Effective Parameters Research Articles

The value of common blood parameters for the differential diagnosis of respiratory tract infections in children

Mycoplasma pneumoniae and influenza A virus are common pathogens that cause respiratory tract infection in children. Both pathogens present with similar clinical symptoms, and their epidemic periods often overlap. Consequently, it is challenging for clinicians to make a rapid preliminary diagnosis. However, common blood tests is simple and efficient, Therefore, the purpose of this study is to preliminarily distinguish Mycoplasma pneumoniae and influenza A virus infection in children by analyzing the results of common blood tests, thereby guiding clinical diagnosis and treatment.The results showed that, compared with children in the influenza A virus-positive group, children in the Mycoplasma pneumoniae-positive group had higher white blood cell (WBC), red blood cell (RBC), haemoglobin (HGB), platelet (PLT) counts, lymphocyte (LYM) and eosinophil (EOS) counts and ratios, as well as higher concentrations of C-reactive protein (CRP) and serum amyloid A (SAA), while neutrophil (NEU) and monocyte (MONO) counts and ratios, Neutrophil to Lymphocyte ratio( NLR) were lower, in addition, LYM, EOS counts and ratios, and NLR were all more effective in differentiating between the two pathogen infections, A combined analysis of these indicators further improved the differentiation efficacy. Therefore, LYM and EOS counts and ratios, along with NLR, can serve as effective blood parameters for differentiating Mycoplasma pneumoniae infections from influenza A virus infections in children.

Shannon Entropy in Uncertainty Quantification for the Physical Effective Parameter Computations of Some Nanofluids

The main aim of this study is probabilistic computer simulation of the effective physical parameters of fluids containing nanoparticles. A deterministic model following the rule of mixtures and some semi-empirical formulas are employed to calculate effective density, heat conductivity, heat capacity, as well as viscosity for the given nanofluid. This models is randomized here using the Monte-Carlo simulation apparatus for estimation of the Shannon entropy of all these physical parameters, which is the crucial novelty of this study. The volume fraction of the nanoparticles is assumed for this purpose as the Gaussian uncertainty source with the given first two moments. The basic probabilistic characteristics of the nanofluids’ homogenized parameters have also been determined here for some validation of Shannon entropy variations in addition to the statistical disorder of the nanoparticle fraction. These research findings contribute to advancing nanofluidic and microfluidic research, offering robust tools for uncertainty analysis and enhancing the reliability of physical parameter predictions in applications requiring high numerical and/or experimental precision.

Tidal Reconstruction of Neutron Star Mergers from Their Late Inspiral

Abstract We investigate the measurement correlation between the effective spin and the effective tidal deformability in gravitational-wave signals from binary neutron star mergers. To efficiently measure the effective tidal deformability parameter, we exploit the fact that the tidal effects in a binary system are prominent when the components are closer, during the late inspiral. Thus, we indicate a computationally efficient strategy of extracting the tidal information compressed within the seconds before the merger. We report our observations for GW170817 and explore the suitability of our approach for the upcoming observation scenarios of the current and future ground-based observatories. Fast and accurate measurements of the tidal deformability parameters can be used to inform astronomers when prioritizing the electromagnetic follow-up efforts for such sources.

Realization of tunable non-Hermitian zero-index photonic crystals

In this work, we present a novel method for designing non-Hermitian zero-index photonic crystals using dielectric materials with tunable parameters. By adding non-Hermitian elements, either gain or loss, Dirac dispersion in the complex frequency domain can be achieved onto the original double-zero-index photonic crystals with accidental degeneracy. Our effective medium theory shows that the composite structure can maintain the near-zero value of the real parts of the effective permittivity ε and permeability μ while their imaginary parts can be designed. Multiple geometrical parameters in the added components can provide a large range of tunability of the imaginary parts of our proposal of non-Hermitian zero-index photonic crystals, which makes it a perfect platform for future non-Hermitian optics applications. With the adjustability of the imaginary part of the effective parameters, we achieve a wide tunability of the surface impedance of the non-Hermitian zero-index photonic crystals designed, and two applications are thus demonstrated. An arbitrary impedance matching is realized by both numerical simulations and microwave experiments so that the impedance mismatch between any two materials can be mitigated by our design. The emergence of a Zak phase will induce interface states between two non-Hermitian zero-index photonic crystals with different surface impedances, which also verifies our successful strategy to engineer material surface impedance. The research offers a general approach to constructing non-Hermitian zero-index materials, paving the road for material realization of non-Hermitian optics devices.

Characterize Firmness Changes of Nectarine and Peach Fruit Associated With Harvest Maturity and Storage Duration Using Parameters of Force-Displacement Curves.

Fruit firmness is a critical attribute for evaluating the quality of peaches and nectarines. The precise measurement of fruit firmness plays a key role in maturity assessment, determining harvest periods, and predicting shelf-life. Texture analyzers are increasingly employed for accurate fruit firmness measurement, offering advantages in reducing operator errors compared to the traditional Magness-Taylor test. However, the parameters defining firmness vary across the literatures. To optimize the parameter(s) for characterizing the firmness of peaches and nectarines, we evaluated 31 parameters derived from force-displacement curves using fruit with various maturity levels and storage durations. Our findings affirmed that the conventional Magness-Taylor measurement effectively delineated firmness changes associated with varying maturity levels, while its ability to capture firmness changes due to storage duration was constrained. On the contrary, parameters extracted from the steady phase (P2), which depict flesh properties after penetrating to a specified depth, exhibited strong performance across diverse maturity stages and storage durations. As effective firmness characterization parameters should differentiate various sample groups based on both maturity and storage duration criteria-pivotal factors influencing softening, the P2-derived parameters are thus deemed more appropriate for firmness characterization. Given the stability of the steady phase (P2) within the force-displacement curve and the high correlation among the P2-derived parameters, it is more recommended to use the end force value of P2, corresponding to the force value at 10 mm depth to represent the firmness of peaches and nectarines.

Dimensionless Machine Learning: Dimensional Analysis to Improve LSSVM and ANN models and predict bearing capacity of circular foundations

This research focuses on developing hybrid intelligence techniques to predict the bearing capacity of circular foundations using the most effective parameters. In this regard, a database involving 968 test circular foundations involving different rock properties, soil characteristics, and foundation radius has been prepared by laboratory tests for training and testing the new model presented in this study. For adequately considering various factors, the several parameters of depth (D) in m, density of soil (DS) in gr/cm3, internal angle of friction (IAF) in degree, cohesion of soil (CS) in kg/cm2, and foundation radius (FR) in m were considered as the input of the model and bearing capacity in kg/cm2 was considered as the target parameter. Three main strategies were addressed in this study. First, four well-known machine learning algorithms, Artificial Neural Network (ANN), Bagging Regressor (BR), Least Squares Support Vector Machine (LSSVM), and Gradient Boosting Regressor (GBR), were adopted to predict bearing capacity. Second, a novel and robust mathematical computation named dimensional analysis (DA) theorem was integrated with machine learning techniques to improve the accuracy and performance of the models by decreasing the number of inputs. Third, based on DA implementation, a rational mathematical formula using gene expression programming (GEP) was structured to anticipate bearing capacity. Furthermore, the sensitivity analysis process specified the impact of the five effective factors. The results of this study demonstrate the effectiveness of integrating DA with machine learning models to predict the BC of circular foundations. Among the developed models, the DA-LSSVM model showed superior performance, achieving an R² of 0.998 and 0.996 for training and testing, respectively, indicating high prediction accuracy. The results indicated that the IAF was the most sensitive factor with r = 0.709, while CS was the least sensitive with r = -0.087. A graphical user interface (GUI) app has been designed to apply the proposed models in this study conveniently. In the last step of this process, the GUI and the DA-based machine learning models were implemented by analyzing two examples. According to the findings, the GUI may be employed to make a reliable and speedy projection of the bearing capacity of circular foundations by considering a variety of input parameters.

A microcantilever-based viscometer for inline determination of liquid viscosity

Abstract Inline viscosity monitoring is crucial for process control in many industrial plants. In this study, a viscometer was designed and fabricated based on microfluidic technology, and the influence of effective parameters on its performance was investigated. The construction of the viscometer involved the fabrication of two microcantilevers using polydimethylsiloxane. One microcantilever was designed with a circular cross-section featuring a diameter of 300 μm, while the other was crafted with a triangular cross-section, characterized by a base of 270 μm and a height of 250 μm. Both microcantilevers measured 3 mm in height and were meticulously positioned within separate millichannels; each dimensioned at 2 × 5 × 30 mm3. The precision required for the millichannels and additional components was achieved using a mini-CNC milling machine. To evaluate the performance of the viscometer, a series of water-glycerol solutions comprising 50%, 60%, 65%, 70%, 75%, and 80% glycerol were injected into a microchannel. The flow rate was systematically varied between 3 and 18 ml min−1 in increments of 3 ml min−1, utilizing a syringe pump for precise control. The resultant displacement of the microcantilever, attributed to the fluid flow, was meticulously recorded using a digital camera. According to the experimental results, the displacement curves of circular and triangular microcantilevers are linear with viscosity; increasing the viscosity and flow rate of the fluid passing through the millichannel increases the microcantilever displacement rate. The response time of the microcantilever with a circular cross-section is 3 to 9 s, and that of the microcantilever with a triangular cross-section is 2 to 12 s. Also, the results of multiple tests in the same conditions showed that the system has a repeatability error of 4%. Finally, it can be concluded that the proposed device can be used to measure the viscosity of liquids within a specific range.

P-582. Long-term effectiveness and tolerability of Dolutegravir/Lamivudine in Korea: 3 year follow up

Abstract Background Many studies have revealed the real-world effectiveness and tolerability of Dolutegravir/Lamivudine (DTG/3TC). However, most studies were conducted in Western countries, and data from Asian countries are still lacking; in particular, the results from long-term use have not been reported in Asian countries. As DTG/3TC has been introduced and is becoming increasingly widespread in Asia, it is necessary to investigate the maintenance rate, reasons for discontinuation, long-term effectiveness, and metabolic parameter changes. Methods We performed a retrospective cohort study with adult people with HIV treated with DTG/3TC specific combination at a tertiary hospital in Korea. Among them, those who were followed up for more than 36 months were included. Both treatment-naïve and those who switched from other antiretroviral therapies to DTG/3TC were included. Baseline characteristics, DTG/3TC maintenance rates, effectiveness, and metabolic parameters changes over 36 months were investigated. Results From July 2020 to April 2024, 305 people with HIV started DTG/3TC. Among them, 134 people with HIV followed for more than 36 months were included (16 treatment-naïve and 118 switching). Most were male (N=126, 94%), and the median age was 45.5 years. There were no cases of switching from DTG/3TC to other ARTs during the 36-month follow-up after starting DTG/3TC. All of the treatment-naïve group maintained HIV RNA < 50 copies/mL from 6 to 36 months after starting DTG/3TC. The rate of HIV RNA < 50 copies/mL at the 36 months in the switching group was 99.2% (117/118). In the treatment-naïve group, CD4 cell count increased from a median of 494 cells/uL at baseline to 795 cells/uL at 36 months (p=0.005). During the 36-month follow-up, there were no significant changes in lipid profile and body weight in both treatment-naïve and switching groups except for an increase in HDL cholesterol in the switching group (from median 45 mg/dL at baseline to median 49 mg/dL at 36-month, p=0.001). Effectiveness of Dolutegravir/Lamivudine for the treatments-naive and switching groups Conclusion In our long-term follow-up study conducted in South Korea, DTG/3TC worked effectively in viral suppression and CD4 count maintenance, and no significant adverse effects were observed on lipid profiles and body weight gain in both treatment-naïve and switching groups. Tolerability of Dolutegravir/Lamivudine for the treatments-naive and switching groups Disclosures All Authors: No reported disclosures

P-852. Not High Enough? Treatment Outcome Comparing High Dose Daptomycin vs. Linezolid in VRE Bacteremia: Implications of Daptomycin PD Target

Abstract Background The best treatment for vancomycin-resistant enterococcus (VRE) bloodstream infection (BSI) remains controversial. In 2020, the CLSI revised the daptomycin breakpoints for E. faecium and recommended a high-dose daptomycin of 8-12 mg/kg/day. However, the effectiveness of high-dose daptomycin versus linezolid remains unanswered. The most effective PD parameter for daptomycin’s effectiveness is the free drug area under the curve to minimum inhibitory concentration ratio (fAUC/MIC). This study compares the clinical outcomes of VRE BSI between patients treated with linezolid and daptomycin within recommended dose. Additionally, we examined whether achieving the fAUC/MIC target influences the outcomes between these two groups.Figure 1.Flow diagram illustrating the selection of patients for the study. Methods An observational cohort study was conducted within National Taiwan University Hospital and its branches. From January 2010 to December 2021, patients treated with more than 8 mg/kg of daptomycin or linezolid for VRE BSI were included. The estimated fAUC was calculated, and the fAUC/MIC target was chosen based on the MIC determined using broth microdilution. The primary outcome was in-hospital mortality.Table 1.Demographics, clinical characteristics and univariable logistic regression analysis of mortality among patients with VRE BSI Results There were 1425 VRE BSI episodes, and 795 met inclusion criteria. The mean age was 67.7 years (SD 14.6), with 57.5% males. The mortality was 59.3%. Of 625 daptomycin-treated patients, 528 had estimated fAUC/MIC available. 114 had estimated fAUC/MIC above target. Mortality was 49.1% for daptomycin-treated patients with the PD above target, 66.2% for those below it, and 44.1% for linezolid-treated patients. Multivariable logistic regression showed Charlson comorbidity index (aOR 1.90, P=0.05), platelet count (aOR 0.96, P< 0.001), and Pitt bacteremia score (aOR 1.31, P< 0.001) to be associated with mortality. Daptomycin below PD target was associated with worse outcome than linezolid (aOR 2.52, P< 0.001), while daptomycin above PD target was not (aOR 1.00, P=0.99).Figure 2.Comparison of Kaplan–Meier survival curves between daptomycin and linezolid in patients with VRE BSI Conclusion Our findings suggest that daptomycin, even within the recommended dosage range, leads to poorer outcomes when it does not reach the estimated PD target compared to linezolid in treating VRE BSI. However, the outcomes are comparable with linezolid when PD target is reached.Table 2.Multivariate logistic regression analysis of the factors associated with in-hospital mortality (N=695) Disclosures All Authors: No reported disclosures

P-2047. Public Health Impact and Economic Value of an Additional Dose of Pfizer-BioNTech XBB.1.5-adapted COVID-19 Vaccine for Older Adults in the United States

Abstract Background To assess the public health impact and economic value of an additional dose of BNT162b2 XBB.1.5-adapted COVID-19 vaccine 6 months after initial dose for those aged ≥65 years, compared to a single dose in the United States.Table 1.Clinical and Economic Outcomes of 2-dose vs 1-dose Strategy in the Population Aged ≥65 Years.LY = life year; QALY = quality adjusted life year; ICER = incremental cost effectiveness ratio Methods A combined Markov and decision tree model was used to estimate the public health impact of those aged ≥65 years receiving an additional BNT162b2 XBB.1.5-adapted dose over for a one-year time horizon (Oct 2023-Sept 2024). Age-stratified (65-74, 75+) annual attack, hospitalization, and vaccine coverage rates were informed by public health national surveillance data. Other age-stratified clinical, cost, and vaccine effectiveness parameters were informed by publications. Parameter uncertainty was examined through scenario and sensitivity analyses. Conservatively, indirect effects (e.g. reduced transmission) and broad societal benefits were not considered. Results For individuals aged 65 years and older, the model demonstrated that compared to a single dose, an additional dose of the BNT162b2 XBB.1.5-adapted COVID-19 Vaccine resulted in 338,148 fewer symptomatic cases, 19,947 fewer hospitalizations, and 591 fewer deaths. Cost of additional vaccinations were offset by costs averted (e.g., Long COVID (∼$1.3B), inpatient (∼$384M), indirect (∼$280M), and outpatient (∼$252M) costs), leading to a total cost savings of ∼$270.5M. The two-dose strategy for older adults improved health outcomes and lowered costs resulting in a dominant ICER (Table 1). The additional dose was predicted to be a budget-efficient solution for payers. Results were most sensitive to variation in the symptomatic rate of infection and the hospitalization rate. Conclusion An additional dose of BNT162b2 XBB.1.5-adapted COVID-19 vaccination for adults aged 65 years and older in the US may generate notable reductions in symptomatic cases, hospitalizations, and deaths and result in cost savings. The results demonstrate that administering an additional COVID-19 vaccine dose to older adults in the US should be an important public health goal, supporting current ACIP and CDC recommendations. Disclosures Alon Yehoshua, PharmD, MS, Pfizer Inc: Employer|Pfizer Inc: Stocks/Bonds (Public Company) Benjamin Yarnoff, PhD, Pfizer Inc: Grant/Research Support Manuela Di Fusco, PhD, Pfizer Inc.: Employee|Pfizer Inc.: Stocks/Bonds (Public Company) Santiago M.C. Lopez, MD, Pfizer Inc.: Employee|Pfizer Inc.: Stocks/Bonds (Public Company) Elizabeth A. Thoburn, MPH, Pfizer Inc: Employer|Pfizer Inc: Stocks/Bonds (Public Company) Abby Rudolph, PhD, Pfizer Inc: Employer|Pfizer Inc: Stocks/Bonds (Public Company) Kinga Marczell, PhD, Pfizer Inc: Grant/Research Support

Genome-wide aggregated trans- effects analysis identifies genes encoding immune checkpoints as core genes for rheumatoid arthritis.

The sparse effector "omnigenic" hypothesis postulates that the polygenic effects of common SNPs on a typical complex trait are mediated by trans- effects that coalesce on expression of a relatively sparse set of core genes. The objective of this study was to identify core genes for rheumatoid arthritis by testing for association of rheumatoid arthritis with genome-wide aggregated trans- effects (GATE) scores for expression of each gene as transcript in whole blood or as circulating protein levels. GATE scores were calculated for 5400 cases and 453705 non-cases of primary rheumatoid arthritis in UK Biobank participants of European ancestry. Testing for association with GATE scores identified 16 putative core genes for rheumatoid arthritis outside the HLA region, of which six - TP53BP1, PDCD1, TNFRSF14, LAIR1, LILRA4, and IDO1 - were supported by Mendelian randomization analysis based on the marginal likelihood of the causal effect parameter. Five of these 16 genes were validated by a reported association of rheumatoid arthritis with SNPs within 200 kb of the transcription site, 8 by association of the measured protein level with rheumatoid arthritis in UK Biobank, 10 by experimental perturbation in mouse models of inflammatory arthritis, and two - CTLA4 and PDCD1 - by evidence that drugs targeting the gene cause or ameliorate inflammatory arthritis in humans. 14 of these 16 genes are in pathways affecting immunity or inflammation and six - CD5, CTLA4, TIGIT, LAIR1, TNFRSF14, PDCD1 - encode receptors that have been characterized as immune checkpoints exploited by cancer cells to escape the immune response. These results highlight the key role of immune checkpoints in rheumatoid arthritis and identify possible therapeutic targets.

Differential diagnosis of hypertrophic cardiomyopathy, fabry cardiomyopathy and transthyretin cardiac amyloidosis: insights from right ventricular strain imaging echocardiography

Abstract Introduction Timely differential diagnosis between hypertrophic cardiomyopathy (HCM), Fabry cardiomyopathy (FC) and wild-type transthyretin cardiac amyloidosis (ATTR-CA) is crucial for appropriate treatment and family screening. Right ventricle (RV) involvement is common in these diseases, making the systematic RV assessment essential. Two-dimensional speckle-tracking echocardiography (2D-STE) offers potential for precise RV myocardial mechanics evaluation, however its utility in distinguishing these conditions remains uncertain. Methods This study retrospectively compared matched controls (n=30) with three patient cohorts of nonobstructive HCM (n=30), ATTR-CA (n=30) and FC (n=30) referred to cardiomyopathy consultation between 2014 and 2021. Two blinded researchers independently performed morfofunctional echocardiographic evaluation of RV and 2D-STE analysis of RV myocardial strain. Receiver operating characteristic (ROC) analysis assessed the diagnostic performance of these parameters. Inter- and intra-observer reproducibility used Bland-Altman analysis and intraclass correlation coefficients. Results Male gender predominated in all groups (ATTR-CA 50%; FC 63%; HCM 63%). ATTR-CA patients were older when compared to FC and HCM (Median [IQR]: 84 [5] vs. 64.5 [18.75] vs. 57 [18.25] years, p<0.001) and had higher NT-proBNP (Median [IQR]: 5841 [11742] vs. 467 [1203] vs. 812 [857] pg/ml, p<0.001). ATTR-CA patients had the highest RV wall thickness (RVWT) in comparison to FC (9.0 vs. 7.4 mm, p=0.001) and HCM (9.0 vs. 5.5 mm, p<0.001). Patients with ATTR-CA had lower TAPSE (p=0.001), RV S’ (p=0.001), and RV-FAC values (p=0.003) compared to FC, with no significant differences compared to HCM. RV global longitudinal strain (RV-GLS) and RV free wall strain (RV-FWS) were significantly reduced in ATTR-CA (11.6% ± 4.7 and 15.5% ± 7.6) comparing to FC (19.3% ± 3.2 and 24.7% ± 3.9) and HCM (18.9% ± 3.1 and 25.6% ± 5.2) (p<0.001). RV systolic dysfunction according to RV strain analysis (RV-FWS <23%) led to substantial reclassification and increased prevalence in all groups (ATTR-CA: 37% to 87%; FA 0% to 20%; HCM: 3% to 27%). In ROC analysis, RV-GLS emerged as the most effective parameter for distinguishing ATTR-CA from FC (AUC 0.91; 95% CI 0.81-0.97, p<0.001) with an optimal cut-off of 15.0% yielding 83% sensitivity and 93% specificity. RVWT was the best discriminative parameter for distinguishing ATTR-CA from HCM (AUC 0.98; 95% CI 0.90-0.99, p<0.001; optimal cut-off of 6.5mm; 97% sensitivity, 90% specificity) and FC from HCM (AUC 0.91, 95% CI 0.81-0.97, p<0.001; optimal cut-off of 6.5mm; 83% sensitivity, 90% specificity). RVWT and strain parameters analyses were consistent Intra- and inter-observer with excellent agreement. Conclusion This study underscores the importance of RV thickness and RV-GLS for the differential diagnosis of HCM from phenocopies.

Analytical and numerical study of wire-coating process using viscoelastic fluid

This paper demonstrates the theoretical study of heat transfer over the wire coating process for the Carreau fluid. The process of coating wire or cables enhances the mechanical and electrical strength of the wire. The aim is to improve the understanding and control of the wire-coating process when using viscoelastic fluids, to optimize coating quality, uniformity, and efficiency, as well as to identify the most effective process parameters. First, we modeled the problem for cylindrical coordinates, and then the Flow governing equation are simplified using normalized variables and parameters. After making changes, we used the perturbation method to solve the final equation and obtain the analytical expression for the velocity distribution as well as the pertinent engineering quantities. Afterward, we used the Runge-Kutta fourth-order approach to solve it numerically. The velocity of molten polymer increases with increasing the values of We. The temperature profile increases with increasing the values of the pressure gradient parameter ( A), (δ) and Brinkman number ( Br). The effects of the [Formula: see text] and pressure gradient are discussed with the help of various graphs. Hybrid nanofluids are versatile and have a wide range of potential applications due to their enhanced thermal, mechanical, and fluidic properties.

Machine learning-driven intelligent water quality assessment for enhanced drinking safety and real-time consumer awareness

ABSTRACT As to the sphere of smart water management and managing water Internet of Things (IoT) systems, water condition safety for drinking is very important. The proposed methodology, known as the Smart Water Consumption Monitoring System (SWCMS), is based on the WaterNet dataset acquired from a standard data repository for training the selected machine learning (ML) models. For water quality parameters such as temperature, turbidity, pH, and some chemical concentrations, the system uses real-time sensors. At the testing phase, information received from the sensors is time-stamped, and with the utilization of applicable ML approaches, potential challenges; assessment of water quality is processed. This encompasses the employment of advanced instruments for the detection of water quality with concentration on pH and other chemical values through a detection accuracy rate of over 95% on any other signs of abnormalities. This processed information is further availed with the timestamps to the consumers' mobile phones through a user interface application for real-time awareness and timely response. With the aid of timely information about their drinking water, the SWCMS increases the water safety parameter by 90% and the overall consumer awareness by 92.5%, thereby creating an effective health parameter among the public.

Dependence of Nonlinear Elastic Parameters of Consolidated Granular Media on Temperature in the Ambient Range

Hysteretic nonlinear elasticity is often observed in consolidated granular media, including concrete, mortar, sandstones, or rocks. Nonlinearity is frequently quantified using Nonlinear Resonant Ultrasonic Spectroscopy (NRUS), which provides tools to define nonlinear parameters for both fast and slow dynamic effects, often observed when analyzing the propagation velocity dependence on strain in such materials. The dependence of these parameters on temperature was studied with the aim of using NRUS to quantify the induced thermal damage; thus, experiments were performed spanning a wide temperature range. However, since most of these materials are used in construction (concrete and sandstone, mostly), it is of interest to understand how sensitive the measured nonlinear parameters are to small environmental temperature fluctuations. In this paper, the dependence on temperature of elastic parameters is investigated, both linear (wave velocity and damping) and nonlinear (the slope and hysteresis of the curves describing the strain dependence of wave velocity and residual conditioning effect on wave velocity), separating the slow from the fast dynamic properties of nonlinearity. The observations reported here denote a different behavior for concrete and Berea sandstone.

Optimized Adaboost Support Vector Machine-Based Encryption for Securing IoT-Cloud Healthcare Data

The Internet of Things (IoT) connects various medical devices that enable remote monitoring, which can improve patient outcomes and help healthcare providers deliver precise diagnoses and better service to patients. However, IoT-based healthcare management systems face significant challenges in data security, such as maintaining a triad of confidentiality, integrity, and availability (CIA) and securing data transmission. This paper proposes a novel AdaBoost support vector machine (ASVM) based on the grey wolf optimization and international data encryption algorithm (ASVM-based GWO-IDEA) to secure medical data in an IoT-enabled healthcare system. The primary objective of this work was to prevent possible cyberattacks, unauthorized access, and tampering with the security of such healthcare systems. The proposed scheme encodes the healthcare data before transmitting them, protecting them from unauthorized access and other network vulnerabilities. The scheme was implemented in Python, and its efficiency was evaluated using a Kaggle-based public healthcare dataset. The performance of the model/scheme was evaluated with existing strategies in the context of effective security parameters, such as the confidentiality rate and throughput. When using the suggested methodology, the data transmission process was improved and achieved a high throughput of 97.86%, an improved resource utilization degree of 98.45%, and a high efficiency of 93.45% during data transmission.

Local time statistics and permeable barrier crossing: From Poisson to birth-death diffusion equations

Barrier crossing is a widespread phenomenon across natural and engineering systems. While abundant cross-disciplinary literature on the topic has emerged over the years, the stochastic underpinnings of the process have yet to be linked quantitatively to easily measurable observables. We bridge this gap by developing a microscopic representation of Brownian motion in the presence of permeable barriers that allows us to treat barriers with constant asymmetric permeabilities. Our approach relies upon reflected Brownian motion and on the crossing events being Poisson processes subordinated by the local time of the underlying motion at the barrier. Within this paradigm, we derive the exact expression for the distribution of the number of crossings and find an experimentally measurable statistical definition of permeability. We employ Feynman-Kac theory to derive and solve a set of governing birth-death diffusion equations and extend them to the case when barrier permeability is constant and asymmetric. As an application, we study a system of infinite, identical, and periodically placed asymmetric barriers for which we derive analytically effective transport parameters. This periodic arrangement induces an effective drift at long times whose magnitude depends on the difference in the permeability on either side of the barrier as well as on their absolute values. As the asymmetric permeabilities act akin to localized ratchet potentials that break spatial symmetry and detailed balance, the proposed arrangement of asymmetric barriers provides an example of a noise-induced drift without the need to time modulate any external force or create temporal correlations on the motion of a diffusing particle. By placing only one asymmetric barrier in a periodic domain, we also show the emergence of a nonequilibrium steady state. Published by the American Physical Society 2025

Altered Effective Connectivity Within a Thalamocortical Corollary Discharge Network in Individuals With Schizophrenia.

Sequential saccade planning requires corollary discharge (CD) signals that provide information about the planned landing location of an eye movement. These CD signals may be altered among individuals with schizophrenia (SZ), providing a potential mechanism to explain passivity and anomalous self-experiences broadly. In healthy controls (HC), a key oculomotor CD network transmits CD signals from the thalamus to the frontal eye fields (FEF) and the intraparietal sulcus (IPS) and also remaps signals from FEF to IPS. Here, we modeled fMRI data using dynamic causal modeling (DCM) to examine patient-control differences in effective connectivity evoked by a double-step (DS) task (30 SZ, 29 HC). The interrogated network was formed from a combination of (1) functionally identified FEF and IPS regions that robustly responded on DS trials and (2) anatomically identified thalamic regions involved in CD transmission. We also examined the relationship between clinical symptoms and effective connectivity parameters associated with task modulation of network pathways. Network connectivity was indeed modulated by the DS task, which involves CD transmission. More importantly, we found reduced effective connectivity from thalamus to IPS in SZ, which was further correlated with passivity symptom severity. These results reaffirm the importance of IPS and thalamocortical connections in oculomotor CD signaling and provide mechanistic insights into CD alterations and consequently agency disturbances in schizophrenia.

Fixed and mixed effects hypsometric equations for Pinus taeda L. stands with different spacing

The objective of this study was to analyze three strategies for fitting hypsometric models for Pinus taeda stands with different spacings. Data from a forest inventory containing 100 trees (5 stands x 4 plots x 5 trees) were used. Four hypsometric models were tested at the plot-level. The selected model was used in the individual adjustment, verifying the significance of the inclusion of the variables of sociological position, uniformity index and number of trees per hectare (strategy 2). In the model selected in strategy 2, the inclusion of a random effect parameter at the plot level was verified. The validation of the recommended model was carried out using the bootstrap method. All adjustments resulted in accurate estimates of total height, with RMSE and MAE values lower than 1.20 m and 0.98 m, respectively, considering an average total height of 20.1 m. In strategy 1, model (1) was selected. In strategy 2, the inclusion of sociological location and number of trees per hectare was significant and improved the estimates. In strategy 3, the inclusion of the random effect at the plot level further improved the model of strategy 2. The generalized mixed effects model was validated by the bootstrap method, and accurate estimates were presented in a short range. It is concluded that generalized mixed modeling is recommended and provides a unique fit for the five planting distances considered.

Crossing the blood-brain barrier: emerging therapeutic strategies for neurological disease.

The blood-brain barrier is a physiological barrier that can prevent both small and complex drugs from reaching the brain to exert a pharmacological effect. For treatment of neurological diseases, drug concentrations at the target site are a fundamental parameter for therapeutic effect; thus, the blood-brain barrier is a major obstacle to overcome. Novel strategies have been developed to circumvent the blood-brain barrier, including CSF delivery, intracranial delivery, ultrasound-based methods, membrane transporters, receptor-mediated transcytosis, and nanotherapeutics. These approaches each have their advantages and disadvantages. CSF delivery and intracranial delivery are direct but invasive techniques that have not yet shown efficacy in clinical trials, although development of novel delivery devices might improve these approaches. Ultrasound-based disruption has shown some efficacy in clinical trials, but it can require invasive procedures. Approaches using membrane transporters and receptor-mediated transcytosis are less invasive than are other techniques, but they can have off-target effects. Nanotherapeutics have shown promise, but these strategies are in early stages of development. Advancements in drug delivery across the blood-brain barrier will require appropriately designed and powered clinical studies, with a focus on the timing of treatment, demographic and genetic considerations, head-to-head comparison with other treatment strategies (rather than a placebo), and relevant primary and secondary outcome measures.