Fitting Parameters Research Articles

Integrating complexity in population modelling: From matrix to dynamic models

Matrix models are widely used in population ecology studies and are valuable for analysing population dynamics, although they are limited in the use of time-varying parameters. This limitation can be overcome by dynamic models. In this study, we revisit a previously published study on a matrix model of a population of the box jellyfish Carybdea marsupialis (L. 1758) in the Western Mediterranean. A dynamic model integrating the transition matrix of the original model is developed in STELLA Architect with the following improvements: (1) Sensitivity study of the reliability of the methodology for calculating the transition matrix and estimation of the errors of the fitting parameters; (2) Closure of the jellyfish life cycle by adding the polyp stage. This will make it possible to simulate scenarios of ecological interest over several years such as a decline in food supply, jellyfish removal strategies, changes in drift currents and changes in substrate availability for planulae to settle. (3) The inclusion of more biological reality. In particular, a temporal pattern of strobilation is added, which improves the fit of the model to the field data.

Powder dosing within continuous manufacturing: A lean approach for gravimetric dosing configuration and equipment selection

This work presents a novel approach to select gravimetric dosing configurations for continuous unit operations in pharmaceutical processing. It optimizes material, time, and personnel use, and allows selections for configurations of materials not included in the model by robust material attribute-based interpolation. The approach does not apply Principal Component Analysis (PCA) and Partial Least Squares (PLS). Instead, a reduced set of material attributes that require measurement was determined from existing material attribute libraries found in literature. Only those identified 17 attributes were measured for 13 materials and employed in this study. The established model proved to be predictive for an even further reduced attribute set of 12 attributes. The model introduces a simplified method for selecting feeding equipment combining precision metrics (relative mean intra-bin variability) and model parameters (fmax, fmin, beta). The reduction of Material Attributes (MAs) in this short-cut method enables fast evaluation and enhances resource efficiency by incorporating only a few selected MAs into the model and therefore introduces a different line of thinking. It was also possible to compare feeding of different hopper geometries, showing that flat bottom-hoppers have higher dosing precision than round bottom-hoppers. In conclusion, this work introduces a smart and innovative model that simplifies the equipment selection process and brings objectivity through a comprehensive numerical description of the discharge characteristics, and provides new options for continuous dosing in pharma through combining precision and curve fitting parameters.

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.

Large-Scale Parameter Estimation for Crystal Structure Prediction. Part 1: Dataset, Methodology, and Implementation.

Crystal structure prediction (CSP) seeks to identify all thermodynamically accessible solid forms of a given compound and, crucially, to establish the relative thermodynamic stability between different polymorphs. The conventional hierarchical CSP workflow suggests that no single energy model can fulfill the needs of all stages in the workflow, and energy models across a spectrum of fidelities and computational costs are required. Hybrid ab initio/empirical force-field (HAIEFF) models have demonstrated a good balance of these two factors, but the force-field component presents a major bottleneck for model accuracy. Existing parameter estimation tools for fitting this empirical component are inefficient and have severe limitations on the manageable problem size. This, combined with a lack of reliable reference data for parameter fitting, has resulted in development in the force-field component of HAIEFF models having mostly stagnated. In this work, we address these barriers to progress. First, we introduce a curated database of 755 organic crystal structures, obtained using high quality, solid-state DFT-D calculations, which provide a complete set of geometry and energy data. Comparisons to various theoretical and experimental data sources indicate that this database provides suitable diversity for parameter fitting. In tandem, we also put forward a new parameter estimation algorithm implemented as the CrystalEstimator program. Our tests demonstrate that CrystalEstimator is capable of efficiently handling large-scale parameter estimation problems, simultaneously fitting as many as 62 model parameters based on data from 445 structures. This problem size far exceeds any previously reported works related to CSP force-field parametrization. These developments form a strong foundation for all future work involving parameter estimation of transferable or tailor-made force-fields for HAIEFF models. This ultimately opens the way for significant improvements in the accuracy achieved by the HAIEFF models.

Physical fitness and body build parameters of children and adolescents participating in the physical activity promotion programme “Athletics for all!”

BackgroundThis study attempts to analyse physical fitness and basic anthropometric parameters of children and adolescents participating in the nationwide physical activity promotion programme “Athletics for All!” (AFA). The programme aims to establish a national system for diagnosing, selecting, recruiting, and identifying talents in youth training. It also aims to build a career development path for athletics, forming the basis of a new structure for youth training in Poland. The primary goal of this study was to assess physical fitness of AFA participants over the years of its implementation (2015–2022) and to identify the leading motor ability with consideration for age, gender, and body build parameters determined with Body Mass Index and Ponderal Index.MethodsNationwide measurements of basic anthropometric parameters as well as physical fitness tests were conducted among 31,790 girls (F) and 22,260 boys (M) participating in the AFA programme. Physical fitness assessments were performed using the OSF test (3 × 10 m shuttle run, standing broad jump, 1 kg medicine ball throw, 4-minute run). Comparative analysis of OSF test results, considering gender, was conducted using the independent samples T-test. The strength and direction of correlations between variables were calculated using the rho-Spearman coefficient.ResultsOSF test results were converted into points, considering age and gender. Gender was found to be a significantly differentiating factor in physical fitness of AFA participants. Among twelve- and fifteen-year-olds, statistically significant differences were observed in all analysed variables, i.e. in each of the four tests and the overall score. It was noted that the examined girls aged 11 to 17 exhibited higher levels of strength compared to their male counterparts. Statistical analysis revealed significant correlations between OSF test results and the age and body build indicators, with the strength of the correlations being negligible in most cases.ConclusionsParticipants of the nationwide programme “Athletics for All!” demonstrate a high level of physical fitness, with endurance being a fundamental motor ability. Physical fitness levels show significant correlations with the anthropometric parameters of children and adolescents. The study results confirm the need and justification for implementing physical activity promotion programmes for the younger generation.

Improved PID control of DC motor

Abstract. In this paper, the circuit optimization problem of precise control of DC motor through PID interface is studied. The main purpose of this research is to strategically coordinate resistance and capacitance elements in circuit design to explore and improve the speed of signal transmission and the accuracy of response. Additionally, by optimizing the interaction between these components, this paper attempts to achieve improved performance and efficiency in the motor control system, that is, changing different K_p and K_d to achieve the best fit parameters for the most system. The experimental approach employed in this study involves a collaboration between Tinkercad and Falstad software platforms to simulate and analyze the effects of various circuit configurations as well as coefficients. The effects of K_p and K_d on the system are obtained through systematic experiments and analysis. Meanwhile, it aim to verify the proposed optimization technique and evaluate its effectiveness in practical applications. The simulation results of Tinkercad and Falstad agree well with the expected theoretical results.

Progressive development of soil arching and deformations in two- and three-dimensional trapdoor tests

In this study, two- and three-dimensional trapdoor tests were conducted using a newly developed trapdoor test device, to investigate the evolution of soil arching and fill deformation with different relative fill densities and fill heights. The test results show that the trapdoor settlements normalised by trapdoor width required for the soil arching ratios to reach minimum and ultimate values increased with fill height. In tests with dense fill, both the minimum and ultimate soil arching ratios were smaller compared to tests with loose fill at the same fill height. Two symmetrical slip surfaces developed from the trapdoor edges, with their inclination angles dependent on the dilatation angle of the sand. The proposed Gaussian distribution function with fitting parameters well matched the measured fill settlement profile. In the dense fill tests, the settlement trough’s width and volume loss induced by trapdoor settlement gradually decreased with fill elevation due to its strong shear dilation behaviour. Conversely, the loose fill exhibited weaker shear dilation behaviour, resulting in a larger settlement region. The settlement trough width and volume loss ratio, derived from the measured fill deformation, can be used to predict the fill deformation, including the surface settlement.

Lifetime mapping using femtosecond time-resolved photoemission electron microscopy.

Time-resolved photoemission electron microscopy (PEEM) has established itself as a versatile experimental technique to unravel the ultrafast electron dynamics of materials with nanometer-scale resolution. However, the approach of performing PEEM-based, pixel-by-pixel lifetime mapping has not been reported thus far. Herein, we describe in detail the data pre-processing procedure and an algorithm to perform time-trace fittings of each pixel. We impose an energy cutoff for each pixel prior to spectral integration to enhance the robustness of our approach. With the energy cutoff, the energy-integrated time traces show improved statistics and lower fitting errors, thus resulting in a more accurate determination of the fit parameters, e.g., decay time constants. Our work allows us to reliably construct PEEM-based lifetime maps, which potentially shed light on the effects of local microenvironment on the ultrafast processes of the material and allow spatial distributions of lifetimes to be correlated with observables obtained from complementary microscopic techniques, hence enabling a more comprehensive characterization of the material.

A novel data-driven framework of elastoplastic constitutive model based on geometric physical information

The advantages of data science have inspired the development of data-driven approaches for solving constitutive modeling problems, which have become a new research focus in engineering mechanics. These approaches help fully utilize the information inherent in the data, bypassing the traditional modeling processes.In order to advance the development of Constitutive Model Based on Data-Driven (CMBDD), we introduced a novel framework called the Geometric Physical Information-enhanced Data-Driven ElastoPlastic constitutive model (IDD-EP) under hysteretic loading paths. IDD-EP adopts an ”Encoder-Decoder” framework, with the information transmission between the encoder and decoder facilitated by the ”Geometric Physical Information” proposed in this paper. Specifically, IDD-EP-I, serving as the encoder, extracts Geometric Physical Information from experimental constitutive images, which is then transmitted to the modular data-driven decoder IDD-EP-II, designed based on physical mechanisms, to compute material responses under arbitrary paths. IDD-EP aims to establish a constitutive model relying solely on a single small sample without using deep learning techniques and avoids the challenge of model parameter fitting in classical models through a non-mathematical model design.In addition to discussing the general framework of IDD-EP, this paper specifically demonstrates a specialized version of the IDD-EP framework based on uniaxial buckling-restrained braces (BRBs), which are commonly used in structural vibration control, in order to showcase a specific implementation example of the IDD-EP model. The IDD-EP method in this paper accurately predicts the mechanical response of the BRB using only one constitutive experimental image, without the need to pre-select a base constitutive model or fit model parameters. This innovative approach to IDD-EP opens a new avenue for constitutive modeling of elastoplastic materials and may offer solutions to a wider range of history-dependent constitutive modeling challenges in the future.

The contribution of methyl groups to electron spin decoherence of nitroxides in glassy matrices.

Long electron spin coherence lifetimes are crucial for high sensitivity and resolution in many pulse electron paramagnetic resonance (EPR) experiments aimed at measuring hyperfine and dipolar couplings, as well as in potential quantum sensing applications of molecular spin qubits. In immobilized systems, methyl groups contribute significantly to electron spin decoherence as a result of methyl torsional quantum tunneling. We examine the electron spin decoherence dynamics of the nitroxide radical 2,2,6,6-tetramethylpiperidin-1-oxyl (TEMPO) in both a methyl-free solvent and a methyl-containing solvent at cryogenic temperature. We model nitroxide and solvent methyl effects on decoherence using cluster correlation expansion (CCE) simulations extended to include methyl tunneling and compare the calculations to experimental data. We show that by using the methyl tunneling frequency as a fit parameter, experimental Hahn echo decays can be reproduced fairly well, allowing structural properties to be investigated in silico. In addition, we examine the Hahn echo of a hypothetical system with an unpaired electron and a single methyl to determine the effect of geometric configuration on methyl-driven electron spin decoherence. The simulations show that a methyl group contributes the most to electron spin decoherence if it is located between 2.5 and 6-7Å from the electron spin, with its orientation being of secondary importance.

Social support, self-efficacy, self-esteem, and self-management behaviors among people living with HIV/AIDS in China: a structural equation modeling analysis

BackgroundUnderstanding the psychosocial factors influencing self-management behaviors among people living with HIV/AIDS (PLWHA) is crucial for effective medical interventions and improving their quality of life. However, few studies have explored the psychosocial mechanisms influencing self-management behaviors among PLWHA in China. This study, conducted in accordance with STROBE guidelines, uses SEM to explore the roles of social support, self-efficacy, and self-esteem in predicting self-management behaviors among Chinese PLWHA.MethodsFrom March 2023 to July 2023, a convenience sample of 282 PLWHA, recruited from one designated AIDS hospital and one Centers for Disease Control and Prevention in Sichuan Province, China, was surveyed. Data were collected via four validated self-report scales (the Social Support Rating Scale, the General Self-Efficacy Scale, the Self-Esteem Scale, and the HIV/AIDS Patient Self-Management Scale). Structural equation modeling was used to assess the relationships among social support, self-efficacy, self-esteem, and self-management behaviors.ResultsThe new model demonstrated acceptable fit parameters (χ2/df = 2.15, GFI = 0.96, AGFI = 0.93, CFI = 0.93, IFI = 0.94, RMSEA = 0.05). The direct effect of social support on self-management behaviors was significant (β = 0.117, P < 0.05). In addition, self-efficacy and self-esteem played significant mediating roles in the influence of social support on self-management behaviors, accounting for 38.73% and 22.79% of the total effect, respectively. Moreover, they served as chain mediators, contributing 9.80% to the total effect.ConclusionsThese findings contribute to our understanding of the psychosocial dynamics influencing self-management behavior in Chinese PLWHA and have broader implications for populations in other countries. Targeted interventions that enhance social support, self-efficacy, and self-esteem could be applied in various cultural contexts to improve self-management practices among PLWHA globally.

Reliability of trap-filling parameters read from OSL dose-response curves measured by procedures with sensitivity correction

As is known from the early stimulated luminescence studies, dose-response curves (DRCs) are not consistent with the curves of the dependence of the electron concentration in the traps on the irradiation dose delivered to a crystal, even for a system consisting of one trap and one recombination centre. However, for the optically stimulated luminescence (OSL) signal originating from more complex trap and recombination centre systems, it is often observed that the DRC can be described by a simple single saturating exponential (SSE) or a double saturating exponential (DSE) function. Using simulations, we show that although good fit compliance can often be achieved, the parameters obtained only in some cases correctly describe the relationship between the occupancy of individual traps and the dose. Simulations performed for the DRC construction procedure included a step allowing for the correction of possible changes in sensitivity. A model of two traps active in the OSL process and two recombination centres was tested. The modelling shows that the results of the DRC analysis using SSE functions strongly depend not only on the relationship of the trapping probability coefficients of traps but also on their concentrations and the concentrations of recombination centres. The shape of the DRC, and therefore the fitting parameters, also change with the annealing temperature used in the DRC measurement protocol.

Optimizing laser-induced phase transformations in Sb2S3 thin films: Simulation framework and experiments

We present a novel simulation approach combined with pulsed laser experiments, spectroscopic ellipsometry, and Raman spectroscopy to comprehensively analyze phase transformation dynamics in thin films. The simulations apply to any thin film stack and incorporate critical factors, such as thin film interference, heat transfer, and temperature-dependent optical properties during heating and melting. As a case study, we investigate the picosecond laser-induced amorphization of antimony sulfide (Sb2S3) thin films, a promising alternative to traditional phase-change materials in photonic applications to validate the simulation model. The computational efficiency of our simulations enables not only the investigation of the laser-induced phase transformation but also the optimization of key process parameters and parameter fitting. The simulations identified optimal film thickness and laser fluence parameters that maximize energy efficiency, melting effectiveness, and quenching rate while ensuring high reflectivity contrast between the amorphous and crystalline states. By constructing a wide-ranging, high-resolution parameter map of the laser fluence and film thickness dependence of the melting process, we demonstrate how this model guides the understanding of phase transformation dynamics. Raman spectroscopy confirms the polycrystalline to amorphous transition of Sb2S3 and provides a semiquantitative estimate of the amorphous fraction as a function of laser fluence, which is qualitatively consistent with the simulation predictions of the model. The open-source simulation framework, experimentally validated, provides valuable insights into laser-induced amorphization dynamics in Sb2S3 and related phase-change material thin films, enabling rapid optimization of photonic devices.

Methodology for comparative assessment of battery technologies: Experimental design, modeling, performance indicators and validation with four technologies

An increasing number of applications with diverse requirements incorporate various battery technologies. Selecting the most suitable battery technology becomes a tedious task as several aspects need to be taken into account. Two of the key aspects are the battery characteristics under temperature variations and their degradation. While numerous contributions using tailored assessment methods to evaluate both aspects for a particular application exist in the literature, a general methodology for analysis is necessary to enable a quantitative comparison between different technologies. We propose in this paper a novel methodology, based on performance indicators, to quantify the potential and limitations of a battery technology for diverse applications sharing a similar operational profile. A quantification of phenomena such as the influence of high and low temperatures on the battery, or the effect of cycling and state of charge on battery aging is obtained. In pursuit of these indicators, an experimental procedure and the fitting of aging model parameters that allow their calculation are proposed. As an additional outcome of this work, a general aging model that allows comprehensive analysis of aging behavior is developed and the trade-off between experimental time and accuracy is analyzed to find an optimal experimental time between 2 and 4 months, depending on the studied battery technology. Finally, the proposed methodology is applied to four battery technologies in order to show its potential in a real case-study.

Dynamic analysis and optimal control of HIV/AIDS model considering the first 95% target

Based on the level of awareness of the population, an HIV/AIDS model is developed, which focused on the first 95% plan developed by UNAIDS. The threshold of model and the expressions of the disease‐free equilibrium and the endemic equilibrium are calculated, proving the existence of backward bifurcation. Backward bifurcation is caused by the imperfect protection rate of susceptible population due to education. Using China's actual data for parameter fitting, it is found that new HIV infections are on an upward trend. In response to this phenomenon, publicity and education, condoms, screening, and treatment of infected populations are considered as control measures. It is concluded that publicity and education is the primary strategy. This measure can not only effectively reduce the number of infected populations but also effectively increase the awareness rate of HIV‐infected populations. It is recommended to use condoms and have fewer sexual partners during sexual contact. Numerical simulation verifies that early stage publicity and education are much more important than post‐infection screening and treatment measures.

Reliability analysis of the vehicle door system EDCU based on Weibull distribution

The paper established a two-parameter Weibull distribution model to analyze the failure law of key components of metro vehicles and employed the least squares method to fit the parameters of the Weibull function. The paper provided a detailed introduction of the model's parameter fitting method based on actual historical failure data. Taking the EDCU (Electrical Door Control Unit) as an example, the failure rate, cumulative failure rate, and reliability of EDCU for 3 different vehicle models were calculated, and the calculation results were verified to conform to the Weibull distribution through Q-Q diagrams. The results show that although the designed service life of EDCU of vehicle door system is 15 years, the reliability of the EDCU decreases significantly around 10 years. The EDCU reliability of the three vehicle models declines by 22%, 4.2%, 10.6% and the failure rates are 2.7%, 0.57%, 1.13%. Based on the reliability of EDCU mentioned above, while ensuring the reliability of components, the maintenance methods of components can be optimized to reduce maintenance costs.

Correlative Activation Free Energy (CAFE) Model: Application to Viscous Processes in Inorganic Oxide Glass-Formers

We explore the concept of correlative activation free energy (CAFE) for the analysis and interpretation of viscosity data of a collection of 847 inorganic oxide glass formers that exhibit various degrees of non-Arrhenius behavior. The CAFE model formalism is strictly based on transition state theory and accounts for the variation in the activation barrier for the viscous dissipation due to the structural evolution the system undergoes upon traversing the glass transition regime. Thus, fitting parameters are meaningful in a statistical thermodynamic context. Compared to the VFT and MYEGA equations, fits using the CAFE model are more robust when extrapolating to infinite temperature because the latter encodes non-enthalpic contributions to the rate coefficient more realistically. The CAFE model-based analysis reveals a strong connection between melt fragility and the degree of change in the potential energy landscape with temperature. Accordingly, while the average ground-state potential energy of the glass forming liquid gradually increases with temperature, the energy of the activated state remains relatively invariant. Our analysis also allows one to estimate the number of atoms involved in the viscous relaxation process, which ranges from approximately 10 to 50 atoms for the oxide glass formers studied. We observe that thermally activated dynamic phenomena exhibited by glassy networks, such as the mixed alkali effect, persist into the supercooled liquid state.

Capability of different multiaxial fatigue evaluation approaches on adhesively butt-bonded hollow cylinders under multiaxial loading with variable amplitudes

Currently, there is a lack of reliable approaches for the fatigue assessment of adhesively bonded joints that are subject to multiaxial stresses with variable amplitudes. To improve the current situation, investigations are made on the capability of three multiaxial evaluation approaches based on fatigue tests of adhesively butt-bonded hollow cylinders under multiaxial loading with constant phase shift and variable amplitudes.The investigated approaches are the Gough-Pollard criterion, the Findley criterion and a new method presented here, which is based on a multiaxial counting method and an invariant equivalent stress hypothesis (MCES-Method).While the Gough-Pollard criterion has a low computational effort, it does not reflect the fatigue life extending effect due to a phase shift without using a fitting parameter that is not physically based. The Findley criterion is less suitable for the investigated multiaxial stress states (with and without phase shift), although the fatigue life prediction under these load conditions is at least conservative. The MCES-Method has the highest accuracy of the methods considered. By combining research findings from published papers in the context of adhesively bonded joints, all investigated load scenarios are estimated with high prognosis quality.

Modelling plausible scenarios for the Omicron SARS-CoV-2 variant from early-stage surveillance

We used a spatially explicit agent-based model of SARS-CoV-2 transmission combined with spatially fine-grained COVID-19 observation data from Public Health Scotland to investigate the initial rise of the Omicron (BA.1) variant of concern. We evaluated plausible scenarios for transmission rate advantage and vaccine immune escape relative to the Delta variant based on the data that would have been available at that time. We also explored possible outcomes of different levels of imposed non-pharmaceutical intervention. The initial results of these scenarios were used to inform the Scottish Government in the early outbreak stages of the Omicron variant.Using the model with parameters fit over the Delta variant epidemic, some initial assumptions about Omicron transmission rate advantage and vaccine escape, and a simple growth rate fitting procedure, we were able to capture the initial outbreak dynamics for Omicron. We found that the modelled dynamics hold up to retrospective scrutiny. The modelled imposition of extra non-pharmaceutical interventions planned by the Scottish Government at the time would likely have little effect in light of the transmission rate advantage held by the Omicron variant and the fact that the planned interventions would have occurred too late in the outbreak’s trajectory. Finally, we found that any assumptions made about the projected distribution of vaccines in the model population had little bearing on the outcome, in terms of outbreak size and timing. Instead, it was the landscape of prior immunity that was most important.

Identification of novel DNA Gyrase inhibitor by combined Pharmacophore modeling, QSAR analysis, Molecular docking, Molecular dynamics, ADMET and DFT approaches

DNA gyrase, an ATP-dependent enzyme, plays a critical role in DNA replication, transcription, and recombination in Mycobacterium tuberculosis (MTB). While fluoroquinolones are effective antibacterial agents targeting DNA gyrase, their clinical use is often limited due to side effects and the emergence of bacterial resistance. In this study, we developed a quantitative structure-activity relationship (QSAR) model to predict the anti-tubercular activity of Quinoline-Aminopiperidine derivatives targeting the DNA gyrase enzyme, using a dataset of 48 compounds obtained from the literature. The QSAR model was validated using both internal and external validation metrics. Model 4, the best predictive model, demonstrated a strong fit with an R² of 0.8393, an adjusted R² (R²adj) of 0.8010, and a lack of fit (LOF) parameter of 0.0626. The QSAR results revealed that DNA gyrase inhibition is significantly influenced by factors such as partition coefficient, molecular flexibility, hydrogen bonding potential, and the presence of fluorine atoms. Twelve quinoline-aminopiperidine derivatives were designed, and their anti-tubercular activity was predicted using QSAR model-4. These compounds were further assessed for pharmacokinetic properties, toxicity, and binding affinity to DNA gyrase. Pharmacophore modeling was also performed and validated using MOE software. The final pharmacophore model includes the features of two aromatic hydrophobic features, one hydrogen bond acceptor, and one hydrogen bond donor. The results indicated that designed compounds QA-3 and dataset compounds C-34 exhibit favorable drug-likeness properties. Molecular dynamics simulations confirmed the stable binding of compounds QA-3 and C-34 to the DNA gyrase protein, highlighting their potential as promising anti-tubercular agents. The developed QSAR Model-4 will facilitate the prediction of anti-tubercular activity in Quinoline-Aminopiperidine derivatives.