Computational Model Research Articles

Decomposing dynamical subprocesses for compositional generalization

A striking feature of human cognition is an exceptional ability to rapidly adapt to novel situations. It is proposed this relies on abstracting and generalizing past experiences. While previous research has explored how humans detect and generalize single sequential processes, we have a limited understanding of how humans adapt to more naturalistic scenarios, for example, complex, multisubprocess environments. Here, we propose a candidate computational mechanism that posits compositional generalization of knowledge about subprocess dynamics. In two samples (N = 238 and N = 137), we combined a novel sequence learning task and computational modeling to ask whether humans extract and generalize subprocesses compositionally to solve new problems. In prior learning, participants experienced sequences of compound images formed from two graphs' product spaces (group 1: G1 and G2, group 2: G3 and G4). In transfer learning, both groups encountered compound images from the product of G1 and G3, composed entirely of new images. We show that subprocess knowledge transferred between task phases, such that in a new task environment each group had enhanced accuracy in predicting subprocess dynamics they had experienced during prior learning. Computational models utilizing predictive representations, based solely on the temporal contiguity of experienced task states, without an ability to transfer knowledge, failed to explain these data. Instead, behavior was consistent with a predictive representation model that maps task states between prior and transfer learning. These results help advance a mechanistic understanding of how humans discover and abstract subprocesses composing their experiences and compositionally reuse prior knowledge as a scaffolding for new experiences.

THE COMPUTER MODELING STUDY OF INTERACTIONS BETWEEN CONTACT SURFACES OF METAL OR POLIMERIC SCREWS AND CORTICAL BONE TISSUE

The continuous growth of fracture rates and surgeries with the use of screws requires modern approaches to improve treatment results. The interaction between a screw and bone tissue is one of the critical factors that affects the stability of a fracture and remains not thoroughly researched until now. The computer modeling method allows for studying precisely the strains and deformities in the contact areas of metal screws, polymeric screws, and cortical bone.Material and methods. The computer modeling was performed in Autodesk Fusion 360 for biomechanical interactions of 3.5 mm AO screws made of stainless steel and polyamide-12 (P-12) with monocortical diaphyseal part of long tubular bone. The static stress study was performed for different loads applied in the pull-out direction with the bonded contact used between the screw and the bone. The displacement and strains were revealed in different parts of the screw thread and surrounding bone tissue for the force applied along the screw axis in the range from 100 N to 1000 N.Results. The increase of the force resulted in stress and strains in the screw and surrounding bone tissue, and the maximum force values can lead to unstable fixation. It was determined that polymeric P-12 screws in all study cases were affecting the bone with less contact pressure than metal screws. In the superficial bone areas this difference was more significant – 24.8 %, and in the deep bone areas it was 8.9 %. The areas of von Mises stress in both superficial and deep parts of polymeric screws were in the range from 1.414 MPa to 20.74 MPa which was lower than that of metal screws (3.484 MPa to 56.24 MPa).Conclusions. Polymeric P-12 screws will fix bone fractures better under low intensive but long-lasting loads, as their destructive effect on bone tissue around screws will be less than of metal ones. On the other hand, metal screws will have the advantage to resist the short lasting but intensive “peak” loads. The less stress areas in the polymeric screw can somehow compensate the lower mechanical strength parameters of P-12 material.Perspective of further research. The obtained results can be taken into account during orthopedics surgeries when screws are used for fixation, as well as for further biomechanical studies.

Editorial: Computational modeling and machine learning methods in neurodevelopment and neurodegeneration: from basic research to clinical applications

Editorial: Computational modeling and machine learning methods in neurodevelopment and neurodegeneration: from basic research to clinical applications

Discovery of Potent Benzothiazole Inhibitors of Oxidoreductase NQO2, a Target for Inflammation and Cancer

Inhibitors of NQO2 (NRH: quinone oxidoreductase) have potential application in several areas of medicine and pharmacology, including cancer, neurodegeneration (PD and AD), stroke, and diabetes. Here, resveratrol, a known inhibitor of NQO2, was used as the lead by replacing the double bond in resveratrol with a benzothiazole scaffold. Fifty-five benzothiazoles were designed as NQO2 inhibitors and synthesized, comprising five benzothiazole series with 3,5-dimethoxy, 2,4-dimethoxy, 2,5-dimethoxy, 3,4-dimethoxy, and 3,4,5-trimethoxy substituents, the key synthetic step being a Jacobson cyclisation with the appropriate thiobenzamide. All compounds were evaluated in an NQO2 enzyme inhibition assay, with four compounds having IC50 values of <100 nM. The most active (IC50 25 nM) was 6-hydroxy-2-(3’,5’-dihydroxyphenyl)benzo[d]thiazole (15), a good mimetic of resveratrol. Three of the 3’,4’,5’-trimethoxybenzothiazole analogues, with 6-methoxy (40, IC50 51 nM), 6-amino (48, IC50 79 nM), and 6-acetamide (49, IC50 31 nM) substituents, were also potent inhibitors of NQO2. Computational modelling indicated the most active compounds exhibited good shape complementarity and polar interactions with the NQO2 active site. Through the inhibition of NQO2, benzothiazole-based compounds may have the potential to enhance the efficiency of cancer therapies or minimise oxidative damage in neuroinflammation.

Remote sensing image scene recognition using MobileNet

Abstract. Remote sensing image scene recognition plays a pivotal role in various applications, including environmental monitoring, disaster response, urban planning, precision agriculture, and aids in resource management and policy formulation. However, utilizing established convolutional neural networks(CNNs) models like AlexNet and VGG9 for this task can be computationally intensive and time-consuming due to their extensive parameter requirements. This dissertation introduces a MobileNet-based CNN optimized for remote sensing image scene recognition. This lightweight model significantly reduces computational load and model size without compromising accuracy, thereby enhancing efficiency. Empirical results on the NWPU45 dataset demonstrate MobileNet's superiority, achieving an accuracy of 91.16%, a Kappa coefficient of 90.96%, and an F1 score of 91.16% on the test set. Moreover, MobileNet's compact architecture, with merely 3.2531 million parameters and 587.9342 million FLOPs, underscores its efficiency and makes it a promising candidate for practical deployment in remote sensing applications. The findings suggest that MobileNet not only addresses the challenge of computational intensity but also opens new avenues for advancing scene recognition technology in the field of remote sensing.

Developing computational and experimental models of heat transfer through multi-layered textile structures

Object signature management is a critical and urgent task that helps conceal and restrict the detection of contemporary optoelectronic systems. The design of thermal camouflage textiles and material solutions constitute a significant scientific area, however publications in this area are restricted because of military competitiveness and technological secrecy. Research on thermal camouflage materials has drawn interest both domestically and internationally for a variety of purposes, especially in military applications. Multi-layered Textile Structures (MTS) is a material with several advantages, such as its simple structure, capacity to combine many different materials with many different qualities, and great applicability. The article includes a model of computation and simulation of heat transfer through multi-layer textiles, as well as tests to assess the heat shielding effect and heat radiation energy of some samples of multi-layer textiles made of domestic materials. The initial computational and experimental results constitute an important foundation for further research and application of multi-layered textile structures.

Computer-Modeling System of Agronomist’s Labor Functions

The goal of the paper is to develop the computer-modeling system of an agronomist’s labor functions as the most optimal solution for teaching preschoolers and primary schoolchildren about trends and technologies in farming, aimed at increasing the attractiveness of professions in the field of agriculture. Among the main objectives of the research is the study of the essence of computer modeling as a teaching method in the works of domestic scientists, as well as the construction of models and their implementation using high-level programming languages in order to obtain an information system for the labor functions of an agronomist.Materials and methods. In the course of the analysis, a study was carried out of scientific and technical literature on the use of computer-modeling systems in the educational field. The analysis of the market for computer-modeling systems in the agricultural sector of crop production was carried out. When visualizing and describing system models, UML modeling notation was used. A diagram of use cases for this notation made it possible to describe the functional requirements and interactions between the system and its user. A UML notation sequence diagram was used to model the interaction of the main menu, game scene, and game character over time. The class diagram made it possible to define the structure of the system and the relationships between its objects, as well as an overview of the attributes and operations of the identified classes. The designed system models were implemented in the C# programming language in the Visual Studio development environment.Results. The study revealed the need to introduce new forms, methods and means of teaching into the content of the modern educational process, the implementation of which, largely, is carried out using information technology. The most optimal solution to the issue of teaching children about trends and technologies in agriculture, which has become relevant in the light of the rapid development of agriculture and its digital transformation, was the introduction of computer- modeling systems. The analysis of literature on the research problem has shown that in the works of L. Zhuk, M. Larionova, N. Rozova, etc. great attention is paid to the use of computer modeling as a teaching tool. According to the author, the use of this technology in the educational process makes it possible to implement such teaching principles as the principle of integrative learning, the principle of a practice-oriented approach, the principle of differentiation of learning and the principle of dialogical learning. There are no domestic developments in the subject area under consideration on the information systems market. The author of the study designed and implemented, using the object-oriented programming language C#, the computer-modeling system of agronomist’s labor functions as a technology for teaching professional tasks of an agronomist at various stages of agrarian evolution. The proposed solution allows you to be acquainted with four significant agrarian revolutions that played a decisive role in the transformation of agriculture: the Neolithic revolution, the Renaissance agricultural revolution, the green revolution and the digital revolution in agriculture. Conclusion. It is important to note that the computer-modeling system of the labor functions of agronomist is of interest for preschool and primary education institutions. This development can also be used in the system of additional education for children. Using a computer game in the educational process will expand children’s knowledge about agriculture: it will familiarize them with different agricultural processes, such as planting, growing and harvesting crops, as well as with various types of crop cultivation technologies. This will contribute to the development of interest in the study of agriculture and, as a result, the growth of students’ motivation to connect their professional activities with agriculture.

Differential intrinsic firing properties in sustained and transient mouse alpha RGCs match their light response characteristics and persist during retinal degeneration.

Retinal ganglion cells (RGCs) are the neuronal connections between the eye and the brain conveying multiple features of the outside world through parallel pathways. While there is a large body of literature how these pathways arise in the retinal network, the process of converting presynaptic inputs into RGC spiking output is little understood. In this study, we show substantial differences in the spike generator across three types of alpha RGCs in female and male mice, the αON sustained, αOFF sustained and αOFF transient RGC. The differences in their intrinsic spiking responses match the differences of the light responses across RGC types. While sustained RGC types have spike generators that are able to generate sustained trains of action potentials at high rates, the transient RGC type fired shortest action potentials enabling it to fire high-frequency transient bursts. The observed differences were also present in late-stage photoreceptor-degenerated retina demonstrating long-term functional stability of RGC responses even when presynaptic circuitry is deteriorated for long periods of time. Our results demonstrate that intrinsic cell properties support the presynaptic retinal computation and are, once established, independent of them.Significance Statement Spiking output from retinal ganglion cells (RGCs) has long been thought to be solely determined by synaptic inputs from the retinal network. We show that the cell-intrinsic spike generator varies across RGC populations and therefore that postsynaptic processing shapes retinal spiking output in three types of mouse alpha RGCs (αRGCs). While sustained αRGC types have spike generators that are able to generate sustained trains of action potentials at high rates, the transient αRGC type fired shortest action potentials enabling them to fire high-frequency transient bursts. Computational modeling suggests that intrinsic response differences are not driven by dendritic morphology but by somatodendritc biophysics. After photoreceptor degeneration, the observed variability is preserved indicating stable physiology across the three αRGC types.

The mechanistic interaction between mechanical dyssynchrony and filling pressure in cardiac resynchronization therapy candidates.

Both left ventricular (LV) mechanical dyssynchrony and filling pressure have been shown to be associated with outcome in heart failure patient treated with cardiac resynchronization therapy (CRT). To investigate the mechanistic link between mechanical dyssynchrony and filling pressure and to assess their combined prognostic value in CRT candidates. Left atrial pressure (LAP) estimation and quantification of mechanical dyssynchrony were retrospectively performed in 219 CRT patients using echocardiography. LAP was elevated (eLAP) in 49% of the population, normal (nLAP) in 40%, and indeterminate (iLAP) in 11%. CRT response was defined as %-decrease in LV end-systolic volume after 12±6 months CRT. Clinical endpoint was all-cause mortality during 4.8 years (interquartile range: 2.7-6.0 years). To investigate the mechanistic link between mechanical dyssynchrony and filling pressure, the CircAdapt computer model was used to simulate cardiac mechanics and hemodynamics in virtual hearts with LBBB and various causes of increased filling pressure. Patients with nLAP had more significant mechanical dyssynchrony than those with eLAP. The combined assessment of both parameters before CRT was significantly associated with reverse LV remodeling and post-CRT survival. Simulations revealed that mechanical dyssynchrony is attenuated by increased LV operational chamber stiffness, regardless of whether it is caused by passive or active factors, explaining the link between mechanical dyssynchrony and filling pressure. Our combined clinical-computational data demonstrate that in patients with LBBB, the presence of mechanical dyssynchrony indicates relatively normal LV compliance and low filling pressure, which may explain their strong association with positive outcomes after CRT.

COMPUTER SIMULATION OF ELECTRICALLY CONDUCTING PROPERTIES OF MATERIAL FOR PERSONAL PROTECTION EQUIPMENT

The article presents an analysis of production factors that have a harmful effect on the health of workers. It has been established that one of the leading factors is an increased electrostatic field that occurs when a static charge accumulates on the surface of materials. An increased level of the electrostatic field can lead to various negative consequences for workers’ health. For full antistatic protection at work, not only special tools and workplaces are needed, but also special footwear made of conductive materials with high surface resistance, as well as other personal protective equipment. A computer model for simulating the occurrence and development of an electrical breakdown in a protective material for personal protective equipment is described. The model is based on energy concepts of the occurrence and development of a discharge, taking into account the statistical heterogeneity of the material’s electrical conductivity. The process of breakdown development is considered as a special case of the percolation effect and a branching random process. The model makes it possible to find a relationship between the heterogeneity of the material and the threshold of its protective properties.

Model analysis and experiment study for effects of thermal viscous and fluid flow on ventilated acoustic metamaterials labyrinth

In many noise scenarios, ventilation is necessary. The practical realization of noise attenuation under the premise of ensuring ventilation is an urgent problem to be solved. In this paper, a ventilated acoustic metamaterial labyrinth (VAML) is proposed, and the corresponding analytical and numerical computational models are developed considering the thermal viscous effect (TVE). The loss in sound transmission of the VAML is quantitatively obtained and experimentally verified. The theoretical results are compared with the experimental results with an error of 0.6%. By comparing the transmission coefficient and the impedance at the entrance of the side branches, the mechanism of the TVE on the performance of VAML is analyzed, and it is clarified that the TVE is responsible for the sound absorption coefficient. The effects of structure parameters on the transmission coefficient of the VAML are analyzed individually. The results show that the resonant frequency of the system decreases as the length of channel 1 l1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$l_1$$\\end{document}, the length of channel 2 l2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$l_2$$\\end{document}, and the width of channel d increase. By adjusting the magnitude of these three parameters, the control of the resonant frequency can be realized. Meanwhile, as l1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$l_1$$\\end{document}, l2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$l_2$$\\end{document} and ventilation radius R decrease the valley of transmission coefficient decreases which means better noise reduction. Finally, the effect of flow velocity on the transmission coefficient is analyzed, revealing the mechanism of fluid action on macroscopic acoustic properties.

A normative framework dissociates need and motivation in hypothalamic neurons.

Physiological needs evoke motivational drives that produce natural behaviors for survival. In previous studies, the temporally intertwined dynamics of need and motivation have made it challenging to differentiate these two components. On the basis of classic homeostatic theories, we established a normative framework to derive computational models for need-encoding and motivation-encoding neurons. By combining the model-based predictions and naturalistic experimental paradigms, we demonstrated that agouti-related peptide (AgRP) and lateral hypothalamic leptin receptor (LHLepR) neuronal activities encode need and motivation, respectively. Our model further explains the difference in the dynamics of appetitive behaviors induced by optogenetic stimulation of AgRP or LHLepR neurons. Our study provides a normative modeling framework that explains how hypothalamic neurons separately encode need and motivation in the mammalian brain.

Study of CdTe detector response functions using different MCNPX computational modeling detailing

The spectra measured with cadmium telluride (CdTe) detectors show high spectral distortions that must be corrected by applying a mathematical algorithm along with the detector's response functions. Simplified computational modeling of the CdTe detector is generally used to obtain its response functions. In this work, the Monte Carlo code MCNPX was used to study the response functions of a CdTe detector using more complex detector modeling and compared it with those obtained by simplified modeling. Raw spectra were corrected using the response matrices obtained for the simplified and detailed modeling of the CdTe and compared with those obtained with reference-validated software.

Multifunctional Organometallic Compounds: An Interesting Luminescent NLO‐Active Alkynylplatinum (II) Complex

AbstractReaction of 4‐methylphenylacetylide with the known chlorido platinum(II) complex bearing the cyclometalated 1,3‐bis(pyridin‐2‐yl)‐4,6‐difluoro‐benzene ligand afforded a novel alkynyl platinum(II) complex, 1, that was fully characterized by elemental analysis, NMR and UV‐visible spectroscopies, by photoluminescence measurements, and by computational modelling. Its structure was determined by X‐ray diffraction studies on a single crystal whereas its second‐order nonlinear optical (NLO) properties were determined in solution by the Electric‐Field Induced Second Harmonic generation method. The novel multifunctional complex 1 is characterized by good luminescence properties, like the related chlorido Pt(II) complex, but by a much higher second‐order NLO response.

Articulation Work and Tinkering for Fairness in Machine Learning

The field of fair AI aims to counter biased algorithms through computational modelling. However, it faces increasing criticism for perpetuating the use of overly technical and reductionist methods. As a result, novel approaches appear in the field to address more socially-oriented and interdisciplinary (SOI) perspectives on fair AI. In this paper, we take this dynamic as the starting point to study the tension between computer science (CS) and SOI research. By drawing on STS and CSCW theory, we position fair AI research as a matter of 'organizational alignment': what makes research 'doable' is the successful alignment of three levels of work organization (the social world, the laboratory, and the experiment). Based on qualitative interviews with CS researchers, we analyze the tasks, resources, and actors required for doable research in the case of fair AI. We find that CS researchers engage with SOI research to some extent, but organizational conditions, articulation work, and ambiguities of the social world constrain the doability of SOI research for them. Based on our findings, we identify and discuss problems for aligning CS and SOI as fair AI continues to evolve.

RESPONSE SURFACE METHODOLOGY (RSM) AS A TOOL IN PHARMACEUTICAL FORMULATION DEVELOPMENT

Response surface methodology (RSM) serves as a valuable tool in pharmaceutical formulation development, facilitating the optimization of drug formulations by systematically exploring the effects of multiple variables on desired responses. This methodology involves the design of experiments to generate mathematical models that predict the relationship between formulation parameters and critical quality attributes. By utilizing statistical techniques such as factorial design, central composite design, and Box-Behnken design, RSM enables the identification of optimal formulation conditions while minimizing the number of experimental trials. Across iterative experimentation and model refinement, RSM assists in understanding the complex interactions between formulation components, process variables, and product characteristics. In this review, we discuss the application of RSM in pharmaceutical formulation studies, highlighting its efficacy in optimizing drug delivery systems, enhancing product stability, and ensuring quality control. In addition, we explore recent advancements in RSM-driven approaches, including its integration with computational modeling and artificial intelligence techniques for enhanced formulation design and process optimization. Overall, RSM offers a systematic and efficient approach for developing robust pharmaceutical formulations, thereby accelerating the drug development process and improving therapeutic outcomes.

Deformation prediction of overlying strata in multi-seam mining based on the influence function method-key stratum hybrid model

The extraction of coal seams from subterranean strata has the potential to induce displacement and deformation within the overlying strata. This leads to fractures in the strata and surface subsidence. The repetitive mining of coal seams, especially in scenarios involving multiple coal seams, can reactivate previously stabilized rock strata, causing them to subside and deform again. This exacerbates deformation and compromises the structural integrity of the strata. Consequently, there is an imperative need to thoroughly investigate the patterns of movement exhibited by overlying rock layers as a result of the recurrent extraction of coal seams. In recent years, significant progress in this field has been the effective utilization of the Influence Function Method-Key Stratum (IFM-KS) hybrid model. This model, distinguished by its amalgamation of mechanical and geometric methodologies, has proven to be efficacious in scrutinizing the movement dynamics of overlying strata in the context of single-layer mining operations. Based on that, this paper introduces a novel model for predicting rock layer movement and deformation in multi-seam mining. The calculation results derived from this model reveal the dynamics of rock layers' movement and deformation following secondary disturbances during repetitive mining. The accuracy and reliability of this newly proposed model in predicting rock movement during dual-layer coal mining are validated through both theoretical calculations and UDEC numerical simulations. The results demonstrate a high degree of consistency between the numerically simulated rock displacement and mathematical calculations and the rationality of the model. Based on the rock strata movement calculation results, the corresponding porosity distribution is also derived. Compared to single-layer coal mining, multi-seam mining could cause greater changes in porosity in the goaf area and extensive damage to rock strata. More fracture pathways between coal seams occur and a volume of air-leakage quantity is expected. This computational model provides invaluable insights for predicting rock strata deformation and porosity distribution in repetitive mining scenarios of a similar nature.

Influence of natural hyoid bone position and surgical repositioning on upper airway patency: A computational finite element modeling study.

A validated finite element model of the rabbit UA was advanced and used to simulate changes in BHP and SHR, alone and in combination. The hyoid was displaced in cranial, caudal, anterior, anterior-cranial and anterior-caudal directions from 1-4mm. Model outcomes included UA collapsibility, measured using closing pressure (Pclose), cross-sectional area (CSA) and soft tissue mechanics (displacement, stress and strain). Graded BHP increments increased Pclose for all directions, and up to 29-43% at 4mm (relative to the original BHP). Anterior-based SHR decreased Pclose (~-115% at 4mm) and increased ΔCSA (~+35% at 4mm). Cranial SHR decreased ΔPclose (-29%), minimally affecting CSA. Caudal SHR increased ΔPclose (+27%) and decreased ΔCSA (-7%). Anterior-cranial and anterior-caudal SHR produced the highest stresses and strains. SHR effects on UA outcomes were dependent on BHP, with more caudal BHPs leading to less effective surgeries. BHP (phenotype) and SHR both alter UA outcomes, with effects dependent on hyoid displacement direction and magnitude. BHP influences the effectiveness of SHR in reducing UA collapsibility. These findings provide further insights into the hyoid's role in UA patency and suggest that considering the hyoid's baseline position and surgical repositioning direction/increment may help improve hyoid surgeries for OSA treatment.

Beyond IC50-A computational dynamic model of drug resistance in enzyme inhibition treatment.

Resistance to therapy is a major clinical obstacle to treatment of cancer and communicable diseases. Drug selection in treatment of patients where the disease is showing resistance to therapy is often guided by IC50 or fold-IC50 values. In this work, through a model of the treatment of chronic myeloid leukaemia (CML), we contest using fold-IC50 values as a guide for treatment selection. CML is a blood cancer that is treated with Abl1 inhibitors, and is often seen as a model for targeted therapy and drug resistance. Resistance to the first-line treatment occurs in approximately one in four patients. The most common cause of resistance is mutations in the Abl1 enzyme. Different mutant Abl1 enzymes show resistance to different Abl1 inhibitors and the mechanisms that lead to resistance for various mutation and inhibitor combinations are not fully known, making the selection of Abl1 inhibitors for treatment a difficult task. We developed a model based on information of catalysis, inhibition and pharmacokinetics, and applied it to study the effect of three Abl1 inhibitors on mutants of the Abl1 enzyme. From this model, we show that the relative decrease of product formation rate (defined in this work as "inhibitory reduction prowess") is a better indicator of resistance than an examination of the size of the product formation rate or fold-IC50 values for the mutant. We also examine current ideas and practices that guide treatment choice and suggest a new parameter for selecting treatments that could increase the efficacy and thus have a positive impact on patient outcomes.

Evaluating the Correlation Between Stimulus Frequency Otoacoustic Emission Group Delays and Tuning Sharpness in a Cochlear Model.

A theoretical framework based on coherent reflection and filter theory predicts that the phase-gradient delays of stimulus frequency otoacoustic emissions (SFOAEs) are correlated with tuning sharpness in the mammalian cochlea. In this paper, we use a computational model of the cochlea to test this theory and to evaluate how SFOAE phase-gradient delays may be used to estimate the sharpness of cochlear tuning. This study is based on a physiologically motivated model which has been previously shown to predict key aspects of cochlear micromechanics. Cochlear roughness is introduced to model the reflection mechanism which underlies SFOAE generation. We then examine how varying the values of key model parameters or of the sound pressure level of the stimulus affects the relation between cochlear tuning and SFOAE delays. Finally, we quantify the ability of model simulations of SFOAE phase-gradient delays to provide reliable estimates of the tuning sharpness of the model. We find that variations of model parameters that cause significant broadening of basilar membrane (BM) tuning typically give rise to a sizeable reduction in SFOAE phase-gradient delays. However, some changes in model parameters may cause a significant broadening of BM tuning with only a moderate decrease in SFOAE delays. SFOAE delays can be used to estimate the tuning sharpness of the model with reasonable accuracy only in cases where broadening of cochlear tuning is associated with a significant reduction in SFOAE delays. The numerical results provide key insights about the correlations between cochlear tuning and SFOAE delays.