of life in women. Twenty-one recreationally active female participants (age 26.3 ± 3.7 years) were included in the study. After completing the pretest, participants applied HIFT at home with bodyweight exercises three times a week for a duration of eight weeks. Cardiovascular endurance, muscular strength, muscular endurance, flexibility, body composition and quality of life assessments were carried out in both pretest and posttest applications. Significant differences were observed between the pretest and posttest results of cardiovascular endurance (p=0.042), muscular strength (p<0.001), muscular endurance (p<0.001) and flexibility (p=0.001) parameters. No significant difference was observed between the pretest and posttest results of body composition analysis. Significant improvement (p=0.045) was found on the quality of life scale. Home-based bodyweight HIFT altered quality of life in recreationally active women and enhanced health related components of fitness, which could prevent the increase of health-related risk factors caused by inactivity.

Acceptability and psychometric properties of four scales assessing the impact of Type 2 diabetes on quality of life-Results of 'YourSAY: Quality of Life'.

To assess and compare the psychometric properties and acceptability of four diabetes-specific quality of life (QoL) scales among adults with Type 2 diabetes (T2D). Adults (≥18 years) with T2D living in the United Kingdom (n = 1465) or Australia (n = 248) completed a cross-sectional, online survey including the following: ADDQoL, DCP, DIDP and Diabetes QoL-Q (presented in randomised order), followed by rating scales to assess clarity, relevance, ease of completion, length and comprehensiveness of each scale. Demographic, clinical and psychosocial characteristics were collected. Acceptability (scale completeness and user ratings), response patterns, structure (exploratory and confirmatory factor analyses) and validity (convergent, confirmatory, divergent and known-groups) were examined. Data were analysed by country to assess cross-country reproducibility. High completion rates (≥89%) and positive user ratings were observed across scales indicating broad acceptability. The DIDP was the strongest performing scale: highest completion rate (97%), user ratings (≥84% positive) and most satisfactory psychometric properties (highest variance explained, consistent factor loadings >0.5 on all items and most permissible model fit parameters). Scale-level floor effects may suggest domain omissions for the brief DIDP. The current study provides novel insights into the acceptability, validity and reliability of diabetes-specific QoL measures for adults with T2D. Consistent with the published Type 1 diabetes cohort findings, the DIDP is recommended as a brief, acceptable and psychometrically sound measure. However, selection needs to be considered in the context of the specific research or clinical aims and further evidence (e.g. responsiveness) may be required before it can be recommended for use in trials or prospective studies.

Assessing Drug Product Shelf Life Using the Accelerated Stability Assessment Program: A Case Study of a GLPG4399 Capsule Formulation

Objective: To evaluate and project the shelf life of GLPG4399, an early-phase clinical drug formulation by applying the Accelerated Stability Assessment Program (ASAP) approach. Methods: Forced degradation conditions were implemented to identify the stability-limiting degradation product. The drug and its degradation products were separated using a validated liquid chromatography method. Then, the selected clinical capsule formulation was placed in a glass vial and exposed to accelerated short-term conditions of combinations of high- and low-level heat and humidity in an open state for 5 weeks. The liquid chromatography results were evaluated using the ASAP, which is based on the moisture-modified Arrhenius principle. The resulting data were fitted using a suitable diffusion kinetics method. Results: The developed model was applied to predict the shelf life of the drug product when using clinically appropriate primary packaging (high-density polyethylene container). The derived stability parameters of the moisture-modified Arrhenius equation were the Arrhenius collision frequency, activation energy, and humidity sensitivity constant. The goodness of fit parameters R2 (>0.95) and goodness of prediction Q2 (>0.80) parameters for the selected model were acceptable. The results of the accelerated, short-term stability study were verified against real-time, long-term 12-month data. Conclusions: We demonstrated the application of the ASAP approach to evaluate the shelf life of a GLPG4399 solid capsule formulation. The studied ASAP approach can be extended to evaluate the stability and shelf-life estimations of other early-phase clinical formulations.

Effects of a 4–Week Detraining Period After 12 Weeks of Combined Training Using Different Weekly Frequencies on Health–Related Physical Fitness in Older Adults

Background: Detraining refers to the decline in physical fitness that occurs after the cessation of exercise, compromising the adaptations resulting from regular exercise training. To understand how long the benefits acquired from an exercise program can be maintained, the present study evaluated the detraining effects of a 4–week exercise cessation period in older adults who performed combined training at various weekly frequencies for 12 weeks. Methods: This randomized controlled trial assigned participants to one of two training programs: a combined training program twice a week (CT2) or four times a week (CT4) over a period of 12 weeks, followed by a four–week detraining period. The resistance training consisted of six bodyweight exercises, while the aerobic training involved either walking or running. Both the CT2 and CT4 groups completed the same total training volume and overload each week; the only difference was the number of training sessions per week. Assessments were conducted at baseline, after the training period, and after the detraining period, and included the 30–s and five–repetition chair–stand tests, isometric handgrip strength, body mass index (BMI), waist circumference, and waist–to–height ratio. Results: Thirty–one participants completed the study (CT2: 17 and CT4: 14). The groups presented similar attendance records during the training period (CT2: 96 ± 18% versus CT4: 94 ± 19%). After the 12–week training period, CT2 and CT4 improved lower limb strength, CT2 improved upper limb strength, and CT4 reduced waist circumference and waist–to–height ratio compared to baseline. After the 4–week detraining period, the lower limb strength remained improved in both groups (CT2: 4 ± 1 repetition; p < 0.001 and CT4: 4 ± 1 repetition; p < 0.001) when compared to the corresponding baseline values. The handgrip strength decreased in CT2 compared to post–training values. And the body composition benefit in CT4 was not sustained after detraining. Conclusions: The effects of 4 weeks of detraining after 12 weeks of training performed two or four times per week are similar on some but not all health-related physical fitness parameters.

Quantitative analysis of high-frequency radiometric databases. Application to the case of Seville

AbstractThe short-term variability of solar resource is one of the main challenges faced by the large-scale implementation of photovoltaic (PV) systems today; this will increase as the installed power of solar PV increases. To evaluate its influence on electrical grid operation, it is essential to analyse the variability of solar resource based on high-frequency data, 30 s and shorter. In this study, the high-frequency measurements of Global Horizontal Irradiation (GHI) and Direct Normal Irradiation (DNI) recorded every 5 s at the radiometric station of the University of Seville for 20 years are analysed and characterised. For this purpose, a corrected database for GHI and DNI was obtained from the application of a correction methodology. To understand the reliability of this database it is required to know its uncertainty. This work proposes a methodology to quantify the uncertainty of high-frequency radiometric databases whose wrong data have been corrected. Applying it, the daily uncertainty is 2.69% for GHI and 4.07% for DNI. To characterize the distribution of the database, the distribution of high frequency kt and kb indices are modelled providing the fitting parameters. To characterize the variability of high-frequency measurements, transition matrices are proposed, which allow identifying both the magnitude and frequency of jumps. The results obtained show that jumps of up to 800 W/m2 occur in both GHI and DNI. In the case of GHI, the percentage of jumps equal to or greater than 500 W/m2 is 1.36%, about 43,000 jumps in a year in measurements every 5 s.

Using k-means to sort spectra: Electronic order mapping from scanning tunneling spectroscopy measurements

Hyperspectral imaging techniques have a unique ability to probe the inhomogeneity of material properties whether driven by compositional variation or other forms of phase segregation. In the doped cuprates, iridates, and related materials, scanning tunneling microscopy/spectroscopy (STM/STS) measurements have found the emergence of pseudogap “puddles” from the macroscopically Mott insulating phase with increased doping. However, categorizing this hyperspectral data by electronic order is not trivial and has often been done with ad hoc methods. In this paper, we demonstrate the utility of k-means, a simple and easy-to-use unsupervised clustering method, as a tool for classifying heterogeneous scanning tunneling spectroscopy data by electronic order for Rh-doped Sr2IrO4, a cuprate-like material. Applied to STM data acquired within the Mott phase, k-means was able to identify areas of Mott order and of pseudogap order. The unsupervised nature of k-means limits avenues for bias and provides clustered spectral shapes without a priori knowledge of the physics. Additionally, we demonstrate the use of k-means as a preprocessing tool to constrain phenomenological function fitting. Clustering the data allows us to reduce the fitting parameter space, limiting over-fitting. We suggest k-means as a fast, simple model for processing hyperspectral data on materials of mixed electronic order.

Effects of short- and long-term thermal stress on developmental stages and adults vis-à-vis reproductive physiology of Spodoptera litura

Abstract Temperature is a critical environmental factor influencing insect development, physiology, and distribution. Global warming is predicted to increase the frequency and severity of extreme heat events, influencing insects differently across life stages. This study investigates the effects of short- and long-term thermal stress on the tobacco cutworm, Spodoptera litura, a polyphagous pest damaging over 389 plant species. We exposed eggs, larvae, pupae, and adults to elevated temperatures of 42°C and 46°C for four hours and one hour, respectively, in single and repeated occasions for two, four, two and two days for egg, larva, pupa and adults, respectively. Our results demonstrate significant variation in biological and reproductive fitness parameters across treatments. Notably, thermal stress skewed the sex ratio towards females. We also observed impacts on offspring survival and potential negative carry-over effects. Overall, the effects of heat stress were dependent on temperature, exposure duration, and life stage, with adults exhibiting the highest tolerance. These findings suggest that S. litura possesses a degree of heat tolerance that may enable it to survive summer heat waves, but its offspring and other life stages could be more vulnerable under future climate scenarios.

Inertial effects on free surface pumping with an undulating surface

Free surface flows driven by boundary undulations are observed in many biological phenomena, including the feeding and locomotion of water snails. To simulate the feeding strategy of apple snails, we develop a centimetric robotic undulator that drives a thin viscous film of liquid with the wave speed $V_w$ . Our experimental results demonstrate that the behaviour of the net fluid flux $Q$ strongly depends on the Reynolds number $Re$ . Specifically, in the limit of vanishing $Re$ , we observe that $Q$ varies non-monotonically with $V_w$ , which has been successfully rationalised by Pandey et al. (Nat. Commun., vol. 14, no. 1, 2023, p. 7735) with the lubrication model. By contrast, in the regime of finite inertia ( ${Re} \sim O(1)$ ), the fluid flux continues to increase with $V_w$ and completely deviates from the prediction of lubrication theory. To explain the inertia-enhanced pumping rate, we build a thin-film, two-dimensional model via the asymptotic expansion in which we linearise the effects of inertia. Our model results match the experimental data with no fitting parameters and also show the connection to the corresponding free surface shapes $h_2$ . Going beyond the experimental data, we derive analytical expressions of $Q$ and $h_2$ , which allow us to decouple the effects of inertia, gravity, viscosity and surface tension on free surface pumping over a wide range of parameter space.

Advances in Gas Detection of Pattern Recognition Algorithms for Chemiresistive Gas Sensor.

Gas detection and monitoring are critical to protect human health and safeguard the environment and ecosystems. Chemiresistive sensors are widely used in gas monitoring due to their ease of fabrication, high customizability, mechanical flexibility, and fast response time. However, with the rapid development of industrialization and technology, the main challenges faced by chemiresistive gas sensors are poor selectivity and insufficient anti-interference stability in complex application environments. In order to overcome these shortcomings of chemiresistive gas sensors, the pattern recognition method is emerging and is having a great impact in the field of sensing. In this review, we focus systematically on the advancements in the field of data processing methods for feature extraction, such as the methods of determining the characteristics of the original response curve, the curve fitting parameters, and the transform domain. Additionally, we emphasized the developments of traditional recognition algorithms and neural network algorithm in gas discrimination and analyzed the advantages through an extensive literature review. Lastly, we summarized the research on chemiresistive gas sensors and provided prospects for future development.

Numerical Modeling of Soil and Structure Behavior for Tunneling in Different Types of Soil

This note studies the correlation between surface and tunnel volume loss in various types of dry soil via finite element method. The effect of small strain stiffness, the buoyancy effect of soil, and tunnel overburden depth are considered in the 2D tunneling model. The results show that both surface volume loss ratio and settlement trough width parameter in the empirical solution can be expressed as a linear equation of tunnel volume loss ratio for 1D overburden shallow tunnels. Furthermore, the surface volume loss ratio can be presented as a non-linear polynomial equation of overburden depth and tunnel volume loss ratio in a 3D space, and this equation holds in different types of soil. The ranges of required fitting parameters and upper and lower bounding surfaces are suggested for various types of soil. Knowledge of this correlation between surface and tunnel volume loss is valuable, as it can be employed in practice for preliminary tunnel design in the absence of tunneling induced maximum ground settlement.

Determining the Fitness Level of People with Down Syndrome Living in Kosovo Based on the ALPHA Protocol

Purpose: This study aimed to establish national norm values for body composition and fitness levels among individuals with Down syndrome. It also aimed to investigate gender differences in body composition features and fitness parameters, analyze the impact of the region where individuals with Down syndrome reside, and compare their fitness levels with international peers. Methods: The sample included 81 participants, 40 females (height: 146.6±4.88 cm, weight: 63.6±16.4 kg) and 41 males (height: 157.4±6.21 cm, weight: 66.8±14.8 kg). To assess the physical fitness levels of the participants with Down syndrome, a modified version of the ALPHA testing protocol was used. Findings: The results demonstrated significant gender differences (p<0.05) in body composition and fitness parameters, with males generally exhibiting better outcomes compared to females. Moreover, significant disparities (p<0.05) in body composition and fitness parameters were observed among individuals with Down syndrome residing in different regions of Kosovo. Noteworthy gender disparities exist in terms of body composition and physical fitness metrics, with male participants achieving superior results compared to their female counterparts. Furthermore, noticeable variations were observed among the regional Down syndrome centers, with participants from older centers displaying improved fitness metrics and body composition features compared to those from newly established facilities. Conclusion: Gender differences in body composition and fitness were evident, with males outperforming females, except in muscle mass. Future studies should explore fitness and health barriers in Kosovo's DS population, with a focus on improving physical activity through tailored strategies.

Mathematical Modelling of Tensile Mechanical Behavior of a Bio-Composite Based on Polybutylene-Succinate and Brewer Spent Grains.

A model based on the fitting of stress-strain data by tensile tests of bio-composites made of a bioplastic (polybutylene succinate (PBS)) and brewer spent grain filler (BSGF) is developed. Experimental tests were performed for various concentrations of BSGF in the range from 2% to 30%. The model is suitable for describing the elastic-plastic behavior of these materials in terms of two mechanical parameters, tensile stress and tensile stiffness (or Young's modulus), depending on the filler concentration. The mechanical characteristics, derived from the fit parameters, show good agreement with the experimental data. The mathematical model used here could be an important aid for the experimentation and manufacturing process as it allows the prediction of the mechanical tensile parameters of a mixture with different filler concentrations, avoiding the long and complex preparation cycle of bio-composites, as well as the specific mechanical tests. The physical properties required by the objects created with the PBS-BSGF bio-composite by the partners/stakeholders of the research project co-financing this research can be quite different; therefore, a mathematical model that predicts some of the mechanical properties in terms of the mixture composition may be useful to speed up the selection of the required amount of BSGF in the mixture.

Memory Effects Explain the Fractional Viscosity Dependence of Rates Associated with Internal Friction: Simple Models and Applications to Butane Dihedral Rotation.

Barrier-crossing rates of biophysical processes, ranging from simple conformational changes to protein folding, often deviate from the Kramers prediction of an inverse viscosity dependence. In many recent studies, this has been attributed to the presence of internal friction within the system. Previously, we showed that memory-dependent friction arising from the nonequilibrium solvation of a single particle crossing a smooth one-dimensional barrier can also cause such a deviation and be misinterpreted as internal friction. Here we introduce a simple diatom model and show that even in the absence of explicit solvent, internal memory effects arise due to coupling of the reaction coordinate motion with frictionally orthogonal degrees of freedom. This results in a fractional viscosity dependence and a deviation from Kramers' theory, typically attributed to the presence of internal friction. This model therefore mimics several biological processes where a local conformational change of a biomolecule is often influenced by its surroundings. This gives rise to an apparent "internal friction" commonly measured in terms of empirical fitting parameters α and σ. We propose a microscopic measure of this internal friction using Grote-Hynes theory which employs memory-dependent friction. We use butane to demonstrate the effect of coupling strength on the internal friction in realistic systems. This model therefore can serve the purpose of understanding internal friction in biological systems in terms of such coupling.

Assessment of Item Parameter and Model-Data Fit of 4IR Teachers' Effectiveness Scale in Secondary Schools

In secondary schools in Southwest Nigeria, the Fourth Industrial Revolution Chemistry Teachers Effectiveness Scale (4IRCTES) items were evaluated for discrimination item parameter and model-data fit to the underlying construct. In this study, a descriptive survey research design was employed. The survey encompassed 4,986 Chemistry teachers in the southwestern region of Nigeria. 35 Chemistry teachers made up the study’s sample. 4IRCTES was the instrument utilised to collect the data. Research question two was based on the absolute overall model-data fit, or M2 statistic, whereas research question one used the Multidimensional Graded Response Model (MGRM) of the Item Response Theory (IRT) to analyse the item parameter (item discrimination). Result showed that items of 4IRCTES discriminated well between teachers with low effectiveness and teachers with high effectiveness. Finally, in the study, result showed that the MGRM of the IRT is the substantial model-data fit for the 4IRCTES. The study concluded that the 4IRCTES items effectively distinguished between teachers who were ineffective and those who were effective.

Intrinsic steady-state pattern of mouse cardiac electrophysiology: analysis using a characterized quantitative electrocardiogram strategy

To explore the intrinsic steady-state electrophysiological properties of mouse heart under physiological conditions by high-resolution quantitative analysis. Twenty-two young adult C57BL/6 mice with a 1:1 male-to-female ratio were used. The limbs of the mice were fixed without anesthesia, and electrocardiographic waveforms, including characteristic P-waves, R-waves, and ST-waves, were recorded using a sensitive 12-lead electrophysiological recorder (ECGsqa) under spontaneous breathing. LabScribe software was used to extract and quantify high-resolution time course and amplitude parameters within a single cardiac cycle from the V3 precordial lead. Pearson correlation test combined with simple linear regression was used to generate a scatter plot of ECG parameter fitting. The common and unique correlation parameters were separately identified by joint associations for profiling the quantitative association network. ECGsqa analysis identified and quantified 14 characteristic ECG parameters, 28.6% of which showed statistical differences between the groups. Compared to male mice, female mice exhibited higher amplitudes and velocities of R and ST waves. Among the 51 association pairs identified in primary association analysis, 47.1% were positively correlated, including shared (29.2%), male-specific (29.2%), and female-specific (41.7%) association groups. Second-order clustering of the association pairs revealed that the amplituderate association pairs of each waveform voltage in both male and female mouse hearts were strongly correlated. The male mice showed an atrioventricular interconnection pattern, while the female mice showed a unique atrial conduction system quality dependence. The distribution network characteristics of the association groups showed that sex-specific and common correlation sets formed a certain series pattern. We discovered a novel intrinsic correlation network of cardiac electrophysiological traits in male and female mice, which reveals the key internal quantitative characteristics and gender difference of both atrial and ventricular conduction systems.

Effectiveness of a 12-week combining tai chi and yoga program on pulmonary function and functional fitness in COPD patients

BackgroundChronic obstructive pulmonary disease (COPD) poses significant challenges to both patients and healthcare providers due to its progressive nature and adverse impact on respiratory function and quality of life (QoL). While pulmonary rehabilitation remains a cornerstone of non-pharmacological COPD management, additional interventions are needed to address patients' diverse needs and preferences. AimThis study investigated the feasibility and potential benefits of a 12-week combining Tai Chi and Yoga (TY combining) program on cardiorespiratory and lung functions, functional fitness, and QoL in older males diagnosed with COPD. MethodsTwenty-four male COPD patients (age: 70 ± 6 years) with moderate to severe disease were recruited and randomized into the TY combining group (n = 12) or control group (n = 12). Assessments were conducted at baseline and at week 12, including pulmonary function tests, quality of life measures, dyspnea, and fatigue. Functional fitness tests were assessed at baseline, week 4, week 8, and week 12. ResultsThe TY combining program significantly improved pulmonary functions, functional fitness, quality of life, and fatigue over the 12-week intervention period. Notably, improvements in functional fitness parameters were observed after just four weeks of training, emphasizing the rapid benefits of the intervention. Moreover, the program exhibited high safety and feasibility, with no reported complications. ConclusionThe 12-week TY combining program represents a safe, feasible, and effective adjunctive therapy for COPD management in older male patients. By addressing multiple dimensions of health and functioning, including pulmonary and cardiovascular health, functional fitness, and quality of life, this holistic approach holds promise for optimizing outcomes in COPD patients. Further research is warranted to validate these findings and explore optimal implementation strategies in clinical practice.

The Key Role of Wettability and Boundary Layer in Dissolution Rate Test.

The present work proposes a mathematical model able to describe the dissolution of poly-disperse drug spherical particles in a solution (Dissolution Rate Test-DRT). DRT is a pivotal test performed in the pharmaceutical field to qualitatively assess drug bioavailability. The proposed mathematical model relies on the key hallmarks of DRT, such as particle size distribution, solubility, wettability, hydrodynamic conditions in the dissolving liquid of finite dimensions, and possible re-crystallization during the dissolution process. The spherical shape of the drug particles was the only cue simplification applied. Two model drugs were considered to check model robustness: theophylline (both soluble and wettable) and praziquantel (both poorly soluble and wettable). The DRT data analysis within the proposed model allows us to understand that for theophylline, the main resistance to dissolution is due to the boundary layer surrounding drug particles, whereas wettability plays a negligible role. Conversely, the effect of low wettability cannot be neglected for praziquantel. These results are validated by the determination of drug wettability performed while measuring the solid-liquid contact angle on four liquids with decreasing polarities. Moreover, the percentage of drug polarity was determined. The proposed mathematical model confirms the importance of the different physical phenomena leading the dissolution of poly-disperse solid drug particles in a solution. Although a comprehensive mathematical model was proposed and applied, the DRT data of theophylline and praziquantel was successfully fitted by means of just two fitting parameters.