Wright's Hierarchical F-Statistics.

This perspective article offers a meditation on FST and other quantities developed by Sewall Wright to describe the population structure, defined as any departure from reproduction through random union of gametes. Concepts related to the F-statistics draw from studies of the partitioning of variation, identity coefficients, and diversity measures. Relationships between the first two approaches have recently been clarified and unified. This essay addresses the third pillar of the discussion: Nei's GST and related measures. A hierarchy of probabilities of identity-by-state provides a description of the relationships among levels of a structured population with respect to genetic diversity. Explicit expressions for the identity-by-state probabilities are determined for models of structured populations undergoing regular inbreeding and recurrent mutation. Levels of genetic diversity within and between subpopulations reflect mutation as well as migration. Accordingly, indices of the population structure are inherently locus-specific, contrary to the intentions of Wright. Some implications of this locus-specificity are explored.

Characterizing quantile-varying covariate effects under the accelerated failure time model.

An important task in survival analysis is choosing a structure for the relationship between covariates of interest and the time-to-event outcome. For example, the accelerated failure time (AFT) model structures each covariate effect as a constant multiplicative shift in the outcome distribution across all survival quantiles. Though parsimonious, this structure cannot detect or capture effects that differ across quantiles of the distribution, a limitation that is analogous to only permitting proportional hazards in the Cox model. To address this, we propose a general framework for quantile-varying multiplicative effects under the AFT model. Specifically, we embed flexible regression structures within the AFT model and derive a novel formula for interpretable effects on the quantile scale. A regression standardization scheme based on the g-formula is proposed to enable the estimation of both covariate-conditional and marginal effects for an exposure of interest. We implement a user-friendly Bayesian approach for the estimation and quantification of uncertainty while accounting for left truncation and complex censoring. We emphasize the intuitive interpretation of this model through numerical and graphical tools and illustrate its performance through simulation and application to a study of Alzheimer's disease and dementia.

"Giant" Colloidal Quantum Well Heterostructures of CdSe@CdS Core@Shell Nanoplatelets from 9.5 to 17.5 Monolayers in Thickness Enabling Ultra-High Gain Lasing.

Semiconductor colloidal quantum wells (CQWs) have emerged as a promising class of gain materials to be used in colloidal lasers. Although low gain thresholds are achieved, the required high gain coefficient levels are barely met for the applications of electrically-driven lasers which entails a very thin gain matrix to avoid charge injection limitations. Here, "giant" CdSe@CdS colloidal quantum well heterostructures of 9.5 to 17.5 monolayers (ML) in total with corresponding vertical thickness from 3.0 to 5.8 nm that enable record optical gain is shown. These CQWs achieve ultra-high material gain coefficients up to ≈140 000 cm-1 , obtained by systematic variable stripe length (VSL) measurements and independently validated by transient absorption (TA) measurements, owing to their high number of states. This exceptional gain capacity is an order of magnitude higher than the best levels reported for the colloidal quantum dots. From the dispersion of these quantum wells, low threshold amplified spontaneous emission in water providing an excellent platform for optofluidic lasers is demonstrated. Also, employing these giant quantum wells, whispering gallery mode (WGM) lasing with an ultra-low threshold of 8 µJ cm-2 is demonstrated. These findings indicate that giant CQWs offer an exceptional platform for colloidal thin-film lasers and in-solution lasing applications.

A Delicate Balance Between Spin-Wave Mediated Weak Localization and Electron-Phonon Scattering in the Design of Zero Temperature Coefficient of Resistivity.

Zero thermal coefficients of resistivity (ZTCR) materials exhibit minimal changes in resistance with temperature variations, making them essential in modern advanced technologies. The current ZTCR materials, which are based on the resistivity saturation effect of heavy metals, tend to function at elevated temperatures because the mean free path approaches the lower limit of the semiclassical Boltzmann theory when the temperature is sufficiently high. ZTCR materials working at low-temperatures are difficult to achieve due to electron-phonon scattering, which results in increased resistivity according to Bloch's theory. In this work, the ZTCR behavior at low-temperatures is realized in pre-microstrained Mn3NiN. The delicate balance between the resistivity contribution from electron-phonon scattering and spin-wave mediated weak localization is well revealed. A remarkable temperature coefficient of resistivity (TCR) value as low as 1.9 ppm K-1 (50 K ≤ T ≤ 200 K) is obtained, which is significantly superior to the threshold value of ZTCR behavior and the application standard of commercial ZTCR materials. The demonstration provides a unique paradigm in the design of ZTCR materials through the contraction effects of two opposite conductance mechanisms with positive and negative thermal coefficients of resistivity.

Effect of Surface Functional Groups on the Electronic Behavior and Optical Spectra of Mn2N Based MXenes.

The extensive applications of MXenes, a novel type of layered materials known for their favorable characteristics, have sparked significant interest. This research focuses on investigating the influence of surface functionalization on the behavior of Mn2NTx (Tx=O2, F2) MXenes monolayers using the "Density functional theory (DFT) based full-potential linearized augmented-plane-wave (FP-LAPW)" method. We elucidate the differences in the physical properties of Mn2NTx through the influence of F and O surface functional groups. We found that O-termination results in half-metallic behavior, whereas the F-termination evolves metallic characteristics within these MXene systems. Similarly, surface termination has effectively influenced their optical absorption efficiency. For instance, Mn2NO2 and Mn2NF2 effectively absorb UV light ~50.15×104 cm-1 and 37.71×104 cm-1, respectively. Additionally, they demonstrated prominent refraction and reflection characteristics, which are comprehensively discussed in the present work. Our predictions offer valuable perspectives into the optical and electronic characteristics of Mn2NTx-based MXenes, presenting the promising potential for implementing them in diverse optoelectronic devices.

Dose length product to effective dose coefficients in adults.

OBJECTIVES: The most accurate method for estimating patient effective dose (a principal metric for tracking patient radiation exposure) from computed tomography (CT) requires time-intensive Monte Carlo simulation. A simpler method multiplies a scalar coefficient by the widely available scanner-reported dose length product (DLP) to estimate effective dose. We developed new adult effective dose coefficients using actual patient scans and assessed their agreement with Monte Carlo simulation. METHODS: A multicenter sample of 216,906 adult CT scans was prospectively assembled in 2015-2020 from the University of California San Francisco International CT Dose Registry and the University of Florida library of computational phantoms. We generated effective dose coefficients for eight body regions, stratified by patient sex, diameter, and scanner manufacturer. We applied the new coefficients to DLPs to calculate effective doses and assess their correlations with Monte Carlo radiation transport-generated effective dose. RESULTS: Effective dose coefficients varied by body region and decreased in magnitude with increasing patient diameter. Coefficients were approximately twofold higher for torso scans in smallest compared with largest diameter categories. For example, abdomen and pelvis coefficients decreased from 0.027 to 0.013 mSv/mGy-cm between the 16-20 cm and 41+ cm categories. There were modest but consistent differences by sex and manufacturer. Diameter-based coefficients used to estimate effective dose produced strong correlations with the reference standard (Pearson correlations 0.77-0.86). The reported conversion coefficients differ from previous studies, particularly in neck CT. CONCLUSIONS: New effective dose coefficients derived from empirical clinical scans can be used to easily estimate effective dose using scanner-reported DLP. CLINICAL RELEVANCE STATEMENT: Scalar coefficients multiplied by DLP offer a simple approximation to effective dose, a key radiation dose metric. New effective dose coefficients from this study strongly correlate with gold standard, Monte Carlo-generated effective dose, and differ somewhat from previous studies. KEY POINTS: • Previous effective dose coefficients were derived from theoretical models rather than real patient data. • The new coefficients (from a large registry/phantom library) differ from previous studies. • The new coefficients offer reasonably reliable values for estimating effective dose.

Relative effects of climate factors and malaria control interventions on changes of parasitaemia risk in Burkina Faso from 2014 to 2017/2018.

BACKGROUND: In Burkina Faso, the prevalence of malaria has decreased over the past two decades, following the scale-up of control interventions. The successful development of malaria parasites depends on several climatic factors. Intervention gains may be reversed by changes in climatic factors. In this study, we investigated the role of malaria control interventions and climatic factors in influencing changes in the risk of malaria parasitaemia. METHODS: Bayesian logistic geostatistical models were fitted on Malaria Indicator Survey data from Burkina Faso obtained in 2014 and 2017/2018 to estimate the effects of malaria control interventions and climatic factors on the temporal changes of malaria parasite prevalence. Additionally, intervention effects were assessed at regional level, using a spatially varying coefficients model. RESULTS: Temperature showed a statistically important negative association with the geographic distribution of parasitaemia prevalence in both surveys; however, the effects of insecticide-treated nets (ITNs) use was negative and statistically important only in 2017/2018. Overall, the estimated number of infected children under the age of 5 years decreased from 704,202 in 2014 to 290,189 in 2017/2018. The use of ITNs was related to the decline at national and regional level, but coverage with artemisinin-based combination therapy only at regional level. CONCLUSION: Interventions contributed more than climatic factors to the observed change of parasitaemia risk in Burkina Faso during the period of 2014 to 2017/2018. Intervention effects varied in space. Longer time series analyses are warranted to determine the differential effect of a changing climate on malaria parasitaemia risk.

Characteristics analysis of solid waste generation and carbon emission of beer production in China.

As the largest beer producer and consumer in the world, China's endeavors to reduce solid waste generation (SWG) and carbon emissions (CEs) in the course of beer production assume paramount significance. This study aims to assess the SWG and CEs in beer production within China at both national and provincial levels, and further delves into the spatial distribution characteristics and evolving patterns across the country. Key findings of the study include:(1) Peak SWG and CEs were recorded in 2013, reaching 861.62 million tons and 2315.10 tCO2e, respectively, followed by a consistent decline. (2) Among the three types of solid waste, spent grain exhibited the highest generation rate, contributing to 94.38% of the total. (3) The emergence of China's beer industry dates back to the 1980s in the northeastern region, expanding to the southeastern and the Yangtze River Basin during the 1990s, ultimately extending nationwide. (4) The spatial distribution of beer production revealed significant regional disparities and notable industry concentration. Notably, many provinces witnessed reduced CEs from beer production starting in 2015, although the extent of reduction varied in different provinces. These findings serve as a scientific foundation for formulating emission reduction strategies in beer producing and offer insights for other food industries in China.

Hybrid Sneaky algorithm-based deep neural networks for Heart sound classification using phonocardiogram.

In the diagnosis of cardiac disorders Heart sound has a major role, and early detection is crucial to safeguard the patients. Computerized strategies of heart sound classification advocate intensive and more exact results in a quick and better manner. Using a hybrid optimization-controlled deep learning strategy this paper proposed an automatic heart sound classification module. The parameter tuning of the Deep Neural Network (DNN) classifier in a satisfactory manner is the importance of this research which depends on the Hybrid Sneaky optimization algorithm. The developed sneaky optimization algorithm inherits the traits of questing and societal search agents. Moreover, input data from the Phonocardiogram (PCG) database undergoes the process of feature extraction which extract the important features, like statistical, Heart Rate Variability (HRV), and to enhance the performance of this model, the features of Mel frequency Cepstral coefficients (MFCC) are assisted. The developed Sneaky optimization-based DNN classifier's performance is determined in respect of the metrics, namely precision, accuracy, specificity, and sensitivity, which are around 97%, 96.98%, 97%, and 96.9%, respectively.

Influence of neutron cross-section resonances on organ/tissue equivalent and effective dose coefficients for the ICRP voxel phantoms.

The materials which compose the ICRP Voxel phantoms used in the computation of conversion coefficients involve neutron interaction cross-sections that have resonances at specific energies. Depending on the energy bin structure used in the computations, these cross-section resonances may occur at energies that fall between energies at which dose coefficients are computed, thus their effects may not be completely accounted for in the reported coefficients. In the present study, a highly refined energy grid that closely follows the resonance structure in the phantom material cross-sections was identified and used to calculate dose coefficients. Both the equivalent organ/tissue doses for male and female voxel phantoms were computed as well as their summation to obtain the effective dose coefficients. The used refined energy grid tracks very closely the cross-sections in the vicinity of the resonances. The resulting refined energy grid coefficients are compared to coefficients for the coarser energy grid used in ICRP Publication 116. Additionally, reference spectra have been folded with both the fine and coarse sets of conversion coefficients. The resulting total effective doses for these reference spectra are used to assess the adequacy of the dose coefficients calculated on the original ICRP 116 energy grid. The dose coefficients were similarly computed for the local skin dose on the trunk of the body using the ICRU Report 95 phantom. The overall impact of the resonances on the organ/tissue equivalent dose, the effective dose, and the local skin dose are presented and discussed. In general, it was found that resonances can impact neutron dose coefficients, but in most cases the wide range of neutron energies encountered minimized this effect. The impact of resonances was further limited when computing effective dose due to organ/tissue summing and sex-averaging. For the neutron fields studied here, the impact was below 5%.

Inertially enhanced mass transport using 3D-printed porous flow-through electrodes with periodic lattice structures.

Electrochemical reactors utilizing flow-through electrodes (FTEs) provide an attractive path toward the efficient utilization of electrical energy, but their commercial viability and ultimate adoption hinge on attaining high currents to drive productivity and cost competitiveness. Conventional FTEs composed of random, porous media provide limited opportunity for architectural control and engineering of microscale transport. Alternatively, the design freedom engendered by additively manufacturing FTEs yields additional opportunities to further drive performance via flow engineering. Through experiment and validated continuum computation we analyze the mass transfer in three-dimensional (3D)-printed porous FTEs with periodic lattice structures and show that, in contrast to conventional electrodes, the mesoscopic length scales in 3D-printed electrodes lead to an increase in the mass correlation exponent as inertial flow effects dominate. The inertially enhanced mass transport yields mass transfer coefficients that exceed previously reported 3D-printed FTEs by 10 to 100 times, bringing 3D-printed FTE performance on par with conventional materials.

CSM-CROPGRO model to simulate safflower phenological development and yield.

Crop simulation models are valuable tools for decision making regarding evaluation and crop improvement under different field conditions. CSM-CROPGRO model integrates genotype, environment and crop management portfolios to simulate growth, development and yield. Modeling the safflower response to varied climate regimes are needed to strengthen its productivity dynamics. The main objective of the study was to evaluate the performance of DSSAT-CSM-CROPGRO-Safflower (Version 4.8.2) under diverse climatic conditions. The model was calibrated using the field observations for phenology, biomass and safflower grain yield (SGY) of the year 2016-17. Estimation of genetic coefficients was performed using GLUE (Genetic Likelihood Uncertainty Estimation) program. Simulated results for days to flowering, maturity, biomass at flowering and maturity and SGY were predicted reasonably with good statistical indices. Model evaluation results elucidate phenological events with low root mean square error (6.32 and 6.52) and high d-index (0.95 and 0.96) for days to flowering and maturity respectively for all genotypes and climate conditions. Fair prediction of safflower biomass at flowering and maturity showed low RMSE (887.3 and 564.3 kg ha-1) and high d-index (0.67 and 0.93) for the studied genotypes across the environments. RMSE for validated safflower grain yield (101.8 kg ha-1) and d-index (0.95) depicted that model outperformed for all genotypes and growing conditions. Longer appropriate growing conditions at NARC-Islamabad took optimal duration to assimilate photosynthetic products lead to higher grain yield. Safflower resilience to different environments showed that it can be used as an alternate crop for different agroecological regions. Furthermore, CROPGRO-Safflower model can be used as tool to further evaluate inclusion of safflower in the existing cropping systems of studied regions.

Supporting the assignment of NMR spectra with variable-temperature experiments.

Nuclear magnetic resonance (NMR) spectroscopy is one of the most powerful tools in analytical chemistry. An important step in the analysis of NMR data is the assignment of resonance frequencies to the corresponding atoms in the molecule being investigated. The traditional approach considers the spectrum's characteristic parameters: chemical shift values, internuclear couplings, and peak intensities. In this paper, we show how to support the process of assigning a series of spectra of similar organic compounds by using temperature coefficients, that is, the rates of change in chemical shift values associated with given changes in temperature.

An ecological approach for skill development and performance in soccer goalkeeper training: Empirical evidence and coaching applications.

Ecological approaches in sport consider that athletes adapt to properties of the task and the surrounding environment. Thus, task and environment are key constraints of performance. Yet, the influence of task and environmental constraints on athletes' performance needs empirical examination, especially in sport-specific contexts such as soccer goalkeeping. This study aimed to examine if and how task and environmental constraints influenced goalkeepers (GKs') performances. We monitored performance coefficients of two professional female GKs across 13 training tasks that varied based on 9 constraints, referring to both interactions among athletes and properties of the surrounding landscape. Results showed that constraints explain ~ 47% of the observed variability in GKs' performances. Numerical complexity (i.e., the potential interactions between athletes) showed a major influence on performance, which indicates that number of interactions among athletes may constrain GKs' perceived opportunities for action. Field dimensions and landscape representativity (including elements such as penalty area(s), target goal(s) and constraints for shooting) showed positive relationships with performance, supporting that training designs retaining closer proximity to the game may benefit GKs' performances. Overall, results supported that athlete-environment couplings could be understood as a multifactorial model and hence, a combination of task constraints are necessary for designing effective learning environments.

Wavefront Changes during a Sustained Reading Task in Presbyopic Eyes.

The objective of this study was to assess the effect of sustained reading on the temporal changes in the wavefront error in the presbyopic eye. The wavefront aberration of the eyes was measured using an IRX3 Shack-Hartmann aberrometer before and after (immediately, 5 min, and 10 min after) a reading task. Temporal changes in C20, C40, and C3-1 coefficient values of the eyes were plotted, showing a predominant number of V-shaped patterns (for C40 and C3-1) and inverse V-shaped patterns (for C20) among the study group, and the percentages (between 27 and 73%) were reported. The median of the total RMS of aberrations and the RMS of HOA (higher-order aberrations), which included comatic (3rd order) and spherical-like aberrations (4th and 6th order), increased immediately after finishing the near-vision reading task and then decreased. The median of RMS of comatic aberrations had a similar pattern of variations, while the median of RMS of spherical-like aberrations displayed an opposite pattern. Simulating the aberration changes due to lens decentration caused by relaxed zonules during 4 D accommodation in an eye model demonstrated that the expected range of changes for the vertical coma and spherical aberrations are in the order of 0.001 and 0.01 µm, respectively, which could justify why the observed changes were not statistically significant. The observed dynamic changes in HOA might be linked to the biomechanical characteristics and alterations in the displacement of the crystalline lens following prolonged near-vision tasks in presbyopic people. Although some predominant patterns under some conditions were shown, they exhibit considerable inter-subject and inter-ocular variability. This might be due to slight misalignments while fixating on the internal extended object in the aberrometer.

Conditional power and information fraction calculations at an interim analysis for random coefficient models.

Random coefficient (RC) models are commonly used in clinical trials to estimate the rate of change over time in longitudinal data. Trials utilizing a surrogate endpoint for accelerated approval with a confirmatory longitudinal endpoint to show clinical benefit is a strategy implemented across various therapeutic areas, including immunoglobulin A nephropathy. Understanding conditional power (CP) and information fraction calculations of RC models may help in the design of clinical trials as well as provide support for the confirmatory endpoint at the time of accelerated approval. This paper provides calculation methods, with practical examples, for determining CP at an interim analysis for a RC model with longitudinal data, such as estimated glomerular filtration rate (eGFR) assessments to measure rate of change in eGFR slope.

A practical guide to the appropriate analysis of eGFR data over time: A simulation study.

In several therapeutic areas, including chronic kidney disease (CKD) and immunoglobulin A nephropathy (IgAN), there is a growing interest in how best to analyze estimated glomerular filtration rate (eGFR) data over time in randomized clinical trials including how to best accommodate situations where the rate of change is not anticipated to be linear over time, often due to possible short term hemodynamic effects of certain classes of interventions. In such situations, concerns have been expressed by regulatory authorities that the common application of single slope analysis models may induce Type I error inflation. This article aims to offer practical advice and guidance, including SAS codes, on the statistical methodology to be employed in an eGFR rate of change analysis and offers guidance on trial design considerations for eGFR endpoints. A two-slope statistical model for eGFR data over time is proposed allowing for an analysis to simultaneously evaluate short term acute effects and long term chronic effects. A simulation study was conducted under a range of credible null and alternative hypotheses to evaluate the performance of the two-slope model in comparison to commonly used single slope random coefficients models as well as to non-slope based analyses of change from baseline or time normalized area under the curve (TAUC). Importantly, and contrary to preexisting concerns, these simulations demonstrate the absence of alpha inflation associated with the use of single or two-slope random coefficient models, even when such models are misspecified, and highlight that any concern regarding model misspecification relates to power and not to lack of Type I error control.

Serious Game with Electromyography Feedback and Physical Therapy in Young Children with Unilateral Spastic Cerebral Palsy and Equinus Gait: A Prospective Open-Label Study.

The clinical effects of a serious game with electromyography feedback (EMGs_SG) and physical therapy (PT) was investigated prospectively in children with unilateral spastic cerebral palsy (USCP). An additional aim was to better understand the influence of muscle shortening on function. Thirty children with USCP (age 7.6 ± 2.1 years) received four weeks of EMGs_SG sessions 2×/week including repetitive, active alternating training of dorsi- and plantar flexors in a seated position. In addition, each child received usual PT treatment ≤ 2×/week, involving plantar flexor stretching and command strengthening on dorsi- and plantar flexors. Five-Step Assessment parameters, including preferred gait velocity (normalized by height); plantar flexor extensibility (XV1); angle of catch (XV3); maximal active ankle dorsiflexion (XA); and derived coefficients of shortening, spasticity, and weakness for both soleus and gastrosoleus complex (GSC) were compared pre and post treatment (t-tests). Correlations were explored between the various coefficients and gait velocities at baseline. After four weeks of EMGs_SG + PT, there was an increase in normalized gait velocity from 0.72 ± 0.13 to 0.77 ± 0.13 m/s (p = 0.025, d = 0.43), a decrease in coefficients of shortening (soleus, 0.10 ± 0.07 pre vs. 0.07 ± 0.08 post, p = 0.004, d = 0.57; GSC 0.16 ± 0.08 vs. 0.13 ± 0.08, p = 0.003, d = 0.58), spasticity (soleus 0.14 ± 0.06 vs. 0.12 ± 0.07, p = 0.02, d = 0.46), and weakness (soleus 0.14 ± 0.07 vs. 0.11 ± 0.07, p = 0.005, d = 0.55). At baseline, normalized gait velocity correlated with the coefficient of GSC shortening (R = -0.43, p = 0.02). Four weeks of EMGs_SG and PT were associated with improved gait velocity and decreased plantar flexor shortening. A randomized controlled trial comparing EMGs_SG and conventional PT is needed.

A critical process variable-regulated, parameter-balancing auxostat, performed using disposed COVID-19 personal protective equipment-based substrate mixture, yields sustained and improved endoglucanase titers.

Fifty percent of the overall operational expenses of biorefineries are incurred during enzymatic-saccharification processes. Cellulases have a global-market value of $1621 USD. Dearth of conventional lignocelluloses have led to the exploration of their waste stream-based, unconventional sources. Native fungus-employing cellulase-production batches fail to yield sustained enzyme titers. It could be attributed to variations in the enzyme-production broth's quasi-dilatant behavior, its fluid and flow properties; heat and oxygen transfer regimes; kinetics of fungal growth; and nutrient utilization. The current investigation presents one of the first-time usages of a substrate mixture, majorly comprising disposed COVID-19 personal protective-equipment (PPE). To devise a sustainable and scalable cellulase-production process, various variable-regulated, continuous-culture auxostats were performed. The glucose concentration-maintaining auxostat recorded consistent endoglucanase titers throughout its feeding-cum-harvest cycles; furthermore, it enhanced oxygen transfer, heat transfer co-efficient, and mass transfer co-efficient by 91.5, 36, and 77%, respectively. Substrate-characterization revealed that an unintended, autoclave-based organsolv pretreatment caused unanticipated increases in endoglucanase titers. The cumulative lab-scale cellulase-production cost was found to be $16.3. The proposed approach is economical, and it offers a pollution-free waste management process, thereby generating carbon credits.

L version of the transformed Kedem-Katchalsky equations for membrane transport of electrolyte solutions and internal energy conversion.

BACKGROUND: One of the important formalisms of non-equilibrium thermodynamics is Peusner network thermodynamics. The description of the energy conversion in membrane processes, i.e., the conversion of the internal energy of the system into the dissipated energy and the free energy used for the work associated with the transport of solution components, allows us to describe the relationship between these energies and the thermodynamic forces acting in the membrane system. OBJECTIVES: The aim of this study was to develop a procedure to transform the Kedem-Katchalsky equations for the transport of binary electrolytic solutions across a membrane into the Kedem-Katchalsky-Peusner equations based on Peusner network thermodynamics. The conversion of electrochemical energy to free energy in the membrane system was also determined. MATERIAL AND METHODS: The nanobiocellulose biomembranes (Biofill) were the subject of the study with experimentally determined transport parameters for aqueous NaCl solutions. The research method is the Kedem-Katchalsky-Peusner formalism for binary electrolyte solutions with introduced Peusner coefficients. RESULTS: The coefficients of the L version of the membrane transport equations and the Peusner coupling coefficients were derived as functions of NaCl concentration in the membrane. Based on these coefficients, the fluxes of internal energy of the system, energy dissipated to the surroundings and free energy related to the transport of electrolyte across the membrane were calculated and presented as functions of the osmotic and electric forces on the membrane. CONCLUSIONS: The Peusner coefficients obtained from the transformations of the coefficients of the Kedem-Katchalsky formalism for the transport of electrolyte solutions through the Biofill membrane were used to calculate the coupling coefficients of the membrane processes and the dissipative energy flux. The dissipative energy flux takes the form of a quadratic form due to the thermodynamic forces on the membrane - second degree curves are obtained. Moreover, the dissipative energy flux as a function of thermodynamic forces allowed us to examine the energy conversion in transport processes in the membrane system.