Real-life Model Research Articles

Recovery from severe cardio-respiratory failure: the trajectory of muscle mass, strength, function and health related quality of life

Abstract Background The impact of intensive care unit acquired weakness (ICUAW) is associated with reduced muscle mass, strength, function and health related quality of life (HRQoL). Patients suffering from severe cardio-respiratory failure are known to lose considerable muscle mass and strength in the first 7 days of admission to the intensive care unit (ICU). Furthermore, patients surviving critical illness have a considerable less HRQoL and physical function with long term outcomes such as inability to return to work being reported. However, more information regarding muscle loss and recovery is required when patients leave hospital. Currently there are no treatments for ICUAW as once the process is established management is supportive, such as physical therapy. Purpose We Sought to investigate the effects of severe cardio-respiratory failure, in patients receiving extra corporeal membrane oxygenation (ECMO), on ICUAW (including muscle mass, strength, function and HRQoL). Researching a real life model of ICUAW allows the observation of the loss of muscle mass and strength in the first stages of critical illness and severe cardio-respiratory failure. Methods Adults receiving ECMO for severe cardiorespiratory failure were included. Muscle mass was measured using ultrasound of the rectus femoris cross sectional area (RFcsa). Muscle strength was measured using hand held dynamometry for both hand held grip strength and isometric leg extension. HRQoL was measured using the EQ-5D-5L. Function was measured using the short physical performance battery (SPPB). Measurements were taken on day 0, day 7, ICU discharge, hospital discharge and at out-patient follow up. Results 17 patients were recruited with 10 patients completing follow up. Patients lost 24% muscle mass in the first 7 days of ICU admission and ECMO initiation, with muscle loss continuing up until ICU discharge. Contrary to the hypothesis only 50% of the patients were seen to recover muscle mass at follow up. Strength and function all considerably improved between ICU discharge and out patient follow up. The EQ5D crosswalk index supported this suggesting considerable functional improvement. Conclusion Patients in severe cardio-respiratory failure lose considerable muscle mass in the first 7 days of admission, with only 50% of these patients recovering the initial muscle loss at follow up. However, strength, function and HRQoL all improve following ICU discharge suggesting an element of functional recovery. Strength and function have shown to improve regardless of the status of the muscle mass. Therefore, given the advantages of the real-life model and novel findings, this could serve as a platform to assess muscle loss and recovery over a longer time frame continuing to build the understanding of the patients recovery trajectory from critical illness.Rectus Femoris Muscle MassHand-Held Grip Strength

Analysis of One-dimensional Double-potential Barrier Structures Resonant Tunnelling Based on Transmission Matrices

The comprehension of the tunnel effect, the passage of matter waves and particles across a high potential barrier, was the most astounding of all discoveries in quantum mechanics. Research on tunnelling in semiconductors and superconductors, as well as the development of scanning tunnelling microscopy, garnered five Nobel prizes in physics. In this study, the resonant tunnelling effect of electron tunnelling through a one-dimensional double-potential barrier was found and verified by solving the time-independent Schrödinger equation and calculating the transmittance rate of the electron tunnelling through the two potential barriers by using the transmission matrix technique performed by MATLAB. According to the analysis, the transmittance rate was one under certain specific conditions (under some specific incident energy values or some specific distance between two potential barriers), which was called as resonant tunnelling. However, in this study, square potential wells were analyzed, which can be considered merely as ideal models in real life, and therefore all results are idealized. For further investigations, researchers can use more realistic parameters to set up potential wells and analyze real-life problems.

Quality-adjusted life years and surgical waiting list: Systematic review of the literature.

The quality-adjusted life year (QALY) is a metric that is increasingly used today in the field of health economics to evaluate the value of different medical treatments and procedures. Surgical waiting lists (SWLs) represent a pressing problem in public healthcare. The QALY measure has rarely been used in the context of surgery. It would be interesting to know how many QALYs are lost by patients on SWLs. To investigate the relationship between QALYs and SWLs in a systematic review of the scientific literature. The study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement. An unlimited search was carried out in PubMed, updated on January 19, 2024. Data on the following variables were investigated and analyzed: Specialty, country of study, procedure under study, scale used to measure QALYs, the use of a theoretical or real-life model, objectives of the study and items measured, the economic value assigned to the QALY in the country in question, and the results and conclusions published. Forty-eight articles were selected for the study. No data were found regarding QALYs lost on SWLs. The specialties in which QALYs were studied the most in relation to the waiting list were urology and general surgery, with 15 articles each. The country in which the most studies of QALYs were carried out was the United States (n = 21), followed by the United Kingdom (n = 9) and Canada (n = 7). The most studied procedure was organ transplantation (n = 39), including 15 kidney, 14 liver, 5 heart, 4 lung, and 1 intestinal. Arthroplasty (n = 4), cataract surgery (n = 2), bariatric surgery (n = 1), mosaicplasty (n = 1), and septoplasty (n = 1) completed the surgical interventions included. Thirty-nine of the models used were theoretical (the most frequently applied being the Markov model, n = 34), and nine were real-life. The survey used to measure quality of life in 11 articles was the European Quality of Life-5 dimensions, but in 32 articles the survey was not specified. The willingness-to-pay per QALY gained ranged from $100000 in the United States to €20000 in Spain. The relationship between QALYs and SWLs has only rarely been studied in the literature. The rate of QALYs lost on SWLs has not been determined. Future research is warranted to address this issue.

A new over-dispersed count model based on Poisson-Geometric convolution

A new two-parameter discrete distribution, namely the PoiG distribution, is derived by the convolution of a Poisson variate and an independently distributed geometric random variable. This distribution generalizes both the Poisson and geometric distributions and can be used for modeling over-dispersed as well as equi-dispersed count data. A number of important statistical properties of the proposed count model, such as the probability generating function, the moment generating function, the moments, the survival function and the hazard rate function have been studied in detail. Monotonic properties such as the log concavity are also studied. Stochastic ordering for the proposed model is also investigated in detail. Method of moments and the maximum-likelihood estimators of the parameters of the proposed model are found to work well in simulation experiments as well as in the real-life data analysis. Asymptotic confidence intervals and the coverage probabilities of the parameters are also studied through extensive simulation experiments. Two real life modelling applications demonstrate that the proposed distribution may prove to be useful for the practitioners for modelling over-dispersed count data compared to its closest competitors.

Analysis of stress-strength reliability with m-step strength levels under type I censoring and Gompertz distribution

<p>Because of modern technology, product reliability has increased, making it more challenging to evaluate products in real-world settings and raising the cost of gathering sufficient data about a product's lifetime. Instead of using stress to accelerate failures, the most practical way to solve this problem is to use accelerated life tests, in which test units are subjected to varying degrees of stress. This paper deals with the analysis of stress-strength reliability when the strength variable has changed m levels at predetermined times. It is common for the observed failure time data of items to be partially unavailable in numerous reliability and life-testing studies. In statistical analyses where data is censored, lowering the time and expense involved is vital. Maximum likelihood estimation when the stress and strength variables follow the Gompertz distribution was introduced under type I censoring data. The bootstrap confidence intervals were deduced for stress-strength reliability under m levels of strength variable and applying the Gompertz distribution to model time. A simulation study was introduced to find the maximum likelihood estimates, bootstrapping, and credible intervals for stress-strength reliability. Real data was presented to show the application of the model in real life.</p>

THE MODEL OF PROVIDING CYBER SECURITY OF THE INTERNET OF THINGS

The Internet of Things is considered to be a new stage in the development of the Internet, where physical objects connected to the network exchange data, and each device can independently interact and establish connections with billions of other things. The Internet of Things allows people to perform various tasks remotely, which will make life much easier in the future. This article explores the specifics of the technology and the importance of developing contingency plans to recover from potential IoT cyberattacks. Special attention will be paid to the role of government entities in ensuring the security of IoT networks, including the development of regulations and cooperation with the private sector and academic institutions. The Internet of Things encompasses a variety of steps: computational, communication-based, temporal and data-based. How these functions as a single system utilizing commercially available components that can be purchased easily and at a low cost. As the number of IoT devices continues to increase, it is expected to have a total of 36 billion members and significant changes will occur. The IoT market is expanding rapidly, this will allow communication service providers, industries and companies to have a large potential for revenue. The article discusses existing approaches to this issue and their benefits and drawbacks. A general description of innovative cybersecurity strategies and approaches is presented, including a new combination of practical strategies and innovative solutions. Components of the model, including access control, data encryption, network monitoring, and intrusion detection, are detailed in depth. Particular attention is devoted to partnerships with IoT device manufacturers in order to successfully apply the proposed model in real life. The conclusion states that cyber security should be constantly improved and altered in response to the increasing dangers and the development of IoT technologies.

The elemental fingerprint as a potential tool for tracking the fate of real-life model nanoplastics generated from plastic consumer products in environmental systems.

Metals and metalloids are widely used in producing plastic materials as fillers and pigments, which can be used to track the environmental fate of real-life nanoplastics in environmental and biological systems. Therefore, this study investigated the metal and metalloids concentrations and fingerprint in real-life model nanoplastics generated from new plastic products (NPP) and from environmentally aged ocean plastic fragments (NPO) using single particle-inductively coupled plasma-mass spectrometry (SP-ICP-TOF-MS) and transmission electron microscopy coupled with energy dispersive X-ray spectroscopy (TEM-EDX). The new plastic products include polypropylene straws (PPS), polyethylene terephthalate bottles (PETEB), white low-density polyethylene bags (LDPEB), and polystyrene foam shipping material (PSF). All real-life model nanoplastics contained metal and metalloids, including Si, Al, Sr, Ti, Fe, Ba, Cu, Pb, Zn, Cd, and Cr, and were depleted in rare earth elements. Nanoplastics generated from the white LDPEB were rich in Ti-bearing particles, whereas those generated from PSF were rich in Cr, Ti, and Pb. The Ti/Fe in the LDPEB nanoplastics and the Cr/Fe in the PSF nanoplastics were higher than the corresponding ratios in natural soil nanoparticles (NNPs). The Si/Al ratio in the PSF nanoplastics was higher than in the NNPs, possibly due to silica-based fillers. The elemental ratio of Si/Al, Fe/Cr, and Fe/Ni in the nanoplastics derived from ocean plastic fragments was intermediate between the nanoplastics derived from real-life plastic products and NNPs, indicating a combined contribution from pigments and fillers used in plastics and from natural sources. This study provides a method to track real-life nanoplastics in controlled laboratory studies based on nanoplastic elemental fingerprints. It expands the realm of nanoplastics that can be followed based on their metallic signatures to all kinds of nanoplastics. Additionally, this study illustrates the importance of nanoplastics as a source of metals and metal-containing nanoparticles in the environment.

Experiencing loneliness by young people with different life variants

The article presents the results of studying the experience of loneliness by young people who choose different life variants. The purposes of the study are aimed at generalising ideas about this phenomenon, at popularisation and development of scientific ideas on individual life variants in modern society for their subsequent use in psychological counseling practice and psychotherapy. The work also implies an empirical analysis and identification of the occurrence features. The “Differential questionnaire of loneliness experience” by E.N. Osin and D.A. Leontev and the «Actual life variant» technique by A.G. Shisheva were used as diagnostic tools. It is shown that the experience of loneliness by young people contributes to self-knowledge, self-development and the ability to establish trusting relationships. The most common life variants among young people are identified: “life as a preface” and “life by the rules”. It is stated that to study real life models of contemporary people in connection with other psychological realities is a promising line of researches.

Efficient sampling techniques for surrogate-based optimization with thermoelastic application

In many real-life models, the objective function may be very expensive to calculate or sometimes a black-box function. Therefore, a surrogate model is required to reduce the cost of the calculations. To build a robust surrogate model, a good sampling technique is needed. This paper suggests two new sampling techniques for surrogate-based optimization, depending on four random walk steps, which in turn give a good chance for building an accurate approximation for the original function. In addition to that, one of these new sampling techniques has a new feature that was not used before. The main advantage of our two suggested sampling techniques is that there is no optimization subproblem will be solved for the next sample point, which in turn saves CPU time. Furthermore, we applied our two sampling techniques to a 1D thermal shock problem for a half-space in the context of the fractional order theory of thermoelasticity to reduce the number of function evaluations and consequently CPU time. Laplace transform techniques are used to obtain the solution of the system in the frequency domain. Applying our algorithms to the few points obtained by using Laplace’s inverse, we can reach the optimal solution for all functions filed. The predictions of our techniques are discussed and compared with the classical method. 2D and 3D graphs are plotted for our numerical results. The temperature, displacement, and stress distributions are computed and represented graphically for different times and several fractional parameters.

ANALYSIS OF STUDENTS' MATHEMATICAL CRITICAL THINKING SKILLS WITH A REALISTIC MATHEMATICS EDUCATION (RME) APPROACH TO TWO-VARIABLE LINEAR EQUATION SYSTEM MATERIAL

Students must have the ability or potential as well as a good mathematical attitude, such as the ability to solve problem in solving problems in this Systems of Linear Equations in Two Variables material. These abilities include mathematical problems, including the abilities that exist within each student so that they can solve problems in the Systems of Linear Equations in Two Variables material. This research was conducted to find out how students solve and apply two-variable linear equation systems at the 10th-grade high school level in real-world problems. This research also examines real-world problems and students' systematic thinking on how students solve or apply mathematics problems in Systems of Linear Equations in Two Variables material. This data collection was carried out by examining class x level students at MAN 1 JEMBER with research themes that had been implemented. The application criteria used in this research use journal articles on Sinta 2 or Google Scholar which must be published within the last 5 years maximum. After all the data has been collected, the next step is the data processing process which is carried out by analyzing the data on the class x high school level learning model in real life. The purpose of this research is to determine the abilities of students with visual, auditory, and kinesthetic learning styles and to be able to conclude the application of how students solve mathematics problems in Systems of Linear Equations in Two Variables material.

Analysis of practical applications using the linear programming model

A linear programming model is a mathematical optimization technique used to find the best possible outcome in a mathematical model with linear relationships under a set of constraints. This technique has various applications in engineering, management, economic analysis, and military operations. The linear programming model is the most popular technique for determining the best course of action, and it is essential for decision-making and resource allocation in modern society. This research paper will introduce the standard form of the linear programming model and explore the differences and solutions between three linear programming models: 0-1 integer programming, mixed integer programming, and multi-objective programming. In the case of introducing the application and optimization effect of different models in real life, list research and compare the different applications and research scenarios of the three models to derive the strengths, weaknesses, and characteristics of the different models to achieve the effect of providing more targeted models for different real-life cases.

On complex fractal-fractional order mathematical modeling of CO 2 emanations from energy sector

This research work is devoted to undertake a mathematical model for emissions of carbon dioxide (CO 2) from energy sector using the concept of fractals-fractional differential (FFD) operator. Here, it should be kept in mind that as the population is expanding, so the need of energy increasing day by day. Burning fossil fuels accounts for a sizable amount of the world’s energy production, which increases the concentration of CO 2 in the atmosphere and causes the global warming. It’s critical to reduce CO 2 emissions from the energy industry. Therefore, via the use of FFD operator, we investigate a mathematical model which is addressing the mentioned process. We deduce some qualitative results regarding the existence of such models in real life using mathematical analysis. The aforesaid analysis is based on some fixed points approaches. Additionally, some analysis devoted to stability is also derived for the proposed model. In addition, a numerical algorithms based on modified Euler method is constructed to simulate the results graphically.

Orthopaedic Surgery in the Metaverse: Current Data on Virtual-Reality Based Training

BACKGROUND: Immersive, realistic, and low-risk training has long been ideal for skill-based disciplines such as surgery. Recent advances in virtual reality technology have led to development of surgical training software with the goal to provide experience without risk. The aim of this review is to summarize the current data for virtual reality-based orthopaedic surgery training to evaluate how beneficial the technology may become in educational circumstances. METHODS: A literature review was completed analyzing eight randomized controlled trials completed between 2019 to 2022 to evaluate the effect of virtual reality on orthopaedic surgery education for medical students and residents. Each trial included groups of learners that were trained on a specific procedure with standard methods (“control”) or virtual reality software (“VR group”). Subjects were then evaluated on completion of procedures with real-life models. Procedures included total hip arthroplasty (n=2), tibial intramedullary nail (n=2), slipped capital femoral epiphysis pinning (n=2), and unicompartmental knee arthroplasty (n=2). The primary metrics assessed were time to complete procedure and objective assessment scores. Secondarily survey results were evaluated regarding subjects’ perceived utility of virtual reality in orthopaedic surgery training. RESULTS: 168 subjects (medical students n=68, residents n=100) were included across the 8 different trials. All trials included at least one objective assessment and it was found that overall, the VR group performed 19.9% better than control group on average (19.875 ± 18.324, 95% CI). Seven of the trials reported time to complete procedure, in which it was found that overall VR group completed the procedures 12% faster than control group on average (12 ± 10.988, 95% CI). Subjective measures showed that over 70% of subjects found the VR learning to be at least “helpful” or “useful”. CONCLUSION: Early studies of the emerging field of virtual reality in surgical training are promising. When looking at objective measures and time to complete procedures, VR trained learners perform as well, if not better, than standard method learners. Inclusion of virtual reality-based practice in medical school curricula and residency training may lead to less surgical errors, increased knowledge of procedures, and more efficient learning in real-life scenarios. This potential impact extends beyond well-resourced institutions, as VR technology can provide a cost-effective and accessible alternative for surgical training in low-income and low-resource areas of the world, democratizing access to high-quality medical education. Continued research on translation into clinical practice is warranted, with the potential to bridge educational disparities and improve surgical outcomes on a global scale.

Optical random soliton solutions to conformable fractional NLSE via statistical distributions

We construct some new stochastic solutions for the fractional nonlinear Schrödinger type equation. Specifically, we introduce these stochastic solutions via geometric and beta distributions. Through these two statistical distributions, the expectation corresponding to solutions are illustrated to depict the influence of random parameters. Actually, the presented results can be used to explain many interesting phenomena in superfluid, optical fibers, plasma physics and vibration propagation in the ground and in structures. Some graphs are offered to illustrate the wave modes of the expectation corresponding to stochastic solutions. Finally, our analysis can be implemented for many other models in real life.

NEW LIFE-TIME CONTINUOUS PROBABILITY DISTRIBUTION WITH FLEXIBLE FAILURE RATE FUNCTION

Recently, the area of distribution theory has been receiving increased interest in generating or defining new classes of continuous probability distributions by way of extending the existing distributions. The new generated distribution is expected to be more flexible and have wider acceptability in modeling and predicting real world data sets. In this research, we proposed and study an extension of Ikum distribution using Zubai G- Family (2018) of distribution called Z-Ikum distribution. Expression of some basic structural properties of the new distribution such as cdf, pdf, quantile functions, moments, moment generating function, characteristics function and order statistics was derived. Survival function, hazard rate function, commutative hazard rate function and reversed hazard rate function was also discussed. Plots of the hazard rate function showincrease, decrease and bathtub shapes.Estimation of the proposed distribution parameters was carried out using MLE method. Performance of the parameter estimation was also evaluated via simulation studies. Result of the simulation studies indicates that our estimator is consistent. Three life data sets were used to evaluate the performance of our proposed distribution over some existing distributions. Result of the empherical study revealed that our proposed distribution performwell in modeling real life data than the competing distributions.

Estimation of a Shape Parameter of a Gompertz-lindley Distribution Using Bayesian and Maximum Likelihood Methods

The Gompertz-Lindley distribution is an extension of the Lindley distribution with three parameters. It was found to be more flexible for modeling real life events. The distribution contains two shape parameters and a scale parameter. Despite the necessity of parameter estimation theory in modeling, it has not been shown that a method of estimation method is better for any of these three parameters of the Gompertz-Lindley distribution. This paper identifies the best estimation method for the shape parameter of the Gompertz-Lindley distribution by deriving Bayesian estimators for the shape parameter of the distribution using two non-informative prior distributions (Uniform and Jeffery) and an informative prior (gamma) under squared error loss function (SELF), quadratic loss function (QLF) and precautionary loss function (PLF). These estimators were evaluated and the results compared with the maximum likelihood estimation method using Monte Carlo simulations with the mean square error (MSE) as a criterion for choosing the best estimator.

A variable step-size implementation of a new one-step block method for integrating Burgers' model equation

This article proposes a variable stepsize implementation of an improved one-step block method (OBM) that uses two intermediate points to solve Burgers' equation. The model's problems under consideration are semi-discretized by reducing them into an equivalent differential system using the method of lines. The OBM is improved with an embedding-like method executed in variable stepsize mode. A few of Burgers' real-life model problems are numerically solved to test the accuracy of our error estimation and mesh selection strategy. The numerical results confirmed that the variable stepsize implementation used in this manuscript performed better than the fixed stepsize implementation.

Statistical analysis of Saudi Arabia and UK Covid-19 data using a new generalized distribution

In this article, we extended the Topp–Leone distribution to create the Odd-Topp–Leone–Gompertz-G distribution, a new family of distributions. We were motivated by the limitations of classical models in modeling real life datasets hence, the creation of a new flexible distribution. Expansion of density, distribution of order statistics, Rényi entropy, moments, quantile, generating functions, residual life function and reverse residual life function, and reliability model are some of its structural aspects that are obtained. We looked at some special cases of the new distribution and concluded that our new model can handle both highly skewed data and non-monotonic hazard rate functions. The maximum likelihood estimation technique was used to estimate the model parameters. A simulation exercise was carried out to evaluate the performance of the proposed family of distribution. The article used the Saudi Arabia and United Kingdom dataset to demonstrate the utility of the new model and it was found that the new model performs better in modeling these datasets as compared to non-nested models presented in this article.

Multipath traveling purchaser problem with time-dependent market structure using quantum-inspired variable length genetic algorithm

In developing countries, rural and semi-urban markets remain open for a particular period of time in a day, and items’ availabilities and prices vary within the opening hours of a market. Nowadays, the Internet of Things (IoT) and Type-2 fuzzy logic (T2FL) systems are used to make real-time decisions. With the logistical and infrastructural development around the world, there are several alternate routes for travel between different markets and cities. Taking the above realities into consideration, here, we develop and analyze IoT-enabled and T2FL system-based multipath traveling purchaser problems with time-dependent market structure (IoT-T2FL-MPTPPswTDMS). In this study, information regarding weather, road surface, and congestion concerning different paths obtained by the IoT are used as inputs in T2FL, and path-wise, the vehicle’s average velocity is obtained using the fuzzy rules. Item availability and price in a particular market change with time. The optimization problem is, for different journey starting times, to select the appropriate markets for the purchase and the corresponding optimum routing path for minimum cost (time) against time (cost) constraint. A multi parent, varied-offspring, variable length quantum-inspired genetic algorithm (MPVOVLQiGA) with quantum selection and mutation and multi parent, varied-offspring crossover is developed to solve the proposed problems. For children, mimicking the real-life parental system, In vitro fertilization (IVF) and adopted child (if IVF failed) are considered alongwith the usual comparison crossover. The algorithm’s superiority is established through a statistical test. A real-life model is numerically illustrated. The dependence on the minimum cost and time on the journey’s commencement time is demonstrated.

Sex differences in spatial tasks: Considering environmental factors, navigation strategies, and age

Sex differences in navigation have been a topic of investigation for decades and has been subjected to various contradictory findings and debates. The aim of this work was to compare the spatial memory of men and women tested in various different types of spatial tasks, while controlling for navigation strategies and aging. It is generally thought that men outperform women in navigation and that women have higher scores on object location tasks. However, many studies fail to control for different factors that may bias one sex or the other. We aggregated the data of 465 participants (349 young adults, 127 older adults) who took part in various studies conducted in our laboratory, which include both published and original unpublished data, in order to investigate sex differences. In these studies, we used a number of different paradigms: virtual radial arm mazes, a virtual wayfinding task, an object location task, a virtual Morris Water Maze, and the invisible sensor task which is a real-life model of the Morris Water Maze. While our results may seem discordant at first glance, they demonstrate that several factors can impact the performance of men and women on spatial tasks, including spontaneous navigation strategies, environmental characteristics, and age. We replicated findings showing that women favor proximal landmarks compared to men who favor distal landmarks, women have better memory than men for the position of objects in the absence of reference frames, but they will have poorer scores when navigation requires specific angles, distances and polar coordinates. Moreover, we found that in aging, women who avoid the use of landmarks when navigating a radial maze show stronger reliance on these non-spatial strategies than men. On the other hand, women who rely on landmarks, do so to the same extent as men. Our findings highlight the need to carefully take into consideration these factors in order to produce a more harmonious understanding of sex differences in navigation. Finally, the interaction between spontaneous navigation strategies, sex, and age is discussed in terms of its implications for risk of Alzheimer’s disease.