Model Analysis Research Articles

An unconstrained four pool model analysis of proton relaxation and magnetization transfer in ex vivo white matter.

Understanding proton relaxation in the brain's white matter remains an active field of magnetic resonance imaging research. Models of varying complexity have been proposed to link measurements to tissue composition/microstructure, in particular myelination. Although the presence of multiple aqueous and nonaqueous proton pools is well established experimentally, so-called "quantitative MRI" is usually based on simpler models due to the large number of model parameters. In this work, a comprehensive set of parameters characterizing a four-pool model is obtained. A piece of fixed porcine spinal-cord WM was investigated at 3T and temperatures between 21 and 35°C. Measurements included a wide range of preparations of the spin system in combination with long echo trains to achieve sensitivity to all model parameters. The results allow the extraction of all intrinsic relaxation and exchange rates as well as assigning them to specific dynamic processes involving tissue water. A critical assessment indicates that simpler models often lack specificity to myelin.

Induction Time of Wetting Films Between Air Bubbles and Hydrophobic Particles in the Presence of Dodecyl Amine Hydrochloride: First Principles Model Analysis and Experimental Validation

An attachment of a particle on a bubble is a very complex process due to the surface chemistry of bubbles and particles, and hence it is difficult to describe the bubble–particle attachment mechanism from first principles. This paper focuses on better understanding of the bubble–particle attachment mechanism by predicting induction time from first principles for the glass beads–dodecyl amine hydrochloride (DAH) system. The induction time for the bubble–particle attachment was determined using an optically based attachment timer. The zeta potentials of bubbles and glass particles were measured by the microelectrophoresis method. The contact angle between a bubble and a particle was obtained using atomic force microscopy. In these calculations, the overall disjoining pressure and the overall energy of bubble–particle interactions comprised a sum of the DLVO and non-DLVO contributions. The overall energy of interactions was used to determine the critical film thickness, while the overall disjoining pressure was employed to estimate the wetting film drainage time using the theoretical models. By comparing experimental data and theoretical models for drainage of wetting films, it was found that the attachment of glass particles to air bubbles in the presence of DAH is accelerated due to the mobility of the air–water interface (of the wetting films), which has incorrectly been assumed as rigid (fully immobile) in the classical Stefan–Reynolds theory.

MONet: cancer driver gene identification algorithm based on integrated analysis of multi-omics data and network models

Cancer progression is orchestrated by the accrual of mutations in driver genes, which endow malignant cells with a selective proliferative advantage. Identifying cancer driver genes is crucial for elucidating the molecular mechanisms of cancer, advancing targeted therapies, and uncovering novel biomarkers. Based on integrated analysis of Multi-Omics data and Network models, we present MONet, a novel cancer driver gene identification algorithm. Our method utilizes two graph neural network algorithms on protein-protein interaction (PPI) networks to extract feature vector representations for each gene. These feature vectors are subsequently concatenated and fed into a multi-layer perceptron model (MLP) to perform semi-supervised identification of cancer driver genes. For each mutated gene, MONet assigns the probability of being potential driver, with genes identified in at least two PPI networks selected as candidate driver genes. When applied to pan-cancer datasets, MONet demonstrated robustness across various PPI networks, outperforming baseline models in terms of both the area under the receiver operating characteristic curve and the area under the precision-recall curve. Notably, MONet identified 37 novel driver genes that were missed by other methods, including 29 genes such as APOBEC2, GDNF, and PRELP, which are corroborated by existing literature, underscoring their critical roles in cancer development and progression. Through the MONet framework, we successfully identified known and novel candidate cancer driver genes, providing biologically meaningful insights into cancer mechanisms.

A simple competition model can predict rainforest tree diversity, species abundance and ecosystem functions

Abstract The coexistence of tree species in tropical forests has remained challenging to explain, characterise and predict with simple theoretical models. To address this phenomenon researchers have focused on processes and factors omitted in simple competition models. Meantime, theoretical considerations of simple models have sought out conditions for stable coexistence of many species. Here we show that a simple competition model parameterised by repeated forest tree inventory data can estimate the stable coexistence of numerous tree species and predict their biomass abundance and productivity in equilibrium communities. We apply a simple Lotka–Volterra competition model to describe species aboveground biomass, and employ leaf biomass as a proxy for exploitative competition among species. In such systems a globally stable multispecies equilibrium arises when, for every species, susceptibility of biomass growth to conspecific (same species) leaf biomass exceeds that to heterospecific leaf biomass. We applied this approach to tree species in the Pasoh 50‐ha plot of Malaysian lowland mixed dipterocarp forest. We parameterised species aboveground biomass productivity by tree growth, by recruitment, and losses from tree mortality. Biomass gains minus losses yields the biomass growth of each species population. Using variation in leaf biomass among quadrat subplots, we estimated the susceptibility of productivity by tree growth to conspecific and heterospecific leaf biomass. Our model analyses with plot census data predicted the stable coexistence of 351 of the 487 tree species assessed. Susceptibility to conspecific versus heterospecific leaf biomass was greater across all species (median: 95 times). The implied effect of conspecific competition appears to reflect ontogeny, that is declining relative tree growth with tree size. The equilibrium biomasses for predicted persistent species were broadly similar to observations. Removal of species indicates that ecosystem biomass and productivity at equilibrium increases asymptotically with species richness. Synthesis. Our analyses with simple model provide a range of non‐trivial insights into tree species coexistence, community structure and ecosystem stability within a species‐rich rainforest. The insights available from such simple models provide references for a reassessment of the insights from more complex models and approaches.

Analysis of a Malaria Transmission Model with Vaccination Proportion and Vaccine-Induced Immunity

This study presents a mathematical model to describe the transmission dynamics of malaria in a highly endemic region, with a focus on vaccination and vaccine-induced immunity as primary control measures. By determining the basic reproduction number (R0), we evaluate the impact of these interventions on malaria-free and malaria-persistent equilibria. Our analysis shows that the malaria-free equilibrium is locally asymptotically stable when R0<1 and unstable otherwise. Numerical simulations demonstrate that increasing vaccination coverage and improving vaccine-induced immunity significantly reduce R0. A sensitivity analysis using partial rank correlation coefficients highlights the influence of key parameters, such as the mosquito-to-human transmission rate and mosquito birth and death rates, on malaria transmission. These findings underscore the potential of integrated strategies, combining vaccination with other interventions, to manage malaria effectively in highly endemic regions.

Analysis and applications of Nakagami constant-stress model using progressive type-II censored data

Abstract In the case of trustworthy products, accelerated life tests are crucial techniques used to gather information regarding the lifetime of the target population with a shorter time frame compared to routine investigations. The received data in higher stress levels than normal are then used to predict the reliability of the product under consideration in regular working circumstances. In this paper, the constant-stress accelerated life tests are employed when the data are obtained through a progressive Type-II censoring strategy from Nakagami populations. Besides estimating the model parameters, the reliability function under the usual use conditions is predicted using four estimation procedures. The maximum likelihood, least squares, weighted least squares and maximum product of spacing estimation approaches are utilized for estimation purposes. In addition, two interval estimation methods are considered utilizing the asymptotic features of the maximum likelihood and maximum product of spacing estimates. A simulation investigation is conducted to evaluate the efficiency of diverse point and interval estimations beneath various strategies involving sample sizes, effective number of failures, and removal designs. From a practical perspective, a pair of datasets are explored to confirm the effectiveness of the theoretical findings.

Non-isothermal mathematical model of blocking tecnogenic fractures

Nowadays, large oil fields have moved to the stage of declining production, to maintain reservoir pressure, it is necessary to apply flooding technologies. To maintain the previous rates of oil production, it is necessary to force selections by increasing the value of downhole pressure on the injection wells. However, the risks of exceeding the fracturing pressure are increasing, which can lead to the formation of technogenic fractures. An intensive increase in the fracture can lead to an increase in the risks of premature water reaching through it into the drainage zone of the producing wells, which will lead to an increase in the value of the water oil ratio. The analysis of current numerical mathematical models of colmatation of technogenic fracture has shown the status of determining the volume of leaks of the colmatation agent beyond the fracture, considering changes in the temperature field at the bottom of the injection well. This problem is relevant, since special research complexes have been conducted at several oil and gas fields to determine the growth of technogenic fractures that arose because of excess fracturing pressure and fell into the drainage zone of producing wells. A change in the temperature field of the reservoir will allow direct changes in the viscosity of the injected colmatation agent, as well as determine the amount of leakage of the agent beyond the limits of the technogenic fractures. The article describes the construction of a non-isothermal physico-mathematical model of injection of a suspension system (water-reagent) into the reservoir, considering changes in the temperature field of the reservoir, the volume of reagent leaks beyond the limits of the technogenic fracture, considered for the first time. The aim of the work is to establish the dependences of the leakage volume of the colmatation agent, the critical time of filling the fracture from changes in the temperature field at the bottom of the injection well. A nonisothermal reservoir simulation model has been constructed showing the stages of initiation of a technogenic fracture with its subsequent colmation. The distribution of the concentration of the colmatation reagent both in the fracture and outside it, depending on the change in the temperature field at the bottom of the well, is obtained. It is determined that the volume of reagent leaks decreases if changes in the temperature field at the bottom of the injection well are considered with identical well operation parameters and geological and physical characteristics of the formation.

GLOBAL EXPERIENCE OF ADVANCED PRACTICE NURSES IN PRIMARY HEALTHCARE: A LITERATURE REVIEW

Introduction. The literature review emphasizes the growing role of advanced practice nurses (APNs) in primary healthcare at the international level. Amid global changes in healthcare systems, these professionals are becoming pivotal in enhancing both access to healthcare services and the quality of care. Aim of the Study. To investigate the global experience of advanced practice nurses within the context of primary healthcare. Materials and Methods. A search of scientific publications was conducted using the PubMed, Scopus, Web of Science, and Google Scholar databases, employing the following keywords: «advanced practice nurses,» «primary health care,» and «registered nurse.» Study Results. The study results indicate that advanced practice nurses significantly improve the quality of care and patient satisfaction. An analysis of various international models demonstrates the successful integration of these professionals into a team-based approach to treatment, leading to a reduction in physician workload and better population health outcomes. Moreover, the presence of clear regulatory frameworks and educational programs has been noted to enhance the efficacy of nurse practice, making them an integral part of the healthcare system. Conclusion. The international experience of advanced practice nurses showcases their significant impact on the efficiency of primary healthcare delivery. Recommendations for adapting successful practices can serve as a foundation for optimizing healthcare systems in various countries, ensuring more sustainable and effective healthcare provision.

GEE analysis in joint mean-covariance model for high-dimensional longitudinal data with HPC

High-dimensional covariate longitudinal data is common in various fields. However, estimating a low-dimensional parameter of interest can be challenging due to the presence of high-dimensional nuisance parameters. Traditional methods using generalized estimating equations become ineffective for estimating mean parameters when the working covariance structure is misspecified. In this paper, we first construct generalized estimating equations for regression parameters in a joint mean-covariance model for fixed-dimensional longitudinal data, based on reparameterization of the correlation structure using angles or hyperspherical coordinates. We then utilize a decorrelated matrix to handle parameter estimation for high-dimensional longitudinal data. This model addresses both the parsimonious modelling of correlations without constraints and the challenge of high-dimensional nuisance parameters. The resulting estimators are shown to be consistent and asymptotically normal, with data simulations supporting the effectiveness of the proposed approach.

Structural Analysis of Multi-Core Processor and Reliability Evaluation Model

In the present paper, the models of structural analysis and evaluation of efficiency indicators (reliability, fault tolerance, viability, and flexibility) of a multi-core processor with variable structure, equipped with multi-functional cores, are considered. Using logical–probabilistic methods, the following has been developed: models for evaluating the reliability and fault tolerance of processor cores as multi-functional elements; logical–probabilistic models of the shortest paths, flexibility, and performance conditions for successful operation of multi-core processors based on multi-functional cores; and models for estimating the reliability, fault tolerance, and lifetime of multi-core processors considering all possible states of performance. The results of the structural analysis of two-core and four-core processors and the trends of increasing the efficiency indicators of multi-core processors are presented.

Pengembangan E-modul Berbasis Problem Based Learning untuk Memfasilitasi Higher Order Thinking Skills (HOTS) Siswa

The purpose of this study was to develop an e-module based on problem based learning to facilitate students' higher order thinking skills (HOTS) with the material taken being trigonometric comparisons. The research design used in this study was the ADDIE development model (analysis, design, development, implementation, evaluation). The subjects in this study were the development subjects and the product trial subjects. The development subjects were validators and the product trial subjects were students of class X Phase E1 of SMA Negeri 1 Belitang. The results of this study were: (1) the developed e-module obtained very valid criteria with media validity reaching 92% and material validity reaching 93%, (2) the e-module met practical criteria based on the results of student and teacher response questionnaires with practicality reaching 89.5%, (3) the effectiveness of the e-module was seen based on the results of the student posttest with an index percentage of 73.1% with effective criteria.

The association of lipid accumulation product with inflammatory parameters and mortality: evidence from a large population-based study

BackgroundObesity is closely associated with lipid metabolism, and the accumulation of lipids leads to low-level inflammation in the body, which can trigger cardiovascular disease. This study aimed to explore the association between a novel marker of lipid accumulation, the abdominal volume index (AVI), inflammatory parameters, and mortality.MethodsThis study enrolled 2,109 older adult senior citizens (aged over 60 years) with hypertension from the National Health and Nutrition Examination Survey. The primary endpoints included all-cause mortality and cardiovascular mortality, which were assessed by linking the data to the National Death Index records. Cox regression model and subgroup analysis were constructed to investigate the associations between AVI and both all-cause and cardiovascular mortality. Restricted cubic splines were employed to further explore the relationships among AVI, inflammatory parameters, and mortality. By considering inflammatory factors as mediators, we investigate the mediating effects of AVI on mortality.ResultsAfter a median follow-up of 69 months, there were 1,260 deaths, with 337 attributed to cardiovascular causes within the older adult population studied. In the multivariable-adjusted model, AVI was positively associated with both all-cause and cardiovascular mortality [Hazard Ratio (HR) = 1.09, 95% CI = 1.06–1.11 for all-cause mortality; HR = 1.07, 95% CI = 1.03–1.12 for cardiovascular mortality]. Kaplan-Meier survival plots indicated an overall median survival time of 144 months. Mediation analysis revealed that Systemic Inflammatory Response Index (SIRI), Monocyte-to-HDL ratio (MHR), and Neutrophil-to-Lymphocyte ratio (NLR) mediated 27.15%, 35.15%, and 16.55%, respectively, of the association between AVI and all-cause mortality.ConclusionAVI is positively associated with all-cause mortality in older adults with hypertension, and this association appears to be partially mediated by inflammatory parameters.

Evolutionary strategies in live-streaming e-commerce: A four-player game model analysis

Background: Live-streaming e-commerce has boomed during the COVID-19 pandemic, leveraging short video platforms to fulfill social and shopping needs. However, its development is hampered by issues like misleading advertising by hosts, weak consumer protection, and inadequate platform oversight. Objective: This study aims to address these challenges and propose solutions for a healthy live-streaming e-commerce ecosystem. Methods: A four-player game model is constructed, considering interactions between live-streaming hosts, consumers, platforms, and suppliers. MATLAB is employed to analyze the model and identify optimal strategies for each player. Results: The model demonstrates that government regulation is essential. It incentivizes positive behavior from platforms and hosts while balancing consumer protection with potential misuse of complaint systems. Conclusions: Without government regulation, the live-streaming e-commerce industry cannot develop sustainably. This research highlights the importance of a multifaceted approach, including reducing consumer protection costs and implementing proactive government regulations for both platforms and hosts.

Predicting Placement in Residential Treatment in a Drug Court Program

With a growing emphasis on alternatives to incarceration for high-risk/high-need individuals who use drugs or alcohol, there is an increased need for intensive treatment services in the community. The current study examines referrals to residential treatment in a drug court setting. Using a sample of 378 drug court participants, this study compares characteristics of drug court participants who received traditional drug court services and those who received residential services. Multivariable logistic regression model analyses indicate that drug of choice (i.e., heroin/opiate use), substance use severity (i.e., early onset of drug use at 15 years and below), and noncompliance (i.e., rearrests prior to referral) were significant predictors of referral to and placement in residential treatment, when controlling for demographic characteristics (i.e., age, race, gender). Research and policy implications are discussed.

Life Prediction of Penstock Based on Strength Simulation and Sediment Wear Test

A hydropower station, which has been in operation for over 50 years, has a penstock located in the plant’s open pipe section. Recently, concerns have been raised regarding the potential risks to the penstock’s safe operation due to wall thinning caused by abrasion. A series of stress tests, strength mathematical model analysis, and sediment erosion tests were performed on the penstock during turbine load rejection events. A stress and strain monitoring system for the steel pressure pipe was developed, enabling real-time monitoring and providing a warning function. The current wall thickness of the steel pressure pipe is about 28 mm. The results indicate that a pipe rupture is unlikely under any load rejection scenario. However, if the wall thickness is reduced to around 24 mm, the maximum equivalent stress of the pipe will approach the safety limit during load rejection. The sediment erosion test showed an erosion rate of 3.509 × 10–5 mm/h at an average sediment concentration of 0.63 kg/m3. Assuming no other factors, such as an increase in river sediment concentration, and based on the design specifications of the steel pressure pipe and the annual average sediment concentration of 0.63 kg/m3, it is projected that the open pipe section can be operated for about 19 years before the wall thickness reaches 24 mm. It is recommended that once the wall thickness reaches 24 mm due to erosion or other factors, the pipeline system undergoes maintenance or replacement. The findings provide significant guidance for the operation of similar power stations.

Effects of Radiation Dose of Photon and Electron Beam Energies and Angles in Radiation Therapy

This study explores the effects of varying radiation beam energy levels and angles on the doses administered to adjacent healthy tissues and tumors during cancer treatment. While electron beams are best suited for superficial tumors because of their shallow penetration depth, photon beams produced by linear accelerators are useful for deep-seated tumors. Radiation doses were measured at different angles with 6 MV and 15 MV photon beams at 0° and 60° and with 6 MeV, 12 MeV, and 15 MeV electron beams at 0° and 15°. The findings demonstrate that larger angles and higher energy produce higher doses at different positions in photon therapy. Energy levels in electron therapy have a greater effect on dose distribution than angles. Our linear regression model analysis found that energy level angles and dose measurements in photon therapy strongly correlate with high R2 scores (above 0.8). Substantial and inconsistent correlations were observed with electron therapy. Despite these variations, a positive correlation was seen between various dose measurements for both treatments. These results emphasize the significance of choosing the right angles and energy levels to maximize treatment efficacy and minimize harm to healthy tissues. The use of these treatment protocols in clinical settings is supported by comparing our results with international standards which guarantee safety and efficacy.

Model analysis of biases in the satellite-diagnosed aerosol effect on the cloud liquid water path

Abstract. The response in cloud water content to changes in cloud condensation nuclei remains one of the major uncertainties in determining how aerosols can perturb cloud properties. In this study, we used an ensemble of large eddy simulations of marine stratocumulus clouds to investigate the correlation between cloud liquid water path (LWP) and the amount of cloud condensation nuclei. We compare this correlation directly from the model to the correlation derived using equations which are used to retrieve liquid water path from satellite observations. Our comparison shows that spatial variability in cloud properties and instrumental noise in satellite retrievals of cloud optical depth and cloud effective radii results in bias in the satellite-derived liquid water path. In-depth investigation of high-resolution model data shows that in large part of a cloud, the assumption of adiabaticity does not hold, which results in a similar bias in the LWP–CDNC (cloud droplet number concentration) relationship as seen in satellite data. In addition, our analysis shows a significant positive bias of between 18 % and 40 % in satellite-derived cloud droplet number concentration. However, for the individual ensemble members, the correlation between the cloud condensation nuclei and the mean of the liquid water path was very similar between the methods. This suggests that if cloud cases are carefully chosen for similar meteorological conditions and it is ensured that cloud condensation nuclei concentrations are well-defined, changes in liquid water can be confidently determined using satellite data.

Kajian Persepsi Masyarakat Pada Pembangunan Pariwisata DSP (Destinasi Super Prioritas) Terhadap Tingkat Pendapatan Masyarakat Pada Objek Wisata Danau Toba

This research aims to determine the impact of the study of super priority destination tourism development on the level of community income at the Lake Toba tourist attraction. This research method is descriptive qualitative research, with the population of the community around Lake Toba (Samosir Regency) who are experiencing the impact of the development of super priority tourism destinations, using data collection techniques through answering questions (questionnaires) and literature study methods. The data analysis method uses Miles & Huberman's interactive model analysis, starting from data collection, data reduction, data presentation, to the process of drawing conclusions. The results of this research show that the existence of the Lake Toba super priority destination development program has had a good impact on the community. The community can experience an increase in income after this program exists on Lake Toba. And with this super priority destination program, the community is also given the opportunity to receive training as business actors in the tourism sector, and the community is actively involved as a provider of suggestions and input in planning and developing Lake Toba as a super priority destination.

Exact and Approximate Analysis of Structural Models with Linear Viscous or Viscoelastic Dampers and Singular Mass Matrices

This research is concerned with model reduction methods in analysis of structural models with viscous or viscoelastic damping and singular mass matrices. These types of models are commonly used in the preliminary design of building structures containing supplemental damping devices to define locations and parameters of the energy dissipaters. In this paper we develop an exact reduced-order technique for the modal analysis of models with singular mass matrices and viscous or viscoelastic supplemental dampers. Using static condensation of generalized coordinates without mass and no damper connection, and using a transformation using the eigenvectors of the damping matrix, an exact state-space formulation with non-singular mass matrix is developed. The above-mentioned alternative model-reduction strategies are revisited and the accuracy of these methods in the estimation of poles (natural frequencies and damping ratios) and frequency response functions is compared with the exact model. To compare the accuracy of the alternative models developed a simple benchmark structural model with singular mass matrix is used.

Analisis Senyapan pada Produksi Ujaran Ayah Mirna dalam Video "Jessica Divonis Membunuh Mirna. Ayah Mirna: Happy Ending I Win!"

This research was conducted to describe the silence that occurs in speakers' speech production. This research also aims to describe the factors that cause silence in speech made by speakers. This research method uses qualitative research methods using primary data in the form of the recitation of Mirna's father in the video entitled Jessica Convicted of Killing Mirna. Mirna's father: "Happy ending, I win!" Data analysis used in this research uses Miles and Huberman (2014) model analysis, namely collecting all notes in the field, then analyzing and classifying the types of silence uttered by Mirna's father in the video, then presenting them to in the pattern that is formed, to produce conclusions and answer the problem being researched. The results of this research found 50 analysis data that had two types of silence, namely silent silence and filled silence. There are three positions of silence, namely grammatical pauses, between constituents, and before the main word in a constituent. Apart from that, three factors were found to cause silence, namely because the speaker forgot the necessary words, the speaker had already started speaking, but was not ready for the entire sentence, the speaker was very careful in choosing words so as not to cause a negative effect.