Systematic Review of Differential Reinforcement in Skill Acquisition.

The purpose of this article was to review and summarize the literature investigating the impact of differential reinforcement on skill acquisition. Researchers synthesized data from 10 articles across the following categories: (1) participant characteristics; (2) setting; (3) reinforcement procedures; (4) within-subject replication; (5) results; and (6) secondary measures (e.g., social validity). Results indicated that most of the participants were male, had a diagnosis of autism, and communicated vocally. The differential reinforcement condition in which reinforcement favored independent responses (e.g., edible for independent; praise for prompted responses) was the most frequently employed differential reinforcement condition and it resulted in the acquisition of more responses or faster acquisition for most participants. In addition, when differing reinforcement procedures manipulating different parameters of reinforcements were compared, better outcomes were attained when the schedule of the reinforcer was manipulated within the differential reinforcement procedure relative to when quality or magnitude were manipulated. Limitations of the previous research, recommendations for future research, and implications for clinical practice are discussed.

Vibration Controlled Transient Elastography Based Parameters Predicts Clinical Outcomes in Liver Transplant Recipients.

BACKGROUND & AIMS: Vibration-controlled transient elastography (VCTE) is used in clinical practice to risk stratify liver transplant (LT) recipients, however, there is currently little data demonstrating the relationship between VCTE and clinical outcomes. METHODS: 362 adult LT recipients with successful VCTE examination between 2015 and 2022 were included. Presence of advanced fibrosis was defined as liver stiffness measurement (LSM) ≥10.5kPa and hepatic steatosis as controlled attenuation parameter (CAP)≥ 270 dB/m. The outcomes of interest included all-cause mortality, myocardial infarction (MI), and graft cirrhosis using cumulative incidence analysis that accounted for the competing risks of these outcomes. RESULTS: The LSM was elevated in 64 (18%) and CAP in 163 (45%) of LT recipients. The baseline LSM values were similar in patients with elevated vs. normal CAP values. After a median follow up of 65 (IQR 20, 140) months from LT to baseline VCTE, 66 (18%) of patients died, 12 (3%) developed graft cirrhosis, and 18 (5%) experienced an MI. Baseline high LSM was independently associated with all-cause mortality (HR 1.97, 95% CI 1.11, 3.50, p=0.02) and new onset cirrhosis (HR 6.74, 95% CI 2.08, 21.79, p<0.01). A higher CAP value was significantly and independently associated with increased risk of experiencing a MI over study follow up with HR 4.14 [95% CI 1.29, 13.27, p=0.017]. CONCLUSIONS: The VCTE based parameters are associated with clinical outcomes and offer the potential to be incorporated into clinical risk stratification strategies to improve outcomes among LT recipients.

Efficient Cardiovascular Parameters Estimation for Fluid-Structure Simulations Using Gappy Proper Orthogonal Decomposition.

As full-scale detailed hemodynamic simulations of the entire vasculature are not feasible, numerical analysis should be focused on specific regions of the cardiovascular system, which requires the identification of lumped parameters to represent the patient behavior outside the simulated computational domain. We present a novel technique for estimating cardiovascular model parameters using gappy Proper Orthogonal Decomposition (g-POD). A POD basis is constructed with FSI simulations for different values of the lumped model parameters, and a linear operator is applied to retain information that can be compared to the available patient measurements. Then, the POD coefficients of the reconstructed solution are computed either by projecting patient measurements or by solving a minimization problem with constraints. The POD reconstruction is then used to estimate the model parameters. In the first test case, the parameter values of a 3-element Windkessel model are approximated using artificial patient measurements, obtaining a relative error of less than 4.2%. In the second case, 4 sets of 3-element Windkessel are approximated in a patient's aorta geometry, resulting in an error of less than 8% for the flow and less than 5% for the pressure. The method shows accurate results even with noisy patient data. It automatically calculates the delay between measurements and simulations and has flexibility in the types of patient measurements that can handle (at specific points, spatial or time averaged). The method is easy to implement and can be used in simulations performed in general-purpose FSI software.

Modelling anaerobic sulfide removal by sulfide shuttling bacteria.

Sulfide oxidizing bacteria are used in industrial biodesulfurization processes to convert sulfide to sulfur. These bacteria can spatially separate sulfide removal from terminal electron transfer, thereby acting as sulfide shuttles. The mechanisms underlying sulfide shuttling are not yet clear. In this work, newly obtained sulfide removal data were used to develop a new model for anaerobic sulfide removal and this model was shown to be an improvement over two previously published models. The new model describes a fast chemical step and a consecutive slow enzymatic step. The improved model includes the effect of pH, with higher total sulfide removal at increasing pH, as well as partial sulfide removal at higher sulfide concentrations. The two-stage model is supported by recent developments in anaerobic sulfide removal research and contributes to a better understanding of the underlying mechanisms. The model is a step toward accurately modelling anaerobic sulfide removal in industrial systems.

Modeling multi-component separation in hydrophobic interaction chromatography with improved parameter-by-parameter estimation method.

Mechanistic models are powerful tools for chromatographic process development and optimization. However, hydrophobic interaction chromatography (HIC) mechanistic models lack an effective and logical parameter estimation method, especially for multi-component system. In this study, a parameter-by-parameter method for multi-component system (called as mPbP-HIC) was derived based on the retention mechanism to estimate the six parameters of the Mollerup isotherm for HIC. The linear parameters (ks,i and keq,i) and nonlinear parameters (ni and qmax,i) of the isotherm can be estimated by the linear regression (LR) and the linear approximation (LA) steps, respectively. The remaining two parameters (kp,i and kkin,i) are obtained by the inverse method (IM). The proposed method was verified with a two-component model system. The results showed that the model could accurately predict the protein elution at a loading of 10 g/L. However, the elution curve fitting was unsatisfactory for high loadings (12 g/L and 14 g/L), which is mainly attributed to the demanding experimental conditions of the LA step and the potential large estimation error of the parameter qmax. Therefore, the inverse method was introduced to further calibrate the parameter qmax, thereby reducing the estimation error and improving the curve fitting. Moreover, the simplified linear approximation (SLA) was proposed by reasonable assumption, which provides the initial guess of qmax without solving any complex matrix and avoids the problem of matrix unsolvable. In the improved mPbP-HIC method, qmax would be initialized by the SLA and finally determined by the inverse method, and this strategy was named as SLA+IM. The experimental validation showed that the improved mPbP-HIC method has a better curve fitting, and the use of SLA+IM reduces the error accumulation effect. In process optimization, the parameters estimated by the improved mPbP-HIC method provided the model with excellent predictive ability and reasonable extrapolation. In conclusion, the SLA+IM strategy makes the improved mPbP-HIC method more rational and can be easily applied to the practical separation of protein mixture, which would accelerate the process development for HIC in downstream of biopharmaceuticals.

Linkages between stem vulnerability curves and tree demography and their implications for plant physiological modeling.

Vulnerability curves (VCs) have been measured extensively to describe the differences in plant vulnerability to cavitation. Although the roles of hydraulic conductivity (Ks,max) and hydraulic safety (P50, embolism resistance), both of which are parameters of VCs ('sigmoidal' type), in tree demography have been evaluated across different forests, the direct linkages between VCs and tree demography are rarely explored. In this study, we combined measured VCs and plot data of 16 tree species in Panamanian seasonal tropical forests to investigate the connections between VCs and tree mortality, recruitment and growth. We found that the mortality and recruitment rates of evergreen species were most significantly positively correlated with P50. However, the mortality and recruitment rates of deciduous species only exhibited significant positive correlations with parameter a, which describes the steepness of VCs and indicates the sensitivity of conductivity loss with water potential decline, but is often neglected. These differences among evergreen and deciduous species may contribute to the poor performance of existing quantitative relationships (such as the fitting relationships for all 16 species) in capturing tree mortality and recruitment dynamics. Additionally, evergreen species presented a significant positive relationship between relative growth rate (RGR) and Ks,max, while deciduous species did not display such relationship. The RGR of both evergreen and deciduous species also displayed no significant correlations with P50 and a. Further analysis demonstrated that species with steeper VCs tended to have high mortality and recruitment rates, while species with flatter VCs were usually those with low mortality and recruitment rates. Our results highlight the important role of parameter a in tree demography, especially for deciduous species. Given that VC is a key component of plant hydraulic models, integrating measured VC rather than optimizing its parameters will help improve the ability to simulate and predict forest response to water availability.

Effects of isotropic stress on the band structure elastic, optical, thermal, and x-ray diffraction properties of TiSnO3.

BACKGROUND: Cubic perovskite titanium stannous oxide (TiSnO3) is a promising material for various applications due to its functional properties. However, understanding how these properties change under external stress is crucial for its development and optimization. METHOD: This study employed density functional theory calculations to investigate the structural, electronic, optical, thermal, and mechanical properties of TiSnO3 under varying degrees of external static isotropic stress (0-120 GPa). RESULTS: The study reveals a significant decrease in the bandgap of TiSnO3 with increasing stress due to lattice modifications and the formation of delocalized electrons. Partial density of states analysis indicates that Sn and O states play a key role in shaping the electronic band structure. TiSnO3 exhibits increased light absorption with stress, accompanied by a blue shift in absorption peaks, whereas, both polarizability and refractive index decrease with increasing stress. Mechanically, all elastic moduli (bulk, shear, and Young's) show an increase under stress, signifying a stiffening response of the material under stress. Similarly, the Pugh ratio suggests a transition from ductile to brittle behaviour at elevated stress levels. Phonon dispersion calculations indicate the instability of the cubic phase at 0 K. However, a phonon gap emerges at 30 GPa and widens with increasing stress. X-ray diffraction further supports these findings by demonstrating a shift in diffraction peaks towards higher angles with increasing stress, consistent with the applied stress. CONCLUSION: In conclusion, this computational study offers a thorough understanding of how external stress influences the properties of TiSnO3, providing valuable insights for potential applications in various fields.

Genetic relationship of energy balance predicted from milk traits with fertility in Japanese Holsteins.

We predicted the energy balance of cows from milk traits and estimated the genetic correlations of predicted energy balance (PEB) with fertility traits for the first three lactations. Data included 9,646,606 test-day records of 576,555 Holstein cows in Japan from 2015 to 2019. Genetic parameters were estimated with a multiple-trait model in which the records among lactation stages and parities were treated as separate traits. Fertility traits were conception rate at first insemination (CR), number of inseminations (NI), and days open (DO). Heritability estimates of PEB were 0.28-0.35 (first lactation), 0.15-0.29 (second), and 0.09-0.23 (third). Estimated genetic correlations among lactation stages were 0.85-1.00 (first lactation), 0.73-1.00 (second), and 0.64-1.00 (third). Estimated genetic correlations among parities were 0.82-0.96 (between first and second), 0.97-0.99 (second and third), and 0.69-0.92 (first and third). Estimated genetic correlations of PEB in early lactation with fertility were 0.04 to 0.19 for CR, -0.03 to -0.19 for NI, and -0.01 to -0.24 for DO. Genetic improvement of PEB is possible. Lower PEB in early lactation was associated with worse fertility, suggesting that improving PEB in early lactation may improve reproductive performance.

JointTracker: Real-time inertial kinematic chain tracking with joint position estimation.

In-field human motion capture (HMC) is drawing increasing attention due to the multitude of application areas. Plenty of research is currently invested in camera-based (markerless) HMC, with the advantage of no infrastructure being required on the body, and additional context information being available from the surroundings. However, the inherent drawbacks of camera-based approaches are the limited field of view and occlusions. In contrast, inertial HMC (IHMC) does not suffer from occlusions, thus being a promising approach for capturing human motion outside the laboratory. However, one major challenge of such methods is the necessity of spatial registration. Typically, during a predefined calibration sequence, the orientation and location of each inertial sensor are registered with respect to the underlying skeleton model. This work contributes to calibration-free IHMC, as it proposes a recursive estimator for the simultaneous online estimation of all sensor poses and joint positions of a kinematic chain model like the human skeleton. The full derivation from an optimization objective is provided. The approach can directly be applied to a synchronized data stream from a body-mounted inertial sensor network. Successful evaluations are demonstrated on noisy simulated data from a three-link chain, real lower-body walking data from 25 young, healthy persons, and walking data captured from a humanoid robot. The estimated and derived quantities, global and relative sensor orientations, joint positions, and segment lengths can be exploited for human motion analysis and anthropometric measurements, as well as in the context of hybrid markerless visual-inertial HMC.

On the Association Between Demographic Structural Change and the Effectiveness of Nurse Staffing Policy for Inpatient Care: Evidence from Taiwan.

Purpose: This study investigates the influence of demographic changes on the effectiveness of hospital nurse staffing policy, measured by the cumulative response of inpatient care quality to adjustments in hospital nurse staffing levels in Taiwan. Methods: The research design utilized in this study aligns with the observational time-series methodology, and a total of 99 monthly time-series observations were collected from multiple databases administered by the Taiwan government over the period from January 2015 to March 2023. Specifically, the time-varying parameter vector autoregressive and autoregressive distributed lag models were employed to investigate the association between age distribution and nurse staffing policy effectiveness. Results: The time-varying impulse responses of the unplanned 14-day readmission rate after discharge to changes in nurse staffing levels indicate a positive association between patient-to-nurse ratios and unplanned 14-day readmission rates across various types of hospitals. Nevertheless, the effectiveness of hospitals' nurse staffing policy is observed to diminish with population aging, particularly evident in medical centers and regional hospitals. Conclusion: Policymakers should establish lower mandated patient-to-nurse ratios, grounded in practical nurse workforce planning, to address the needs of an aging society and enhance inpatient care quality through improved nurse staffing in hospitals.

Research on the characteristics of electro-hydraulic position servo system of RBF neural network under fuzzy rules.

A radial basis function neural network PID controller under fuzzy rules (FUZZY-RBF-PID) was designed for the electro-hydraulic position servo system under the influence of uncertain factors such as load mutation, and load stiffness change. Firstly, the mathematical model of the system is established, and the frequency domain and time domain analysis of the system are carried out. Secondly, based on the analysis results, a radial basis function (RBF) neural network PID controller is designed, and fuzzy rules are innovatively used to adjust the learning rate of PID parameters in the RBF neural network learning algorithm in real time. Thirdly, the simulation results show that under the action of the FUZZY-RBF-PID controller, the unit step response of the system has high steady-state accuracy, fast response speed, and under the condition of large load stiffness, the system can recover to the steady-state value faster after being disturbed. At the same time, when the input signal is the sinusoidal signal of 10 HZ, the system under the action of the FUZZY-RBF-PID controller has no obvious phase lag phenomenon, and the tracking error is minimal. The proposed method can effectively improve the comprehensive performance of the electro-hydraulic position servo system under the influence of uncertain factors.

Binding of single/double stranded ct-DNA with graphene oxide­silver nanocomposites in vitro: A multispectroscopic approach.

The fundamental binding of single-stranded (ssDNA) and double-stranded DNA (dsDNA) with graphene oxide-Ag nanocomposites (GO-AgNCPs) has been systematically investigated by multi spectroscopic methods, i.e. ultraviolet-visible (UV-vis) absorption, fluorescence spectroscopy, and circular dichroism (CD). The experimental and theoretical results demonstrate that both ssDNA and dsDNA can be adsorbed onto the GO-AgNCPs surface. All of the evidence indicated that there were relatively strong binding of ssDNA/dsDNA with GO-AgNCPs. The article compares the differences in binding between the two types of DNA and the nanomaterials using spectroscopic and thermodynamic data. UV-vis absorption spectroscopy experiments indicate that the characteristic absorbance intensity of both ss DNA and ds DNA increases, but the rate of change in absorbance is different. The fluorescence results revealed that ss/dsDNA could interact with the GO-AgNCPs surface, in spite of the different binding affinities. The Ka value of ssDNA binding with GO-AgNCPs is greater than that of dsDNA at each constant temperature, indicating that the affinity of dsDNA toward GO-AgNCPs is comparatively weak. Molecular docking studies have corroborated the mentioned experimental results. The calculated thermodynamic parameters showed that the binding process was thermodynamically spontaneous, van der Waals force and hydrogen bonding played predominant roles in the binding process. The mechanism of ss/ds DNA binding with GO-AgNCPs was also investigated, and the results indicated that GO-AgNCPs directly binds to the minor groove of ss/ds DNA by replacing minor groove binders.

Total ankle arthroplasty improves discrete and continuous stance phase gait symmetry.

BACKGROUND: Total ankle arthroplasty (TAA) is used to treat symptomatic end-stage ankle arthritis (AA). However, little is known about TAA's effects on gait symmetry. RESEARCH QUESTION: Determine if symmetry changes from before surgery through two years following TAA utilizing the normalized symmetry index (NSI) and statistical parametric mapping (SPM). METHODS: 141 patients with end-stage unilateral AA were evaluated from a previously collected prospective database, where each participant was tested within two weeks of surgery (Pre-Op), one year and two years following TAA. Walking speed, hip extension angle and moment, hip flexion angle, ankle plantarflexion angle and moment, ankle dorsiflexion angle, weight acceptance (GRF1), and propulsive (GRF2) vertical ground reaction forces were calculated for each limb. Gait symmetry was assessed using the NSI. A linear mixed effects model with a single response for each gait symmetry variable was used to examine the fixed effect of follow-up time (Pre-Op, Post-1 yr, Post-2 yr) and the random effect of participant with gait speed as a covariate in the model. A one-dimensional repeated measures analysis of variance (ANOVA) statistical parameter mapping (SPM) was completed to examine differences in the time-series NSI to determine regions of significant differences between follow-up times. RESULTS: Relative to Pre-Op values, GRF1, and GRF2 showed increased symmetry for discrete metrics and the time-series NSI across sessions. Hip extension moment had the largest symmetry improvement. Ankle plantarflexion angle was different between Pre-Op and Post-2 yr (p=0.010); and plantarflexion moment was different between Pre- Op and each post-operative session (p<0.001). The time-series Ankle Angle NSI was greater during the early stance phase in the Pre-Op session compared to Post-2 yr. SIGNIFICANCE: Symmetry across most of the stance phase improved following TAA indicating that TAA successfully improves gait symmetry and future work should determine if these improvements restore symmetry to levels equivalent with health age-match controls.

A mathematical model for wound healing in the reef-building coral Pocillopora damicornis.

Coral reefs, among the most diverse ecosystems on Earth, currently face major threats from pollution, unsustainable fishing practices , and perturbations in environmental parameters brought on by climate change. Corals also sustain regular wounding from other sea life and human activity. Recent reef restoration practices have even involved intentional wounding by systematically breaking coral fragments and relocating them to revitalize damaged reefs, a practice known as microfragmentation. Despite its importance, very little research has explored the inner mechanisms of wound healing in corals. Some reef-building corals have been observed to initiate an immunological response to wounding similar to that observed in mammalian species. Utilizing prior models of wound healing in mammalian species as the mathematical basis, we formulated a mechanistic model of wound healing, including observations of the immune response and tissue repair in scleractinian corals for the species Pocillopora damicornis. The model consists of four differential equations which track changes in remaining wound debris, number of cells involved in inflammation, number of cells involved in proliferation, and amount of wound closure through re-epithelialization. The model is fit to experimental wound size data from linear and circular shaped wounds on a live coral fragment. Mathematical methods, including numerical simulations and local sensitivity analysis, were used to analyze the resulting model. The parameter space was also explored to investigate drivers of other possible wound outcomes. This model serves as a first step in generating mathematical models for wound healing in corals that will not only aid in the understanding of wound healing as a whole, but also help optimize reef restoration practices and predict recovery behavior after major wounding events.

Effects of Melia azedarach extract on demographic and biochemical characteristics of the cabbage aphid, Brevicoryne brassicae.

The cabbage aphid, Brevicoryne brassicae L. (Aphididae: Hemiptera) a destructive aphid, is native to Europe and is now found in many other parts of the world. Currently, one of the main problems of Iranian cabbage growers is the significant damage caused by this pest. Also, due to the fresh eating of cabbage, it is necessary to use non-chemical methods to control the pests. Our bioassay tests showed that Melia azedarach L. (Meliaceae) fruit extract showed high toxicity to cabbage aphid. In this study, sublethal effects of M. azedarach extract was investigated on some demographic and biochemical properties of B. brassicae. The results showed that the sublethal concentrations (LC10 and LC20) and LC50 values were 0.68, 1.16, and 3.42 µg/ml, respectively. Compared to the control, sublethal concentrations of insecticide significantly decreased the gross reproductive rate (GRR), net reproductive rate (R0), intrinsic rate of increase (rm), finite rate of increase (λ), intrinsic rate of birth (b), intrinsic rate of death (d), weekly growth rate (rw), reproductive rate and adult longevity of the pest. Meanwhile, the mean generation time (T) and population doubling time (DT) of this aphid increased significantly. Additionally, sublethal doses of insecticide reduced the energy reserves of the pest such as carbohydrate, protein and lipid content compared to the controls. In addition to modify the pH, this extract also changed the distribution and concentration of sodium and potassium ions in haemolymph. Therefore, sublethal concentrations of M. Azedarach fruit extract can be used in the management program of B. brassicae.

Improving Proteomic Identification Using Narrow Isolation Windows with Zeno SWATH Data-Independent Acquisition.

Data-independent acquisition (DIA) techniques such as sequential window acquisition of all theoretical mass spectra (SWATH) acquisition have emerged as the preferred strategies for proteomic analyses. Our study optimized the SWATH-DIA method using a narrow isolation window placement approach, improving its proteomic performance. We optimized the acquisition parameter combinations of narrow isolation windows with different widths (1.9 and 2.9 Da) on a ZenoTOF 7600 (Sciex); the acquired data were analyzed using DIA-NN (version 1.8.1). Narrow SWATH (nSWATH) identified 5916 and 7719 protein groups on the digested peptides, corresponding to 400 ng of protein from mouse liver and HEK293T cells, respectively, improving identification by 7.52 and 4.99%, respectively, compared to conventional SWATH. The median coefficient of variation of the quantified values was less than 6%. We further analyzed 200 ng of benchmark samples comprising peptides from known ratios ofEscherichia coli, yeast, and human peptides using nSWATH. Consequently, it achieved accuracy and precision comparable to those of conventional SWATH, identifying an average of 95,456 precursors and 9342 protein groups across three benchmark samples, representing 12.6 and 9.63% improved identification compared to conventional SWATH. The nSWATH method improved identification at various loading amounts of benchmark samples, identifying 40.7% more protein groups at 25 ng. These results demonstrate the improved performance of nSWATH, contributing to the acquisition of deeper proteomic data from complex biological samples.

Measurable residual disease testing by next generation sequencing is more accurate compared with multiparameter flow cytometry in adults with B-cell acute lymphoblastic leukemia.

Results of measurable residual disease (MRD)-testing by next-generation sequencing (NGS) correlate with relapse risk in adults with B-cell acute lymphoblastic leukemia (ALL) receiving chemotherapy or an allotransplant from a human leukocyte antigen (HLA)-identical relative or HLA-matched unrelated donor. We studied cumulative incidence of relapse (CIR) and survival prediction accuracy using a NGS-based MRD-assay targeting immunoglobulin genes after 2 courses of consolidation chemotherapy cycles in 93 adults with B-cell ALL most receiving HLA-haplotype-matched related transplants. Prediction accuracy was compared with MRD-testing using multi-parameter flow cytometry (MPFC). NGS-based MRD-testing detected residual leukemia in 28 of 65 subjects with a negative MPFC-based MRD-test. In Cox regression multi-variable analyses subjects with a positive NGS-based MRD-test had a higher 3-year CIR (Hazard Ratio [HR] = 3.37; 95 % Confidence Interval [CI], 1.34-8.5; P = 0.01) and worse survival (HR = 4.87 [1.53-15.53]; P = 0.007). Some data suggest a lower CIR and better survival in NGS-MRD-test-positive transplant recipients but allocation to transplant was not random. Our data indicate MRD-testing by NGS is more accurate compared with testing by MPFC in adults with B-cell ALL in predicting CIR and survival. (Registered in the Beijing Municipal Health Bureau Registration N 2007-1007 and in the Chinese Clinical Trial Registry [ChiCTR-OCH-10000940 and ChiCTROPC-14005546]).

Adaptation of the Foster-Greer-Thorbecke poverty measures for the measurement of catastrophic health expenditures.

In this paper we provide an adaptation of the Foster-Greer-Thorbecke (FGT) family of poverty measures for the measurement and analysis of catastrophic health expenditure (CHE). The adaptation entails introducing the FGT-type family of CHE measures with a single CHE aversion parameter whose value can be increased to put greater emphasis on the health expenditure proportions that overshoot the prescribed threshold proportions for CHE characterization by the greatest margins. The subgroup decomposition property of the FGT-type family of CHE measures (i.e., the ability to isolate the contributions of the various mutually exclusive population subgroups to the overall FGT-type CHE measure) is discussed along with other normative properties. We also show how the estimation and subgroup decomposition of the FGT-type family of CHE measures can be conveniently accomplished using ordinary least squares regression. An illustrative example is also provided to show how the FGT approach can provide valuable insights into the distribution of CHE among the healthcare spending units that incur CHE.

A novel two-layer fuzzy neural network for solving inequality-constrained ℓ1-minimization problem with applications.

In this paper, we propose a novel two-layer fuzzy neural network model (TLFNN) for solving the inequality-constrained ℓ1-minimization problem. The stability and global convergence of the proposed TLFNN model are detailedly analyzed using the Lyapunov theory. Compared with the existing three-layer neural network model (TLNN) recently designed by Yang et al., the proposed TLFNN model possesses less storage, stronger robustness, faster convergence rate and higher convergence accuracy. These advantages are illustrated by some numerical experiments, where it is shown that the TLFNN model can achieve a convergence accuracy of 10-13 within 5s while the TLNN model can only acquire 10-6 in 105s when some random coefficient matrices are applied. Since the linear equality-constrained conditions can be equivalently transformed into double inequality-constrained ones, some simulation experiments for sparse signal reconstruction show that the proposed TLFNN model also has less convergence time and stronger robustness than the existing state-of-the-art neural network models for the equality-constrained ℓ1-minimization problem.

Study on the effect of aeration system on the mass transfer performance of supersaturated total dissolved gas.

ABSTRACTThe release of supersaturated total dissolved gas (STDG) from dams has been linked to the development of gas bubble disease, which can ultimately result in the death of fish. In order to minimize the impact of STDG on aquatic ecology, the effect of aeration on mass transfer at the air-liquid interface is taken into account. This paper selects four commonly used aerators to carry out indoor aeration tower experiments under different aeration conditions (aeration aperture, aeration water depth, and aeration volume), exploring aerators that can efficiently promote STDG release. The results indicated that the diaphragm aerator was found to have the greatest effect on STDG release, followed by corundum and spin mix aerator. In contrast, a pinhole aerator was found to have the least beneficial impact on STDG release. The increase in the release coefficient for the diaphragm aerator in comparison to the pinhole aerator is 32%. A prediction model for the aeration system was developed based on the mass transfer mechanism at the gas-liquid interface. The parameters in the model were determined using experimental data, which effectively improved the model's prediction accuracy. The findings of this study may serve as a reference point for the selection of the most suitable aerator in the actual engineering of STDG mitigation by aeration technology.